cheating in exams essay

Cheating in College and Its Forms Words: 574
Student Cheating in an Exam and Its Consequences Words: 758
Academic Dishonesty and Its Detrimental Effects Words: 1122
Class Size Effects on Student Achievement Words: 2702
Negative Effects of Stress on a College Student Words: 873
Excellent Academic Performance: Causes and Effects Words: 562
Academic Honesty: Cheating & Plagiarism Words: 848
Why Some Students Cheat Words: 361

Exam Cheating, Its Causes and Effects

Introduction, definition of cheating, works cited.

The ability of a nation to compete effectively on the international front hinges on the quality of its education. With this in mind, it is okay to conclude that cheating in exams undermines the standard of education in a country and consequently hinders its ability to compete at the world stage. Indeed, students who cheat in exams become poor decision makers in their careers. Their productivity and level of integrity is adversely dented by their belief of having everything the easy way. Academic dishonesty is not new but with the increase in competition for jobs, most students have resorted to cheating in order to qualify for these jobs (Anderman and Johnston 75). The purpose of this paper is to research in detail the causes and effects of cheating in exams.

In the education fraternity, cheating entails: copying from someone, Plagiarizing of academic work and paying someone to do your homework. There are numerous reasons why students cheat in exams however; this action elicits harsh repercussions if one is caught. This may include: suspension, dismissal and/or cancellation of marks (Davis, Grover, Becker and McGregor 16).

One of the major reasons that make students cheat in exams is the over-emphasis that has been placed on passing exams. Apparently, more effort has been directed towards passing of exams than learning due to the high competition in the job market. Similarly, most interviewers focus more on certificates rather than the knowledge of the candidate. It is no wonder most learning institutions these days focus on teaching how to pass an exam and completely disregard impacting knowledge to students.

In some cases, students cheat because they are not confident of their ability or skills in academics. Whenever this feeling is present, students resort to cheating as a way of avoiding ridicule in case of failure. In essence, some of these students are very bright but the fear of failure and the lack of adequate preparations compel them to cheat. The paradox is that when cheating, most students swear that they will never do it again but this only serves as the beginning of a vicious cycle of cheating (Anderman and Johnston 76).

Societal pressure is another major cause for cheating in schools. Parents, teachers and relatives always, with good intentions, mount too much pressure on students to get good grades in order to join good schools and eventually get high paying jobs. All this pressure creates innate feelings that it is okay to cheat in exams if only to satisfy their parents and teachers egos.

There are times when students justify cheating because others do it. In most cases, if the head of the class is cheating then most of the other students will feel they have enough reason to also cheat. The system of education is such that it does not sufficiently reprimand those who cheat and tends to hail those who pass exams regardless of how they have done—the end justifies the means.

With the advent of the internet, it has become very easy to access information from a website using a phone or a computer. Search engines such as Google and Yahoo have made it very easy for students to buy custom-made papers for their class work. It is very easy for students from all over the world to have the same answer for an assignment as they all use a similar website. Indeed, plagiarism is the order of the day, all on has to do is to have the knowledge to search for the different reports and essays on the net (Davis, Grover, Becker and McGregor 18).

Nowadays, most tutors spend most of their class time giving lectures. In fact, it is considered old fashioned to give assignments during class time. Consequently, these assignments are piled up and given during certain durations of the semester. This poses a big challenge to students who have to strike a balance between attending to their homework and having fun. As a result, the workload becomes too much such that it is easier to pay for it to be done than actually do it—homework then becomes as demanding as a full-time job (Jordan 234).

From a tender age, children are taught that cheating is wrong; yet most of them divert from this course as they grow up. In fact, most of them become so addicted to the habit that they feel the need to perfect it. Most often, if a student cheats and never gets caught, he is likely to cheat all his life. Research has shown that students who cheat in high school are twice likely to cheat in college. The bigger problem is that this character is likely to affect one’s career in future consequently tarnishing his/her image.

Cheating in exams poses a great problem in one’s career. To get a good grade as a result of cheating is a misrepresentation of facts. Furthermore, it is difficult for a tutor to isolate students who genuinely need specialized coaching. It becomes a huge embarrassment when a cheating student is expected to give a perfect presentation and fails to demonstrate his ability as indicated by his/her grades. In addition, students who cheat in examination do not get a chance to grasp important concepts in class and are likely to face difficulties in the future when the same principles are applied in higher levels of learning.

The worst-case scenario in cheating in an exam is being caught. Once a student is caught, his reputation is dealt a huge blow. It is likely that such a student will be dismissed or suspended from school. This hinders his/her ability to land a good job or join graduate school. It can also lead to a complete damage of one’s reputation making it hard for others to trust you including those who cheat (Jordan 235).

Cheating in exams and assignments can be attributed to many reasons. To begin with, teaching today concentrates so much on the exams and passing rather than impacting knowledge. Lack of confidence in one’s ability and societal pressure is another reason why cheating is so wide spread. Cheating cannot solely be blamed on the students; lecturers have also played their part in this. Apparently, most lectures concentrate on teaching than giving assignments during class time. This leaves the students with loads of work to cover during their free time.

Technology has also played its part in cheating—many students turn to the internet in a bid to complete their assignments. On the other hand, it is important to note than choices have consequences and the repercussions of cheating in an exams are dire. First, it completely ruins one’s reputation thereby hindering chances of joining college or getting a good job. It also leads to suspensions and/or expulsion from school. Furthermore, the habit is so addictive that it is likely to replicate in all aspects of life—be it relationships, work, business deals etc. It is important to shun this habit as nothing good can come out of it.

Anderman, Erick and Jerome Johnston. “TV News in the Classroom: What are Adolescents Learning?” Journal of Adolescent Research , 13 (1998): 73-100. Print.

Davis, Stephen, Cathy Grover, Angela, Becker, and Loretta McGregor. “Academic Dishonesty: Prevalence, Determinants, Techniques, and Punishments”. Teaching of Psychology , 19 (1) (1996): 16–20. Print.

Jordan, Augustus E. “College Student Cheating: The Role of Motivation, Perceived Norms, Attitudes, and Knowledge of Institutional Policy. Ethics and Behavior , 11, (2001): 233–247. Print.

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Why Students Cheat—and What to Do About It

A teacher seeks answers from researchers and psychologists.

“Why did you cheat in high school?” I posed the question to a dozen former students.

“I wanted good grades and I didn’t want to work,” said Sonya, who graduates from college in June. [The students’ names in this article have been changed to protect their privacy.]

My current students were less candid than Sonya. To excuse her plagiarized Cannery Row essay, Erin, a ninth-grader with straight As, complained vaguely and unconvincingly of overwhelming stress. When he was caught copying a review of the documentary Hypernormalism , Jeremy, a senior, stood by his “hard work” and said my accusation hurt his feelings.

Cases like the much-publicized ( and enduring ) 2012 cheating scandal at high-achieving Stuyvesant High School in New York City confirm that academic dishonesty is rampant and touches even the most prestigious of schools. The data confirms this as well. A 2012 Josephson Institute’s Center for Youth Ethics report revealed that more than half of high school students admitted to cheating on a test, while 74 percent reported copying their friends’ homework. And a survey of 70,000 high school students across the United States between 2002 and 2015 found that 58 percent had plagiarized papers, while 95 percent admitted to cheating in some capacity.

So why do students cheat—and how do we stop them?

According to researchers and psychologists, the real reasons vary just as much as my students’ explanations. But educators can still learn to identify motivations for student cheating and think critically about solutions to keep even the most audacious cheaters in their classrooms from doing it again.

Rationalizing It

 First, know that students realize cheating is wrong—they simply see themselves as moral in spite of it.

“They cheat just enough to maintain a self-concept as honest people. They make their behavior an exception to a general rule,” said Dr. David Rettinger , professor at the University of Mary Washington and executive director of the Center for Honor, Leadership, and Service, a campus organization dedicated to integrity.

According to Rettinger and other researchers, students who cheat can still see themselves as principled people by rationalizing cheating for reasons they see as legitimate.

Some do it when they don’t see the value of work they’re assigned, such as drill-and-kill homework assignments, or when they perceive an overemphasis on teaching content linked to high-stakes tests.

“There was no critical thinking, and teachers seemed pressured to squish it into their curriculum,” said Javier, a former student and recent liberal arts college graduate. “They questioned you on material that was never covered in class, and if you failed the test, it was progressively harder to pass the next time around.”

But students also rationalize cheating on assignments they see as having value.

High-achieving students who feel pressured to attain perfection (and Ivy League acceptances) may turn to cheating as a way to find an edge on the competition or to keep a single bad test score from sabotaging months of hard work. At Stuyvesant, for example, students and teachers identified the cutthroat environment as a factor in the rampant dishonesty that plagued the school.

And research has found that students who receive praise for being smart—as opposed to praise for effort and progress—are more inclined to exaggerate their performance and to cheat on assignments , likely because they are carrying the burden of lofty expectations.

A Developmental Stage

When it comes to risk management, adolescent students are bullish. Research has found that teenagers are biologically predisposed to be more tolerant of unknown outcomes and less bothered by stated risks than their older peers.

“In high school, they’re risk takers developmentally, and can’t see the consequences of immediate actions,” Rettinger says. “Even delayed consequences are remote to them.”

While cheating may not be a thrill ride, students already inclined to rebel against curfews and dabble in illicit substances have a certain comfort level with being reckless. They’re willing to gamble when they think they can keep up the ruse—and more inclined to believe they can get away with it.

Cheating also appears to be almost contagious among young people—and may even serve as a kind of social adhesive, at least in environments where it is widely accepted. A study of military academy students from 1959 to 2002 revealed that students in communities where cheating is tolerated easily cave in to peer pressure, finding it harder not to cheat out of fear of losing social status if they don’t.

Michael, a former student, explained that while he didn’t need to help classmates cheat, he felt “unable to say no.” Once he started, he couldn’t stop.

A student cheats using answers on his hand.

Technology Facilitates and Normalizes It

With smartphones and Alexa at their fingertips, today’s students have easy access to quick answers and content they can reproduce for exams and papers. Studies show that technology has made cheating in school easier, more convenient, and harder to catch than ever before.

To Liz Ruff, an English teacher at Garfield High School in Los Angeles, students’ use of social media can erode their understanding of authenticity and intellectual property. Because students are used to reposting images, repurposing memes, and watching parody videos, they “see ownership as nebulous,” she said.

As a result, while they may want to avoid penalties for plagiarism, they may not see it as wrong or even know that they’re doing it.

This confirms what Donald McCabe, a Rutgers University Business School professor, reported in his 2012 book ; he found that more than 60 percent of surveyed students who had cheated considered digital plagiarism to be “trivial”—effectively, students believed it was not actually cheating at all.

Strategies for Reducing Cheating

Even moral students need help acting morally, said Dr. Jason M. Stephens , who researches academic motivation and moral development in adolescents at the University of Auckland’s School of Learning, Development, and Professional Practice. According to Stephens, teachers are uniquely positioned to infuse students with a sense of responsibility and help them overcome the rationalizations that enable them to think cheating is OK.

1. Turn down the pressure cooker. Students are less likely to cheat on work in which they feel invested. A multiple-choice assessment tempts would-be cheaters, while a unique, multiphase writing project measuring competencies can make cheating much harder and less enticing. Repetitive homework assignments are also a culprit, according to research , so teachers should look at creating take-home assignments that encourage students to think critically and expand on class discussions. Teachers could also give students one free pass on a homework assignment each quarter, for example, or let them drop their lowest score on an assignment.

2. Be thoughtful about your language. Research indicates that using the language of fixed mindsets , like praising children for being smart as opposed to praising them for effort and progress , is both demotivating and increases cheating. When delivering feedback, researchers suggest using phrases focused on effort like, “You made really great progress on this paper” or “This is excellent work, but there are still a few areas where you can grow.”

3. Create student honor councils. Give students the opportunity to enforce honor codes or write their own classroom/school bylaws through honor councils so they can develop a full understanding of how cheating affects themselves and others. At Fredericksburg Academy, high school students elect two Honor Council members per grade. These students teach the Honor Code to fifth graders, who, in turn, explain it to younger elementary school students to help establish a student-driven culture of integrity. Students also write a pledge of authenticity on every assignment. And if there is an honor code transgression, the council gathers to discuss possible consequences.

4. Use metacognition. Research shows that metacognition, a process sometimes described as “ thinking about thinking ,” can help students process their motivations, goals, and actions. With my ninth graders, I use a centuries-old resource to discuss moral quandaries: the play Macbeth . Before they meet the infamous Thane of Glamis, they role-play as medical school applicants, soccer players, and politicians, deciding if they’d cheat, injure, or lie to achieve goals. I push students to consider the steps they take to get the outcomes they desire. Why do we tend to act in the ways we do? What will we do to get what we want? And how will doing those things change who we are? Every tragedy is about us, I say, not just, as in Macbeth’s case, about a man who succumbs to “vaulting ambition.”

5. Bring honesty right into the curriculum. Teachers can weave a discussion of ethical behavior into curriculum. Ruff and many other teachers have been inspired to teach media literacy to help students understand digital plagiarism and navigate the widespread availability of secondary sources online, using guidance from organizations like Common Sense Media .

There are complicated psychological dynamics at play when students cheat, according to experts and researchers. While enforcing rules and consequences is important, knowing what’s really motivating students to cheat can help you foster integrity in the classroom instead of just penalizing the cheating.

Consequences Of Cheating In Exams: Examples And Effects

Cheating in exams is a serious issue that has far-reaching consequences for both individuals and society as a whole. It undermines the integrity of the education system, diminishes the value of qualifications, and erodes trust between students, teachers, and institutions.

Consequently, deserving students may miss out on opportunities such as scholarships or admission into competitive programs due to unfair competition from those who cheat.

Consequences of Cheating in College

Cheating in college exams can have serious consequences for students .

1. Cheating can lead to Class Failure

Academic dishonesty, such as cheating during exams, has the potential to result in students failing their classes. When students resort to cheating as a means to achieve better class performance, they not only compromise their academic integrity but also put their future at risk. The consequences of cheating can extend beyond immediate academic repercussions and have long-lasting effects on a student’s educational journey.

One of the primary academic consequences of cheating is the failure to grasp essential concepts and skills that are necessary for success in subsequent courses. Cheating stains a student’s reputation and raises questions about their character and reliability. A failed class due to cheating may leave a permanent mark on their academic transcript, potentially limiting opportunities for internships or postgraduate studies.

2. Legal consequences

The legal consequences of cheating in exams can have a long-lasting impact on one’s future. When employers or educational institutions discover that an individual has been involved in academic dishonesty, it raises questions about their character and ability to follow ethical practices. This can severely damage their reputation and hinder their chances of securing employment or admission into higher education programs. Moreover, having a criminal record for cheating can limit one’s opportunities for professional licensure or certification in certain fields where integrity is highly valued.

Cheating in exams not only undermines educational integrity but also carries significant legal consequences. Those who engage in such practices risk facing legal actions that can have far-reaching effects on their future prospects. It is important for individuals to understand the gravity of these consequences and make ethical choices when it comes to academic pursuits.

3. Cheating leads to Suspension and expulsion

Suspension and expulsion are disciplinary measures commonly imposed in response to dishonest practices that compromise the integrity of the educational system. When students engage in cheating during exams, they not only undermine their own learning but also violate the trust and fairness upon which academic institutions are built.

The consequences of suspension can be severe, as it involves a temporary removal from school for a specified period of time. During this period, students are barred from attending classes, participating in extracurricular activities , and accessing resources provided by the institution. This interruption in education can significantly impact a student’s academic progress and overall development.

Expulsion is an even more drastic repercussion of academic dishonesty. It entails a permanent dismissal from the educational institution, effectively ending any further enrollment or association with the school. Expulsion carries long-lasting consequences beyond just missing out on education opportunities. It tarnishes one’s academic record and reputation, making it difficult to gain admission into other institutions or pursue certain career paths that require a clean disciplinary history.

4. Academic reputation

A strong academic reputation is built upon a foundation of integrity and ethical conduct in educational institutions. Academic integrity refers to the honesty, trustworthiness, and ethical behavior expected from students and faculty members within an academic setting. It encompasses various aspects such as avoiding plagiarism, citing sources correctly, and conducting research with honesty and transparency.

Reputation management plays a crucial role in maintaining the academic reputation of an institution. Ethical behavior is essential for creating a conducive learning environment where knowledge is valued and respected. When students engage in cheating during exams, it undermines the principles of fairness and equal opportunities for all learners. To uphold academic integrity and manage their reputation effectively, educational institutions need to emphasize ethical behavior among their students through awareness campaigns, workshops on proper citation techniques, and clear guidelines on acceptable conduct during exams.

5. Cheating makes it hard to secure a Job

Cheating during exams not only undermines a student’s academic integrity but also raises serious concerns about their ethical values, which can have far-reaching consequences on their future career opportunities. Employers value honesty and integrity as fundamental qualities in potential employees, and discovering a candidate’s history of cheating can severely tarnish their chances of securing a job.

With competition for employment becoming increasingly fierce, employers are constantly seeking candidates who possess strong moral character and uphold the principles of fairness and trustworthiness. Consequently, those who succumb to the allure of cheating must grapple with the long-term impact on their personal growth, self-esteem, and ability to make ethically sound choices in future endeavors.

6. Cheating can cost you a scholarship

Scholarship opportunities can be lost as a result of engaging in dishonest practices during academic evaluations. Cheating not only undermines the integrity of the evaluation process but also has long-term consequences that can impact one’s future prospects. Many scholarships require applicants to demonstrate academic excellence and ethical conduct, making cheating a significant deterrent.

The impact on future prospects cannot be overstated. Scholarships provide financial support for students pursuing higher education and open doors to various opportunities such as internships, research projects, or study abroad programs. Cheating not only disqualifies individuals from immediate consideration but also diminishes their reputation and credibility over time. The impact extends beyond financial aid as it hinders access to valuable experiences and raises doubts about one’s abilities in competitive environments where integrity is paramount.

7. Creation of a false character

When students resort to creating a false character in order to cheat in exams, they not only undermine their own personal growth but also compromise the principles upon which academic institutions are built. The consequences of creating a false character extend beyond personal growth and affect the broader notion of academic integrity. It creates an unfair advantage for those who engage in such deceitful practices while disadvantaging honest students who have diligently worked towards achieving genuine success.

8. Cheating in school erodes your independence

When students resort to cheating in school, they are essentially relinquishing their independence by relying on illicit means to achieve academic success. By not putting in the necessary effort and taking shortcuts, students miss out on valuable opportunities for personal growth and development. In essence, cheating prevents them from learning essential skills such as critical thinking, problem-solving, and perseverance that are crucial for their future endeavors.

The impact of cheating on personal growth extends beyond the educational setting and can have severe consequences in adulthood. Students who habitually cheat may struggle with decision-making and lack confidence in their abilities to tackle challenges independently. This eroded sense of independence can hinder their professional development as they enter the workforce or pursue higher education.

9. Cheating in school prevents progress

Academic dishonesty in educational settings hinders the forward momentum of personal and intellectual growth, creating a stagnant environment where genuine progress becomes elusive. When students resort to cheating in school , they bypass the essential process of learning and understanding the material. By taking shortcuts, they deprive themselves of valuable opportunities to develop critical thinking skills, problem-solving abilities, and a deep understanding of the subject matter.

To prevent cheating and promote integrity in schools, academic institutions have implemented various measures such as academic integrity programs. These programs aim to educate students about the importance of ethical behavior in academia and provide resources for developing good study habits. By instilling a sense of responsibility and emphasizing honesty, these initiatives encourage students to take ownership of their education and learn through legitimate means.

10. Cheating in universities causes stress

Cheating in universities contributes to heightened levels of stress among students. The pressure to perform well academically can lead some students to resort to cheating as a means of achieving success. However, the consequences of such actions often result in increased stress levels. Students who cheat may experience constant anxiety and fear of getting caught, which can negatively impact their mental well-being.

One major factor contributing to the stress caused by cheating is the lack of effective stress management techniques. When students rely on cheating instead of developing their skills and knowledge, they miss out on opportunities for personal growth and self-improvement. This reliance on dishonest practices creates a cycle of stress and dependence, as students become increasingly anxious about maintaining their academic performance through unethical means.

11. Cheating in school brings Embarrassment

Embarrassment is a common emotion experienced by students who engage in dishonest practices within the educational system. Cheating in school not only undermines the integrity of the academic environment but also has significant psychological and social consequences for those involved.

When students resort to cheating, they often experience a profound sense of embarrassment, knowing that their actions go against established norms and values. The psychological impact of cheating-induced embarrassment can be profound. Students may feel guilty and ashamed for their dishonesty, leading to increased stress and anxiety levels. This emotional burden can affect their overall well-being and academic performance, as it becomes difficult to focus on learning when plagued by feelings of embarrassment.

12. Cheating is a form of disrespect.

One of the key aspects to consider when examining the act of cheating is the underlying disrespect it displays towards the educational system and its values. Cheating in exams is a form of disrespectful behavior that undermines the principles of academic integrity and moral values. This disrespectful behavior not only compromises their own personal growth but also diminishes the credibility and value of education as a whole.

Cheating reflects a lack of appreciation for the learning process and devalues the efforts put forth by both educators and students who adhere to ethical principles. It sends a message that shortcuts and deceitful practices are acceptable means to achieve success, undermining the foundational basis upon which education stands.

Effect of Cheating on the Learning Process

The impact of dishonesty during exams can have significant implications for the overall educational experience. Cheating not only undermines the integrity of the learning process but also has detrimental effects on motivation. When students resort to cheating, they are essentially bypassing the opportunity to engage with the material and develop a deep understanding of the subject matter. This lack of genuine effort and comprehension can lead to a decrease in intrinsic motivation, as students become more focused on achieving high grades rather than truly mastering the content

Examples of cheating in college

Cheating in college can take various forms, including copying from fellow students during exams or assignments. Another example of cheating is when someone pays another person to write essays or papers for them.

1. Copying from fellow students

Copying from fellow students during exams undermines the integrity of the assessment process and compromises the fairness of grading. This act not only has serious consequences for the individuals involved but also poses ethical implications and challenges academic integrity. When students resort to copying, they disregard the importance of genuine learning and academic growth. Consequently, their education becomes superficial and lacks the necessary depth that would prepare them for future challenges.

Copying from fellow students during exams not only has immediate consequences for those involved but also raises important ethical concerns regarding academic integrity. The act itself undermines genuine learning opportunities and inhibits personal growth in critical areas such as problem-solving and independent thinking. Moreover, it disrupts fairness in grading processes and erodes trust within educational institutions.

2. When someone writes essays or papers for you.

Outsourcing the writing of essays or papers undermines the authenticity of academic work and hinders the development of critical thinking skills and independent research abilities. When someone else writes an essay or paper on behalf of a student, it not only compromises their academic integrity but also deprives them of valuable learning opportunities.

Plagiarism detection tools have become increasingly sophisticated in recent years, making it easier for educators to identify instances of outsourced writing. The prevalence of such unethical practices raises serious ethical implications within educational institutions.

Outsourcing the writing of essays or papers has severe consequences on both individual students’ academic growth as well as broader educational systems’ integrity. It undermines authenticity by compromising academic rigor while hindering critical thinking skills and independent research abilities. The use of plagiarism detection tools serves as a deterrent against such practices but cannot completely eradicate them entirely.

3. Using textbooks, notes, and formula lists on exams

Utilizing textbooks, notes, and formula lists during examinations can significantly impact the educational integrity of the assessment process while potentially hindering the development of critical thinking skills and a deep understanding of the subject matter. Academic dishonesty is a serious concern in educational institutions, as it goes against the principles of fairness and equality.

Allowing students to rely on external resources during exams undermines the purpose of assessing their knowledge and proficiency in a particular subject. When students have access to textbooks, notes, or formula lists during exams, they may rely solely on these materials instead of actively engaging with the course content. This reliance not only diminishes their ability to think critically but also prevents them from fully comprehending complex concepts. Exams are designed not just to test factual recall but also to assess students’ analytical skills and their ability to synthesize information.

Allowing students to use textbooks, notes, and formula lists during examinations can compromise educational integrity by promoting academic dishonesty. It limits opportunities for critical thinking development and impedes a thorough grasp of course material. To ensure an effective assessment process that fosters genuine learning outcomes, it is crucial for educational institutions to discourage such exam preparation methods that undermine intellectual growth and hinder academic progress.

4. Collaborating in tests or exams without permission

Collaborating with others during tests or exams without proper authorization can compromise the integrity of the assessment process and undermine the principles of fairness and equality in education. Collaborative learning, when properly facilitated and authorized by instructors, can be a valuable educational tool that promotes critical thinking and problem-solving skills.

Collaborating in tests or exams without proper authorization is detrimental to both individuals involved and the integrity of education as a whole. It is important for students to understand that academic success should be based on one’s own efforts and abilities rather than relying on unauthorized collaboration. Upholding ethical behavior is crucial for maintaining fairness, equality, and credibility within educational institutions.

5. Copying from Online Tutors

Online tutoring has become increasingly popular due to its convenience and accessibility. Students can seek help from qualified tutors anytime, anywhere, and access a wide range of study materials. While online tutoring offers numerous benefits for students, it is important to recognize the potential risks associated with this practice. Copying answers directly from online tutors not only undermines the purpose of examinations but also violates academic integrity. Plagiarism prevention strategies play a crucial role in addressing this issue.

Educational institutions should prioritize implementing strict policies against cheating and plagiarism, educating students about the importance of academic honesty, and providing resources for developing effective study skills. Implementing plagiarism prevention strategies and comprehensive academic integrity programs can help instill a sense of responsibility among students while promoting ethical conduct in their educational journey.

Solutions to cheating in school

In order to address the issue of cheating in school, it is crucial to educate students on the importance of honesty and integrity. This can be done through regular discussions and workshops that highlight the negative consequences of cheating and emphasize the value of ethical behavior.

1. Educating students on the importance of honesty

To instill principles of honesty in students, it is imperative to educate them about the significance of integrity during examinations. Emphasizing the importance of ethical behavior in academic settings helps foster a culture of integrity and promotes academic honesty. By educating students on the consequences of cheating and highlighting the value of honesty, educational institutions can create an environment where students understand the long-term benefits of maintaining their integrity.

Educating students about the importance of ethical behavior lays the foundation for fostering a culture of integrity within educational institutions. When students are aware that dishonesty can have serious repercussions not only on their academic journey but also on their personal growth and development, they are more likely to adhere to guidelines promoting honesty. Promoting academic honesty goes beyond just preventing cheating; it encourages critical thinking skills, self-discipline, and intellectual growth.

2. Creating anti-cheating pledges

Creating anti-cheating pledges can be a powerful tool in addressing the issue of cheating in exams. These pledges serve as a visible reminder for students to uphold their integrity and make ethical choices when faced with academic challenges. By signing such a pledge, students publicly declare their commitment to honest practices, creating awareness not only among themselves but also among their peers. This collective effort towards maintaining academic honesty can have a profound impact on reducing incidents of cheating.

Creating anti-cheating pledges is an effective strategy for discouraging cheating in exams as it creates awareness about its consequences, promotes student accountability, and builds trust within educational institutions. By encouraging students to actively commit themselves to uphold academic honesty through these pledges, a culture of integrity and personal responsibility can be fostered. Implementing such measures not only deters cheating but also instills valuable life skills and values in students that extend beyond the academic realm.

3. Instructors changing the definition of success

An alternative approach employed by instructors involves redefining the criteria for achieving success within an academic context. Rather than solely focusing on exam performance, instructors are changing expectations and placing greater emphasis on alternative assessments to evaluate students’ understanding and knowledge.

