research on study skills

The Innovative Instructor

Pedagogy – best practices – technology.

An Evidence-based Approach to Effective Studying

Dr. Culhane is Professor and Chair of the Department of Pharmaceutical Sciences at Notre Dame of Maryland University School of Pharmacy.

If you are like me, much of your time is spent ensuring that the classroom learning experience you provide for your students is stimulating, interactive and impactful. But how invested are we in ensuring that what students do outside of class is productive? Based on my anecdotal experience and several studies 1,2,3 looking at study strategies employed by students, the answer to this question is not nearly enough! Much like professional athletes or musicians, our students are asked to perform at a high level, mastering advanced, information dense subjects; yet unlike these specialists who have spent years honing the skills of their craft, very few students have had any formal training in the basic skills necessary to learn successfully. It should be no surprise to us that when left to their own devices, our students tend to mismanage their time, fall victim to distractions and gravitate towards low impact or inefficient learning strategies. Even if students are familiar with high impact strategies and how to use them, it is easy for them to default back to bad habits, especially when they are overloaded with work and pressed for time.

Several years ago, I began to seriously think about and research this issue in hopes of developing an evidence-based process that would be easy for students to learn and implement. Out of this work I developed a strategy focused on the development of metacognition – thinking about how one learns. I based it on extensively studied, high impact learning techniques to include: distributed learning, self-testing, interleaving and application practice. 4 I call this strategy the S.A.L.A.M.I. method. This method is named after a metaphor used by one of my graduate school professors. He argued that learning is like eating a salami. If you eat the salami one slice at a time, rather than trying to eat the whole salami in one setting, the salami is more likely to stay with you. Many readers will see that this analogy represents the effectiveness of distributed learning over the “binge and purge” method which many of our students gravitate towards.

S.A.L.A.M.I. is a “backronym” for S ystematic A pproach to L earning A nd M etacognitive I mprovement. The method is structured around typical, daily learning experiences that I refer to as the five S.A.L.A.M.I. steps:

• Pre-class preparation
• In-class engagement
• Post-class review
• Pre-exam preparation
• Post-assessment review

When teaching the S.A.L.A.M.I. method, I explain how each of the five steps correspond to different “stages” or components of learning (see figure 1). Through mastery of skills associated with each of the five S.A.L.A.M.I. steps, students can more efficiently and effectively master a subject area.

Despite its simplicity, this model provides a starting point to help students understand that learning is a process that takes time, requires the use of different learning strategies and can benefit from the development of metacognitive awareness. Specific techniques designed to enhance metacognition and learning are employed during each of the five steps, helping students use their time effectively, maximize learning and achieve subject mastery. Describing all the tools and techniques recommended for each of the five steps would be beyond the scope of this post, but I would like to share two that I have found useful for students to evaluate the effectiveness of their learning and make data driven changes to their study strategies.

Let us return to our example of professional athletes and musicians: these individuals maintain high levels of performance by consistently monitoring and evaluating the efficacy of their practice as well as reviewing their performance after games or concerts. If we translate this example to an academic environment, the practice or rehearsal becomes student learning (in and out of class) and the game or concert acts as the assessment.  We often evaluate students’ formative or summative “performances” with grades, written or verbal feedback. But what type of feedback do we give them to help improve the efficacy of their preparation for those “performances?” If we do give them feedback about how to improve their learning process, is it evidenced-based and directed at improving metacognition, or do we simply tell them they need to study harder or join a study group in order to improve their learning? I would contend that we could do more to help students evaluate their approach to learning outside of class and examination performance. This is where a pre-exam checklist and exam wrapper can be helpful.

The inspiration for the pre-exam checklist came from the pre-flight checklist a pilot friend of mine uses to ensure that he and his private aircraft are ready for flight.  I decided to develop a similar tool for my students that would allow them to monitor and evaluate the effectiveness of their preparation for upcoming assessments. The form is based on a series of reflective questions that help students think about the effectiveness of their daily study habits. If used consistently over time and evaluated by a knowledgeable faculty or learning specialist, this tool can help students be more successful in making sustainable, data driven changes in their approach to learning.