This shift in mindset aims to reduce the pressure that often leads to cheating and encourages students to engage more deeply with the material. By changing the definition of success, instructors aim to create a learning environment that focuses on growth and understanding rather than simply memorizing information for exams. This change has a significant impact on students as it encourages them to develop critical thinking skills, problem-solving abilities, and a deeper comprehension of the subject matter.

Cheating in exams has serious consequences in college. Students who are caught cheating may face disciplinary actions such as receiving a failing grade for the exam or even being expelled from the institution. To combat cheating, schools can implement various solutions. Firstly, they can promote a culture of academic honesty by educating students about the negative consequences of cheating and emphasizing the importance of ethical conduct.

Schools can implement strict monitoring measures during exams to deter and detect instances of cheating. This can include using proctors or invigilators during exams or employing technology tools such as anti-plagiarism software to identify plagiarized content. By promoting academic integrity and implementing effective preventive measures, we can ensure that exams serve their intended purpose – assessing students’ true abilities and preparing them for success in their future endeavors without resorting to dishonest practices.

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Argumentative Essay About Cheating

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Identify possible reasons for the problem you have selected. To find the most effective strategies, select the reason that best describes your situation, keeping in mind there may be multiple relevant reasons.

Students cheat on assignments and exams..

Students might not understand or may have different models of what is considered appropriate help or collaboration or what comprises plagiarism.

Students might blame their cheating behavior on unfair tests and/or professors.

Some students might feel an obligation to help certain other students succeed on exams—for example, a fraternity brother, sorority sister, team- or club-mate, or a more senior student in some cultures.

Some students might cheat because they have poor study skills that prevent them from keeping up with the material.

Students are more likely to cheat or plagiarize if the assessment is very high-stakes or if they have low expectations of success due to perceived lack of ability or test anxiety.

Students might be in competition with other students for their grades.

Students might perceive a lack of consequences for cheating and plagiarizing.

Students might perceive the possibility to cheat without getting caught.

Many students are highly motivated by grades and might not see a relationship between learning and grades.

Students are more likely to cheat when they feel anonymous in class.

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How Common is Cheating in Online Exams and did it Increase During the COVID-19 Pandemic? A Systematic Review

Open access
Published: 04 August 2023
Volume 22 , pages 323–343, ( 2024 )

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Philip M. Newton ORCID: orcid.org/0000-0002-5272-7979 1 &
Keioni Essex 1

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Academic misconduct is a threat to the validity and reliability of online examinations, and media reports suggest that misconduct spiked dramatically in higher education during the emergency shift to online exams caused by the COVID-19 pandemic. This study reviewed survey research to determine how common it is for university students to admit cheating in online exams, and how and why they do it. We also assessed whether these self-reports of cheating increased during the COVID-19 pandemic, along with an evaluation of the quality of the research evidence which addressed these questions. 25 samples were identified from 19 Studies, including 4672 participants, going back to 2012. Online exam cheating was self-reported by a substantial minority (44.7%) of students in total. Pre-COVID this was 29.9%, but during COVID cheating jumped to 54.7%, although these samples were more heterogenous. Individual cheating was more common than group cheating, and the most common reason students reported for cheating was simply that there was an opportunity to do so. Remote proctoring appeared to reduce the occurrence of cheating, although data were limited. However there were a number of methodological features which reduce confidence in the accuracy of all these findings. Most samples were collected using designs which makes it likely that online exam cheating is under-reported, for example using convenience sampling, a modest sample size and insufficient information to calculate response rate. No studies considered whether samples were representative of their population. Future approaches to online exams should consider how the basic validity of examinations can be maintained, considering the substantial numbers of students who appear to be willing to admit engaging in misconduct. Future research on academic misconduct would benefit from using large representative samples, guaranteeing participants anonymity.

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Introduction

Distance learning came to the fore during the global COVID-19 pandemic. Distance learning, also referred to as e-learning, blended learning or mobile learning (Zarzycka et al., 2021 ) is defined as learning with the use of technology where there is a physical separation of students from the teachers during the active learning process, instruction and examination (Armstrong-Mensah et al., 2020 ). This physical separation was key to a sector-wide response to reducing the spread of coronavirus.

COVID prompted a sudden, rapid and near-total adjustment to distance learning (Brown et al., 2022 ; Pokhrel & Chhetri, 2021 ). We all, staff and students, had to learn a lot, very quickly, about distance learning. Pandemic-induced ‘lockdown learning’ continued, in some form, for almost 2 years in many countries, prompting predictions that higher education would be permanently changed by the pandemic, with online/distance learning becoming much more common, even the norm (Barber et al., 2021 ; Dumulescu & Muţiu, 2021 ). One obvious potential change would be the widespread adoption of online assessment methods. Online exams offer students increased flexibility, for example the opportunity to sit an exam in their own homes. This may also reduce some of the anxiety experienced during attending in-person exams in an exam hall, and potentially reduce the administrative cost to universities.

However, assessment poses many challenges for distance learning. Summative assessments, including exams, are the basis for making decisions about the grading and progress of individual students, while aggregated results can inform educational policy such as curriculum or funding decisions (Shute & Kim, 2014 ). Thus, it is essential that online summative assessments can be conducted in a way that allows for their basic reliability and validity to be maintained. During the pandemic, Universities shifted, very rapidly, in-person exams to an online format, with limited time to ensure that these methods were secure. There were subsequent media reports that academic misconduct was now ‘endemic’, with universities supposedly ‘turning a blind eye’ towards cheating (e.g. Henry, 2022 ; Knox, 2021 ). However, it is unclear whether this media anxiety is reflected in the real-world experience in universities.

Dawson defines e-cheating as ‘cheating that uses or is enabled by technology’ (Dawson, 2020 , p. 4). Cheating itself is then defined as the gaining of an unfair advantage (Case and King 2007, in Dawson, 2020 , P4). Cheating poses an obvious threat to the validity of online examinations, a format which relies heavily on technology. Noorbebahani and colleagues recently reviewed the research literature on a specific form of e-cheating; online exam cheating in higher education. They found that students use a variety of methods to gain an unfair advantage, including accessing unauthorized materials such as notes and textbooks, using an additional device to go online, collaborating with others, and even outsourcing the exam to be taken by someone else. These findings map onto the work of Dawson, 2020 , who found a similar taxonomy when considering ‘e-cheating’ more generally. These can be driven by a variety of motivations, including a fear of failure, peer pressure, a perception that others are cheating, and the ease with which they can do it (Noorbehbahani et al., 2022 ). However, it remains unclear how many students are actually engaged in these cheating behaviours. Understanding the scale of cheating is an important pragmatic consideration when determining how, or even if, it could/should be addressed. There is an extensive literature on the incidence of other types of misconduct, but cheating in online exams has received less attention than other forms of misconduct such as plagiarism (Garg & Goel, 2022 ).

One seemingly obvious response to concerns about cheating in online exams is to use remote proctoring systems wherein students are monitored through webcams and use locked-down browsers. However, the efficacy of these systems is not yet clear, and their use has been controversial, with students feeling that they are ‘under surveillance’, anxious about being unfairly accused of cheating, or of technological problems (Marano et al., 2023 ). A recent court ruling in the USA found that the use of a remote proctoring system to scan a student’s private resident prior to taking an online exam was unconstitutional (Bowman, 2022 ), although, at the time of writing, this case is ongoing (Witley, 2023 ). There is already a long history of legal battles between the proctoring companies and their critics (Corbyn, 2022 ), and it is still unclear whether these systems actually reduce misconduct. Alternatives have been offered in the literature, including guidance for how to prepare online exams in a way that reduces the opportunity for misconduct (Whisenhunt et al., 2022 ), although it is unclear whether this guidance is effective either.

There is a large body of research literature which examines the prevalence of different types of academic dishonesty and misconduct. Much of this research is in the form of survey-based self-report studies. There are some obvious problems with using self-report as a measure of misconduct; it is a ‘deviant’ or ‘undesirable’ behaviour, and so those invited to participate in survey-based research have a disincentive to respond truthfully, if at all, especially if there is no guarantee of anonymity. There is also some evidence that certain demographic characteristics associated with an increased likelihood of engaging in academic misconduct are also predictive of a decreased likelihood of responding voluntarily to surveys, meaning that misconduct is likely under-reported when a non-representative sampling method is used such as convenience sampling (Newton, 2018 ).

Some of these issues with quantifying academic misconduct can be partially addressed by the use of rigorous research methodology, for example using representative samples with a high response rate, and clear, unambiguous survey items (Bennett et al., 2011 ; Halbesleben & Whitman, 2013 ). Guarantees of anonymity are also essential for respondents to feel confident about answering honestly, especially when the research is being undertaken by the very universities where participants are studying. A previous systematic review of academic misconduct found that self-report studies are often undertaken with small, convenience samples with low response rates (Newton, 2018 ). Similar findings were reported when reviewing the reliability of research into the prevalence of belief in the Learning Styles neuromyth, suggesting that this is a wider concern within survey-based education research (Newton & Salvi, 2020 ).

However, self-report remains one of the most common ways that academic misconduct is estimated, perhaps in part because there are few other ways to meaningfully measure it. There is also a basic, intuitive objective validity to the method; asking students whether they have cheated is a simple and direct approach, when compared to other indirect approaches to quantifying misconduct, based on (for example) learner analytics, originality scores or grade discrepancies. There is some evidence that self-report correlates positively with actual behaviour (Gardner et al., 1988 ), and that data accuracy can be improved by using methods which incentivize truth-telling (Curtis et al., 2022 ).

Here we undertook a systematic search of the literature in order to identify research which studied the prevalence of academic dishonesty in summative online examinations in Higher Education. The research questions were thus.

How common is self-report of cheating in online exams in Higher Education? (This was the primary research question, and studies were only included if they addressed this question).

Did cheating in online exams increase during the COVID-19 pandemic?

What are the most common forms of cheating?

What are student motivations for cheating?

Does online proctoring reduce the incidence of self-reported online exam cheating?

The review was conducted according to the principles of the PRISMA statement for reporting systematic reviews (Moher et al., 2009 ) updated for 2020 (Page et al., 2021 ). We adapted this methodology based on previous work systematically reviewing survey-based research in education, misbelief and misconduct (Fanelli, 2009 ; Newton, 2018 ; Newton & Salvi, 2020 ), based on the limited nature of the outcomes reported in these studies (i.e. percentage of students engaging in a specific behaviour).

Search Strategy and Information Sources

Searches were conducted in July and August 2022. Searches were first undertaken using the ERIC education research database (eric.ed.gov) and then with Google Scholar. We used Google Scholar since it covers grey literature (Haddaway et al., 2015 ), including unpublished Masters and PhD theses (Jamali & Nabavi, 2015 ) as well as preprints. The Google Scholar search interface is limited, and the search returns can include non-research documents search as citations, university policies and handbooks on academic integrity, and multiple versions of papers (Boeker et al., 2013 ). It is also not possible to exclude the results of one search from another. Thus it is not possible for us to report accurately the numbers of included papers returned from each term. ‘Daisy chaining’ was also used to identify relevant research from studies that had already been identified using the aforementioned literature searches, and recent reviews on the subject (Butler-Henderson & Crawford, 2020 ; Chiang et al., 2022 ; Garg & Goel, 2022 ; Holden et al., 2021 ; Noorbehbahani et al., 2022 ; Surahman & Wang, 2022 ).

Selection Process

Search results were individually assessed against the inclusion/exclusion criteria, starting with the title, followed by the abstract and then the full text. If a study clearly did not meet the inclusion criteria based on the title then it was excluded. If the author was unsure, then the abstract was reviewed. If there was still uncertainty, then the full text was reviewed. When a study met the inclusion criteria (see below), the specific question used in that study to quantify online exam cheating was then itself also used as a search term. Thus the full list of search terms used is shown in Supplementary Online Material S1 .

Eligibility Criteria

The following criteria were used to determine whether to include samples. Many studies included multiple datasets (e.g. samples comprising different groups of students, across different years). The criteria here were applied to individual datasets.

Inclusion Criteria

Participants were asked whether they had ever cheated in an online exam (self-report).

Participants were students in Higher Education.

Reported both total sample size and percent of respondents answering yes to the relevant exam cheating questions, or sufficient data to allow those metrics to be calculated.

English language publication.

Published 2013-present, with data collected 2012-present. We wanted to evaluate a 10 year timeframe. In 2013, at the beginning of this time window, the average time needed to publish an academic paper was 12.2 months, ranging from 9 months (chemistry) to 18 months (Business) (Björk & Solomon, 2013 ). It would therefore be reasonable to conclude that a paper published in 2013 was most likely submitted in 2012. Thus we included papers whose publication date was 2013 onwards, unless the manuscript itself specifically stated that the data were collected prior to 2012.

Exclusion Criteria

Asking participants would they cheat in exams (e.g. Morales-Martinez et al., 2019 ), or did not allow for a distinction between self-report of intent and actual cheating (e.g. Ghias et al., 2014 ).

Phrasing of survey items in a way that does not allow for frequency of online exam cheating to be specifically identified according to the criteria above. Wherever necessary, study authors were contacted to clarify.

Asking participants ‘how often do others cheat in online exams’.

Asking participants about helping other students to cheat.

Schools, community colleges/further education, MOOCS.

Cheating in formative exams, or did not distinguish between formative/summative (e.g. quizzes/exams (e.g. Alvarez, Homer et al., 2022 ; Costley, 2019 ).

Estimates of cheating from learning analytics or other methods which did not include directly asking participants if they had cheated.

Published in a predatory journal (see below).

Predatory Journal Criteria

Predatory journals and publishers are defined as “ entities which prioritize self-interest at the expense of scholarship and are characterised by false or misleading information, deviation from best editorial and publication practices, a lack of transparency, and/or the use of aggressive and indiscriminate solicitation practices .” (Grudniewicz et al., 2019 ). The inclusion of predatory journals in literature reviews may therefore have a negative impact on the data, findings and conclusions. We followed established guidelines for the identification and exclusion of predatory journals from the findings (Rice et al., 2021 ):

Each study which met the inclusion criteria was checked for spelling, punctuation and grammar errors as well as logical inconsistencies.

Every included journal was checked against open access criteria;

If the journal was listed on the Directory of Open Access Journals (DOAJ) database (DOAJ.org) then it was considered to be non-predatory.

If the journal was not present in the DOAJ database, we looked for it in the Committee on Publication Ethics (COPE) database (publicationethics.org). If the journal was listed on the COPE database then it was considered to be non-predatory.

Only one paper met these criteria, containing logical inconsistencies and not listed on either DOAJ or COPE. For completeness we also searched an informal list of predatory journals ( https://beallslist.net ) and the journal was listed there. Thus the study was excluded.

All data were extracted by both authors independently. Where the extracted data differed between authors then this was clarified through discussion. Data extracted were, where possible, as follows:

Author/date

Year of Publication

Year study was undertaken . If this was a range (e.g. Nov 2016-Apr 2017) then the most recent year was used as the data point (e.g. 2017 in the example). If it was not reported when the study was undertaken, then we recorded the year that the manuscript was submitted. If none of these data were available then the publication year was entered as the year that the study was undertaken.

Publication type. Peer reviewed journal publication, peer reviewed conference proceedings or dissertation/thesis.

Population size. The total number of participants in the population, from which the sample is drawn and supposed to represent. For example, if the study is surveying ‘business students at University X’, is it clear how many business students are currently at University X?

Number Sampled. The number of potential participants, from the population, who were asked to fill in the survey.

N . The number of survey respondents.

Cheated in online summative examinations . The number of participants who answered ‘yes’ to having cheated in online exams. Some studies recorded the frequency of cheating on a scale, for example a 1–5 Likert scale from ‘always’ to ‘never’. In these cases, we collapsed all positive reports into a single number of participants who had ever cheated in online exams. Some studies did not ask for a total rate of cheating (i.e. cheating by any/all methods) and so, for analysis purposes the method with the highest rate of cheating was used (see Results).

Group/individual cheating. Where appropriate, the frequency of cheating via different methods was recorded. These were coded according to the highest level of the framework proposed by Noorbehbahani (Noorbehbahani et al., 2022 ), i.e. group vs. individual. More fine-grained analysis was not possible due to the number and nature of the included studies.

Study Risk of Bias and Quality metrics

Response rate . Defined as “ the percentage of people who completed the survey after being asked to do so” (Halbesleben & Whitman, 2013 ).

Method of sampling. As one of the following; convenience sampling, where all members of the population were able to complete the survey, but data were analysed from those who voluntarily completed it. ‘Unclassifiable’ where it was not possible to determine the sampling method based on the data provided (no other sampling methods were used in the included studies).

Ethics. Was it reported whether ethical/IRB approval had been obtained? (note that a recording of ‘N’ here does not mean that ethical approval was not obtained, just that it is not reported)

Anonymity . Were participants assured that they were answering anonymously? Students who are found to have cheated in exams can be given severe penalties, and so a statement of anonymity (not just confidentiality) is important for obtaining meaningful data.

Synthesis Methods

Data are reported as mean ± SEM unless otherwise stated. Datasets were tested for normal distribution using a Kolmogorov-Smirnov test prior to analysis and parametric tests were used if the data were found to be normally distributed. The details of the specific tests used are in the relevant results section.

25 samples were identified from 19 studies, containing a total of 4672 participants. Three studies contained multiple distinct samples from different participants (e.g. data was collected in different years (Case et al., 2019 ; King & Case, 2014 ), or were split by two different programmes of study (Burgason et al., 2019 ), or whether exams were proctored or not (Owens, 2015 ). Thus, these samples were treated as distinct in the analysis since they represent different participants. Multiple studies asked the same groups of participants about different types of cheating, or the conditions under which cheating happens. The analysis of these is explained in the relevant results subsection. A summary of the studies is in Table 1 . The detail of each individual question asked to study participants is in supplementary online data S2 .

Descriptive Metrics of Studies

Sampling method.

23/25 samples were collected using convenience sampling. The remaining two did not provide sufficient information to determine the method of sampling.

Population Size

Only two studies reported the population size.

Sample Size

The average sample size was 188.7 ± 36.16.

Response Rate

Fifteen of the samples did not report sufficient information to allow a response rate to be calculated. The ten remaining samples returned an average response rate of 55.6% ±10.7, with a range from 12.2 to 100%.

Eighteen of the 23 samples (72%) stated that participant responses were collected anonymously.

Seven of the 25 samples (28%) reported that ethical approval was obtained for the study.

How Common is Self-Reported Online Exam Cheating in Higher Education?

44.7% of participants (2088/4672) reported engaging in some form of cheating in online exams. This analysis included those studies where total cheating was not recorded, and so the most commonly reported form of cheating was substituted in. To check the validity of this inclusion, a separate analysis was conducted of only those studies where total cheating was recorded. In this case, 42.5% of students (1574/3707) reported engaging in some form of cheating. An unpaired t -test was used to compare the percentage cheating from each group (total vs. highest frequency), and returned no significant difference ( t (23) = 0.5926, P = 0.56).

Did the Frequency of Online Exam Cheating Increase During COVID?

The samples were classified as having been collected pre-COVID, or during COVID (no samples were identified as having been collected ‘post-COVID’). One study (Jenkins et al., 2022 ) asked the same students about their behaviour before, and during, COVID. For the purposes of this specific analysis, these were included as separate samples, thus there were 26 samples, 17 pre-COVID and 9 during COVID. Pre-COVID, 29.9% (629/2107) of participants reported cheating in online exams. During COVID this figure was 54.7% (1519/2779).

To estimate the variance in these data, and to test whether the difference was statistically significant, the percentages of students who reported cheating for each study were grouped into pre-and during-COVID and the average calculated for each group. The average pre-COVID was 28.03% ± 4.89, (N = 17), whereas during COVID the average is 65.06 ± 9.585 (N = 9). An unpaired t- test was used to compare the groups, and returned a statistically significant difference ( t (24) = 3.897, P = 0.0007). The effect size (Hedges g) was 1.61, indicating that the COVID effect was substantial (Fig. 1 ).

Increased self-report of cheating in online exams during the COVID-19 pandemic. Data represent the mean ± SEM of the percentages of students who self-report cheating in online exams pre-and-during COVID. *** = P < 0.005 unpaired t- test

To test the reliability of this result, we conducted a split sample test as in other systematic reviews of the prevalence of academic misconduct (Newton, 2018 ), wherein the data for each group were ordered by size and then every other sample was extracted into a separate group. So, the sample with the lowest frequency of cheating was allocated into Group A, the next smallest into Group B, the next into Group A, and so on. This was conducted separately for the pre-COVID and ‘during COVID’. Each half-group was then subject to an unpaired t- test to determine whether cheating increased during COVID in that group. Each group returned a significant difference ( t (10) = 2.889 P = 0.0161 for odd-numbered samples, t (12) = 2.48, P = 0.029 for even-numbered samples. This analysis gives confidence that the observed increase in self-reported online exam cheating during the pandemic is statistically robust, although there may be other variables which contribute to this (see discussion).

Comparison of Group vs. Individual Online Exam Cheating in Higher Education

In order to consider how best to address cheating in online exams, it is important to understand the specific behaviours of students. Many studies asked multiple questions about different types of cheating, and these were coded according to the typology developed by Noorbehbehani which has a high-level code of ‘individual’ and ‘group’ (Noorbehbahani et al., 2022 ). More fine-grained coding was not possible due to the variance in the types of questions asked of participants (see S2). ‘Individual’ cheating meant that, whatever the type of cheating, it could be achieved without the direct help of another person. This could be looking at notes or textbooks, or searching for materials online. ‘Group’ cheating meant that another person was directly involved, for example by sharing answers, or having them sit the exam on behalf of the participant (contract cheating). Seven studies asked their participants whether they had engaged in different forms of cheating where both formats (Group and Individual) were represented. For each study we ranked all the different forms of cheating by the frequency with which participants reported engaging in it. For all seven of the studies which asked about both Group and Individual cheating, the most frequently reported cheating behaviour was an Individual cheating behaviour. For each study we calculated the difference between the two by subtracting the frequency of the most commonly reported Group cheating behaviour from the frequency of the most commonly reported Individual cheating behaviour. The average difference was 23.32 ± 8.0% points. These two analyses indicate that individual forms of cheating are more common than cheating which involves other people.

Effect of Proctoring/Lockdown Browsers

The majority of studies did not make clear whether their online exams were proctored or unproctored, or whether they involved the use of related software such as lockdown browsers. Thus it was difficult to conduct definitive analyses to address the question of whether these systems reduce online exam cheating. Two studies did specifically address this issue in both cases there was a substantially lower rate of self-reported cheating where proctoring systems were used. Jenkins et al., in a study conducted during COVID, asked participants whether their instructors used ‘anti cheating software (e.g., Lockdown Browser)’ and, if so, whether they had tried to circumvent it. 16.5% admitted to doing this, compared to the overall rate of cheating of 58.4%. Owens asked about an extensive range of different forms of misconduct, in two groups of students whose online exams were either proctored or unproctored. The total rates of cheating in each group did not appear to be reported. The most common form of cheating was the same in both groups (‘web search during an exam’) and was reported by 39.8% of students in the unproctored group but by only 8.5% in the proctored group (Owens, 2015 ).

Reasons Given for Online Exam Cheating

Ten of the studies asked students why they cheated in online exams. These reasons were initially coded by both authors according to the typology provided in (Noorbehbahani et al., 2022 ). Following discussion between the authors, the typology was revised slightly to that shown in Table 1 , to better reflect the reasons given in the reviewed studies.

Descriptive statistics (the percentages of students reporting the different reasons as motivations for cheating) are shown in Table 2 . Direct comparison between the reasons is not fully valid since different studies asked for different options, and some studies offered multiple options whereas some only identified one. However in the four studies that offered multiple options to students, three of them ranked ‘opportunities to cheat’ as the most common reason (and the fourth study did not have this as an option). Thus students appear to be most likely to cheat in online exams when there is an opportunity to do so.

We reviewed data from 19 studies, including 25 samples totaling 4672 participants. We found that a substantial proportion of students, 44.7%, were willing to admit to cheating in online summative exams. This total number masks a finding that cheating in online exams appeared to increase considerably during the COVID-19 pandemic, from 29.9 to 54.7%. These are concerning findings. However, there are a number of methodological considerations which influence the interpretation of these data. These considerations all lead to uncertainty regarding the accuracy of the findings, although a common theme is that, unfortunately, the issues highlighted seem likely to result in an under-reporting of the rate of cheating in online exams.

There are numerous potential sources of error in survey-based research, and these may be amplified where the research is asking participants to report on sensitive or undesirable behaviours. One of these sources of error comes from non-respondents, i.e. how confident can we be that those who did not respond to the survey would have given a similar pattern of responses to those that did (Goyder et al., 2002 ; Halbesleben & Whitman, 2013 ; Sax et al., 2003 ). Two ways to minimize non-respondent error are to increase the sample size as a percentage of the population, and then simply to maximise the percentage of the invited sample who responds to the survey. However only nine of the samples reported sufficient information to even allow the calculation of a response rate, and only two reported the total population size. Thus for the majority of samples reported here, we cannot even begin to estimate the extent of the non-response error. For those that did report sufficient information, the response rate varied considerably, from 12.2% to 100, with an average of 55.6%. Thus a substantial number of the possible participants did not respond.

Most of the surveys reviewed here were conducted using convenience sampling, i.e. participation was voluntary and there was no attempt to ensure that the sample was representative, or that the non-respondents were followed up in a targeted way to increase the representativeness of the sample. People who voluntarily respond to survey research are, compared to the general population, older, wealthier, more likely to be female and educated (Curtin et al., 2000 ). In contrast, individuals who engage in academic misconduct are more likely to be male, younger, from a lower socioeconomic background and less academically able (reviewed in Newton, 2018 ). Thus the features of the survey research here would suggest that the rates of online exam cheating are under-reported.

A second source of error is measurement error – for example, how likely is it that those participants who do respond are telling the truth? Cheating in online exams is clearly a sensitive subject for potential survey participants. Students who are caught cheating in exams can face severe penalties. Measurement error can be substantial when asking participants about sensitive topics, particularly when they have no incentive to respond truthfully. Curtis et al. conducted an elegant study to investigate rates of different types of contract cheating and found that rates were substantially higher when participants were incentivized to tell the truth, compared to traditional self-report (Curtis et al., 2022 ). Another method to increase truthfulness is to use a Randomised Response Technique, which increases participants confidence that their data will be truly anonymous when self-reporting cheating (Mortaz Hejri et al., 2013 ) and so leads to increased estimates of the prevalence of cheating behaviours when measured via self-report (Kerkvliet, 1994 ; Scheers & Dayton, 1987 ). No studies reviewed here reported any incentivization or use of a randomized response technique, and many did not report IRB (ethical) approval or that participants were guaranteed anonymity in their responses. Absence of evidence is not evidence of absence, but it again seems reasonable to conclude that the majority of the measurement error reported here will also lead to an under-reporting of the extent of online exam cheating.

However, there are very many variables associated with likelihood of committing academic misconduct (also reviewed in Newton, 2018 ). For example, in addition to the aforementioned variables, cheating is also associated with individual differences such as personality traits (Giluk & Postlethwaite, 2015 ; Williams & Williams, 2012 ), motivation (Park et al., 2013 ), age and gender (Newstead et al., 1996 ) and studying in a second language (Bretag et al., 2019 ) as well as situational variables such as discipline studied (Newstead et al., 1996 ). None of the studies reviewed here can account for these individual variables, and this perhaps explains, partly, the wide variance in the studies reported, where the percentage of students willing to admit to cheating in online exams ranges from essentially none, to all students, in different studies. However, almost all of the variables associated with differences in likelihood of committing academic misconduct were themselves determined using convenience sampling. In order to begin to understand the true nature, scale and scope of academic misconduct, there is a clear need for studies using large, representative samples, with appropriate methodology to account for non-respondents, and rigorous analyses which attempt to identify those variables associated with an increased likelihood of cheating.

There are some specific issues which must be considered when determining the accuracy of the data showing an increase in cheating during COVID. In general, the pre-COVID group appears to be a more homogenous set of samples, for example, 11 of the 16 samples are from students studying business, and 15 of the 16 pre-COVID samples are from the USA. The during-COVID samples are from a much more diverse range of disciplines and countries. However the increase in self-reported cheating was replicated in the one study which directly asked students about their behaviour before, and during, the pandemic; Jenkins and co-workers found that 28.4% of respondents were cheating pre-COVID, nearly doubling to 58.4% during the pandemic (Jenkins et al., 2022 ), very closely mirroring the aggregate results.

There are some other variables which may be different between the studies and so affect the overall interpretation of the findings. For example, the specific questions asked of participants, as shown in the supplemental online material ( S2 ) reveal that most studies do not report on the specific type of exam (e.g. multiple choice vs. essay based), or the exam duration, weighting, or educational level. This is likely because the studies survey groups of students, across programmes. Having a more detailed understanding of these factors would also inform strategies to address cheating in online exams.

It is difficult to quantify the potential impact of these issues on the accuracy of the data analysed here, since objective measures of cheating in online exams are difficult to obtain in higher education settings. One way to achieve this is to set up traps for students taking closed-book exams. One study tested this using a 2.5 h online exam administered for participants to obtain credit from a MOOC. The exam was set up so that participants would “likely not benefit from having access to third-party reference materials during the exam” . Students were instructed not to access any additional materials or to communicate with others during the exam. The authors built a ‘honeypot’ website which had all of the exam questions on, with a button ‘click to show answer’. If exam participants went online and clicked that button then the site collected information which allowed the researchers to identify the unique i.d. of the test-taker. This approach was combined with a more traditional analysis of the originality of the free-text portions of the exam. Using these methods, the researchers estimated that ~ 30% of students were cheating (Corrigan-Gibbs et al., 2015b ). This study was conducted in 2014-15, and the data align reasonably well with the pre-COVID estimates of cheating found here, giving some confidence that the self-report measures reported here are in the same ball park as objective measures, albeit from only one study.

The challenges of interpreting data from small convenience samples will also affect the analysis of the other measures made here; that students are more likely to commit misconduct on their own, because they can. The overall pattern of findings though does align somewhat, suggesting that concerns may be with the accuracy of the numbers rather than a fundamental qualitative problem (i.e. it seems reasonable to conclude that students are more likely to cheat individually, but it is challenging to put a precise number to that finding). For example, the apparent increase in cheating during COVID is associated with a rapid and near-total transition to online exams. Pre-covid, the use of online exams would have been a choice made by education providers, presumably with some efforts to ensure the security and integrity of that assessment. During COVID lockdown, the scale and speed of the transition to online exams made it much more challenging to put security measures in place, and this would therefore almost certainly have increased the opportunities to cheat.

It was challenging to gather more detail about the specific types of cheating behaviour, due to the considerable heterogeneity between the studies regarding this question. The sector would benefit from future large-scale research using a recognized typology, for example those proposed by Dawson (Dawson, 2020 , p. 112) or Noorbehbahani (Noorbehbahani et al., 2022 ).

Another important recommendation that will help the sector in addressing the problem is for future survey-based research of student dishonesty to make use of the abundant methodological research undertaken to increase the accuracy of such surveys. In particular the use of representative sampling, or analysis methods which account for the challenges posed by unrepresentative samples. Data quality could also be improved by the use of question formats and survey structures which motivate or incentivize truth-telling, for example by the use of methods such as the Randomised Response Technique which increase participant confidence that their responses will be truly anonymous. It would also be helpful to report on key methodological features of survey design; pilot testing, scaling, reliability and validity, although these are commonly underreported in survey based research generally (Bennett et al., 2011 ).

Thus an aggregate portrayal of the findings here is that students are committing misconduct in significant numbers, and that this has increased considerably during COVID. Students appear to be more likely to cheat on their own, rather than in groups, and most commonly motivated by the simple fact that they can cheat. Do these findings and the underlying data give us any information that might be helpful in addressing the problem?

One technique deployed by many universities to address multiple forms of online exam cheating is to increase the use of remote proctoring, wherein student behaviour during online exams is monitored, for example, through a webcam, and/or their online activity is monitored or restricted. We were unable to draw definitive conclusions about the effectiveness of remote proctoring or other software such as lockdown browsers to reduce cheating in online exams, since very few studies stated definitively that the exams were, or were not, proctored. The two studies that examined this question did appear to show a substantial reduction in the frequency of cheating when proctoring was used. Confidence in these results is bolstered by the fact that these studies both directly compared unproctored vs. proctored/lockdown browser. Other studies have used proxy measures for cheating, such as time engaged with the exam, and changes in exams scores, and these studies have also found evidence for a reduction in misconduct when proctoring is used (e.g. (Dendir & Maxwell, 2020 ).

The effectiveness (or not) of remote proctoring to reduce academic misconduct seems like an important area for future research. However there is considerable controversy about the use of remote proctoring, including legal challenges to its use and considerable objections from students, who report a net negative experience, fuelled by concerns about privacy, fairness and technological challenges (Marano et al., 2023 ), and so it remains an open question whether this is a viable option for widespread general use.

Honour codes are a commonly cited approach to promoting academic integrity, and so (in theory) reducing academic misconduct. However, empirical tests of honour codes show that they do not appear to be effective at reducing cheating in online exams (Corrigan-Gibbs et al., 2015a , b ). In these studies the authors likened them to ‘terms and conditions’ for online sites, which are largely disregarded by users in online environments. However in those same studies the authors found that replacing an honour code with a more sternly worded ‘warning’, which specifies the consequences of being caught, was effective at reducing cheating. Thus a warning may be a simple, low-cost intervention to reduce cheating in online exams, whose effectiveness could be studied using appropriately conducted surveys of the type reviewed here.

Another option to reduce cheating in online exams is to use open-book exams. This is often suggested as a way of simultaneously increasing the cognitive level of the exam (i.e. it assesses higher order learning) (e.g. (Varble, 2014 ), and was suggested as a way of reducing the perceived, or potential increase in academic misconduct during COVID (e.g. (Nguyen et al., 2020 ; Whisenhunt et al., 2022 ). This approach has an obvious appeal in that it eliminates the possibility of some common forms of misconduct, such as the use of notes or unauthorized web access (Noorbehbahani et al., 2022 ; Whisenhunt et al., 2022 ), and can even make this a positive feature, i.e. encouraging the use of additional resources in a way that reflects the fact that, for many future careers, students will have access to unlimited information at their fingertips, and the challenge is to ensure that students have learned what information they need and how to use it. This approach certainly fits with our data, wherein the most frequently reported types of misconduct involved students acting alone, and cheating ‘because they could’. Some form of proctoring or other measure may still be needed in order to reduce the threat of collaborative misconduct. Perhaps most importantly though, it is unclear whether open-book exams truly reduce the opportunity for, and the incidence of, academic misconduct, and if so, how might we advise educators to design their exams, and exam question, in a way that delivers this as well as the promise of ‘higher order’ learning. These questions are the subject of ongoing research.

In summary then, there appears to be significant levels of misconduct in online examinations in Higher Education. Students appear to be more likely to cheat on their own, motivated by an examination design and delivery which makes it easy for them to do so. Future research in academic integrity would benefit from large, representative samples using clear and unambiguous survey questions and guarantees of anonymity. This will allow us to get a much better picture of the size and nature of the problem, and so design strategies to mitigate the threat that cheating poses to exam validity.

Alvarez, Homer, T., Reynald, S., Dayrit, Maria Crisella, A., Dela Cruz, C. C., Jocson, R. T., Mendoza, A. V., & Reyes (2022). & Joyce Niña N. Salas. Academic dishonesty cheating in synchronous and asynchronous classes: A proctored examination intervention. International Research Journal of Science, Technology, Education, and Management , 2 (1), 1–1.

Armstrong-Mensah, E., Ramsey-White, K., Yankey, B., & Self-Brown, S. (2020). COVID-19 and Distance Learning: Effects on Georgia State University School of Public Health Students. Frontiers in Public Health , 8 . https://www.frontiersin.org/articles/ https://doi.org/10.3389/fpubh.2020.576227 .

Barber, M., Bird, L., Fleming, J., Titterington-Giles, E., Edwards, E., & Leyland, C. (2021). Gravity assist: Propelling higher education towards a brighter future - Office for Students (Worldwide). Office for Students. https://www.officeforstudents.org.uk/publications/gravity-assist-propelling-higher-education-towards-a-brighter-future/ .

Bennett, C., Khangura, S., Brehaut, J. C., Graham, I. D., Moher, D., Potter, B. K., & Grimshaw, J. M. (2011). Reporting guidelines for Survey Research: An analysis of published Guidance and Reporting Practices. PLOS Medicine , 8 (8), e1001069. https://doi.org/10.1371/journal.pmed.1001069 .

Article Google Scholar

Björk, B. C., & Solomon, D. (2013). The publishing delay in scholarly peer-reviewed journals. Journal of Informetrics , 7 (4), 914–923. https://doi.org/10.1016/j.joi.2013.09.001 .

Blinova, O., & WHAT COVID TAUGHT US ABOUT ASSESSMENT: STUDENTS’ PERCEPTIONS OF ACADEMIC INTEGRITY IN DISTANCE LEARNING. (2022). INTED2022 Proceedings , 6214–6218. https://doi.org/10.21125/inted.2022.1576 .

Boeker, M., Vach, W., & Motschall, E. (2013). Google Scholar as replacement for systematic literature searches: Good relative recall and precision are not enough. BMC Medical Research Methodology , 13 , 131. https://doi.org/10.1186/1471-2288-13-131 .

Bowman, E. (2022, August 26). Scanning students’ rooms during remote tests is unconstitutional, judge rules. NPR . https://www.npr.org/2022/08/25/1119337956/test-proctoring-room-scans-unconstitutional-cleveland-state-university .

Bretag, T., Harper, R., Burton, M., Ellis, C., Newton, P., Rozenberg, P., Saddiqui, S., & van Haeringen, K. (2019). Contract cheating: A survey of australian university students. Studies in Higher Education , 44 (11), 1837–1856. https://doi.org/10.1080/03075079.2018.1462788 .

Brown, M., Hoon, A., Edwards, M., Shabu, S., Okoronkwo, I., & Newton, P. M. (2022). A pragmatic evaluation of university student experience of remote digital learning during the COVID-19 pandemic, focusing on lessons learned for future practice. EdArXiv . https://doi.org/10.35542/osf.io/62hz5 .

Burgason, K. A., Sefiha, O., & Briggs, L. (2019). Cheating is in the Eye of the beholder: An evolving understanding of academic misconduct. Innovative Higher Education , 44 (3), 203–218. https://doi.org/10.1007/s10755-019-9457-3 .

Butler-Henderson, K., & Crawford, J. (2020). A systematic review of online examinations: A pedagogical innovation for scalable authentication and integrity. Computers & Education , 159 , 104024. https://doi.org/10.1016/j.compedu.2020.104024 .

Case, C. J., King, D. L., & Case, J. A. (2019). E-Cheating and Undergraduate Business Students: Trends and Role of Gender. Journal of Business and Behavioral Sciences , 31 (1). https://www.proquest.com/openview/9fcc44254e8d6d202086fc58818fab5d/1?pq-origsite=gscholar&cbl=2030637 .

Chiang, F. K., Zhu, D., & Yu, W. (2022). A systematic review of academic dishonesty in online learning environments. Journal of Computer Assisted Learning , 38 (4), 907–928. https://doi.org/10.1111/jcal.12656 .

Corbyn, Z. (2022, August 26). ‘I’m afraid’: Critics of anti-cheating technology for students hit by lawsuits. The Guardian . https://www.theguardian.com/us-news/2022/aug/26/anti-cheating-technology-students-tests-proctorio .

Corrigan-Gibbs, H., Gupta, N., Northcutt, C., Cutrell, E., & Thies, W. (2015a). Measuring and maximizing the effectiveness of Honor Codes in Online Courses. Proceedings of the Second (2015) ACM Conference on Learning @ Scale , 223–228. https://doi.org/10.1145/2724660.2728663 .

Corrigan-Gibbs, H., Gupta, N., Northcutt, C., Cutrell, E., & Thies, W. (2015b). Deterring cheating in Online environments. ACM Transactions on Computer-Human Interaction , 22 (6), 28:1–2823. https://doi.org/10.1145/2810239 .

Costley, J. (2019). Student perceptions of academic dishonesty at a Cyber-University in South Korea. Journal of Academic Ethics , 17 (2), 205–217. https://doi.org/10.1007/s10805-018-9318-1 .

Curtin, R., Presser, S., & Singer, E. (2000). The Effects of Response Rate Changes on the index of consumer sentiment. Public Opinion Quarterly , 64 (4), 413–428. https://doi.org/10.1086/318638 .

Curtis, G. J., McNeill, M., Slade, C., Tremayne, K., Harper, R., Rundle, K., & Greenaway, R. (2022). Moving beyond self-reports to estimate the prevalence of commercial contract cheating: An australian study. Studies in Higher Education , 47 (9), 1844–1856. https://doi.org/10.1080/03075079.2021.1972093 .

Dawson, R. J. (2020). Defending Assessment Security in a Digital World: Preventing E-Cheating and Supporting Academic Integrity in Higher Education (1st ed.). Routledge. https://www.routledge.com/Defending-Assessment-Security-in-a-Digital-World-Preventing-E-Cheating/Dawson/p/book/9780367341527 .

Dendir, S., & Maxwell, R. S. (2020). Cheating in online courses: Evidence from online proctoring. Computers in Human Behavior Reports , 2 , 100033. https://doi.org/10.1016/j.chbr.2020.100033 .

Dumulescu, D., & Muţiu, A. I. (2021). Academic Leadership in the Time of COVID-19—Experiences and Perspectives. Frontiers in Psychology , 12 . https://www.frontiersin.org/article/ https://doi.org/10.3389/fpsyg.2021.648344 .

Ebaid, I. E. S. (2021). Cheating among Accounting Students in Online Exams during Covid-19 pandemic: Exploratory evidence from Saudi Arabia. Asian Journal of Economics Finance and Management , 9–19.

Elsalem, L., Al-Azzam, N., Jum’ah, A. A., & Obeidat, N. (2021). Remote E-exams during Covid-19 pandemic: A cross-sectional study of students’ preferences and academic dishonesty in faculties of medical sciences. Annals of Medicine and Surgery , 62 , 326–333. https://doi.org/10.1016/j.amsu.2021.01.054 .

Fanelli, D. (2009). How many scientists fabricate and falsify Research? A systematic review and Meta-analysis of Survey Data. PLOS ONE , 4 (5), e5738. https://doi.org/10.1371/journal.pone.0005738 .

Gardner, W. M., Roper, J. T., Gonzalez, C. C., & Simpson, R. G. (1988). Analysis of cheating on academic assignments. The Psychological Record , 38 (4), 543–555. https://doi.org/10.1007/BF03395046 .

Garg, M., & Goel, A. (2022). A systematic literature review on online assessment security: Current challenges and integrity strategies. Computers & Security , 113 , 102544. https://doi.org/10.1016/j.cose.2021.102544 .

Gaskill, M. (2014). Cheating in Business Online Learning: Exploring Students’ Motivation, Current Practices and Possible Solutions. Theses, Student Research, and Creative Activity: Department of Teaching, Learning and Teacher Education . https://digitalcommons.unl.edu/teachlearnstudent/35 .

Ghias, K., Lakho, G. R., Asim, H., Azam, I. S., & Saeed, S. A. (2014). Self-reported attitudes and behaviours of medical students in Pakistan regarding academic misconduct: A cross-sectional study. BMC Medical Ethics , 15 (1), 43. https://doi.org/10.1186/1472-6939-15-43 .

Giluk, T. L., & Postlethwaite, B. E. (2015). Big five personality and academic dishonesty: A meta-analytic review. Personality and Individual Differences , 72 , 59–67. https://doi.org/10.1016/j.paid.2014.08.027 .

Goff, D., Johnston, J., & Bouboulis, B. (2020). Maintaining academic Standards and Integrity in Online Business Courses. International Journal of Higher Education , 9 (2). https://econpapers.repec.org/article/jfrijhe11/v_3a9_3ay_3a2020_3ai_3a2_3ap_3a248.htm .

Goyder, J., Warriner, K., & Miller, S. (2002). Evaluating Socio-economic status (SES) Bias in Survey Nonresponse. Journal of Official Statistics , 18 (1), 1–11.

Google Scholar

Grudniewicz, A., Moher, D., Cobey, K. D., Bryson, G. L., Cukier, S., Allen, K., Ardern, C., Balcom, L., Barros, T., Berger, M., Ciro, J. B., Cugusi, L., Donaldson, M. R., Egger, M., Graham, I. D., Hodgkinson, M., Khan, K. M., Mabizela, M., Manca, A., & Lalu, M. M. (2019). Predatory journals: No definition, no defence. Nature , 576 (7786), 210–212. https://doi.org/10.1038/d41586-019-03759-y .

Haddaway, N. R., Collins, A. M., Coughlin, D., & Kirk, S. (2015). The role of Google Scholar in evidence reviews and its applicability to Grey Literature Searching. Plos One , 10 (9), https://doi.org/10.1371/journal.pone.0138237 .

Halbesleben, J. R. B., & Whitman, M. V. (2013). Evaluating Survey Quality in Health Services Research: A decision Framework for assessing Nonresponse Bias. Health Services Research , 48 (3), 913–930. https://doi.org/10.1111/1475-6773.12002 .

Henry, J. (2022, July 17). Universities “turn blind eye to online exam cheats” as fraud rises. Mail Online . https://www.dailymail.co.uk/news/article-11021269/Universities-turning-blind-eye-online-exam-cheats-studies-rates-fraud-risen.html .

Holden, O. L., Norris, M. E., & Kuhlmeier, V. A. (2021). Academic Integrity in Online Assessment: A Research Review. Frontiers in Education , 6 . https://www.frontiersin.org/articles/ https://doi.org/10.3389/feduc.2021.639814 .

Jamali, H. R., & Nabavi, M. (2015). Open access and sources of full-text articles in Google Scholar in different subject fields. Scientometrics , 105 (3), 1635–1651. https://doi.org/10.1007/s11192-015-1642-2 .

Janke, S., Rudert, S. C., Petersen, Ä., Fritz, T. M., & Daumiller, M. (2021). Cheating in the wake of COVID-19: How dangerous is ad-hoc online testing for academic integrity? Computers and Education Open , 2 , 100055. https://doi.org/10.1016/j.caeo.2021.100055 .

Jantos, A., & IN SUMMATIVE E-ASSESSMENT IN HIGHER EDUCATION - A QUANTITATIVE ANALYSIS. (2021). MOTIVES FOR CHEATING. EDULEARN21 Proceedings , 8766–8776. https://doi.org/10.21125/edulearn.2021.1764 .

Jenkins, B. D., Golding, J. M., Grand, L., Levi, A. M., M. M., & Pals, A. M. (2022). When Opportunity knocks: College Students’ cheating amid the COVID-19 pandemic. Teaching of Psychology , 00986283211059067. https://doi.org/10.1177/00986283211059067 .

Jones, I. S., Blankenship, D., Hollier, G., & I CHEATING? AN ANALYSIS OF ONLINE STUDENT PERCEPTIONS OF THEIR BEHAVIORS AND ATTITUDES. (2013). AM. Proceedings of ASBBS , 59–69. http://asbbs.org/files/ASBBS2013V1/PDF/J/Jones_Blankenship_Hollier(P59-69).pdf .

Kerkvliet, J. (1994). Cheating by Economics students: A comparison of Survey results. The Journal of Economic Education , 25 (2), 121–133. https://doi.org/10.1080/00220485.1994.10844821 .

King, D. L., & Case, C. J. (2014). E-CHEATING: INCIDENCE AND TRENDS AMONG COLLEGE STUDENTS. Issues in Information Systems , 15 (1), 20–27. https://doi.org/10.48009/1_iis_2014_20-27 .

Knox, P. (2021). Students “taking it in turns to answer exam questions” during home tests. The Sun . https://www.thesun.co.uk/news/15413811/students-taking-turns-exam-questions-cheating-lockdown/ .

Larkin, C., & Mintu-Wimsatt, A. (2015). Comparing cheating behaviors among graduate and undergraduate Online Business Students—ProQuest. Journal of Higher Education Theory and Practice , 15 (7), 54–62.

Marano, E., Newton, P. M., Birch, Z., Croombs, M., Gilbert, C., & Draper, M. J. (2023). What is the Student Experience of Remote Proctoring? A Pragmatic Scoping Review . EdArXiv. https://doi.org/10.35542/osf.io/jrgw9 .

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Group, T. P. (2009). Preferred reporting items for systematic reviews and Meta-analyses: The PRISMA Statement. PLOS Medicine , 6 (7), e1000097. https://doi.org/10.1371/journal.pmed.1000097 .

Morales-Martinez, G. E., Lopez-Ramirez, E. O., & Mezquita-Hoyos, Y. N. (2019). Cognitive mechanisms underlying the Engineering Students’ Desire to Cheat during Online and Onsite Statistics Exams. Cognitive mechanisms underlying the Engineering Students’ Desire to Cheat during Online and Onsite Statistics Exams , 8 (4), 1145–1158.

Mortaz Hejri, S., Zendehdel, K., Asghari, F., Fotouhi, A., & Rashidian, A. (2013). Academic disintegrity among medical students: A randomised response technique study. Medical Education , 47 (2), 144–153. https://doi.org/10.1111/medu.12085 .

Newstead, S. E., Franklyn-Stokes, A., & Armstead, P. (1996). Individual differences in student cheating. Journal of Educational Psychology , 88 , 229–241. https://doi.org/10.1037/0022-0663.88.2.229 .

Newton, P. M. (2018). How Common Is Commercial Contract Cheating in Higher Education and Is It Increasing? A Systematic Review. Frontiers in Education , 3 . https://www.frontiersin.org/article/ https://doi.org/10.3389/feduc.2018.00067 .

Newton, P. M., & Salvi, A. (2020). How Common Is Belief in the Learning Styles Neuromyth, and Does It Matter? A Pragmatic Systematic Review. Frontiers in Education , 5 . https://doi.org/10.3389/feduc.2020.602451 .

Nguyen, J. G., Keuseman, K. J., & Humston, J. J. (2020). Minimize Online cheating for online assessments during COVID-19 pandemic. Journal of Chemical Education , 97 (9), 3429–3435. https://doi.org/10.1021/acs.jchemed.0c00790 .

Noorbehbahani, F., Mohammadi, A., & Aminazadeh, M. (2022). A systematic review of research on cheating in online exams from 2010 to 2021. Education and Information Technologies . https://doi.org/10.1007/s10639-022-10927-7 .

Owens, H. (2015). Cheating within Online Assessments: A Comparison of Cheating Behaviors in Proctored and Unproctored Environment. Theses and Dissertations . https://scholarsjunction.msstate.edu/td/1049 .

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Bmj , 71. https://doi.org/10.1136/bmj.n71 .

Park, E. J., Park, S., & Jang, I. S. (2013). Academic cheating among nursing students. Nurse Education Today , 33 (4), 346–352. https://doi.org/10.1016/j.nedt.2012.12.015 .

Pokhrel, S., & Chhetri, R. (2021). A Literature Review on Impact of COVID-19 pandemic on teaching and learning. Higher Education for the Future , 8 (1), 133–141. https://doi.org/10.1177/2347631120983481 .

Rice, D. B., Skidmore, B., & Cobey, K. D. (2021). Dealing with predatory journal articles captured in systematic reviews. Systematic Reviews , 10 , 175. https://doi.org/10.1186/s13643-021-01733-2 .

Romaniuk, M. W., & Łukasiewicz-Wieleba, J. (2022). Remote and stationary examinations in the opinion of students. International Journal of Electronics and Telecommunications , 68 (1), 69.

Sax, L. J., Gilmartin, S. K., & Bryant, A. N. (2003). Assessing response Rates and Nonresponse Bias in web and paper surveys. Research in Higher Education , 44 (4), 409–432. https://doi.org/10.1023/A:1024232915870 .

Scheers, N. J., & Dayton, C. M. (1987). Improved estimation of academic cheating behavior using the randomized response technique. Research in Higher Education , 26 (1), 61–69. https://doi.org/10.1007/BF00991933 .

Shute, V. J., & Kim, Y. J. (2014). Formative and Stealth Assessment. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of Research on Educational Communications and Technology (pp. 311–321). Springer. https://doi.org/10.1007/978-1-4614-3185-5_25 .

Subotic, D., & Poscic, P. (2014). Academic dishonesty in a partially online environment: A survey. Proceedings of the 15th International Conference on Computer Systems and Technologies , 401–408. https://doi.org/10.1145/2659532.2659601 .

Surahman, E., & Wang, T. H. (2022). Academic dishonesty and trustworthy assessment in online learning: A systematic literature review. Journal of Computer Assisted Learning , n/a (n/a). https://doi.org/10.1111/jcal.12708 .

Tahsin, M. U., Abeer, I. A., & Ahmed, N. (2022). Note: Cheating and Morality Problems in the Tertiary Education Level: A COVID-19 Perspective in Bangladesh. ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (COMPASS) , 589–595. https://doi.org/10.1145/3530190.3534834 .

Valizadeh, M. (2022). CHEATING IN ONLINE LEARNING PROGRAMS: LEARNERS’ PERCEPTIONS AND SOLUTIONS. Turkish Online Journal of Distance Education , 23 (1), https://doi.org/10.17718/tojde.1050394 .

Varble, D. (2014). Reducing Cheating Opportunities in Online Test. Atlantic Marketing Journal , 3 (3). https://digitalcommons.kennesaw.edu/amj/vol3/iss3/9 .

Whisenhunt, B. L., Cathey, C. L., Hudson, D. L., & Needy, L. M. (2022). Maximizing learning while minimizing cheating: New evidence and advice for online multiple-choice exams. Scholarship of Teaching and Learning in Psychology , 8 (2), 140–153. https://doi.org/10.1037/stl0000242 .

Williams, M. W. M., & Williams, M. N. (2012). Academic dishonesty, Self-Control, and General Criminality: A prospective and retrospective study of academic dishonesty in a New Zealand University. Ethics & Behavior , 22 (2), 89–112. https://doi.org/10.1080/10508422.2011.653291 .

Witley, S. (2023). Virtual Exam Case Primes Privacy Fight on College Room Scans (1) . https://news.bloomberglaw.com/privacy-and-data-security/virtual-exam-case-primes-privacy-fight-over-college-room -scans?context=search&index=1.

Zarzycka, E., Krasodomska, J., Mazurczak-Mąka, A., & Turek-Radwan, M. (2021). Distance learning during the COVID-19 pandemic: Students’ communication and collaboration and the role of social media. Cogent Arts & Humanities , 8 (1), 1953228. https://doi.org/10.1080/23311983.2021.1953228 .

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Acknowledgements

We would like to acknowledge the efforts of all the researchers whose work was reviewed as part of this study, and their participants who gave up their time to generate the data reviewed here. We are especially grateful to Professor Carl Case at St Bonaventure University, NY, USA for his assistance clarifying the numbers of students who undertook online exams in King and Case ( 2014 ) and Case et al. ( 2019 ).