Another tool that I use is called an exam wrapper. There are many examples of exam wrappers online, however, I developed my own wrapper based on the different stages or components of learning shown in figure 1. The S.A.L.A.M.I. wrapper  is divided into five different sections. Three of the five sections focus on the following stages or components of learning: understanding and building context, consolidation, and application. The remaining two sections focus on exam skills and environmental factors that may impact performance. Under each of the five sections is a series of statements that describe possible reasons for missing an exam question. The student analyzes each missed question and matches one or more of the statements on the wrapper to each one. Based on the results of the analysis, the student can identify the component of learning, exam skill or environmental factors that they are struggling with and begin to take corrective action. Both the pre-exam checklist and exam wrapper can be used to help “diagnose” the learning issue that academically struggling students may be experiencing.

Two of the most common issues that I diagnose involve illusions of learning 5 . Students who suffer from the ‘illusion of knowledge’ often mistake their understanding of a topic for mastery. These students anticipate getting a high grade on an assessment but end up frustrated and confused when receiving a much lower grade than expected. Information from the S.A.L.A.M.I. wrapper can help them realize that although they may have understood the concept being taught, they could not effectively recall important facts and apply them. Students who suffer from the ‘illusion of productivity’ often spend extensive time preparing for an exam, however, the techniques they use are extremely passive. Commonly used passive study strategies include: highlighting, recopying and re-reading notes, or listening to audio/video recordings of lectures in their entirety. The pre-exam checklist can help students identify the learning strategies they are using and reflect on their effectiveness. When I encounter students favoring the use of passive learning strategies I use the analogy of trying to dig a six-foot deep hole with a spoon: “You will certainly work hard for hours moving dirt with a spoon, but you would be a lot more productive if you learned how to use a shovel.” The shovel in this case represents adopting strategies such as distributed practice, self-testing, interleaving and application practice.

Rather than relying on anecdotal advice from classmates or old habits that are no longer working, students should seek help early, consistently practice effective and efficient study strategies, and remember that digesting information (e.g. a  S.A.L.A.M.I.) in small doses is always more effective at ‘keeping the information down’ so it may be applied and utilized successfully later.

• Kornell, N., Bjork, R. The promise and perils of self-regulated study. Psychon Bull Rev. 2007;14 (2): 219-224.
• Karpicke, J. D., Butler, A. C., & Roediger, H. L. Metacognitive strategies in student learning: Do students practice retrieval when they study on their own? Memory . 2009; 17: 471– 479.
• Persky, A.M., Hudson, S. L. A snapshot of student study strategies across a professional pharmacy curriculum: Are students using evidence-based practice? Curr Pharm Teach Learn. 2016; 8: 141-147.
• Dunlosky , J.,  Rawson , K.A.,  Marsh , E.J.,  Nathan , M.J.,  Willingham , D.T. Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology. Psychol Sci Publ Int. 2013; 14 (1): 4-58.
• Koriat, A., & Bjork, R. A. Illusions of competence during study can be remedied by manipulations that enhance learners’ sensitivity to retrieval conditions at test.  Memory & Cognition . 2006; 34 : 959-972.

James M. Culhane, Ph.D. Chair and Professor, School of Pharmacy, Notre Dame of Maryland University

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Study Skills

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• Carrie R. Ball 3  

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Study strategies ; Study tactics

Study Skills comprise an integrated repertoire of tactics and strategies, which facilitates acquisition, organization, retention, and application of new information.

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Study skills encompass a broad range of tactics and strategies that ultimately allow students to effectively learn, organize, and recall new information. Although children are often expected to develop study skills naturally, research indicates that many students exhibit study skill deficits and require explicit instruction to acquire and appropriately use study skills [ 5 ]. Additionally, the degree to which students are able to study effectively is a strong predictor of academic achievement [ 1 ].

An important distinction must be drawn between study tactics and study strategies, both of which are often used interchangeably with study skills. Study tactics, or the specific techniques involved in studying, form the building blocks for effective study skill...

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DiPerna, J. C. (2006). Academic enablers and student achievement: Implications for assessment and intervention services in the schools. Psychology in the Schools, 43 , 7–17.

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Gettinger, M., & Ball, C. (2006). Study skills. In G. G. Bear & K. M. Minke (Eds.), Children’s needs III: Development, prevention, and intervention (pp. 459–472). Bethesda, MD: National Association of School Psychologists.

Harvey, V. S., & Chickie-Wolfe, L. A. (2007a). Best practices in teaching study skills. In A. Thomas & J. Grimes (Eds.), Best practices in school psychology V (pp. 1121–1136). Bethesda, MD: National Association of School Psychologists.