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Newton, P.M., Essex, K. How Common is Cheating in Online Exams and did it Increase During the COVID-19 Pandemic? A Systematic Review. J Acad Ethics 22 , 323–343 (2024). https://doi.org/10.1007/s10805-023-09485-5

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Education: Why Do Students Cheat? Essay

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Introduction

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Cheating is a common phenomenon among students at all levels of education. It happens in high schools, colleges, and universities. In addition, it occurs in both traditional and online settings of learning. Students have sufficient time and resources that give them the opportunity to work hard and pass their exams through personal effort (Davis et al. 35). This begs the question: why do students cheat?

Research has revealed that several reasons and factors are responsible for cheating in schools. A study conducted to find out the prevalence of cheating in colleges found out that approximately 75 percent of college students cheat at one time in the course of their stay at school (Davis et al. 36).

There is need to find a lasting solution because cheating does not reflect the real potential of students. Effects of cheating are reflected in students’ performance at workplaces. Students cheat because many schools define excellence through grades, lack of self-confidence with one’s ability, pressure from parents and teachers to do well, and poor teaching methods that do not fulfill the goals of learning (McCabe et al. 51).

Students cheat because many institutions of learning value grades more than attainment of knowledge (Davis et al. 36). Many school systems have placed more value on performing well in tests and examination than on the process of learning. When assessment tests and examinations play a key role in determining the future of a student, cheating becomes an appropriate channel to perform well (McCabe et al. 51).

Few institutions encourage mastery of learning materials rather than tests. In such institutions, students develop a positive attitude towards education because they are not worried about their performance in tests (Davis et al. 37). They focus more on the attainment of knowledge and skills. Psychologists argue that placing high value on tests teaches students to value short-term effects of education and ignore the long-term effects.

True or false questions, multiple choice questions, and matching tests are examples of assessments used by institutions that value grades (McCabe et al. 53). On the other hand, essay questions, research papers, and term papers are methods used to teach in institutions that value the learning experience and attainment of knowledge more than grades (Davis et al. 39).

Lack of confidence in their abilities motivates students to cheat. Lack of adequate skills and knowledge are some of the reasons that lead to the loss of confidence by students. According to McCabe et al,

“Teachers who focus more on grades have poor methods of teaching compared to teachers who value knowledge.” (51).

Students who think that they are not smart enough to cheat are more likely to cheat in order to get good grades. Learning that puts emphasis on grades involves repetition and memorization of learning materials (Davis et al. 41). Students forget much of the knowledge gained after sitting for their exams. Bored students have little or no connection to their teachers and are therefore likely to cheat because they are never prepared.

Such learning methods make learning boring and uninteresting (McCabe et al. 53). It does not motivate students to work hard and attain knowledge that could be useful in their careers. Interactive learning endows students with the confidence, which makes them believe in their ability to handle all kinds of challenges and situations (Davis et al. 42).

Students cheat because of pressure exerted on them by their parents and teachers to attain good grades (McCabe et al. 54). Many teachers and parents gauge the abilities of students by their grades. Many colleges use grades as a way of choosing the students who are qualified to join college. Self-efficacy is an important aspect of learning because it gives students the confidence to handle various tasks (McCabe et al. 55).

Teachers can cultivate a sense of self-efficacy in students by believing in all students regardless of their grades. However, many teachers alienate students who get low grades and give more attention to students that get high grades. On the other hand, many parents promise to take their children to college only if they get high grades. This motivates students to cheat in order to gain entry into college.

It is important for teachers and parents to find the weaknesses and strengths of all students and help them to exploit their potential. Sidelining some students is wrong and a good enough reason to cheat.

Another reason that explains why students teach is poor leaning and teaching methods (Davis et al.44). Good learning methods involve movements, inventions, creativity, discussions, and interactions. These methods improve comprehension among students and facilitate proper sharing of knowledge. However, many teachers find these methods tedious and time-consuming.

The aftermath is resentment form students because the teachers use methods that make learning boring. People learning through various methods. In addition, different students have different learning needs (McCabe et al. 56). Therefore, using a single teaching method does not serve the needs of all students. Some students develop a negative attitude towards learning and their teacher.

These students are likely to cheat in exams. Teachers should evaluate their students in order to develop teaching methods that cater to them all (McCabe et al. 58). Otherwise, some students might feel neglected in case they fail to comprehend certain subjects or disciplines.

Finally, students cheat because of laziness and lack of focus. According to Parker, students cheat because of lack f goo morals and laziness. According to Parker,

“A startling number attributed variously to the laziness of today’s students, their lack of a moral compass, or the demands of a hypercompetitive society.” (McCabe et al. 59)

She further argues that society demands much of students. This leads to cheating because students feel under pressure to perform well. Laziness is common among students. Students who waste their time on unimportant things have little time to study and do their homework (McCabe et al. 62).

They are unprepared during exams and result to cheating in order to perform well. On the other hand, many employees determine the capabilities of potential employees based on their grades. This motivates students to cheat in order to get high grades.

Reasons for cheating include lack of self-confidence in one’s ability to perform well, pressure from parents and teachers, and poor teaching methods that do not fulfill the learning needs of all students. In addition, many learning institutions place great value on grades rather than the acquisition of knowledge. Cheating is a common phenomenon among students at different levels of learning.

More research needs to be conducted in order to ascertain why students cheat. Further research is necessary because different students cheat for various reasons. Moreover, it is important for teachers to lay more emphasis on the acquisition of knowledge and skills rather than good grades.

Students have different learning needs that are satisfied using different teaching and learning methods. Teachers should evaluate their students in order to determine the most important teaching methods that cater to the learning needs of all students.

Davis, Stephen, Drinan Patrick, and Gallant Tricia. Cheating in School: What We Know and What We Can Do . New York: John Wiley & Sons, 2011. Print.

McCabe, Donald, Butterfield Kenneth, and Trevino Linda. Cheating in College: Why Students Do It and What Educators Can Do About It. New York: JHU Press, 2012. Print.

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The Effects of Cheating on Exams

How it works

Cheating on exams has become more prevalent throughout the 21st century as the importance of learning is eliminated. It disobeys the expectations for a well-behaved Stuyvesant student, and the offense becomes a violation of the morals of society. In highly-competitive schools, such as Stuyvesant, students are prone to running after success through their academics. Everybody is so concerned over competing to be the best in the class that most students have actually forgotten that a school’s purpose is to educate.

The obsession with running after success is so intense that students try finding any way possible to get to the top and some, to extreme cases, resort to cheating. Cheating embodies the sins of incontinence, violence, and fraud to which the punishments are and aren’t appropriate; these characteristics are comparable to the different circles of Hell in Dante’s Inferno.

Cheating is acting dishonestly to gain advantage in a competitive situation. Success in academic achievements is often earned through a student’s hard work and dedication. However, neglection to such means may usually lead to their tendency to cheat off of others because they do not believe in their own abilities and accomplishments. The students can only become guilty of their undeserving grade. Cheating is immoral because it consists of stealing other students’ intellect and calling it your own. It creates a sense of disrespect and injustice amongst the honest students that actually put the time and effort into studying. Furthermore, cheating stimulates a loss of truthfulness and suspicion between students or a student and a teacher.

The theme of incontinence is great significantly in students’ lack of self control and gluttony in the Third Circle of Hell. The culture of cheating has certainly developed along the years. Some students are forced into believing that they must cheat in order to be successful and get the best grades. Additionally, peer pressure and overwhelmness of workload may lead to temptation. However, when teachers fail to notice cheating, the student starts believing that they can get away with it a second time; this cycle will eventually become a habit where he/she is unable to restraint from temptation. This situation is comparable to that of gluttony, which is the overindulgence of food. In both cases, the guilty parties face a lack of restraint from their inclination. In the Third Circle, the Gluttons are submerged beneath “gross hailstones, water gray with filth, and snow come streaking down across the shadowed air” (6.13-4). By rolling around in the dirty hail for eternity, the Gluttons are symbolized as pigs. The sinners are treated like pigs because they gorge themselves in food, displaying animalistic qualities.

The violence depicted in the Circles of Hell are far more severe than the violence present when cheating in examination. Violence is usually portrayed as physically and intentionally using force to harm others. In Dante’s Inferno, most of the sinners in the Seventh Circle of Hell have committed acts of brutality. While the Circle is divided into three rings, those violent against their neighbors and property, such as Murderers and Tyrants, are sent to the first ring “near the stream of blood .. [to] boil” (12.47-8). These sinners were burned, as a punishment, in the symbolic amount of blood they spilled killing those injured violently. Those who are violent to themselves and commit suicide are sent to the second ring where the soul “rises as a sapling, a wild plant; and then the Harpies, feeding on its leaves, cause pain and for that pain provide a vent” (13.100-2). Here, the souls are turned into trees because they are ungrateful about their body. In comparison to cheating, the offenses in the Circles of Hell are far more immoral. Most cases of violence for cheating usually only relate to peer pressure from bullies and possible threats to share answers; students who are hesitant to help their “friends” are afraid of rejection. Nonetheless, the violence in cheating is unparalleled to the violence in Inferno because there is no true sign of intentions to harm students.

The school’s expected counter-penalty for cheating in examination is usually an automatic zero and a call home notifying parents of the unacceptable behavior. Punishments are certainly necessary for committing a sin as bad as cheating. If the school were to not reprimand them, students would continuously get away with such behavior and no one will learn what’s right. The appropriateness of the counter-penalty is well, but its effectiveness is low. Failing a student because they cheated on a particular assessment will encourage them to be more serious about the situation. However, further cheating cases should not be detention because it will not effectively allow them to be reflective on the situation. The purpose of cheating is because the students feel that they are lacking. Instead of detention, an effective punishment is forcing the students to handwrite the test paper several times until they have the information memorized. This will allow for better understanding of the text and removes the need for cheating. The rationale behind this counter-penalty is to suggest that if the students are interested in looking at other test examinations, they might as well rewrite and memorize every portion of the exam afterwards. Detention and forcing students to stay at home will not effectively help on their self-improvement.

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Cheating in Examinations. Why Do Some Students Do It?

What is cheating?
Reasons why students cheat in exams
Effects of cheating on students

Cheating can be defined as a dishonest act to gain an undue advantage. In educational parlance, cheating is usually associated with examinations.

It includes various forms of cheating like plagiarizing content, copying, or even impersonating another person to write an exam.

In The Cheating Culture: Why More Americans Are Doing Wrong To Get Ahead , David Callahan, co-founder and research director of Manhattan-based public policy think-tank Demos, demonstrates cheating through different means.

Professional athletes’ use of performance-enhancing steroids, reporters’ disguise of fiction as journalism, physicians’ promotion of drugs of questionable efficacy in exchange for payments from pharmaceutical companies, students’ cheating on exams and submitting plagiarized work, and music fans’ piracy of CDs on the internet, as well as theft by employees and high-stakes corporate crime.

Why Do Students Cheat in Exams?

In schools and colleges, cheating is not unheard of. There have been numerous instances where students have been caught cheating in examinations. The important question to answer here is why do students cheat?

There are many reasons why students cheat in exams. We have enumerated a few of these reasons below.

1.Poor Time Management

One of the main reasons why students cheat in exams is because they are pressed for time. With lack of time, students resort to cheating because they are unable to finish studying portions.

To overcome this problem, students must get into the practice of making realistic timetables . A timetable can help you set time for each subject, giving more time to tougher subjects and a bit more relaxed time for easier subjects.

This stress is one of the main reasons for students to cheat in exams. Unable to bear the stress and tension, students may resort to unlawful means like cheating during examinations.

3. Fear of Failure

No one likes to fail. It is a known fact that failure is looked upon as a taboo in our society. Students who fail are ridiculed by society.

These students are often looked down upon with disdain. Therefore, to avoid being ostracized by the community, students often resort to cheating in exams.

4. Educational System Pressure

The educational system today does not exactly have a scientific approach. It is not cut out for individual minds.

The education system caters to the bulk of the student population, leaving out a section of students unable to cope with the system.

So, what happens to these students? Well, these students are pressured to keep pace with the syllabus even if they cannot do so.

What do these students do then? These students resort to cheating and other dishonest methods of keeping up with the syllabus.

5. Family Expectations

Another reason why students cheat in exams is because of the pressure put on them by parents and other members of the family. This is one of the main reasons why students cheat.

Let’s take a typical example of a parent, who has a very high educational qualification and runs a successful business or enterprise.

Such a parent will also expect their child to study well and secure higher degrees and educational qualifications.

However, what if the child is incapable of performing to the parent’s expectation? What if the child is an average student?

The child may also want to prove to his or her parents that they can be as successful as their parents. This can lead to cheating to perform to parents’ expectations.

6. Comparison with Friends

Another reason why students cheat in exams is that they want to perform as well as their classmates and friends.

Healthy competition is not a bad concept. However, if this competition turns more serious, then it can lead to cheating and unfair means to achieve higher scores.

7. Cut-Offs and Limited Seats in Prestigious Institutions

Many institutions have a minimum cut-off below which students will not get admission into the institute.

Therefore students resort to cheating in exams to achieve high scores and get into prestigious institutions or pass prestigious administrative examinations.

8. “Everybody Is Doing It” Attitude

Another reason why students cheat in exams is because of the “everybody is doing it” attitude. This attitude discourages diligent and truthful students from studying and working hard.

Such students may think if others are cheating and getting marks then why should they study hard and get the same marks. So, they give in, even though they can study and achieve great success.

Cheating in Exams Causes and Effects

These were just some of the answers to the question why do students cheat? To understand this better, we can try and decipher some of the causes and effects of cheating in exams and find possible solutions for the problem of students cheating in examinations.

As mentioned above, some of the reasons why students cheat in exams are also the causes of cheating.

In addition to the above reasons, we can also mention media as one of the main causes of cheating

amongst students. You may ask how the media can play a role in this? The answer is simple.

Over the years, the means of communication have increased tenfold. Students have access to more than one means of communication.

Today, apart from television and radio, students have social media, cellular mobile phones, and facetime to communicate. This communication , though a boon in many cases can also be a bane.

Many times, media houses showcase successful people from prestigious institutes. Unknowingly, media houses indirectly advertise that the only way to reach success is through a particular channel of education and no other way.

Thus, this undue showcase of successful careers can influence students the wrong way. Students come to think that the only way to succeed is by getting into a particular university for a particular course. Thus, paving the way for students to think about getting it through hook or by crook.

The media portrays these successful personalities with a lot of wealth, fame, and respect in society . This blindly encourages students to try and achieve that success even if it means by unfair methods.

Therefore, we can safely conclude that one of the causes of cheating is the socio-economic disparity between classes and sections of people.

In an urge to become rich and successful overnight, students may employ shortcut methods like cheating.

An article published by the Carnegie Mellon University states several reasons why students cheat in exams:

Unfair tests and unprofessional teachers
Obligation to help other students fair better in examinations
Poor study skills
Competition
Exam anxiety
Lack of knowledge on the consequences of cheating
The perception of escaping punishment

The causes and effects of cheating in exams are straightforward. There are numerous ill effects of cheating.

They can have a deep impact on the career and life of students. We have enumerated some of the effects of cheating on students.

1. Admonishments

Students caught cheating in examinations are severely punished. These punishments can range from getting debarred in exams, expelled from school, or even suspended for the rest of the academic year.

Consequently, these severe punishments can have grave repercussions on the student’s wellbeing.

2. Lifelong Record

When a student cheats on an exam, the incident is put on record and becomes a bad black spot on the student’s life ahead. It can affect a student’s career and life.

3. Meaningless Careers

Getting a job through unfair means can only take you through the first step. Sustaining yourself in the job will purely rest on the knowledge you have acquired. Through cheating, you can pass examinations but you will not acquire knowledge.

4. Loss of Reputation

Your reputation defines your character . It takes a lifetime to build a good reputation but a minute to lose it all.

Your single moment of cheating can ruin your reputation for the rest of your life. So, remember, the reputation for a thousand years can depend on your conduct in a single moment.

These are the causes and effects of cheating in exams, it can be rightly said that cheating can lead to worse situations that can affect your entire life and career ahead.

So, remember, it is up to you to decide if you want to make it the right way. Cheating is a choice, not a mistake.

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Cheating in Exams, Essay Example

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Cheating in exams can be defined as committing acts of dishonesty during an exam in order to score good grades. This is normally done by students when they fail to prepare for the exams or when they feel that the test is too hard for them and they want to score good grades.

Various acts are considered as cheating: first when a student gets access to exam papers be it part of them or all the exam papers before the exam is considered as cheating. Another way of cheating is by having materials that are not authorized in the exam room either electronic or non electronic in their reach from which the students copy or even copying answers from scripts of other candidates or allowing your script to be copied from by other candidates. Such materials include phones in which they store data; some phones have memory cards that store huge amounts of data and thus a student can even carry the whole syllabus in their phones from which they copy. Other electronic materials are calculators in which students store formulas especially for science and math exams. Science and math formulas may also be written on the desktop which they hide from their supervisors by covering with the answer sheet. Non electronic materials include small notes which the students make on something they suspect will be tested. Such writings are made on small pieces of paper, on the palm or on sole tapes which the students stick on their clothes. Another way of cheating is when a student impersonates another one and ends up doing the exam for them or even communicating with fellow candidates during an exam session. These forms don’t exhaust the many ways of cheating.

When students succeed in their first attempt of cheating they will always be tempted to repeat the act since it enables them to pass exams without struggling however this may bring serious consequences for the students. The problems may be short lived or long term. Short term consequences include being awarded a zero score by the lecturer because they believe that the candidate does not know anything. Getting a fail forces the student to repeat the unit .This means an addition on the other terms work a burden which may make the student fail other units hence causing a cycle of failing. Other lecturers punish these students by suspending them for a given period of time .Such students get it rough in explaining to their parents the reasons for being suspended. They may also become the laughing stock in the village when fellow students spread the rumours. Another short term consequence is when the lecturer forces the students to take remedial studies as others go for holiday hence denying them the opportunity to enjoy their holidays.

Long term consequences include being expelled from school. This means the student has to look for another school and hence the student delays from finishing college which consequently affects their chances in the job market because most job advertisements specify age limit. Cheating students also gain bad reputation from fellow students and lectrurers.Fellow students always see you as a liar and lecturers lose faith in you and it becomes difficulty to convince them that you didn’t cheat at times when you pass.

In the long term a student who passed her exams through cheating may have problems when it comes to delivering services in a job. This is because a student may cheat in exams, graduate from college but have difficulties when solving problems touching on their field of study in work environment since the certificates they present don’t really show their capability but what they pretend to be. When it comes to giving ideas during discussions in the office the cheaters will strain to contribute and also the manner in which they present themselves in such meetings will be affected since they fear that fellow workers will notice their dormancy. Without a question poor performance in the job will lead to job loss.

Cheating in an exam also denies a student important knowledge in their lives which they would have gained if they take their studies seriously A student may escape being caught cheating and get good grades which would sound okay but the truth is they may lie to their teachers and parents but they cannot cheat themselves .the truth will remain that they waste their money and time in college but at the end of it they wont gain any knowledge since what they show to have gained is not theirs. In some colleges like the ones offering ACCA when a candidate is caught cheating they are discontinued from doing the other papers and this may kill the student’s dream of venturing in such a field.

The consequences of cheating in an exam are just too much to bear and so students should avoid such instances by ensuring they revise utilise their time well and revise thoroughly for their exams.

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A systematic review of research on cheating in online exams from 2010 to 2021

Fakhroddin noorbehbahani.

Faculty of Computer Engineering, University of Isfahan, Azadi square, 8174673441 Isfahan, Iran

Azadeh Mohammadi

Mohammad aminazadeh.

In recent years, online learning has received more attention than ever before. One of the most challenging aspects of online education is the students' assessment since academic integrity could be violated due to various cheating behaviors in online examinations. Although a considerable number of literature reviews exist about online learning, there is no such review study to provide comprehensive insight into cheating motivations, cheating types, cheating detection, and cheating prevention in the online setting. The current study is a review of 58 publications about online cheating, published from January 2010 to February 2021. We present the categorization of the research and show topic trends in the field of online exam cheating. The study can be a valuable reference for educators and researchers working in the field of online learning to obtain a comprehensive view of cheating mitigation, detection, and prevention.

Introduction

Today, distance education has been transformed into online settings, and the COVID-19 pandemic has raised online learning significantly across the world. The COVID-19 enforced the closing of traditional learning all over the world, resulting in 1.5 billion students and 63 million educators shifting from face-to-face learning to online learning. This situation has revealed the strengths and weaknesses of the digital transformation of education (Valverde-Berrocoso et al., 2020 ).

In (Martin et al., 2020 ), it has been shown that the online learning publications are continuously being increased from 2009 to 2018, and one of the leading research themes is course assessment. Course assessment is very challenging in online learning due to the lack of direct control over students and educators.

For an educational institution, assessment integrity is essential because it affects institutional reputation. It is necessary to employ traditional cheating detection besides prevention methods and new digital monitoring and validation techniques to support assessment integrity in online exams (Fluck, 2019 ).

The study (Watson & Sottile, 2010 ) has reported that students are remarkably more likely to get answers from others during online exams or quizzes compared to live (face-to-face) ones. Therefore, preserving the integrity of online exams is more challenging. There are some strategies to mitigate online exam cheating, such as getting offline (face-to-face) proctored exam, developing cheat-resistant questions (e.g., using subjective measures instead of objective measures), and lessening the exam score percentage contributing to the overall course grade.

Traditional cheating methods include, hiding notes in a pencil case, behind ruler, or clothes, writing on arms/hands, leaving the room, etc. (Curran et al., 2011 ). Technological advances and online learning have enhanced education, however, they also have facilitated cheating in courses (Turner & Uludag, 2013 ). For instance, an examinee could use a mobile phone to text someone to get the answer. Although this would be difficult in the exam hall, some examinees could text without looking at the mobile phone. Applying scientific calculators, Mp3 players calculator, and wireless equipment such as an earphone and a microphone are other tools that facilitate cheating in offline exams (Curran et al., 2011 ).

Although cheating motivations in online and offline exams are not significantly different (Turner & Uludag, 2013 ), detecting and mitigating online cheating could be more intricate. This is because, in addition to traditional cheating methods that also could be exploited in online exam cheating, there exist various technologies and tools that could be applied for cheating in online exams more easily. For example, using remote desktop and share screen, searching for solutions on Internet, using social networks, etc.

Cheating in an online setting is more convenient than a traditional offline exam. Accordingly, detecting and preventing online cheating is critical for online assessment. Therefore, this issue is one of the biggest challenges that MOOC (Massive Open Online Courses) summative assessment faces.

Recent researches imply that a critical issue in online education is academic dishonesty and cheating. Today, paid services exist that impersonate students in online courses to ensure their identity. In recent years, proctoring technologies such as identity authentication, keystroke recognition, and webcam proctoring will be extended to secure online exams (Xiong & Suen, 2018 ). Apart from direct proctoring, there are some techniques such as controlling the browser, limiting exam time, randomizing questions and choices, etc. However, it seems cheating in online courses is pretty common (Dendir & Maxwell, 2020 ).

Although one of the most critical challenges in online learning is to mitigate and handle cheating, there is no comprehensive literature review and classification in this field. Hence, in this paper, we present a systematic mapping review of researches in online examination cheating. The research questions are as follows:

RQ1: What are the publication trends in online cheating?
RQ2: What are the main reasons for online cheating?
RQ3: What are the cheating types in online exams?
RQ4: How can online cheating be detected?
RQ5: How can online exam cheating be prevented?

The paper is structured as follows. In Section 2 , the research method is described, including study selection criteria, databases and search strategy, and study selection. Section 3 presents review results and provides the answers to research questions. Sections 4 and 5 discuss the results and conclude the paper, respectively.

The current study is a literature review about cheating in online exams. A literature review identifies, selects, and synthesizes primary research studies in order to provide a picture of the topic under investigation. According to (Page et al., 2021 ), a record is the title or abstract (or both) of a report indexed in a database or website, and a report is a document (in paper or electronic format) supplying information about a particular study. It could be a journal article, preprint, conference abstract, study register entry, clinical study report, dissertation, unpublished manuscript, government report, or any other document providing relevant information. The current literature search has been performed based on the well-established PRISMA principles (Page et al., 2021 ).

Inclusion and exclusion criteria

The main criteria for the articles considered in the current review are as follows.

Inclusion criteria:

Researches should be written in English.
Records should be retrieved utilizing the designed search query.
Studies should be published between January 2010 and February 2021.
In cases where several papers reported the same study, only the most recent ones were included (i.e., theses and papers extracted from theses, extended version of papers published in journals).

Exclusion criteria:

Papers merely related to methods applicable to traditional cheating types, detection, and prevention are eliminated.
Studies not related to research questions are ignored.
Articles only related to cyber-attacks to online exam systems are excluded.
Low-quality researches are discarded (i.e., studies published by non-reputable publishers without peer review, too short review time, and so on, studies with poor theoretical background, experimental evaluation, or structure).

Databases and search strategy

We applied a wide range of databases as our primary source, including Google Scholar, Web of Science, and Scopus. We also added the publications which had cited the extracted records. Records were searched using the following search terms for the title, keywords, and abstract sections.

(Cheat OR e-Cheating OR Fraud OR Dishonesty OR Anti-cheating OR Cheat-resistant OR Abnormal behavior OR Misconduct OR Integrity OR Plagiarism) AND

(Electronic OR Online OR Digital OR Virtual OR Cyber OR Academic) AND

(Exam OR e-Exam OR Course OR e-Course OR Assessment OR e-Assessment OR Test OR e-Test OR Environment OR e-Environment) AND

(Prevent OR Detect OR Mitigate OR Reduce OR Minimize OR Monitor OR Proctor OR Reason OR Motivation OR Type OR Deter OR Control).

Study selection

The search result included 289 records, 26 of which were duplicated, and so they were deleted. From 263 screened records, 54 records were excluded by examining either the title or the abstract. In the next step, 12 reports were eliminated because they were not retrieved because were not accessible. Furthermore, after full-text eligibility checking, 144 reports have been excluded according to the inclusion and exclusion criteria as mentioned earlier. ‌

This resulted in 53 reports that along with 5 other reports (obtained from citation searching and assessed for eligibility), were finally selected for literature review about online cheating. The flow of information through different phases of the review is presented in the PRISMA flow diagram depicted in Fig. Fig.1 1 .

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The PRISMA flow diagram

After selecting 58 studies, three domain experts were asked to assign a Credibility Score (CS) to each study. After evaluation of each study, experts agreed on a credibility score ranging from 0 to 5 based on the following criteria: publisher credibility, number of citations per year, theoretical and experimental quality, and organization and structure. CS statistics are as follows: mean = 3.81, SD =0.79, min = 2.5, max =5.

A summary of online cheating research papers and their study themes is presented in Table Table1. 1 . (Appendix (Appendix1 1 .)

Online cheating studies

No.	Reference	Subject	Pub Type	Study Theme				No. of Citations	CS	Research Purpose
No.	Reference	Subject	Pub Type	Cheating Reasons	Cheating Prevention	Cheating Detection	Cheating Types	No. of Citations	CS	Research Purpose
1	(H. R. Bawarith, )	Student Cheating Detection System in E-exams	Thesis	-	✓	✓	✓	0	3	Investigating cheating methods and designing an e-exam management system.
2	(Migut et al., )	Cheat me not: Automated Proctoring of Digital Exams on Bring-Your-Own-Device	Conference	-	-	✓	-	5	2.5	Presenting preliminary results on automated video proctoring, which can reduce manual effort and scale-up digital assessment.
3	(Amigud & Lancaster, )	246 Reasons to Cheat: an Analysis of Students’ Reasons for Seeking to Outsource Academic Work	Journal	✓	-	-	-	33	5	Examination of the reasons cause outsourcing academic work.
4	(Weiner & Hurtz, )	A Comparative Study of Online Remote Proctored vs. Onsite Proctored	Journal	-	-	✓	-	21	4.5	Comparing test scores between kiosk-based remote online proctored and onsite proctored exams.
5	(Idemudia et al., )	A Smart Approach of E-Exam Assessment Method Using Face Recognition to Address Identity Theft and Cheating	Journal	-	-	✓	-	3	3.5	Proposed an authentication system using face recognition.
6	(Holden et al., )	Academic Integrity in Online Testing A Research Review	Journal	✓	✓	✓	-	4	3	Provided a research review with a focus on methods used to improve academic integrity.
7	(Opgen-Rhein et al., )	An Application to Discover Cheating in Digital Exams	Conference	-	-	✓	-	9	3	Proposed a system to verify the author of assignments using programming style.
8	(Prathish et al., )	An Intelligent System for Online Exam Monitoring	Conference	-	-	✓	-	12	3.5	Designed a multimodal system for online exam proctoring and automated cheating detection.
9	(Jalali & Noorbehbahani, )	An Automatic Method for Cheating Detection in Online Exams by Processing the Student's Webcam Images	Conference	-	-	✓	-	6	4	Automatic cheating detection during online exams through processing webcam images.
10	(Li et al., )	Anti-cheating Online Exams by Minimizing the Cheating Gain	Journal	-	✓	-	-	1	3.5	Cheating prevention by minimizing cheating gain with the help of question order randomization.
11	(Wong et al., )	Assessing the Usability of Smartwatches for Academic Cheating During Exams	Journal	-	-	-	✓	11	3.5	Examining the usability of smartwatches for cheating in various exam designs.
12	(Atoum et al., )	Automated Online Exam Proctoring	Conference	-	-	✓	-	54	5	Presented a multimedia (image and voice) analytics system for cheating detection during exams.
13	(Korman, )	Behavioral Detection of cheating	Thesis	✓	✓	✓	✓	5	5	Studies of online examination cheating detection through human-computer interaction dynamics.
14	(Gruenigen et al., )	Best practices in e-assessments with a special focus on cheating prevention	Conference	-	✓	✓	-	8	2.5	Discussed methods of cheating prevention during e-assessments.
15	(Topîrceanu, )	Breaking up Friendships in Exams: a Case Study for Minimizing Student Cheating in Higher Education Using Social Network Analysis	Journal	-	✓	-	-	16	5	Methods are discussed for identifying students’ friends via their social network analysis, to divide friends into different groups.
16	(Saba et al., )	Categorizing the Students' Activities for Automated Exam Proctoring Using Proposed Deep L2-GraftNet CNN Network and ASO Based Feature Selection Approach	Journal	-	-	✓	-	0	5	Designed an automated exam proctor that categorizes students’ body movements.
17	(Kasliwal, )	Cheating Detection in Online Examinations	Thesis	-	✓	✓	✓	2	5	Developed and analyzed a tool for monitoring students’ browsing activities.
18	(Manoharan, )	Cheat-resistant Multiple-choice Examinations Using Personalization	Journal	-	✓	✓	-	15	5	Preventing cheating in multiple-choice questions via personalized exams (each student gets a different set of questions).
19	(Lancaster & Clarke, )	Rethinking Assessment By Examination in the Age of Contract Cheating	Conference	-	✓	-	✓	22	4	Proposing different techniques of contract cheating and a discussion around the exam design to address these issues.
20	(Garg et al., )	Convolutional Neural Network based Virtual Exam Controller	Conference	-	✓	✓	-	2	3	Automated cheating detection via webcam recording.
21	(Corrigan-Gibbs et al., )	Deterring Cheating in Online Environments	Journal	-	✓	✓	✓	53	5	Measuring the amount of cheating after employing three distinct methods including, honor codes, controlling, and warning.
22	(Chuang et al., )	Detecting Probable Cheating During Online Assessments Based on Time Delay and Head Pose	Journal	-	-	✓	-	8	4	Identifying test takers’ behaviors for detecting cheating, with a focus on time delay and head pose.
23	(Aisyah et al., )	Development of Continuous Authentication System on Android-Based Online Exam Application	Conference	-	✓	✓	-	2	3	Developed a continuous authentication system for an android-based online learning application.
24	(Diedenhofen & Musch, )	Pagefocus: Using Paradata to Detect and Prevent Cheating on Online Achievement Tests	Journal	-	✓	✓	-	31	5	Developed a system called pageFocus, which detects unauthorized activities such as opening another window or tab beside the exam window.
25	(Tiong & Lee, )	E-cheating Prevention Measures: Detection of Cheating at Online Examinations Using Deep Learning Approach-A Case Study	Journal	-	✓	✓	-	0	4	Developed an intelligent cheating detector based on two modules: 1) IP detector, 2) Behavior detector.
26	(R. Bawarith et al., )	E-exam Cheating Detection System	Journal	-	✓	✓	✓	17	4	Investigates the methods used to detect cheating in online exams, mostly through continuous authentication and online proctoring.
27	(Traore et al., )	Ensuring Online Exam Integrity Through Continuous Biometric Authentication	Book	-	-	✓	-	21	5	Proposed a system that continuously authenticates examinees using face, keystroke and mouse dynamics.
28	(Maeda, )	Exam Cheating Among Cambodian Students: When, How, and Why It Happens	Journal	✓	-	-	-	6	4	Studied Cambodian students’ cheating practices and the reasons behind them.
29	(Fontaine et al., )	Exam Cheating Among Quebec’s Preservice Teachers	Journal	✓	-	-	✓	0	4	Presented the results of a search that aimed to examine the phenomenon of student cheating on exams in faculties of education in Quebec university.
30	(Moten et al., )	Examining Online College Cyber Cheating Methods and Prevention Measures	Journal	-	✓	-	✓	73	4.5	Mentioning some types of cheating practices and their curtailment techniques.
31	(H. M. Alessio et al., )	Examining the Effect Of Proctoring On Online Test Scores	Journal	-	✓	-	-	33	3.5	Compared test results (scores) between proctored and non-proctored online exams.
32	(Reisenwitz, )	Examining the Necessity of Proctoring Online Exams	Journal	-	✓	-	-	5	3	Investigated the differences between non-proctored and proctored online exam scores.
33	(Fan et al., )	Gesture Based Misbehavior Detection in Online Examination	Conference	-	-	✓	-	7	3.5	Introduced a gesture-based solution for misbehavior detection using Microsoft Kinect device.
34	(Cluskey et al., )	Thwarting Online Exam Cheating Without Proctor Supervision	Journal	-	✓	-	-	96	4.5	Examines the control issues related to online exams.
35	(X. Li et al., )	Massive Open Online Proctor Protecting the Credibility of MOOCS Certificates	Conference	-	-	✓	-	32	4	Proposed a massive open online proctoring (MOOP) framework, which combines both automatic and collaborative approaches to detect cheating behaviors in online tests.
36	(Nguyen et al., )	Minimize Online Cheating for Online Assessments During COVID-19 Pandemic	Journal	-	✓	-	-	6	3.5	Presented strategies that effectively minimize cheating while addressing learning outcomes.
37	(Chirumamilla & Sindre, )	Mitigation of Cheating in Online Exams Strengths and Limitations of Biometric Authentication	Journal	-	✓	✓	✓	3	3.5	Delivered a categorization of different types of high-stakes assessments, different ways of cheating, and what types of cheating are most relevant for what types of assessments.
38	(Srikanth & Asmatulu, )	modern Cheating Techniques, Their Adverse Effects on Engineering Education and Preventions	Journal	-	✓	-	-	21	4	Evaluated some of the high-tech cheating systems and devices that have been a major threat to engineering education.
39	(Fayyoumi & Zarrad, )	Novel Solution Based on Face Recognition to Address Identity Theft and Cheating in Online Examination Systems	Journal	-	-	✓	-	24	4	Provided a solution for detecting cheating behaviors such as looking at an adjacent PC or reading from an external source using video capturing.
40	(Bilen & Matros, )	Online Cheating Amid COVID-19	Journal	✓	-	-	-	6	3.5	Presented evidence of cheating that had taken place in online exams during COVID-19 lockdowns and proposed a solution based on the experience accumulated by online chess communities.
41	(Chua & Lumapas, )	Online Examination System with Cheating Prevention Using Question Bank Randomization and Tab Locking	Conference	-	✓	-	-	2	3	Presented the results of interviews with a group of online exam proctors to identify the root causes of academic malpractice.
42	(Arnautovski, )	Face Recognition Technology in the Exam Identity Authentication System. Implementation Concept	Conference	-	✓	-	-	0	2.5	Proposed a unimodal authentication system, which captures the image of the test-taker at random time intervals.
43	(Sabbah, )	Security of Online Examinations	Book	-	✓	✓	-	2	4	Proposed two major schemes for continuous authentication.
44	(Mengash, )	Automated Detection for Student Cheating During Written Exams: An Updated Algorithm Supported by Biometric of Intent	Conference	-	-	✓	-	2	2.5	Proposed a system that detects cheating intentions using a thermal detector, a surveillance camera and an eye movement tracker
45	(Dobrovska, )	Technical Student Electronic Cheating on Examination	Conference	✓	-	-	✓	0	3	The study gauged the forms, frequency, and variety of electronic cheating of university students, and the teacher attitudes toward cheating.
46	(Kigwana & Venter, )	Proposed High-Level Solutions to Counter Online Examination Fraud Using Digital Forensic Readiness Techniques	Conference	-	✓	✓	✓	1	2.5	Explored the various ways of student cheating and proposed a high-level digital forensic readiness techniques.
47	(Varble, )	Reducing Cheating Opportunities in Online Tests	Journal	-	✓	-	-	20	3.5	Focused on reducing cheating opportunities of online test assessments.
48	(Hu et al., )	Research on abnormal behavior detection of online examination based on image information	Conference	-	-	✓	-	3	3	Proposed a system that uses a webcam to monitor candidates' head posture and mouth state to detect abnormal behavior during online exams.
49	(Ullah, )	Security and Usability of Authentication by Challenge Questions in Online Examination	Thesis	-	✓	✓	-	2	4	Proposed a profile-based challenge question approach to create and consolidate a student’s profile during the learning prcess to be used for authentication in the examination process.
50	(Mott, )	The Detection and Minimization of Cheating During Concurrent Online Assessments Using Statistical Methods	Journal	-	-	✓	-	8	4	Developed a statistical algorithm to detect group cheating by investigating identical incorrect responses.
51	(Peytcheva-Forsyth et al., )	The Impact of Technology on Cheating and Plagiarism in the Assessment, the Teachers' and Students' Perspectives	Conference	-	✓	-	✓	12	3.5	Investigated the impact of technology on cheating and plagiarism from the perspective of teachers and students of Sofia university related to both aspects of facilitation and prevention of such behaviors.
52	(H. Alessio, )	The Impact of Video Proctoring in Online Courses	Journal	-	✓	-	-	4	3	Analyzed the change in grade distributions across 29 courses and instructors on a college campus before and after video proctoring.
53	(Backman, )	Students' Experiences of Cheating in the Online Exam Environment	Thesis	✓	✓	-	✓	1	4	Produced recommendations to teachers who instruct online courses on how to teach courses to mitigate online cheating.
54	(Norris, )	University Online Cheating - How to Mitigate the Damage	Journal	✓	✓	-	✓	2	3	Discussed the history and motivations for cheating, and the proliferating number of entrepreneurs and products that assist students in completing their courses in ways that compromise academic integrity.
55	(He et al., )	Using Face Recognition to Detect “Ghost Writer” Cheating in Examination	Conference	-	-	✓	-	1	3.5	Proposed a three layers architecture to detect the ghostwriter who takes the exam for others.
56	(Hylton et al., )	Utilizing Webcam-Based Proctoring to Deter Misconduct in Online Exams	Journal	-	✓	-	-	74	5	Investigated the deterrent effect of webcam-based proctoring on misconduct during online exams.
57	(Cote et al., )	Video Summarization for Remote Invigilation of Online Exams	Conference	-	-	✓	-	13	4	Focused on video summarization of abnormal behavior for remote proctoring.
58	(Parks et al., )	Why Students Engage in Cyber-Cheating Through a Collective Movement a Case of Deviance and Collusion	Journal	✓	-	-	✓	15	5	Conducted a case study of “Tasribat”, a Facebook page that facilitates cyber cheating among certain social groups of students in Morocco.

Several findings emerged as a result of the research synthesis of the selected fifty-eight records on online cheating. The selected studies were categorized into four main topics, namely Cheating reasons, Cheating types, Cheating detection, and Cheating prevention, as shown in Fig. Fig.2. 2 . All subsequent classifications reported in this paper have been provided by the authors. The studies under every four main topics are investigated by three experts, and a list of items is extracted for each category. Notably, some studies were corresponded to multiple main topics. Next, several brainstorming sessions have been conducted to classify each main topic further. To extract the classifications, the XMind tool has been employed, which is a professional and popular mind mapping software.

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Online cheating research classification

In the following sub-sections, the detailed analysis of the review results is described according to the five research questions we defined to drive the research.

Publication trends

In Fig. Fig.3, 3 , the number of publications per year is displayed (in this study, the final publication date is applied). In 2017, the greatest number of studies corresponding to the conducted review have been published. As shown in Fig. Fig.4, 4 , the dominant publication type is journal papers with 53% of the total publications. In terms of the average citations of the selected studies regarding their classes, the maximum average citations belong to the journal papers with an average citation of 19.65 (see Fig. Fig.5 5 ).

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Number of publications per year

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Distribution of publication per types

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Average citation per publication type

There are 747 works cite the selected studies related to the review. As displayed in Fig. Fig.6, 6 , the greatest and lowest shares of the total citations pertain to the journal articles and the theses, respectively. The number of publications per research theme is shown in Fig. Fig.7. 7 . The cheating prevention and detection themes are the most prevalent research themes in online cheating. In the following four subsections, the studies under each of the four research themes are described and classified thoroughly.

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Distribution of publications according to citations

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Number of publications per research theme

Cheating reasons

The primary reason for cheating is that examinees feel the rewards outweigh the risks (Lancaster & Clarke, 2017 ). There exists a wide variety of reasons why candidates decide to commit cheating, still, they could be categorized into four general reasons, namely Teacher-related, Institutional, Internal, and Environmental reasons. The complete classification of the cheating reasons is displayed in Fig. Fig.8, 8 , which is described in the following sections.

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Teacher-related reasons

All the reasons related to the teacher or the course instructor are put into this category. Maeda ( 2019 ), has observed that the student’s relationship with the teacher has crucial influences on academic integrity. Teachers’ unethical behaviors, such as favoring those who have bribed over those who have not, or favoring the students who participated in private tutoring sessions, motivate the oppressed students to cheat. The author also found that teachers’ low interest in students’ depth of learning, which also results in a poor pedagogical style, could be an important reason that motivates students to participate in any kind of unethical behavior (Maeda, 2019 ).

Course difficulty could motivate the examinees to cheat. Some students blamed their teachers for complicated and complex course materials. In some specific cases, this reason could be a consequence of students’ lack of perseverance. They find cheating as a way to relieve these difficulties (Amigud & Lancaster, 2019 ).

As a result of distributed learning with online courses and examinations, Moten et al. ( 2013 ), have expressed that students feel isolated in an online environment. They often become frustrated when they do not get the help they immediately need, for instance, the night before an exam. This situation is closely dependent on the presence time of the teacher in online communication environments.

Some teachers restrain from punishing the cheaters appropriately due to ethical issues. This could be due to the sympathy of some teachers with cheaters. After listening to the cheater’s excuses and justifications, the teacher might give them a second chance. Sometimes, teachers are worried about the consequences of punishments and the corresponding pressures that cheaters experience, hence they don’t punish the cheater or the punishment is too mellow.

This increases the students’ courage to cheat during online exams due to decreased risk of being punished after being caught and implies that cheating penalties are insignificant over the long run (Topîrceanu, 2017 ).

Exam design is one of the most important contributing factors that motivates examinees to cheat in the exam. Weakly designed exams such as similar multiple-questions for every examinee or easy accessibility of solutions over the web, can make it easy to cheat. On the other hand, questions being too complex and irrelevant to course materials, forces students to commit cheating during online exams (Srikanth & Asmatulu, 2014 ).

Institutional reasons

In (Maeda, 2019 ), it is observed that the rules and policies of the institution are directly related to the number of unethical behaviors occurrences. It is found that institutions with stricter regulations and better commitment to strengthening academic integrity, face much less cheating behavior between their students. Institutional policies not only create an anti-cheating atmosphere, but also makes dishonest academic behaviors challenging to take place. Also, Backman ( 2019 ) emphasizes that if it becomes easy for students to cheat, they will cheat.

Impulsiveness is a crucial reason why students try to cheat during online examinations. They feel isolated and disconnected, so they may imagine they won’t get caught or the instructor does not care if they commit academic dishonesty. Unethical behaviors have a direct relationship with the student’s impulsiveness (Moten et al., 2013 ).

Moreover, in an isolated environment, due to the lack of face-to-face communications with teachers, students have much less respect for their teachers that leads to increasing misbehaviors. That is why teachers should personalize the online environment for students by calling their names or listening to their voices, so that online classes become more engaging and interactive for students (Moten et al., 2013 ).

Dobrovska ( 2017 ), expressed that the poor quality of the institution’s online learning system discourages students from learning the course materials, and makes it difficult for them to learn, hence, they are more motivated to cheat.

Academic aptitude is one of the most important and underrated reasons leading students to commit misbehaviors. It means educational institutions don’t discriminate between students and ignore their unique abilities, skills, and different levels of preparedness for a specific task. This makes unprepared students feel frustrated about that particular task or course, which leads them to seek help from more talented and prepared students in that specific context (Amigud & Lancaster, 2019 ).

Internal reasons

Another category of cheating reasons is internal motivators. The motivators over which the candidate has complete control, including intrinsic factors, personality and psychological characteristics, lie in this category. The internal reasons are divided into three subcategories as follows.

Student’s academic performance

One significant internal factor is the student’s academic performance. There are several reasons that could result in poor academic performance as follows: lack of learning and skills to find resources, students unwillingness to follow recommended practices, inability to seek appropriate help, procrastination, poor time management (Dobrovska, 2017 ), and lack of confidence in their ability to learn course materials (Norris, 2019 ).

Low intrinsic interest in the course materials

Low intrinsic interest in the course is another reason mentioned in (Dobrovska, 2017 ), which could be caused by a lack of sufficient interest in course materials and subjects or the mindset that these materials and knowledge are unnecessary and unimportant for future life (Norris, 2019 ).

Personal characteristics

There is a strong relationship between students’ moral attitudes toward cheating and their level of participation in academic misbehaviors (Maeda, 2019 ). Therefore, conscientious belief is considered as an internal reason stopping students from unethical behaviors. However, it has been shown that religious beliefs do not necessarily lower cheating behaviors (Srikanth & Asmatulu, 2014 ).

Other reasons included in studies are student’s laziness for sufficient home preparation before the exam (Dobrovska, 2017 ), competition with others and the desire to get ahead (Amigud & Lancaster, 2019 ), desire to help other peers (Moten et al., 2013 ) and the student’s thrill of taking risk (Hylton et al., 2016 ).

Environmental reasons

The reasons mentioned in this section highly depend on the atmosphere and type of environment a student is in, either during the online exam or beforehand in social media or communication with people. We put these reasons in four major categories: Peers’ behavior, Parents’ attitudes, Personal issues and, Social factors.

Peers’ behavior

Peers could influence individuals in a manner that their cheating motivations are increased. In an academic environment, however, it is primarily because of the competing objectives, such as the desire to get ahead in scores. This depends on the amount of competition in the academic environment (Amigud & Lancaster, 2019 ).

Experimental research among Cambodian students, has figured out that being among a group of cheaters, psychologically drives the students to repeat their peers’ actions and commit cheating. In addition, there is high pressure on those who do not collaborate with peers, or reject participating in their group work. It is found that they are blamed for being odd and unkind (Maeda, 2019 ).

According to (Srikanth & Asmatulu, 2014 ), being in an environment where peers’ cheating remains undetected, gives this kind of feeling to non-cheaters that they are setting back in scores and are unfairly disadvantaged compared to those cheaters.

Parents’ attitude

Parents’ acceptance of cheating behaviors, massively affects the student’s mindset toward these behaviors. As expressed in (Maeda, 2019 ), parents’ behaviors toward their child’s cheating, vary from complete unacceptance to active involvement and support. Another reason related to parents’ attitudes is putting their children under pressure to achieve good or higher than average grades (Backman, 2019 ).

Personal issues

Personal issues could be mental and physical health problems (Amigud & Lancaster, 2019 ), problems within the family (e.g., parents arguing, separation and divorce, etc.), and fear of failure in exams and its further consequences like financial and time setbacks (Hylton et al., 2016 ).

Societal factors

Poor economic conditions and the development level of a country are examples of societal factors affecting students’ motivation to cheat and achieve academic success (Maeda, 2019 ).

Countries with various cultures, social expectancies, and people’s attitudes have different behaviors regarding academic performance. In some countries, academic performance and grades are known to be crucial for success in life, whereas, in other countries, academic performance is relatively low valued. This range of different expectations from students leads to various social beliefs and behaviors toward cheating (Maeda, 2019 ). In research presented in (Holden et al., 2020 ), it is shown that a primary reason could be the existence of a cheating culture. Some students may cheat because they desire to portray a better image of themselves to their society (Norris, 2019 ). Another societal factor influencing cheating behaviors is the technology evolution that strengthens cheating motivation (Maeda, 2019 ). This is because technology brings about increased access to cheating resources. The evolution of technology, specifically search engines and social media, makes it easier for students to cheat.

Cheating types and facilitators

To mitigate cheating behaviors effectively and efficiently, cheating methodologies, types, and facilitators should be known. Cheating is performed either individually or by the cooperation of others (called group cheating). Figure Figure9 9 displays the complete classification of cheating types.

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Cheating types

Individual cheating

Individual cheating is carried out without any assistance from any person. This type of cheating could be categorized as using forbidden materials and other types are described as follows.

Using forbidden materials

Individual cheating can occur by using forbidden materials during the exam, such as looking at a textbook or a cheat sheet (Fontaine et al., 2020 ), (Holden et al., 2020 ), searching the web, using offline electronic resources such as images, voices, etc. (Korman, 2010 ), (Holden et al., 2020 ), or even using objects in the exam room to hide notes.

Other types

Other types of individual cheating include accessing the questions and solutions before the exam, which Korman ( 2010 ) refers to as “unauthorized intelligence”. Another dishonest behavior is social engineering, which is grade negotiation with the teacher through fake facts and exploiting personal sympathy.

Group cheating

Cheating methods through cooperation with others could be categorized as Impersonation, and Collaboration types.

Impersonation

Impersonation means employing someone to take the exam for the examinee, either the whole exam or some parts of it (Korman, 2010 ), (Holden et al., 2020 ). It can occur in forms of voice conversion, face presentation attack and face impersonation, fake identity matching to a stored biometric, and attack on the keystroke dynamics (Chirumamilla & Sindre, 2019 ). These are attacks on the biometric system to bypass the authentication mechanisms. The other impersonation techniques include remote desktop control by a third party (Kasliwal, 2015 ), (Gruenigen et al., 2018 ), sharing the screen with a third party (Gruenigen et al., 2018 ), (Bawarith, 2017 ), and credential sharing, which is impersonation via shared username and password of an academic account or LMS (Learning Management System) (Dobrovska, 2017 ).

Collaboration

Collaboration is defined as getting any kind of help from others to answer the exam questions. It could be in the form of sign language communications that come in numerous forms, such as foot-tapping, pencil or any object dropping during the proctored exam, abnormal coughing, or suspicious actions (Srikanth & Asmatulu, 2014 ).

Listening to a third party’s whispers behind the camera (Chirumamilla & Sindre, 2019 ), any type of communication which is unauthorized such as sending or receiving messages, or voice and video calls (Korman, 2010 ), are also considered as collaborative cheating.

Other cheating methods in this category are remote desktop control (Kasliwal, 2015 ) and sharing the screen with others to collaborate with others about questions (Gruenigen et al., 2018 ), applying small hidden micro cameras to capture images and record videos for sharing with other peers (Bawarith, 2017 ), and finally, organizational cheating which is a result of institution’s personnel corruption (Korman, 2010 ).

The last one, as Korman ( 2010 ) showed, can take place when personnel help candidates to cheat. Changing the exam grade or exam answers after the exam (exam integrity corruption), giving the solutions to the candidate during the exam, or just bribing the proctor not to report the cheating or not to punish after being caught (Kigwana & Venter, 2016 ) are instances of organized cheating.

Contract work is a type of collaboration that means doing work with the help of someone else under the obligations of a contract. Contract workers may provide some or all of the exam answers. In this case, sometimes impersonating the student through the whole academic course is reported (Chirumamilla & Sindre, 2019 ).

Cheating facilitators

Methods discussed here act as cheating facilitators to support the process of cheating. In other words, these facilitators can be applied to perform any kind of cheating. A study presented in (Peytcheva-Forsyth et al., 2018 ), indicates that technology in general, is the leading facilitator of cheating practices. Cheating facilitators are classified as shown in Fig. Fig.10 10 .

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Three different methodologies are used by students to facilitate cheating, either individually or in a group, described as follows.

Interrupting to get more time

Sometimes examinees try to buy more time to work more on the exam answers. For instance, the examinee may report an error about the exam system or exam proctoring software to convince the teacher to restart the exam session. This enables the candidate to get more time for cheating and finding the solutions during this interval when the session is closed (Motenet al., 2013 ). Another interruption method is to submit corrupted answer files by the candidate. In this case, the teacher reports that the files were corrupted and asks the candidate to resubmit the answer files. Most of the time, during the first submission and the second one, there exists at least one day, which implies the candidate gets at least one more day to answer the exam questions (Moten et al., 2013 ).

Other more classical methods to interrupt are toilet requests during the exam (Chirumamilla & Sindre, 2019 ), communication break and delay in answering oral exam right after a question is asked (Chirumamilla & Sindre, 2019 ), circumventing the exam process at a specific time with different excuses, and postponing taking the exam (Fontaine et al., 2020 ), (Korman, 2010 ). By deferring taking the exam, students can buy more time to become more prepared, either by studying more, or getting access to the exam questions and solutions.

Employing multiple devices

In proctored exams, either by a camera or software, students try to use multiple devices and answer the questions with the primary one while cheating via the secondary device. Several types of devices could be employed as the second device, such as computers and laptops (Moten et al., 2013 ), smartwatches (Wong et al., 2017 ), smart glasses such as Google glasses (Srikanth & Asmatulu, 2014 ), smartphones and tablets (Korman, 2010 ), programmable and graphical calculators to store notes and formulas (Kigwana & Venter, 2016 ), and tiny earpieces for remote voice support during the exam (Bawarith, 2017 ).

Other facilitators

Redirecting the webcam to hide something from its field of view (Sabbah, 2017 ), (Srikanth & Asmatulu, 2014 ), or disabling the webcam or microphone completely (Srikanth & Asmatulu, 2014 ) are other tricks used to facilitate cheating.

By using virtual machines on a computer, the user can run a virtual operating system on the primary one. This technique would hide the activities done on the second operating system from the software or the human proctoring the primary operating system. (Kasliwal, 2015 ).