Harvey, V. S., & Chickie-Wolfe, L. A. (2007b). Fostering independent learning: Practical strategies to promote student success . New York: Guilford.

Scanlon, D. J., Deshler, D. D., & Schumaker, J. B. (1996). Can a strategy be taught and learned in secondary inclusive classrooms?. Learning Disabilities Research and Practice, 7 , 142–146.

Wood, E., Woloshyn, V. E., & Willoughby, T. (Eds.). (1995). Cognitive strategy instruction for middle and high school . Cambridge, MA: Brookline.

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Six research-tested ways to study better

Psychology’s latest insights for preparing students for their next exams.

• Learning and Memory

Many students are missing a lesson in a key area that can help guarantee their success: how to study effectively. 

It’s common for students to prepare for exams by re-reading class notes and cramming textbook chapters—study techniques that hinge on the assumption that memories are like recording devices that can play back memories during an exam. “But the storage and retrieval operations of human memory differ from recording devices in almost every way possible,” says psychology professor Robert Bjork, PhD, co-director of the Learning and Forgetting Lab at University of California, Los Angeles. 

What does help our brains retain information? Study strategies that require the brain to work to remember information—rather than passively reviewing material. 

Bjork coined the term “desirable difficulty” to describe this concept, and psychologists are homing in on exactly how students can develop techniques to maximize the cognitive benefits of their study time.  

Here are six research-tested strategies from psychology educators. 

1. Remember and repeat

Study methods that involve remembering information more than once—known as repeated retrieval practice—are ideal because each time a memory is recovered, it becomes more accessible in the future, explains Jeffrey Karpicke, PhD, a psychology researcher at Purdue University in Indiana who studies human learning and memory. 

The benefits of this technique were evident when Karpicke conducted a study in which students attempted to learn a list of foreign language words. Participants learned the words in one of four ways: 

• Studying the list once.
• Studying until they had successfully recalled each word once.
• Studying until they had successfully recalled each word three times consecutively.
• Studying until they had recalled each word three times spaced throughout the 30-minute learning session. 

In the last condition, the students would move on to other words after correctly recalling a word once, then recall it again after practicing other words.

A week later, the researchers tested the students on the words and discovered that participants who had practiced with repeated spaced retrieval—the last condition—far outperformed the other groups. Students in this group remembered 80% of the words, compared to 30% for those who had recalled the information three times in a row—known as massed retrieval practice—or once. The first group, which involved no recall, remembered the words less than 1% of the time ( Journal of Experimental Psychology: Learning, Memory, and Cognition , Vol. 37, No. 5, 2011).

Many students assume that recalling something they’ve learned once is proof that they’ve memorized it. But, says Karpicke, just because you can retrieve a fact in a study session doesn’t mean you will remember it later on a test. “Just a few repeated retrievals can produce significant effects, and it’s best to do this in a spaced fashion.” 

2. Adapt your favorite strategies

Other research finds support for online flashcard programs, such as Study Stack or Chegg, to practice retrieving information—as long as students continue retesting themselves in the days leading up to the test, says John Dunlosky, PhD, who studies self-regulated learning at Kent State University in Ohio. For flashcards with single-word answers, the evidence suggests that thinking of the answer is effective, but for longer responses like definitions, students should type, write down, or say aloud the answers, Dunlosky says. If the answer is incorrect, then study the correct one and practice again later in the study session. “They should continue doing that until they are correct, and then repeat the process in a couple more days,” he says. 

Concept mapping — a diagram that depicts relationships between concepts—is another well-known learning technique that has become popular, but cognitive psychology researchers caution students to use this strategy only if they try to create a map with the book closed. Karpicke demonstrated this in a study in which students studied topics by creating concept maps or by writing notes in two different conditions: with an open textbook or with the textbook closed. With the closed textbook, they were recalling as much as they could remember. One week later, the students took an exam that tested their knowledge of the material, and students who had practiced retrieving the information with the book closed had better performances ( Journal of Educational Psychology , Vol. 106, No. 3, 2014).

“Concept maps can be useful, as long as students engage in retrieval practice while using this strategy,” Karpicke says. 

3. Quiz yourself

Students should also take advantage of quizzes—from teachers, in textbooks or apps like Quizlet—to refine their ability to retain and recall information. It works even if students answer incorrectly on these quizzes, says Oregon State University psychology professor Regan Gurung, PhD. “Even the process of trying and failing is better than not trying at all,” he says. “Just attempting to retrieve something helps you solidify it in your memory.”