Corrupting the exam system’s integrity to change the exam results after being held (e.g., changing the scores or answers after the examination) is another notable case (Korman, 2010 ). Lastly, in (Parks et al., 2018 ), the authors have investigated that social media and channels operating on them could act as cheating facilitation environments.

Cheating detection

Cheating detection methods can be categorized into during the exam and after the exam detection methods. Further classification of the cheating detection methods is presented in Fig. Fig.11 11 .

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Cheating detection during the exam

To ensure academic integrity in online examinations, it is essential to detect cheating during the exam. Cheating detection can be partitioned into two main categories, namely, continuous authentication and online proctoring. Continuous authentication methods verify the identity of test-takers, and online proctoring monitors the examinees to detect any misbehavior during the exam. In the following, we will mention different techniques in each category.

Continuous authentication

One of the main types of cheating is impersonating. Therefore, it is essential to authenticate students before exam registration and prevent unauthorized candidates from taking the examination. In addition, it is necessary to validate the identity of the test-taker during the exam continuously. The continuous authentication systems are mainly based on biometric or behaviometric modalities and can be categorized into unimodal and multimodal schemes.

Unimodal authentication is the automatic recognition and identification of candidates using a unique characteristic. This characteristic could be either static (physiological) such as the face, fingerprint, hand geometry, and iris, or could be dynamic (behavioral) such as voice, handwriting, keystroke, and mouse dynamics (Chirumamilla & Sindre, 2019 ).

As a unimodal authentication system, Arnautovski ( 2019 ) designed a face recognition system, which captures the image of the test-taker at random time intervals. The facial recognition module continuously verifies the examinee’s identity by comparing captured images to the image from the exam registration process. In (Aisyah et al., 2018 ), an Android-based online exam application is implemented that takes photos of the examinee with random intervals and a web-based application lets the admin or supervisor of examination validate pictures of participants. In addition, Idemudia et al. ( 2016 ) proposed a system that tracks and detects faces continuously to verify the candidates. If the authentication failure remains for more than a few seconds, the system will stop the examination.

In (Sabbah, 2017 ), a scheme called ISEEU is proposed, in which each examinee’s session is streamed using a webcam. A proctor monitors the video screens and can generate alerts when any suspicious action is detected. He et al. ( 2018 ) proposed an anti-ghostwriter system using face recognition methods. The ghostwriter merges the student’s photo and their photo to make a fake one, or they change their appearance to mislead the examiners. The experimental results in (He et al., 2018 ), indicate that the proposed framework can detect ghostwriters with an acceptable level of accuracy.

Since some candidates may refuse to use a camera due to privacy concerns, Bilen et al. (2020) suggested that instructors offer their students two options. An examinee can agree to use a camera during the exam. In this situation, the record will be used as evidence if they are accused of cheating. However, if the examinee doesn’t accept using a camera, the instructor can claim cheating without providing evidence to the student.

In (Bawarith, 2017 ), the system authenticates the examinees continuously through an eye tracker. The data obtained from the eye tracker are translated into a set of pixel coordinates so that the presence or absence of eyes in different screen areas can be investigated.

Multimodal biometric authentication systems utilize different biometric or behaviometric traits simultaneously, which makes impersonating more difficult. In this regard, Bawarith et al. ( 2017 ) proposed a system that utilizes fingerprint and eye-tracking for authentication. The eye tribe tracker is used to continuously ensure that test-takers are the ones they are claiming to be. Whenever the system detects the examinee is no longer present in front of the screen, the system is locked, and the test-taker must be authenticated again via fingerprint.

In (Sabbah, 2017 ), a multimodal scheme called SABBAH is proposed, which adds continuous fingerprint and keystroke dynamics to the ISEEU scheme (Sabbah, 2017 ). In contrast to ISEEU, SABBAH uses an automatic system to detect fingerprint, keystroke, or video violations. Traore et al. ( 2017 ) proposed a system that continuously authenticates examinees using three complementary biometric technologies, i.e., face, keystroke, and mouse dynamics. In this system, test-takers are continuously authenticated in the background during the exam, and alarms are created and sent to the instructor through the proctoring panel.

Online proctoring

Online proctoring is essential to promote academic integrity. Alessio et al. ( 2017 ) reported significant grade disparities in proctored versus un-proctored online exams. Online proctoring can be categorized into human and automated proctoring. In human proctoring, a human proctor monitors the students remotely to detect suspicious behavior. In contrast, in automated proctoring, the cheating behaviors are flagged or detected automatically by the proctoring system.

Recently, several technologies have been developed to facilitate proctoring online exams remotely. For example, Kryterion™ Live Video Monitoring and ProctorU allow users to be monitored by a human proctor via a webcam during examination (Hylton et al., 2016 ). In (Reisenwitz, 2020 ), substantial support for online proctoring is provided. The results show a significant difference between the scores of exams that were not proctored and those proctored using ProctorU software.

Some systems can capture screenshots of the candidates’ PCs at random times during the examination (Migut et al., 2018 ). Consequently, if examinees use any forbidden resource on their computer, it will be shown to the proctor. Alessio ( 2018 ) applied video proctoring via a webcam at Miami University. The results demonstrate that students are less likely to cheat when monitored with a webcam during online testing.

In another study, kiosk-based remote online proctored examinations are compared with tests administered under a traditional proctoring environment. In kiosk-based proctoring, the test is taken on special computer kiosks located at accessible places such as libraries. The kiosks are equipped with enhanced webcams and are supervised online by a live remote proctor. The results indicated that examinees’ scores obtained under online kiosk-based proctoring are comparable to examinations taken in test centers with onsite proctors (Weiner & Hurtz, 2017 ).

A different approach for cheating detection is a class mole that means the instructor enrolls in students’ groups under another name as a mole to detect and combat collusion. In this way, they can discover dishonest students when they discuss cheating amongst themselves (Moten et al., 2013 ).

Human proctoring is costly and labor-intensive. Therefore, different automated proctoring systems are proposed to monitor the students during the examination and detect unauthorized behavior. In the following, we discuss several automated methods.

Chuang et al. proposed a semi-automatic proctoring system that employs two factors, namely, time delay in answering the questions and head-pose variation, to detect suspicious behavior. Afterward, a human proctor could use more evidence to decide whether a student has cheated (Chuang et al., 2017 ).

Garg et al. ( 2020 ) proposed a system to detect the candidate’s face using Haar Cascade Classifier and deep learning. If the examinee’s face moves out of the examination frame or multiple faces are detected in the frame, the test will automatically be terminated, and the administrator will receive a notification. In (Fayyoumi & Zarrad, 2014 ), a two-second candidate video is taken during the examination period. The images in the video are analyzed to verify whether the examinee is looking somewhere other than their screen. If the test-taker doesn’t focus on their screen, it may indicate cheating behaviors such as looking at an adjacent PC or reading from an external source.

In (Hu et al., 2018 ), the proposed system uses a webcam to monitor candidates' head posture and mouth state to detect abnormal behavior. Through the rule-based reasoning method, the system can detect suspicious behavior such as turning heads and speaking during the online examination.

Prathish et al. ( 2016 ), developed a multimodal system for online proctoring. The system captures audios and videos of the candidates as well as their active windows. If yaw angle variations, audio presence, or window changes are detected in any time frame, it can be considered an indicator of cheating. Consequently, the captured video, audio, and system usage are fed into a rule-based inference system to detect the possibilities of misbehaviors. ProctorTrack is another automated online exam proctoring product that employs facial and audio recognition, body movements, and computer activity monitoring to detect any suspicious action during examination (Norris, 2019 ).

Atoum et al., ( 2017 ) developed a system that can detect a wide variety of cheating behaviors during an online exam using a webcam, wearcam, and microphone. Using wearcam makes it possible to monitor what the student observes. It helps to detect any phone or text in the testing room that is prohibited. In addition, by using the wearcam, the system can detect another form of cheating that is reading from books, notes, etc. Furthermore, the system can estimate the head gaze of the test-taker by combining the information from the webcam and wearcam. Another form of cheating is getting verbal assistance from another person in the same room, or remotely via a phone call. The system can detect this kind of cheating using the microphone and speech detection. Considering the mentioned aspects, the proposed multimedia system can perform automatic online exam proctoring.

Saba et al. ( 2021 ), developed an automatic exam activity recognition system, which monitors the body movements of the students through surveillance cameras and classifies activities into six categories using a deep learning approach. The action categories are normal performing, looking back, watching towards the front, passing gestures to other fellows, watching towards left or right, and other suspicious actions. Movement recognition based on video images is highly dependent on the quality of images. Therefore, Fan et al. ( 2016 ), employed a Microsoft Kinect device to capture the examinee’s gesture. The duration and frequency of the detected action events are then used to distinguish the misbehavior from the normal behavior.

The system presented in (Mengash, 2019 ) includes a thermal detector attached with a surveillance camera and an eye movement tracker. When examinees intend to cheat, their body will emit a specific range of heat, and the emitted heat will trigger the camera to focus and detect the candidate’s face. Then the eye tracker detects eye movements, and the system detects the cheating intentions of the test-taker. There are other biometric-based methods for cheating detection. For example, keystroke and linguistic dynamics can detect stress, which indicates suspicious behavior (Korman, 2010 ).

Diedenhofen and Musch ( 2017 ), developed a JavaScript application called PageFocus, which can be added to the test page and run in the background. Whenever the examinee switches to a page other than the test page, a defocusing event is registered. The script captures when and how frequently defocusing and refocusing events occur on the test page. Another method is to permit students to get to just a couple of sites that are whitelist. If the examinee tries to open a site that is not allowed (one from blacklist), the instructor will be informed through an Android application or Internet (Kasliwal, 2015 ).

Tiong and Lee ( 2021 ), proposed an e-cheating intelligent agent composed of two modules, namely the internet protocol (IP) detector and the behavior detector. The first module could monitor the examinees’ IP addresses and enable the system to alert if a student changes their device or location. The second module detects abnormal behavior based on the speed of answering questions. Another method for cheating detection is comparing the IP addresses of the examinees to check whether two participants are in the same place (Bawarith, 2017 ).

Cheating detection after the exam

Even though different methods are employed to prevent students from cheating, some will still cheat during the examination. Consequently, a bunch of techniques is proposed to detect cheating students after the exam. This way, the reliability of online assessments will be improved. In the following, we will discuss different methods of cheating detection after the exam.

Video monitoring

The University of Amsterdam has developed a system that records the student’s video screen and the environment during the exam. Later a human proctor views the recording and flags and reports any suspicious behavior (Norris, 2019 ). Proctoring software proposed in (Alessio et al., 2017 ), records everything students do during the examination. After the exam, the recordings can be reviewed by the professor, teaching assistants, or employees of the proctoring vendor to identify cheating behaviors.

Human proctoring is a tedious and time-consuming process. To reduce the time and cost of proctoring, an automatic system can be employed to detect and flag suspicious events using machine learning methods. In this regard, Cote et al. ( 2016 ) proposed a system for the automatic creation of video summaries of online exams. The proposed method employs head pose estimations to model a normal and abnormal examinee’s behavior. Afterward, a video summary is created from sequences of detected abnormal behavior. The video summaries can assist remote proctors in detecting cheating after the exam.

Jalali and Noorbehbahani ( 2017 ), implemented an automatic method for cheating detection using a webcam. During the exam, images are recorded every 30 seconds by a webcam for each candidate. After the exam, the recorded images are compared with reference images of that student. If the difference exceeds a threshold, the image will be labeled as a cheating state.

Li et al. ( 2015 ), proposed a Massive Open Online Proctoring framework that consists of three components. First, the Automatic Cheating Detector (ACD) module uses webcam video to monitor students, and automatically flag suspected cheating behavior. Then, ambiguous cases are sent to the Peer Cheating Detector (PCD) module, which asks students to review videos of their peers. Finally, the list of suspicious cheating behaviors is forwarded to the Final Review Committee (FRC) to make the final decision.

Other methods

There are various ways of cheating, and therefore, different methods are used to detect cheating after the exam. For example, one of the cheating behaviors is to collude and work on tests together. However, most learning management systems allow the instructor to view IP addresses. Therefore, if different students submit their assessments by the same IP address in a short time frame, it could be detected and considered as a sign of collusion (Moten et al., 2013 ).

In addition, statistical methods can be used to analyze student responses to assessments and detect common errors and the similarities of answers (Korman, 2010 ). Mott ( 2010 ) stated that the distribution of identical incorrect responses between examinee pairs is a Polya distribution. The degree of cheating for each examination will follow the skewness or third central moment of the distribution.

Predictive analytics systems implicitly collect data while the students interact with the virtual learning environment. The collected data, which include student’s location, access patterns, learning progress, device characteristics, and performance, is used to predict trends and patterns of student behavior. Consequently, any unusual pattern may indicate suspicious behavior (Norris, 2019 ). Answering an examination takes a reasonable amount of time. Therefore, another indicator of dishonest behavior is an extremely short interval between the access time and the completion of the assessments, which can be detected by log time analysis (Moten et al., 2013 ).

In (Bawarith et al., 2017 ), an E-exam management system is proposed that classifies participants as cheating or non-cheating based on two parameters, namely the total time and the number of times the examinee is out of the screen. The focus of the test-taker is recorded using an eye tracker during the exam.

Kasliwal (Kasliwal, 2015 ), designed an online examination tool that captures the network traffic during the exam using a kismet server. The captured package can then be analyzed to determine the frequency of URLs accessed by students. If one of the URLs is getting accessed more frequently or very rarely, it could be considered suspicious.

To detect plagiarism in papers or essay-type questions, platforms such as DupliChecker.com 1 or Turnitin.com 2 can be used. These websites compute a similarity index and show all potential plagiarisms. Based on the similarity index, the instructor decides about further actions (Moten et al., 2013 ).

A weakness of similarity detection software is that it computes the resemblance of a submitted assessment with others' works and cannot detect an original text written by others for the student in question. Stylometry discovers this issue by checking the consistency of the delivered contents with other texts written by the same student. If the style of a text does not match with the previous works of that student, it may indicate complicity (Chirumamilla & Sindre, 2019 ). Opgen-Rhein et al. ( 2018 ) presented an application that employs machine learning methods to learn the programming styles of students. This work is based on the assumption that the programming style of each student is unique, and therefore, the model can be used to verify the author of assignments.

Another way of cheating detection is using a cheating trap, which means creating websites that could be found when the students search for answers. The solutions in trap websites are incorrect, and consequently, dishonest students could be detected (Korman, 2010 ). However, this method contradicts professional ethics.

In addition, the teacher can search the internet by hand periodically and try to find all possible web pages that provide solutions matching the exam questions. This approach could be applied to create a pool of potential solutions from the internet that will be used for plagiarism detection purposes after the exam (Norris, 2019 ).

Cheating prevention

After discussing and analyzing the examinees’ motivations for cheating and the reasons which directly or indirectly drive them to commit unethical actions during online examinations, a great deal of concern is gathered around how to decrease cheating in online exams and lower the probability of these actions taking place.

We categorized cheating prevention into two major types, namely, before-exam prevention and during-exam prevention. Figure Figure12 12 displays the classification of the cheating prevention methods.

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Before-exam prevention

To prevent examinees from cheating, there exist several methods that should be implemented before the exam is held. Each will be discussed in detail as follows.

Exam design

In any situation that prevention is concerned, a proven and low-cost approach is a “cheat-resistant” design -A design that inherently prevents some specific cheating types from happening. This is why exam design is so critical. A cheat-resistant exam design, by its nature, prevents a range of possible forms of cheatings from occurring.

One way of achieving a good design is developing personalized exams for each candidate separately. There are several ways to do so, such as parameterization (Manoharan, 2019 ), which is a set of fixed questions with variable assumption values, using data banks with a large pool of questions to select questions randomly (Manoharan, 2019 ), (Norris, 2019 ) or implementing an AI-based method to produce unique exams (Chua & Lumapas, 2019 ).

Li et al. ( 2020 ) has put effort into designing a method for randomizing the question orders for each candidate. Their general idea is to show the questions one by one, and besides that, each student gets a different question at a time. This research mathematically proves that examinees cannot get much cheating gain.

In (Manoharan, 2019 ), the author has investigated an approach to personalizing multiple-choice examinations using the macro. Macro is a computer program fragment that stores data. It has a set of particular inputs for generating random exams based on a question bank. This method could bring freedom and flexibility to the exam design, but it needs basic programming skills.

Another aspect of exam design concentrates specifically on question design. Some of the most valuable methods are listed below.

Using novel questions: This type of question design is so unique in design and phrasing that it becomes very challenging to be plagiarized even with searching the web (Nguyen et al., 2020 ).
Using knowledge-based questions instead of information-based questions: These questions challenge the level of knowledge. The answers are not on the web or in reference books, and they need critical thinking and reasoning (Nguyen et al., 2020 ).
Using essay questions rather than multiple-choice questions: During an online exam, multiple-choice questions are highly susceptible to cheating. Hence, long essay questions are preferred (Varble, 2014 ).
Using questions with specific assumptions and facts: Although giving extra and not useful facts may mislead any candidate, even those taking the exam honestly, it will reduce the possibility of web-based plagiarism considerably by making it less straightforward to search online (Nguyen et al., 2020 ).
Having an open-book exam: Open-book exam questions should test students’ understanding, critical reasoning, and analytical skills. Since the answers to these questions are not found in any sources directly, open-book exams may reduce the cheating opportunity (Varble, 2014 ), (Backman, 2019 ).

Finally, other methods not placed into the above categories are mentioned below.

Showing questions one by one without the option of going backward is effective in cheating prevention. If it is employed besides strict time limitations and random question series, collaborative cheating will become quite challenging (Chirumamilla & Sindre, 2019 ), (Backman, 2019 ). By setting strict time limitations, the students do not have enough time to handle cheating, therefore, exam cheating efforts are reduced (Backman, 2019 ).

Cluskey et al. ( 2011 ), emphasize low-cost approaches for addressing online exam cheating. They introduce online exam control procedures (OECP) to achieve this target. Taking the exam only at a defined time and avoiding postponing it for any reason, or changing at least one-third of the questions in the next exam, are some instances of these procedures.

Authentication

Authentication is mainly for impersonation prevention before examinations. It could be done classically by checking the school ID badges or government-issued ID by the webcam (Moten et al., 2013 ) or by a more modern approach like biometrics through fingerprint, palm vein scan (Korman, 2010 ), eye vein scan (Kigwana & Venter, 2016 ), voice, and keystroke biometrics (Norris, 2019 ).

An interesting method to prevent cheating has been presented in (Moten et al., 2013 ). Students should call the instructor at a predetermined time to get the password. After the students’ voices are recognized by the instructor, they are authenticated and receive a random password for exam entrance. The password is valid until the end of the exam time limit, thus this method makes cheating more difficult (Moten et al., 2013 ).

The last method of authentication is the one discussed in (Norris, 2019 ) which uses challenge questions. These are the questions only the student will know, for instance, student ID or personal information. In (Ullah, 2016 ), an approach is proposed that creates and consolidates a student’s profile during the learning process. This information is collected in the form of questions and answers. The questions are pre-defined or extracted from a student’s learning activities. A subset of questions is used for authentication, and the students should answer these questions correctly to get access to the online examination. This approach ensures that the person taking the exam is the same one who has completed the course.

Clustering means partitioning students into several groups based on a predefined similarity measure. In (Topîrceanu, 2017 ), random and strategic clustering methods are proposed to break friendships during the exam, as cheating prevention techniques. The advantages of random clustering are time and cost efficiencies; however, it is imprecise, and some clusters may include unbroken friendships.

Breaking friendships through clustering relies on two hypotheses (Topîrceanu, 2017 ):

Students tend to communicate and cheat with the people they know and feel close to.
An individuals’ relationship with others on social networks is closely related to their real-life relationships with people.

Regarding the second hypothesis, social network analysis could find students’ close friends and people they know. After clustering students, a unique set of exam questions are prepared for each cluster. Consequently, the collaboration of friends to cheat during the online exam becomes challenging.

Lowering cheating motivation

Approaches expressed in this section are based on mental and psychological aspects driving students toward academic misbehaviors, and the work being done to reduce these behaviors through controlling mental drivers.

There are several tactics to develop students’ moral beliefs encouraging them to avoid unethical behaviors. For instance, implementing honor systems helps build a healthy and ethical environment (Korman, 2010 ). Another tactic is clarifying academic integrity and morality ideals through establishing educational integrity programs (Korman, 2010 ).

As Korman ( 2010 ) further investigated, changing the students' perception about the goal of studying, could decrease cheating. This could be done by reminding them why learning matters and how it affects their future success. In (Varble, 2014 ), it is stated that emphasizing the actual value of education will lead to the same result.

Varble ( 2014 ), indicates that by improving students’ skills such as time management skills, their academic performance will be highly enhanced; accordingly, their academic misbehaviors will be declined. The risks of being caught and the significance of punishments, are inversely related to students’ motivation for cheating.

Varble ( 2014 ) also mentions that applying formative assessment rather than summative assessment effectively reduces examinees’ desire for cheating due to improving their learning outcomes. Formative assessments aim to enhance the candidates’ learning performance rather than testing them. On the other hand, summative assessments mostly care about measuring candidates’ knowledge and are used to check if they are eligible to pass the course or not.

As an additional description about getting a formative assessment to work, Nguyen et al., ( 2020 ) mention that increasing the exam frequency forces students to study course materials repeatedly, resulting in longer retention of information and knowledge in students’ minds. This brings about alleviating candidates’ motivation for cheating (Nguyen et al., 2020 ). Varble ( 2014 ), also suggests that reducing the value of each test lowers the reward gained by the cheaters over each test; consequently, the motivation for cheating is declined.

A cost-efficient and effective method to lower cheating motivation is to declare the cheating policy for examinees before the exam starts (Moten et al., 2013 ). Warning students of the consequences of being caught makes them nervous and can significantly decrease cheating. It is necessary to have a confirmation button, so that no excuses can be made by cheaters after the exam. It is such effective that in two experiments, it decreased the number of cheatings by 50% (Corrigan-Gibbs et al., 2015 ). It is worth mentioning that in the online environment, having an honor system is much less effective than warning about the consequences of cheating if being caught (Fontaine et al., 2020 ).

During-exam prevention

Most cheating prevention methods were discussed in the before-exam section; still, there exist some during-exam prevention tactics, which are presented in this sub-section.

Think-aloud request

A rarely mentioned method called Think-aloud request was discussed in (Chirumamilla & Sindre, 2019 ). In this method, a request is sent to the student to think aloud about a specific subject (or current question) at random times during the exam. The student has to respond to the request orally, and the voice is recorded for further investigation and cheating detection (e.g., slow response and voice impersonation detection). This mechanism forces students to continuously be ready for responding, which reduces the chance of student cheating. The authors have also mentioned that this system and its questions could be implemented by an AI agent.

Cheat-resistant systems

Using cheat-resistant systems will inherently prevent some kinds of cheatings, although they are costly to be implemented (Korman, 2010 ). Using a browser tab locker (Chua & Lumapas, 2019 ) is one of them that prevents unauthorized movements and also identifies them by sniffing their network packets. Another method is using wireless jammers (Chirumamilla & Sindre, 2019 ) to disrupt any radio signals (Internet) in an area which usually is the examination hall, during semi-online exams.

In (Chirumamilla & Sindre, 2019 ), some valuable suggestions are given for oral exams. One is conducting the oral exam as a flow of short questions and answers, instead of a long initial question and an extended answer afterward. This is because a flowing dialogue significantly reduces the chance of the examinee following someone else’s cues of the solution. They have also suggested that asking the examinee to respond quickly, will facilitate achieving this goal. Besides that, if candidates delay, they may be known suspicious. If a candidate was detected suspicious by the instructor, it is good to interrupt the current question with a new question. This will neutralize the effort made by a third party to help the candidate answer the question.

Another suggestion presented in (Chirumamilla & Sindre, 2019 ), is to prepare a big pool of questions for oral exams to prevent questions repetition. As a result, the candidates cannot adjust themselves to the questions asked from previous candidates.

Bribery is a kind of organizational cheating. In (Kigwana & Venter, 2016 ) it is indicated that by assigning a random human proctor for the exam right before it started, bribery and beforehand contractions between examinee and proctor would be impossible.

There is no doubt that online education has changed significantly in recent years. One of the main challenges in online education is the validity of the assessment. Specifically, during the COVID19 pandemic, the integrity of online examinations has become a significant concern. Cheating detection and prevention are hot topics in online assessments. In addition, it is needed to conduct more research on cheating motivation and cheating types. In this research, we review and classify online exam cheating comprehensively.

In this review, only publications written in English were investigated. This could result in review bias, however, it is too difficult and infeasible to review studies in all languages. Many systematic mapping researches consider only publications in English, such as (Nikou & Economides, 2018 ) (Martin et al., 2020 ) (Noorbehbahani et al., 2019 ) (Wei et al., 2021 ).

Figure Figure3 3 indicates that the publications trend is decreasing, contrary to the hypothesis that online learning is rising, especially with the emergence of the COVID-19. Notably, in this study, online cheating researches have been reviewed. So, Fig. Fig.3 3 specifically corresponds to online cheating publications not online learning studies in general. However, more investigations of online cheating studies from February 2021 onwards are required to further analyzing the trends.

Several reviewed studies have made no distinction between cheating detection and prevention (Bawarith, 2017 ; Bawarith et al., 2017 ; Korman, 2010 ; Tiong & Lee, 2021 ). They employed detection methods to identify dishonest behaviors. Then preventive actions such as making an alarm to the student, or closing the browser tab are performed to deter student cheating. Regarding this definition of prevention, several studies have applied these terms interchangeably, confusing the reader. In this study, we define cheating prevention as strategies and methods that try to prevent the occurrence of cheating in online exams. Considering the latter definition, we attempted to provide a better review and clearer classification to the readers.

One limitation in this domain is the lack of statistics on the popularity of the types, methods, and tools. In (Sabbah, 2017 ), the most common cheating behaviors and their average risks have been discussed; however, the results are limited to 10 cheating types. Hence, more investigation is required to determine the prevalence of each cheating type and cheating motivation.

An important cheating reason that is overlooked by researchers is learning styles. Students and educators have different preferred learning styles (auditory, visual, kinesthetic and read/write). If teachers and educational institutes don’t consider this issue, the course will not be apprehensible for some students, and consequently, they will be motivated to cheat.

Another issue that should be addressed is to evaluate the feasibility of cheating detection and prevention methods. If the equipment for securing online exams is expensive, the students cannot afford it. Therefore, this factor should be considered when developing detection and prevention methods. Cluskey et al. ( 2011 ), believe that some solutions (e.g., proctors) that detect cheating during online exams are too costly, and their costs outweigh their benefits in some cases. Therefore, cost-effective systems and methods should be implemented.

Privacy and convenience are also vital for examinees. If employed security mechanism for online exams violates privacy and disturbs student convenience, the evaluation will not be practical due to induced stress. Accordingly, these aspects should be considered in cheating detection and prevention systems.

In this study, cheating in online exams is reviewed and classified comprehensively. It provides the reader with valuable and practical insights to address online exam cheating. To mitigate students cheating, first, it is necessary to know cheating motivations and cheating types and technologies. Furthermore, cheating detection and prevention methods are needed to combat forbidden actions. Detection methods without applying prevention methods could not be effective. As cheating detection and prevention methods are evolved, new cheating types and technologies emerge as well. Consequently, no system can mitigate all kinds of cheating in online exams, and more advanced methods should be employed. It seems the most efficient strategy for cheating handling is to lower cheating motivation.

It should be mentioned that we have not covered studies related to technical attacks and intrusions to online exam systems and teacher devices. This topic could be considered for conducting another review study.

The impact of COVID-19 on online learning and cheating in online exams could be analyzed in future work.

Another future work is to explore how ignoring students’ learning styles in teaching and assessment could affect cheating motivation.

Privacy issues, user convenience, and enforced costs of cheating detection and prevention technologies need to be examined in other studies.

In this study, publications from 2010 to 2021 have been reviewed. More investigations are required to review accepted but unpublished studies and publications in 2022.

Table Table1Table 1

Declarations

The authors declare that they have no competing interests.

1 http://www.duplichecker.com

2 http://www.turnitin.com

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Contributor Information

Fakhroddin Noorbehbahani, Email: ri.ca.iu.gne@inahabhebroon .

Azadeh Mohammadi, Email: [email protected] .

Mohammad Aminazadeh, Email: [email protected] , Email: [email protected] .

Aisyah, S., Bandung, Y., & Subekti, L. B. (2018). Development of Continuous Authentication System on Android-Based Online Exam Application. In 2018 International Conference on Information Technology Systems and Innovation, ICITSI 2018 (pp. 171–176). Padang, Indonesia: IEEE. 10.1109/ICITSI.2018.8695954
Alessio H. The Impact of Video Proctoring in Online Courses. Journal on Excellence in Col- Lege Teaching. 2018; 29 (3):1–10. [ Google Scholar ]
Alessio HM, Malay N, Maurer K, Bailer AJ, Rubin B. Examining the Effect of Proctoring on Online Test Scores. Online Learning. 2017; 2013 (1):1–16. [ Google Scholar ]
Amigud A, Lancaster T. 246 reasons to cheat: An analysis of students’ reasons for seeking to outsource academic work. Computers and Education. 2019; 134 :98–107. doi: 10.1016/j.compedu.2019.01.017. [ CrossRef ] [ Google Scholar ]
Arnautovski, L. (2019). Face recognition technology in the exam identity authentication system - implementation concept. In 2nd International Scientific Conference MILCON’19 (pp. 51–56). Olsztyn, Poland.
Atoum Y, Chen L, Liu AX, Hsu SDH, Liu X. Automated Online Exam Proctoring. IEEE Transactions on Multimedia. 2017; 19 (7):1609–1624. doi: 10.1109/TMM.2017.2656064. [ CrossRef ] [ Google Scholar ]
Backman, J. (2019). Student s ’ Experiences of Cheating in the Online Exam Environment.
Bawarith, H. R. (2017). Student Cheating Detection System in E-exams . KING ABDULAZIZ UNIVERSITY.
Bawarith R, Basuhail A, Fattouh A, Gamalel-din PS. E-exam Cheating Detection System. International Journal of Advanced Computer Science and Applications. 2017; 8 (4):176–181. doi: 10.14569/IJACSA.2017.080425. [ CrossRef ] [ Google Scholar ]
Bilen E, Matros A. Online Cheating Amid COVID-19. Journal of Economic Behavior & Organization. 2021; 182 :196–211. doi: 10.1016/j.jebo.2020.12.004. [ CrossRef ] [ Google Scholar ]
Chirumamilla, A., & Sindre, G. (2019). Mitigation of Cheating in Online Exams: Strengths and Limitations of. In Biometric Authentication in Online Learning Environments (pp. 47–68). IGI Global. 10.4018/978-1-5225-7724-9.ch003
Chua, S. S., & Lumapas, Z. R. (2019). Online Examination System with Cheating Prevention Using Question Bank Randomization and Tab Locking. 2019 4th International Conference on Information Technology (InCIT) , 126–131.
Chuang CY, Craig SD, Femiani J. Detecting probable cheating during online assessments based on time delay and head pose. Higher Education Research and Development. 2017; 36 (6):1123–1137. doi: 10.1080/07294360.2017.1303456. [ CrossRef ] [ Google Scholar ]
Cluskey GR, Jr, Ehlen CR, Raiborn MH. Thwarting Online Exam Cheating without Proctor Supervision. 2011; 4 :1–7. [ Google Scholar ]
Corrigan-Gibbs, H., Gupta, N., Northcutt, C., Cutrell, E., & Thies, W. (2015). Deterring cheating in online environments. ACM Transactions on Computer-Human Interaction , 22 (6). 10.1145/2810239
Cote, M., Jean, F., Albu, A. B., & Capson, D. (2016). Video Summarization for Remote Invigilation of Online Exams. In 2016 IEEE Winter Conference on Applications of Computer Vision (pp. 1–9). NY, USA.
Curran K, Middleton G, Doherty C. Cheating in Exams with Technology. International Journal of Cyber Ethics in Education. 2011; 1 (2):54–62. doi: 10.4018/ijcee.2011040105. [ CrossRef ] [ Google Scholar ]
Dendir S, Maxwell RS. Cheating in online courses: Evidence from online proctoring. Computers in Human Behavior Reports. 2020; 2 :100033. doi: 10.1016/j.chbr.2020.100033. [ CrossRef ] [ Google Scholar ]
Diedenhofen B, Musch J. PageFocus: Using paradata to detect and prevent cheating on online achievement tests. Behavior Research Methods. 2017; 49 (4):1444–1459. doi: 10.3758/s13428-016-0800-7. [ PubMed ] [ CrossRef ] [ Google Scholar ]
Dobrovska D. Technical Student Electronic Cheating on Examination. In: Auer ME, Guralnick D, Uhomoibhi J, editors. Interactive Collaborative Learning. Springer International Publishing; 2017. pp. 525–531. [ Google Scholar ]
Fan, Z., Xu, J., Liu, W., & Cheng, W. (2016). Gesture based Misbehavior Detection in Online Examination. In The 11th International Conference on Computer Science & Education (pp. 234–238). NagoyaF, Japan.
Fayyoumi A, Zarrad A. Novel Solution Based on Face Recognition to Address Identity Theft and Cheating in Online Examination Systems. Advances in Internet of Things. 2014; 4 (April):5–12. doi: 10.4236/ait.2014.42002. [ CrossRef ] [ Google Scholar ]
Fluck AE. An international review of eExam technologies and impact. Computers & Education. 2019; 132 :1–15. doi: 10.1016/j.compedu.2018.12.008. [ CrossRef ] [ Google Scholar ]
Fontaine S, Frenette E, Hébert M. Exam cheating among Quebec’s preservice teachers : the influencing factors. International Journal for Educational Integrity. 2020; 16 (14):1–18. [ Google Scholar ]
Garg, K., Verma, K., Patidar, K., Tejra, N., & Petidar, K. (2020). Convolutional Neural Network based Virtual Exam Controller. In Proceedings of the International Conference on Intelligent Computing and Control Systems, ICICCS 2020 (pp. 895–899). Secunderabad, India. 10.1109/ICICCS48265.2020.9120966
Gruenigen, D. Von, de Azevedo e Souza, F. B., Pradarelli, B., Magid, A., & Cieliebak, M. (2018). Best practices in e-assessments with a special focus on cheating prevention. In 2018 {IEEE} Global Engineering Education Conference, {EDUCON} 2018, Santa Cruz de Tenerife, Tenerife, Islas Canarias, Spain, April 17-20, 2018 (pp. 893–899). IEEE. 10.1109/EDUCON.2018.8363325
He, H., Zheng, Q., Li, R., & Dong, B. (2018). Using Face Recognition to Detect “ Ghost Writer ” Cheating in Examination. In Edutainment, Lecture Notes in Computer Science (Vol. 11462, pp. 389–397). Springer International Publishing. 10.1007/978-3-030-23712-7
Holden, O., Kuhlmeier, V., & Norris, M. (2020). Academic Integrity in Online Testing: A Research Review. 10.31234/osf.io/rjk7g
Hu, S., Jia, X., & Fu, Y. (2018). Research on Abnormal Behavior Detection of Online Examination Based on Image Information. In 10th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC) (Vol. 02, pp. 88–91). Hangzhou, China: IEEE. 10.1109/IHMSC.2018.10127
Hylton K, Levy Y, Dringus LP. Computers & Education Utilizing webcam-based proctoring to deter misconduct in online exams. Computers & Education. 2016; 92–93 :53–63. doi: 10.1016/j.compedu.2015.10.002. [ CrossRef ] [ Google Scholar ]
Idemudia, S., Rohani, M. F., Siraj, M., & Othman, S. H. (2016). A Smart Approach of E-Exam Assessment Method Using Face Recognition to Address Identity Theft and Cheating. International Journal of Computer Science and Information Security , 14 (10), 515–522. Retrieved from https://sites.google.com/site/ijcsis/
Jalali, K., & Noorbehbahani, F. (2017). An Automatic Method for Cheating Detection in Online Exams by Processing the Students Webcam Images. In 3rd Conference on Electrical and Computer Engineering Technology (E-Tech 2017), Tehran, Iran (pp. 1–6). Tehran, Iran.
Kasliwal, G. (2015). Cheating Detection in Online Examinations.
Kigwana, I., & Venter, H. (2016). Proposed high-level solutions to counter online examination fraud using digital forensic readiness techniques. Proceedings of the 11th International Conference on Cyber Warfare and Security, ICCWS 2016 , 407–414.
Korman, M. (2010). Behavioral detection of cheating in online examination. Retrieved from https://pure.ltu.se/ws/files/31188849/LTU-DUPP-10112-SE.pdf
Lancaster, T., & Clarke, R. (2017). Rethinking Assessment By Examination in the Age of Contract Cheating. Plagiarism Across Europe and Beyond 2017 .
Li, M., Sikdar, S., Xia, L., & Wang, G. (2020). Anti-cheating Online Exams by Minimizing the Cheating Gain, (May). 10.20944/preprints202005.0502.v1
Li, X., Yueran, K. C., & Alexander, Y. (2015). Massive Open Online Proctor : Protecting the Credibility of MOOCs Certificates, 1129–1137.
Maeda, M. (2019). Exam cheating among Cambodian students : when , how , and why it happens. Compare: A Journal of Comparative and International Education , 1–19. 10.1080/03057925.2019.1613344
Manoharan S. Cheat-resistant multiple-choice examinations using personalization. Computers and Education. 2019; 130 :139–151. doi: 10.1016/j.compedu.2018.11.007. [ CrossRef ] [ Google Scholar ]
Martin F, Sun T, Westine CD. A systematic review of research on online teaching and learning from 2009 to 2018. Computers & Education. 2020; 159 :104009. doi: 10.1016/j.compedu.2020.104009. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
Mengash, H. (2019). Automated Detection for Student Cheating During Written Exams: An Updated Algorithm Supported by Biometric of Intent. In First International Conference on Computing (pp. 303–3111). Riyadh, Saudi Arabia. 10.1007/978-3-030-36368-0
Migut, G., Koelma, D., Snoek, C. G., & Brouwer, N. (2018). Cheat Me Not: Automated Proctoring Of Digital Exams On Bring-Your-Own-Device. In The 23rd Annual ACM Conference On In- novation And Technology In Computer Science Education (p. 388). New York, NY, USA.
Moten JM, Jr, Fitterer A, Brazier E, Leonard J, Brown A, Texas A. Examining Online College Cyber Cheating Methods and Prevention Measures. Electronic Journal of E-Learning. 2013; 11 (2):139–146. [ Google Scholar ]
Mott JH. The Detection and Minimization of Cheating During Concurrent Online Assessments Using Statistical Methods. Collegiate Aviation Review. 2010; 28 (2):32–46. [ Google Scholar ]
Nguyen, J. G., Keuseman, K. J., & Humston, J. J. (2020). Minimize Online Cheating for Online Assessments During COVID-19 Pandemic. 10.1021/acs.jchemed.0c00790
Nikou SA, Economides AA. Mobile-based assessment: A literature review of publications in major referred journals from 2009 to 2018. Computers & Education. 2018; 125 :101–119. doi: 10.1016/j.compedu.2018.06.006. [ CrossRef ] [ Google Scholar ]
Noorbehbahani, F., Salehi, F., & Jafar Zadeh, R. (2019). A systematic mapping study on gamification applied to e-marketing. Journal of Research in Interactive Marketing , 13 (3). 10.1108/JRIM-08-2018-0103
Norris M. University online cheating - how to mitigate the damage. Research in Higher Education Journal. 2019; 37 :1–20. [ Google Scholar ]
Opgen-Rhein, J., Küppers, B., & Schroeder, U. (2018). An application to discover cheating in digital exams. In ACM International Conference Proceeding Series . Koli, Finland. 10.1145/3279720.3279740
Page, M. J., Moher, D., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., & Mckenzie, J. E. (2021). PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. BMJ, 372 ,. 10.1136/bmj.n160 [ PMC free article ] [ PubMed ]
Parks RF, Lowry PB, Wigand RT, Agarwal N, Williams TL. Why students engage in cyber-cheating through a collective movement: A case of deviance and collusion. Computers and Education. 2018; 125 :308–326. doi: 10.1016/j.compedu.2018.04.003. [ CrossRef ] [ Google Scholar ]
Peytcheva-Forsyth, R., Aleksieva, L., & Yovkova, B. (2018). The impact of technology on cheating and plagiarism in the assessment – The teachers’ and students’ perspectives. In AIP Conference Proceedings 2048 (Vol. 020037, pp. 1–11).
Prathish, S., Athi Narayanan, S., & Bijlani, K. (2016). An intelligent system for online exam monitoring. In Proceedings - 2016 International Conference on Information Science, ICIS 2016 (pp. 138–143). Dublin, Ireland. 10.1109/INFOSCI.2016.7845315
Reisenwitz TH. Examining the Necessity of Proctoring Online Exams. Journal of Higher Education Theory and Practice. 2020; 20 (1):118–124. [ Google Scholar ]
Saba T, Rehman A, Jamail NSM, Marie-Sainte SL, Raza M, Sharif M. Categorizing the Students’ Activities for Automated Exam Proctoring Using Proposed Deep L2-GraftNet CNN Network and ASO Based Feature Selection Approach. IEEE Access. 2021; 9 :47639–47656. doi: 10.1109/ACCESS.2021.3068223. [ CrossRef ] [ Google Scholar ]
Sabbah, Y. W. (2017). Security of Online Examinations. In Data Analytics and Decision Support for Cybersecurity (pp. 157–200). Springer International Publishing.
Srikanth M, Asmatulu R. Modern Cheating Techniques, Their Adverse Effects on Engineering Education and preventions. International Journal of Mechanical Engineering Education. 2014; 42 (2):129–140. doi: 10.7227/IJMEE.0005. [ CrossRef ] [ Google Scholar ]
Tiong, L. C. O., & Lee, H. J. (2021). E-cheating Prevention Measures: Detection of Cheating at Online Examinations Using Deep Learning Approach -- A Case Study, XX (Xx), 1–9. Retrieved from http://arxiv.org/abs/2101.09841
Topîrceanu A. Breaking up friendships in exams: A case study for minimizing student cheating in higher education using social network analysis. Computers and Education. 2017; 115 :171–187. doi: 10.1016/j.compedu.2017.08.008. [ CrossRef ] [ Google Scholar ]
Traore, I., Nakkabi, Y., Saad, S., & Sayed, B. (2017). Ensuring Online Exam Integrity Through Continuous Biometric Authentication. In Information Security Practices (pp. 73–81). Springer International Publishing. 10.1007/978-3-319-48947-6
Turner, S. W., & Uludag, S. (2013). Student perceptions of cheating in online and traditional classes. Proceedings - Frontiers in Education Conference, FIE , (October 2013), 1131–1137. 10.1109/FIE.2013.6685007
Ullah, A. (2016). Security and Usability of Authentication by Challenge Questions in Online Examination . University of Hertfordshire.
Valverde-Berrocoso, J., Garrido-Arroyo, M. del C., Burgos-Videla, C., & Morales-Cevallos, M. B. (2020). Trends in Educational Research about e-Learning: A Systematic Literature Review (2009–2018). Sustainability , 12 (12). 10.3390/su12125153
Varble, D. (2014). Reducing Cheating Opportunities in Online Test Online Tests, 3 (3).
Watson, G., & Sottile, J. (2010). Cheating in the Digital Age: Do Students Cheat More in Online Courses?. Online Journal of Distance Learning Administration , 13 (1).
Wei X, Saab N, Admiraal W. Assessment of cognitive, behavioral, and affective learning outcomes in massive open online courses: A systematic literature review. Computers & Education. 2021; 163 :104097. doi: 10.1016/j.compedu.2020.104097. [ CrossRef ] [ Google Scholar ]
Weiner JA, Hurtz GM. A comparative Study of Online Remote Proctored Vs Onsite Proctored. Journal of Applied Testing Technology. 2017; 18 (1):13–20. [ Google Scholar ]
Wong, S., Yang, L., Riecke, B., Cramer, E., & Neustaedter, C. (2017). Assessing the usability of smartwatches for academic cheating during exams. Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2017 . 10.1145/3098279.3098568
Xiong Y, Suen HK. Assessment approaches in massive open online courses: Possibilities, challenges and future directions. International Review of Education. 2018; 64 (2):241–263. doi: 10.1007/s11159-018-9710-5. [ CrossRef ] [ Google Scholar ]

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August 23, 2022

What is cheating?

How to cheat in an exam, what are the consequences of cheating in schools.

Cheating definition:

Cheating is the act of obtaining advantages or rewards without following the rules that apply to others. Examples include cheating in a board game or in a test at school.

What causes cheating?

The problem is related to the issue of merit and rising competition. Students have to fight for the best possible grades in order to get into the most valued courses at university. Cheating in an exam is seen as an easy solution.
This spirit of competition usually translates into the idea that all is fair, that only the result counts. But this idea is challenged by well-known sportsmen and women who are regularly involved in doping cases, even though they are role models for the younger generation . 🚴🏼
When a child is under family pressure and is not allowed to make mistakes , or there is no room for failure, fraud and cheating may appear to be the only way to live up to expectations.
Finally, a student may start cheating to join a group of peers or friends who encourage this malpractice, to try and rebel or to challenge the school system.

But seriously, do you really think I'm going to encourage your child to commit a crime? Certainly not.

We all know the trick of the scientific calculator on which it is possible to record formulas or even definitions (but this does not work in French or English lessons!)
A cheat sheet can be written behind the label on the water bottle or hidden in the bottom of a pencil case
The mobile phone wallpaper acts as a notepad, which we pretend to use to look at the time 👀

All these tricks are well known classics that sometimes work during an assessment but are incredibly risky, and evidence of malpractice and cheating in exams.

Online tools

During school isolation periods in the past few years, even the most serious students enjoyed the thrill of cheating on online exams, which were much more difficult to monitor by teachers and schools.

This may have been collaborative fraud via chat groups with classmates on platforms such as Snapchat or WhatsApp. Others even paid more advanced candidates to take the exams for them. Or, more simply, they took their tests online with a second computer open on the Google homepage.

But keep in mind that whether online or face-to-face, the cheating student still faces the same risk of punishment! 👮

Cases of cheating in class

If a student hasn’t managed to revise , wants to cheat and is caught in class, it can seriously damage his or her results, as well as reputation or even place at the school. They could get a zero on their assessment, contact home or even detentions and exclusion from the school.

Parents and guardians even make an agreement with the school before their child starts to never cheat or be involved in any malpractice, which schools are serious about throughout their time there.

What are the penalties for exam fraud?

National qualifications such as GCSEs , A-Levels and exams at university are all official exams recognised by the government. If an exam invigilator catches your child cheating in the examination room, a verbal and written report will be drawn up and an investigation will begin.

Depending on the seriousness of the situation and the exam board or school, cheating at the exam can lead to different types of sanctions:

Reprimand. This is a disciplinary sanction, a call to order without too serious consequences, usually reserved for internal school exams only (not National qualifications where consequences are more serious)
Removal from the course or overall diploma, sometimes resulting in having to restart completely
Immediate contact to the exams regulation authority, JCQ , who monitor most exam boards like AQA or Edexcel
No awarded mark, grade, GCSE, A-Level or points for the course at university in that subject (usually named an ‘Ungraded’ or U)
Sometimes a ban on taking any National exams for a number of years
Sometimes, but infrequently, a ban on enrolling into a higher education institution for 5 years

Exam malpractice is rising; in 2019 Ofqual reported an 11% rise in malpractice reports, and this includes teachers and schools helping students to cheat!

Can you pass your driving test if you cheat at your exam?

I've always heard that a student who is caught cheating on the exam is then likely to be barred from taking any other official exam, including the assessment to get their UK driving licence. 🚗

Today, I can officially tell you that this is an urban legend. As the driving licence is not linked with our education certification system, it is not affected by the sanctions. But, cheating in an exam (and getting caught) can change your mindset to all other exams you go on to sit for the worse.

But rather than having to ask yourself this question, the best thing to do is to book some lessons online with our tutors. They will help your child to prepare well for challenging exams like GCSEs, without the need to cheat!

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Cheating in College Exams

Why some students cheat.

The Hidden World of Exam Cheating
People Cheat on Tests, But the Way They Do it May Surprise You

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College Students Cheating on Exams Pages: 3 (807 words)
Deconstructing the psychology of cheating in AIT gym: “Cheating is a choice, not a mistake” Pages: 9 (2579 words)
Should Exams be Abolished or Not? Pages: 2 (443 words)
Debating the Merits of Exams: A Controversial Educational Assessment Pages: 1 (300 words)
Is it time to scrap exams? Pages: 4 (1120 words)
Critical Examination of Final Exams: Educational Dilemmas and Benefits Pages: 3 (746 words)
Navigating Telemedicine Challenges: Exams, Rules, Reimbursement, Tech Pages: 3 (647 words)
Strategies for Success in Final Cumulative Exams Pages: 3 (822 words)
The Prevalence of Cheating in Sports Pages: 5 (1341 words)
Cheating: How To Change The Academic Culture Pages: 6 (1680 words)

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Incident of cheating at the exams (primary 4 essay for 10 year olds by elijah wee, singapore).

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Wow! You so smart leh

Students are ready to do everything to pass their exams, including cheating, if you wonder why they prefer this instead of studying a displine, this source can explain you in details http://livecustomwriting.com/blog/why-do-students-cheat-on-assignments-and-exams

this is a good example that if children did not study for their test or examination, they will cheat.If they cheat, they would be found out very soon no matter how much they hide from the invigilator. Good example :D

Nice story . No wonder you got good marks for your exam . Congratulations to you !!!!!

Wow! very impressive story

Vry waL DEN

"was a momentary silence as the frantic writing of text ceased" can I know the meaning?? I searched it on Google but I still can get it...

AI Cheating Is Getting Worse

Colleges still don’t have a plan.

Three ChatGPT window prompts, with "Write me an essay" typed into them

Produced by ElevenLabs and News Over Audio (NOA) using AI narration.

K yle Jensen, the director of Arizona State University’s writing programs, is gearing up for the fall semester. The responsibility is enormous: Each year, 23,000 students take writing courses under his oversight. The teachers’ work is even harder today than it was a few years ago, thanks to AI tools that can generate competent college papers in a matter of seconds.

A mere week after ChatGPT appeared in November 2022, The Atlantic declared that “ The College Essay Is Dead .” Two school years later, Jensen is done with mourning and ready to move on. The tall, affable English professor co-runs a National Endowment for the Humanities–funded project on generative-AI literacy for humanities instructors, and he has been incorporating large language models into ASU’s English courses. Jensen is one of a new breed of faculty who want to embrace generative AI even as they also seek to control its temptations. He believes strongly in the value of traditional writing but also in the potential of AI to facilitate education in a new way—in ASU’s case, one that improves access to higher education.

Read: The first year of AI college ends in ruin

But his vision must overcome a stark reality on college campuses. The first year of AI college ended in ruin, as students tested the technology’s limits and faculty were caught off guard. Cheating was widespread. Tools for identifying computer-written essays proved insufficient to the task . Academic-integrity boards realized they couldn’t fairly adjudicate uncertain cases: Students who used AI for legitimate reasons, or even just consulted grammar-checking software, were being labeled as cheats. So faculty asked their students not to use AI, or at least to say so when they did, and hoped that might be enough. It wasn’t.

Now, at the start of the third year of AI college, the problem seems as intractable as ever. When I asked Jensen how the more than 150 instructors who teach ASU writing classes were preparing for the new term, he went immediately to their worries over cheating. Many had messaged him, he told me, to ask about a recent Wall Street Journal article about an unreleased product from OpenAI that can detect AI-generated text. The idea that such a tool had been withheld was vexing to embattled faculty.

ChatGPT arrived at a vulnerable moment on college campuses, when instructors were still reeling from the coronavirus pandemic. Their schools’ response—mostly to rely on honor codes to discourage misconduct—sort of worked in 2023, Jensen said, but it will no longer be enough: “As I look at ASU and other universities, there is now a desire for a coherent plan.”

L ast spring, I spoke with a writing professor at a school in Florida who had grown so demoralized by students’ cheating that he was ready to give up and take a job in tech. “It’s just about crushed me,” he told me at the time. “I fell in love with teaching, and I have loved my time in the classroom, but with ChatGPT, everything feels pointless.” When I checked in again this month, he told me he had sent out lots of résumés, with no success. As for his teaching job, matters have only gotten worse. He said that he’s lost trust in his students. Generative AI has “pretty much ruined the integrity of online classes,” which are increasingly common as schools such as ASU attempt to scale up access. No matter how small the assignments, many students will complete them using ChatGPT. “Students would submit ChatGPT responses even to prompts like ‘Introduce yourself to the class in 500 words or fewer,’” he said.

If the first year of AI college ended in a feeling of dismay, the situation has now devolved into absurdism. Teachers struggle to continue teaching even as they wonder whether they are grading students or computers; in the meantime, an endless AI-cheating-and-detection arms race plays out in the background. Technologists have been trying out new ways to curb the problem; the Wall Street Journal article describes one of several frameworks. OpenAI is experimenting with a method to hide a digital watermark in its output, which could be spotted later on and used to show that a given text was created by AI. But watermarks can be tampered with, and any detector built to look for them can check only for those created by a specific AI system. That might explain why OpenAI hasn’t chosen to release its watermarking feature—doing so would just push its customers to watermark-free services.

Other approaches have been tried. Researchers at Georgia Tech devised a system that compares how students used to answer specific essay questions before ChatGPT was invented with how they do so now. A company called PowerNotes integrates OpenAI services into an AI-changes-tracked version of Google Docs, which can allow an instructor to see all of ChatGPT’s additions to a given document. But methods like these are either unproved in real-world settings or limited in their ability to prevent cheating. In its formal statement of principles on generative AI from last fall, the Association for Computing Machinery asserted that “reliably detecting the output of generative AI systems without an embedded watermark is beyond the current state of the art, which is unlikely to change in a projectable timeframe.”

Read: A generation of AI guinea pigs

This inconvenient fact won’t slow the arms race. One of the generative-AI providers will likely release a version of watermarking, perhaps alongside an expensive service that colleges can use in order to detect it. To justify the purchase of that service, those schools may enact policies that push students and faculty to use the chosen generative-AI provider for their courses; enterprising cheaters will come up with work-arounds, and the cycle will continue.

But giving up doesn’t seem to be an option either. If college professors seem obsessed with student fraud, that’s because it’s widespread. This was true even before ChatGPT arrived: Historically, studies estimate that more than half of all high-school and college students have cheated in some way. The International Center for Academic Integrity reports that, as of early 2020, nearly one-third of undergraduates admitted in a survey that they’d cheated on exams. “I’ve been fighting Chegg and Course Hero for years,” Hollis Robbins, the dean of humanities at the University of Utah, told me, referring to two “homework help” services that were very popular until OpenAI upended their business . “Professors are assigning, after decades, the same old paper topics—major themes in Sense and Sensibility or Moby-Dick ,” she said. For a long time, students could just buy matching papers from Chegg, or grab them from the sorority-house files; ChatGPT provides yet another option. Students do believe that cheating is wrong , but opportunity and circumstance prevail.