Gurung investigated different approaches to using quizzes in nine introductory psychology courses throughout the country. In the study, the researchers worked with instructors who agreed to participate in different conditions. Some required students to complete chapter quizzes once while others required them to take each quiz multiple times. Also, some students were told to complete all the chapter quizzes by one deadline before the exam, while others were expected to space their quizzes by meeting deadlines throughout the course. The students who spaced their quizzes and took them multiple times fared the best on the class exams ( Applied Cognitive Psychology , Vol. 33, No. 5, 2019).

Although trying and failing on practice quizzes may be an effective study strategy, psychology professor Nate Kornell, PhD, of Williams College in Massachusetts, was skeptical that students would choose to learn this way because many people inherently do not like getting things wrong. He was eager to explore whether it was possible to create a retrieval practice strategy that increased the odds of students getting the right answer without sacrificing the quality of learning. To test this possibility, he led a study in which participants tried to remember word pairs, such as “idea: seeker.” The goal was to remember the second word after seeing only the first one. The students could choose to practice by restudying all the pairs or by self-testing with different options for hints—seeing either two or four letters of the second word in the pair, or no letters at all ( Cognitive Research: Principles and Implications , Vol. 4, 2019).

Most of the students preferred self-testing over restudying, and the results showed that even with hints, the self-testing group performed better on the final test of the words than the restudying group. “It’s a win-win situation because the technique that worked most effectively was also the one that they enjoyed the most,” says Kornell. 

Even more important, students think they are learning more effectively when they answer correctly while practicing, which means they’ll be even more motivated to try retrieval practice if hints are available, says Kornell. To apply this strategy, he suggests adding hints to self-generated flash cards or quizzes, such as the first letter of the answer or one of the words in a definition.

4. Make the most of study groups

Many students also enjoy studying with classmates. But when working in groups, it’s important for students to let everyone have an opportunity to think of the answers independently, says Henry Roediger, III, PhD, a professor in the psychology department at Washington University in St. Louis. One study highlighted the importance of this: Participants tried to learn words in a foreign language by either answering aloud or by listening to their partners give the answers ( Journal of Experimental Psychology: Applied (PDF, 426KB) , Vol. 24, No. 3, 2018). As expected, those who had answered aloud outperformed the listeners on a test two days later. The researchers also compared participants who answered aloud with partners who silently tried to recall the answers. Everyone received feedback about whether they had gotten the correct answer. Both groups had comparable performances. “Waiting for others to think of answers may slow down the process, but it produces better retention for everyone because it requires individual effort,” Roediger says. 

5. Mix it up

Researchers have also investigated the potential benefits of “interleaving,” or studying for different courses in one study session ( Journal of Experimental Psychology: Applied , Vol. 23, Nov. 4, 2017). For example, rather than dedicating two hours to studying for a psychology exam, students could use that time to study for exams in psychology, biology and statistics courses. A few days later, students could study for the same courses again during another block of time. “This strategy, versus blocking one’s study by course, naturally introduces spacing, so students practice retrieving information over time,” Bjork says. 

But the research on interleaving has had mixed results, says Aaron Richmond, PhD, a professor of educational psychology and human development at Metropolitan State University in Denver. “If the concepts from two subjects overlap too closely, then this could interfere with learning,” says Richmond. “But chemistry and introduction to psychology are so different that this doesn’t create interference.”

6. Figure out what works for you

The ability to effectively evaluate one’s approach to learning and level of attainment is known as metacognitive ability. Research has shown that “when people are new to learning about a topic, their subjective impressions of how much they know are the most inflated,” says Paul Penn, PhD, a senior lecturer in the psychology department at East London University and author of the 2019 book “The Psychology of Effective Studying.” 

“If your impression of your learning is inflated, you have little incentive to look at the way you're approaching learning,” he says.

To increase awareness about the value of sound study strategies, administrators at Samford University in Alabama invited psychology professor Stephen Chew, PhD, to talk to first-year students about this topic during an annual convocation each fall semester. Though an assessment study, he realized that the lecture prompted immediate changes in beliefs and attitudes about studying, but long-term change was lacking. “Students forgot the specifics of the lecture and fell back into old habits under the stress of the semester,” Chew says. 