S tudents are not alone in feeling that generative AI might solve their problems. Instructors, too, have used the tools to boost their teaching. Even last year, one survey found, more than half of K-12 teachers were using ChatGPT for course and lesson planning. Another one, conducted just six months ago, found that more than 70 percent of the higher-ed instructors who regularly use generative AI were employing it to give grades or feedback to student work. And the tech industry is providing them with tools to do so: In February, the educational publisher Houghton Mifflin Harcourt acquired a service called Writable , which uses AI to give grade-school students comments on their papers.

Jensen acknowledged that his cheat-anxious writing faculty at ASU were beset by work before AI came on the scene. Some teach five courses of 24 students each at a time. (The Conference on College Composition and Communication recommends no more than 20 students per writing course and ideally 15, and warns that overburdened teachers may be “spread too thin to effectively engage with students on their writing.”) John Warner, a former college writing instructor and the author of the forthcoming book More Than Words: How to Think About Writing in the Age of AI , worries that the mere existence of these course loads will encourage teachers or their institutions to use AI for the sake of efficiency, even if it cheats students out of better feedback. “If instructors can prove they can serve more students with a new chatbot tool that gives feedback roughly equivalent to the mediocre feedback they received before, won’t that outcome win?” he told me. In the most farcical version of this arrangement, students would be incentivized to generate assignments with AI, to which teachers would then respond with AI-generated comments.

Stephen Aguilar, a professor at the University of Southern California who has studied how AI is used by educators, told me that many simply want some leeway to experiment. Jensen is among them. Given ASU’s goal to scale up affordable access to education, he doesn’t feel that AI has to be a compromise. Instead of offering students a way to cheat, or faculty an excuse to disengage, it might open the possibility for expression that would otherwise never have taken place—a “path through the woods,” as he put it. He told me about an entry-level English course in ASU’s Learning Enterprise program, which gives online learners a path to university admission. Students start by reading about AI, studying it as a contemporary phenomenon. Then they write about the works they read, and use AI tools to critique and improve their work. Instead of focusing on the essays themselves, the course culminates in a reflection on the AI-assisted learning process.

Read: Here comes the second year of AI college

Robbins said the University of Utah has adopted a similar approach. She showed me the syllabus from a college writing course in which students use AI to learn “what makes writing captivating.” In addition to reading and writing about AI as a social issue, they read literary works and then try to get ChatGPT to generate work in corresponding forms and genres. Then they compare the AI-generated works with the human-authored ones to suss out the differences.

But Warner has a simpler idea. Instead of making AI both a subject and a tool in education, he suggests that faculty should update how they teach the basics. One reason it’s so easy for AI to generate credible college papers is that those papers tend to follow a rigid, almost algorithmic format. The writing instructor, he said, is put in a similar position, thanks to the sheer volume of work they have to grade: The feedback that they give to students is almost algorithmic too. Warner thinks teachers could address these problems by reducing what they ask for in assignments. Instead of asking students to produce full-length papers that are assumed to stand alone as essays or arguments, he suggests giving them shorter, more specific prompts that are linked to useful writing concepts. They might be told to write a paragraph of lively prose, for example, or a clear observation about something they see, or some lines that transform a personal experience into a general idea. Could students still use AI to complete this kind of work? Sure, but they’ll have less of a reason to cheat on a concrete task that they understand and may even want to accomplish on their own.

“I long for a world where we are not super excited about generative AI anymore,” Aguilar told me. He believes that if or when that happens, we’ll finally be able to understand what it’s good for. In the meantime, deploying more technologies to combat AI cheating will only prolong the student-teacher arms race. Colleges and universities would be much better off changing something— anything , really—about how they teach, and what their students learn. To evolve may not be in the nature of these institutions, but it ought to be. If AI’s effects on campus cannot be tamed, they must at least be reckoned with. “If you’re a lit professor and still asking for the major themes in Sense and Sensibility ,” Robbins said, “then shame on you.”

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About the Author

Statistical analysis can detect when ChatGPT is used to cheat on multiple-choice chemistry exams

by McKenzie Harris, Florida State University

As the use of generative artificial intelligence continues to extend into all reaches of education, much of the concern related to its impact on cheating has focused on essays, essay exam questions and other narrative assignments. Use of AI tools such as ChatGPT to cheat on multiple-choice exams has largely gone ignored.

A Florida State University chemist is half of a research partnership whose latest work is changing what we know about this type of cheating, and their findings have revealed how the use of ChatGPT to cheat on general chemistry multiple-choice exams can be detected through specific statistical methods. The work was published in Journal of Chemical Education .

"While many educators and researchers try to detect AI assisted cheating in essays and open-ended responses, such as Turnitin AI detection, as far as we know, this is the first time anyone has proposed detecting its use on multiple-choice exams," said Ken Hanson, an associate professor in the FSU Department of Chemistry and Biochemistry. "By evaluating differences in performances between student- and ChatGPT-based multiple-choice chemistry exams, we were able to identify ChatGPT instances across all exams with a false positive rate of almost zero."

Researchers collected previous FSU student responses from five semesters worth of exams, input nearly 1,000 questions into ChatGPT and compared the outcomes. Average score and raw statistics were not enough to identify ChatGPT-like behavior because there are certain questions that ChatGPT always answered correctly or always answered incorrectly resulting in an overall score that was indistinguishable from students.

"That's the thing about ChatGPT—it can generate content, but it doesn't necessarily generate correct content," Hanson said. "It's simply an answer generator. It's trying to look like it knows the answer, and to someone who doesn't understand the material, it probably does look like a correct answer."

By using fit statistics, researchers fixed the ability parameters and refit the outcomes, finding ChatGPT's response pattern was clearly different from that of the students.

On exams, high-performing students frequently answer difficult and easy questions correctly, while average students tend to answer some difficult questions and most easy questions correctly. Low-performing students typically only answer easy questions correctly. But on repeated attempts by ChatGPT to complete an exam, the AI tool sometimes answered every easier question incorrectly and every hard question correctly. Hanson and Sorenson used these behavior differences to detect the use of ChatGPT with almost 100-percent accuracy.

The duo's strategy of employing a technique known as Rasch modeling and fit statistics can be readily applied to any and all generative AI chat bots, which will exhibit their own unique patterns to help educators identify the use of these chat bots in completing multiple-choice exams.

The research is the latest publication in a seven-year collaboration between Hanson and machine learning engineer Ben Sorenson.

Hanson and Sorenson, who first met in third grade, both attended St. Cloud State University in Minnesota for their undergraduate degrees and stayed in touch after moving into their careers. As a faculty member at FSU, Hanson became curious about measuring how much knowledge his students retained from lectures, courses and lab work.

"This was a conversation that I brought to Ben, who's great with statistics, computer science and data processing ," said Hanson, who is part of a group of FSU faculty working to improve student success in gateway STEM courses such as general chemistry and college algebra. "He said we could use statistical tools to understand if my exams are good, and in 2017, we started analyzing exams."

The core of this Rasch model is that a student's probability of getting any test question correct is a function of two things: how difficult the question is and the student's ability to answer the question. In this case, a student 's ability refers to how much knowledge they have and how many of the necessary components are needed to answer the question they have. Viewing the outcomes of an exam in this way provides powerful insights, researchers said.

"The collaboration between Ken and I, though remote, has been a really seamless, smooth process," Sorenson said. "Our work is a great way to provide supporting evidence when educators might already suspect that cheating may be happening. What we didn't expect was that the patterns of artificial intelligence would be so easy to identify."

Journal information: Journal of Chemical Education

Provided by Florida State University

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As results released, CXC reveals rise in cheating

CARIBBEAN Examinations Council (CXC) director of operations Dr Nicole Manning revealed a notable rise in cheating in this year's CSEC exam as the organisation launched the release of results, available to individual pupils online at CSEC and CAPE level.

The launch was held in Dominica on August 20, with the feature address delivered by CXC registrar and CEO Dr Wayne Wesley.

Manning said cases of cheating, which she referred to as "irregularities," rose from 36 pupils caught last year to 54 cases this year.

"We are seeing a lot of cheating using the cellphone," she said. "One candidate said he was googling the answer."

Manning used the occasion to ask pupils not to cheat, but instead to uphold ethics and integrity.

"We will research why candidates would not have been prepared."

She said some pupils tried to sneak unauthorised papers into the exam room, others were caught checking their phones for information they had previously stored, and others tried to communicate with each other during exam sessions.

"It is speaking to a level of ill-preparedness for the exam," she reiterated, saying this was also a common reason for pupils not turning up to sit the exam.

Across the region, the CAPE results included 100 per cent of pupils passing French Unit Two, 97 per cent passing both physics Units One and Two, and 96 per cent passing information technology Unit Two. However Wesley lamented the low pass rate in CSEC maths, saying it must be addressed.

[UPDATED] Imbert: Time for Trinidad and Tobago to go cashless

San fernando man killed on birthday, [updated] woman, 18, dies in accident on hochoy highway, iwer brings new nightclub to tobago, ex-windies skipper daren sammy is utc brand ambassador, developer revamping hevron heights into luxury apartments, "as results released, cxc reveals rise in cheating", more in this section, sportt wins $30m judgment for life sport contract, princes town woman, 82, stabbed 16 times in home invasion, gun, ammo found in point fortin, arima, dengue cases cross 900.

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Guest Essay

How Harris Has Completely Upended the Presidential Race, in 14 Maps

Daniel Zvereff

By Doug Sosnik Graphics by Quoctrung Bui

Mr. Sosnik was a senior adviser to President Bill Clinton from 1994 to 2000 and has advised more than 50 governors and U.S. senators.

With Kamala Harris now at the top of the ticket, the enthusiasm and confidence within the Democratic Party feel stronger than at any point I’ve seen since Barack Obama ran for president in 2008. And it’s not just vibes: The paths to victory in the Electoral College have been completely reshaped for the Democrats – and for Donald Trump – since my last analysis of the electoral map on July 12, nine days before Joe Biden exited the race.

Not only have Democrats come home to support their party’s nominee, they are now also more energized about the election than Republicans. Ms. Harris has quickly picked up support from nonwhite and younger voters.

We are now back to the same electoral map that we had before Mr. Biden’s summertime polling collapse: Once again, the winner in November will come down to the seven battleground states of Arizona, Georgia, Michigan, Nevada, North Carolina, Pennsylvania and Wisconsin.

The seven swing states that will most likely decide the 2024 presidential election.

Current polling shows the transformed race: While Mr. Biden trailed Mr. Trump in all seven battleground states last month, Ms. Harris is now leading Mr. Trump by four points in Michigan, Pennsylvania and Wisconsin in the latest New York Times/Siena College polls . Other polls show Ms. Harris in a statistical dead heat in Georgia and Arizona .

Those polls also reveal one of Mr. Trump’s biggest obstacles to winning the election: A majority of the country has never supported him, either as president or as a candidate for office. In the Times/Siena surveys, Mr. Trump had polled at only 46 percent in Michigan, Pennsylvania and Wisconsin. And with the race no longer between two unpopular nominees, support for third-party candidates has dropped, making it much more difficult for Mr. Trump to win.

And yet: Republicans have a structural advantage in the Electoral College system of voting, giving Mr. Trump at least one advantage against a surging Ms. Harris.

The G.O.P. lost the popular vote in seven out of the last eight presidential elections, yet won the White House in three of those elections. In 2016, Mr. Trump eked out Electoral College wins in swing states like Wisconsin even as Hillary Clinton crushed him in the most populous states like California. The Republican edge has only grown stronger with the reallocation of electoral votes based on the most recent census.

Given that structural advantage, Georgia, and its 16 Electoral College votes, is increasingly becoming a pivotal state that Mr. Trump can’t lose. If Ms. Harris is able to carry Georgia – and Mr. Trump seems to be trying to help her by inexplicably attacking the popular incumbent Republican governor and his wife – then she would have 242 electoral votes, only 28 short of the 270 needed to win.

Mr. Trump may not understand the political consequences of losing Georgia, but his advisers appear to: His campaign and biggest aligned super PAC spent four times as much in advertising in the state in the two weeks since Ms. Harris became the Democratic Party nominee as they did in the rest of 2024 combined. And in this coming week, of the $37 million in ad buys that the Trump campaign has placed nationally, almost $24 million are in Georgia.

Pennsylvania looks increasingly to be the other key battleground state, and both parties know it. According to AdImpact , over $211 million in paid media has so far been purchased in Pennsylvania from March 6 until Election Day, which is more than double the amount in any other state.

Given its size and support for Democratic candidates in the past, if Ms. Harris loses Pennsylvania, that could be just as damaging to her candidacy as a loss in Georgia would be to Mr. Trump’s chances.

This is why Georgia and Pennsylvania are the two most important states to watch to see if one candidate is able to establish a decisive path to 270 electoral votes.

Ms. Harris starts out with 226 likely electoral votes compared to 219 for Mr. Trump, with 93 votes up for grabs. However, unlike Mr. Biden last month, she has multiple paths to 270 electoral votes.

The first path for Ms. Harris is to carry Pennsylvania , which Mr. Biden won by more than 80,000 votes in 2020 and has voted for the Democratic candidate in seven out of the last eight presidential elections. Assuming that Ms. Harris wins Pennsylvania, she will have 245 electoral votes and six paths to 270.

Scenario 1 Then all Ms. Harris needs are Michigan and Wisconsin (assuming that she carries the Second Congressional District in Nebraska) …

Scenario 2 … or Wisconsin and Georgia …

Scenario 3 … or Wisconsin, Arizona and Nevada …

Scenario 4 … or Michigan and Arizona …

Scenario 5 … or Michigan and Georgia …

Scenario 6 … or Georgia and Arizona.

The second path for Ms. Harris does not require her winning Pennsylvania. Instead she needs to win Wisconsin , Michigan , Georgia and …

Scenario 1 … Arizona …

Scenario 2 … or Nevada .

Based on past elections, Mr. Trump starts out with 219 Electoral College votes, compared to 226 for Ms. Harris, with 93 votes up for grabs.

It’s difficult to see how Mr. Trump could win the election if he cannot carry North Carolina , which generally favors Republican presidential candidates. That would give Mr. Trump 235 electoral votes and multiple paths to 270.

The first path involves carrying Georgia , a state he lost by fewer than 12,000 votes in 2020. Before then, Republicans won Georgia in every election since 1992. If Mr. Trump carried North Carolina and Georgia, he would have a base of 251 electoral votes.

Scenario 1 Then all Mr. Trump needs is Pennsylvania …

Scenario 2 … or Michigan and Nevada …

Scenario 3 … or Michigan and Arizona …

Scenario 4 … or Arizona and Wisconsin …

The second and more difficult path for Mr. Trump would be if he carried North Carolina but lost Georgia. He would then have only 235 electoral votes and would need to win three of the six remaining battleground states.

Scenario 1 Like Arizona, Michigan and Wisconsin …

Scenario 2 … or Arizona, Nevada and Pennsylvania .

A Look Ahead to November

Ms. Harris clearly has the momentum going into the Democratic National Convention, but she has not really been tested yet. At some point she will need to demonstrate that she can perform under pressure in order to win over undecided voters and less enthusiastic moderates and independents.

As unruly as this election year has been, there are still certain rules of politics that apply to the presidential race. History has repeatedly shown that the winning candidates are usually the ones best able to define who they are, whom they are running against and what the election is about.

Mr. Trump had made the election a referendum of his presidency compared to Mr. Biden’s – that he was a strong leader and Mr. Biden was weak.

In the past three weeks, Ms. Harris has set the terms of the campaign as a choice between change versus going backward – a positive view of the future compared to a dystopian view of the present with a desire to go back to the past.

But even though Ms. Harris’s favorability has gone up significantly since she announced her candidacy, the increase in support is soft. That is the reason that the Democratic convention is such an important opportunity for her to close the deal with key swing voters.

Mr. Trump, on the other hand, is fully defined in the minds of most voters, and has elected to double down on catering to his MAGA base despite alienating the key swing voter blocs that will determine the outcome of the election. During the last hour of his convention speech, and every day since then, Mr. Trump has offered words and actions that remind Americans why they voted him out of office in 2020.

Mr. Trump has increasingly looked like a washed-up rock star who can play only his greatest hits for his dwindling group of fans. If he loses in November, he will have been a one-hit wonder who led the Republican Party to four presidential and midterm election-cycle losses in a row.

More on the 2024 presidential election

What the Polls Say About Harris That the Trump Team Doesn’t Like

If a major change on the Democratic ticket fires up progressives, it wouldn’t be unusual to see a slightly higher number of progressive likely voters.

By Kristen Soltis Anderson

Don’t Listen to the Right. The Kamalanomenon Is Real.

There was Obama-level excitement at Harris’s Atlanta rally.

By Michelle Goldberg

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The Problem of Cheating in Exams: An Argumentative Essay Example
Cheating Your Way Through Exams: Best Tricks
Cheating on the Exam Essay Example
Exam Cheating, Its Causes and Effects
Student Cheating in an Exam and Its Consequences
SOLUTION: Examination or cheating in exams

COMMENTS

Exam Cheating, Its Causes and Effects
In the education fraternity, cheating entails: copying from someone, Plagiarizing of academic work and paying someone to do your homework. There are numerous reasons why students cheat in exams however; this action elicits harsh repercussions if one is caught. This may include: suspension, dismissal and/or cancellation of marks (Davis, Grover ...
Why Students Cheat—and What to Do About It
Cases like the much-publicized (and enduring) 2012 cheating scandal at high-achieving Stuyvesant High School in New York City confirm that academic dishonesty is rampant and touches even the most prestigious of schools.The data confirms this as well. A 2012 Josephson Institute's Center for Youth Ethics report revealed that more than half of high school students admitted to cheating on a test ...
Consequences Of Cheating In Exams: Examples And Effects
12. Cheating is a form of disrespect. One of the key aspects to consider when examining the act of cheating is the underlying disrespect it displays towards the educational system and its values. Cheating in exams is a form of disrespectful behavior that undermines the principles of academic integrity and moral values.
Essay About Cheating On Exams
Essay About Cheating On Exams. 795 Words4 Pages. Cheating on Exams Have you ever thought what make students cheat during exams and what the consequences are? Cheating can be considered as one of the main problems that some schools or universities may suffer from. Due to the pressure that many students may face during their educational life ...
Students' Behavior and Cheating During Exams Essay (Critical Writing)
Response. The study concerning cheating by college students does not require an informed consent because of various reasons. First, an evaluation of students' behavior during an examination is an educational practice that is necessary to establish behaviors associated with examination cheating. Students are aware of guidelines that restrict ...
Consequences of a College Student Cheating in Exams Essay
One of the consequences involves failure in the specific course which leads to the overall failure. This is because cheating may result in getting a zero mark. Apart from the failure, the student may also face the academic examination and disciplinary body which may make severe judgment for instance suspension or probation in case of first ...
Cheating on exams: Investigating Reasons, Attitudes, and the Role of
The most common method for cheating was looking at others' exam papers. They too call for legislative actions to be taken toward cheating. Ahanchiyan et al. (2016) used a qualitative approach to delineate factors involved in cheating. They came up with the two kinds of internal and external factors related to the act of cheating.
Why Do Students Cheat?
Sometimes they have a reason to cheat like feeling [like] they need to be the smartest kid in class.". Kayla (Massachusetts) agreed, noting, "Some people cheat because they want to seem cooler than their friends or try to impress their friends. Students cheat because they think if they cheat all the time they're going to get smarter.".
Argumentative Essay About Cheating
Cheating, a prevalent issue across educational institutions, has sparked debates about its moral implications and consequences. From cheating on exams to plagiarizing assignments, the act of dishonesty raises questions about the values and integrity of individuals. In this argumentative essay, we will delve into the various aspects of cheating ...
Students cheat on assignments and exams.
Students are more likely to cheat or plagiarize if the assessment is very high-stakes or if they have low expectations of success due to perceived lack of ability or test anxiety. Students might be in competition with other students for their grades. Students might perceive a lack of consequences for cheating and plagiarizing.
How Common is Cheating in Online Exams and did it Increase ...
Academic misconduct is a threat to the validity and reliability of online examinations, and media reports suggest that misconduct spiked dramatically in higher education during the emergency shift to online exams caused by the COVID-19 pandemic. This study reviewed survey research to determine how common it is for university students to admit cheating in online exams, and how and why they do ...
Education: Why Do Students Cheat?
Students cheat because many institutions of learning value grades more than attainment of knowledge (Davis et al. 36). Many school systems have placed more value on performing well in tests and examination than on the process of learning. When assessment tests and examinations play a key role in determining the future of a student, cheating ...
The Effects of Cheating on Exams
Essay Example: Cheating on exams has become more prevalent throughout the 21st century as the importance of learning is eliminated. It disobeys the expectations for a well-behaved Stuyvesant student, and the offense becomes a violation of the morals of society. In highly-competitive schools
Cheating behaviour in online exams: On the role of needs, conceptions
We also provided some examples (multiple-choice exams, essays, closed/open-book formats and take-home exams handed in after, e.g., 24 h) and counterexamples (practical exams, oral exams or exams that are written over a longer period of time, such as term papers and portfolio exams). ... In addition, some students saw no reason in cheating when ...
Why Do Students Cheat in Exams?: Effects & Causes Listed
For a student, the pressure or tension is felt when the student is unable to cope with the syllabus. This stress is one of the main reasons for students to cheat in exams. Unable to bear the stress and tension, students may resort to unlawful means like cheating during examinations. 3. Fear of Failure.
Cheating in Exams, Essay Example
Cheating in exams can be defined as committing acts of dishonesty during an exam in order to score good grades. This is normally done by students when they fail to prepare for the exams or when they feel that the test is too hard for them and they want to score good grades. Various acts are considered as cheating: first when a student gets ...
Student Cheating in an Exam and Its Consequences Free Essay Example
The first category is the direct or immediate consequences. The direct consequences refer to the consequences a student faces when caught cheating. Different colleges have different policies for dealing with students caught cheating in exams. The second category of consequences of cheating in an exam is the long-term effects.
Consequences Of Cheating In Exams
Consequences Of Cheating In Exams. In todays age when you look at the word Cheating, you may find many different definitions or meanings. Whether you cheat at work; known as fraud, cheat at home; known as dishonesty, or at school, this act of conduct can lead to many consequences made by ones choice. Cheating is defined in the dictionary as, to ...
A systematic review of research on cheating in online exams from 2010
Notably, in this study, online cheating researches have been reviewed. So, Fig. 3 specifically corresponds to online cheating publications not online learning studies in general. However, more investigations of online cheating studies from February 2021 onwards are required to further analyzing the trends.
What are the consequences of cheating in exams?
If an exam invigilator catches your child cheating in the examination room, a verbal and written report will be drawn up and an investigation will begin. Depending on the seriousness of the situation and the exam board or school, cheating at the exam can lead to different types of sanctions: Reprimand. This is a disciplinary sanction, a call to ...
PDF Friends with Benefits: Causes and Effects of Learners' Cheating ...
reason to cheat were: Not preparing for the exam, lack of time to study, carelessness and lack of punishment from instructors. The most common methods of cheating were found to be copying from other test studies and talking to neighbors during the exam, besides using certain gestures to get answers from others (Ahmadi, 2012).
The problem of cheating in exams
18950. The problem of cheating in exams is not a new problem. This problem may origin from the students' ability to cheat during exams. There are many reasons for cheating. I am going to discuss three main reasons for cheating. First of all, the main reason which leads students to cheat on the tests is that they want to get good grades.
Online learning expert suggests best practices for promoting academic
Whether cheating is more or less prevalent in remote coursework has been the topic of debate since online coursework went mainstream in the early 2000s. While online learning provides access to education for nontraditional students and in nontraditional circumstances (such as the COVID-19 pandemic), it's important to ensure that students are ...
ChatGPT cheating is endemic in schools, and no one knows ...
The International Center for Academic Integrity reported that nearly one-third of undergraduates admitted to cheating on exams as of ... compare students' responses to essay questions before and ...
Incident of cheating at the exams (Primary 4 essay for 10 ...
I am particularly proud of this essay I wrote when I was in Primary 4 (10 years old) at Ngee Ann Primary School - received my personal best score for this one, entitled "Incident of cheating at the exams". John was a lazy boy. He would always play computer games and watch television. One day, before his English examination, he began to panic as ...
Colleges Still Don't Have a Plan for AI Cheating
Cheating was widespread. Tools for identifying computer-written essays proved insufficient to the task. Academic-integrity boards realized they couldn't fairly adjudicate uncertain cases ...
The Cheating Scandal Rocking the World of Elite High-School Math
Online leaks of tests for the country's best-known math contest—the 74-year-old American Mathematics Competitions—are upsetting students who have spent years preparing for the exams.
Statistical analysis can detect when ChatGPT is used to cheat on
As the use of generative artificial intelligence continues to extend into all reaches of education, much of the concern related to its impact on cheating has focused on essays, essay exam ...
As results released, CXC reveals rise in cheating
News As results released, CXC reveals rise in cheating Sean Douglas 24 Hrs Ago CXC logo. - File photo. CARIBBEAN Examinations Council (CXC) director of operations Dr Nicole Manning revealed a notable rise in cheating in this year's CSEC exam as the organisation launched the release of results, available to individual pupils online at CSEC and CAPE level.
How Harris Has Completely Upended the Presidential Race, in 14 Maps
Mr. Sosnik was a senior adviser to President Bill Clinton from 1994 to 2000 and has advised more than 50 governors and U.S. senators. Aug. 16, 2024 With Kamala Harris now at the top of the ticket ...

Exam Cheating, Its Causes and Effects

Why Students Cheat—and What to Do About It

Rationalizing It

A Developmental Stage

Technology Facilitates and Normalizes It

Strategies for Reducing Cheating

Consequences Of Cheating In Exams: Examples And Effects

Consequences of Cheating in College

1. Cheating can lead to Class Failure

2. Legal consequences

3. Cheating leads to Suspension and expulsion

4. Academic reputation

5. Cheating makes it hard to secure a Job

6. Cheating can cost you a scholarship

7. Creation of a false character

8. Cheating in school erodes your independence

9. Cheating in school prevents progress

10. Cheating in universities causes stress

11. Cheating in school brings Embarrassment

12. Cheating is a form of disrespect.

Effect of Cheating on the Learning Process

Examples of cheating in college

1. Copying from fellow students

2. When someone writes essays or papers for you.

3. Using textbooks, notes, and formula lists on exams

4. Collaborating in tests or exams without permission

5. Copying from Online Tutors

Solutions to cheating in school

1. Educating students on the importance of honesty

2. Creating anti-cheating pledges

3. Instructors changing the definition of success

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Identify possible reasons for the problem you have selected. To find the most effective strategies, select the reason that best describes your situation, keeping in mind there may be multiple relevant reasons.

How Common is Cheating in Online Exams and did it Increase During the COVID-19 Pandemic? A Systematic Review

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Introduction

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Predatory Journal Criteria

Study Risk of Bias and Quality metrics

Synthesis Methods

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Response Rate

How Common is Self-Reported Online Exam Cheating in Higher Education?

Did the Frequency of Online Exam Cheating Increase During COVID?

Comparison of Group vs. Individual Online Exam Cheating in Higher Education

Effect of Proctoring/Lockdown Browsers

Reasons Given for Online Exam Cheating

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