To provide an accessible resource, he launched a series of five 7-minute videos on the common misconceptions about studying, how to optimize learning and more. Professors throughout the school assign the videos as required classwork, and the videos have been viewed 3 million times throughout the world by high school, college and medical students. 

While this form of campus-wide education about studying is somewhat rare, psychology researchers are optimistic that this could become more common in the coming years. “There is a lot more discussion now than even 10 years ago among teachers about the science of learning,” Karpicke says. “Most students do not know how to study effectively, and teachers are increasingly eager to change that.” 

Further reading

• Improving Self-Regulated Learning with a Retrieval Practice Intervention. Ariel, R., Karpicke, J.D., Journal of Experimental Psychology: Applied , 2018.
• Practice Tests, Spaced Practice, and Successive Relearning: Tips for Classroom Use and for Guiding Students’ Learning (PDF, 53KB) . Scholarship of Teaching and Learning in Psychology , Dunlosky, J. & Rawson, K.A., 2015.
• Performance Bias: Why Judgments of Learning Are not Affected by Learning . Kornell, N. and Hausman, H., Memory & Cognition , 2017.

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Fostering students’ motivation towards learning research skills: the role of autonomy, competence and relatedness support

Louise maddens.

1 Centre for Instructional Psychology and Technology, Faculty of Psychology and Educational Sciences, KU Leuven and KU Leuven Campus Kulak Kortrijk, Etienne Sabbelaan 51 – bus 7800, 8500 Kortrijk, Belgium

2 Itec, imec Research Group at KU Leuven, imec, Leuven, Belgium

3 Vives University of Applied Sciences, Kortrijk, Belgium

Fien Depaepe

Annelies raes.

In order to design learning environments that foster students’ research skills, one can draw on instructional design models for complex learning, such as the 4C/ID model (in: van Merriënboer and Kirschner, Ten steps to complex learning, Routledge, London, 2018). However, few attempts have been undertaken to foster students’ motivation towards learning complex skills in environments based on the 4C/ID model. This study explores the effects of providing autonomy, competence and relatedness support (in Deci and Ryan, Psychol Inquiry 11(4): 227–268, https://doi.org/10.1207/S15327965PLI1104_01, 2000) in a 4C/ID based online learning environment on upper secondary school behavioral sciences students’ cognitive and motivational outcomes. Students’ cognitive outcomes are measured by means of a research skills test consisting of short multiple choice and short answer items (in order to assess research skills in a broad way), and a research skills task in which students are asked to integrate their skills in writing a research proposal (in order to assess research skills in an integrative manner). Students’ motivational outcomes are measured by means of students’ autonomous and controlled motivation, and students’ amotivation. A pretest-intervention-posttest design was set up in order to compare 233 upper secondary school behavioral sciences students’ outcomes among (1) a 4C/ID based online learning environment condition, and (2) an identical condition additively providing support for students’ need satisfaction. Both learning environments proved equally effective in improving students’ scores on the research skills test. Students in the need supportive condition scored higher on the research skills task compared to their peers in the baseline condition. Students’ autonomous and controlled motivation were not affected by the intervention. Although, unexpectedly, students’ amotivation increased in both conditions, students’ amotivation was lower in the need supportive condition compared to students in the baseline condition. Theoretical relationships were established between students’ need satisfaction, students’ motivation (autonomous, controlled, and amotivation), and students’ cognitive outcomes. These findings are discussed taking into account the COVID-19 affected setting in which the study took place.

Introduction

Several scholars have argued that the process of learning research skills is often obstructed by motivational problems (Lehti & Lehtinen, 2005 ; Murtonen, 2005 ). Some even describe these issues as students having an aversion towards research (Pietersen, 2002 ). Examples of motivational problems are that students experience research courses as boring, inaccessible, or irrelevant to their daily lives (Braguglia & Jackson, 2012 ). In a research synthesis on teaching and learning research methods, Earley ( 2014 ) argues that students fail to see the relevance of research methods courses, are anxious or nervous about the course, are uninterested and unmotivated to learn the material, and have poor attitudes towards learning research skills. It should be mentioned that the studies mentioned above focused on the field of higher university education. In upper secondary education, to date, students’ motivation towards learning research skills has rarely been studied. As difficulties while learning research seem to relate to problems involving students’ previous experiences regarding learning research skills (Murtonen, 2005 ), we argue that fostering students’ motivation from secondary education onwards is a promising area of research.

The current study combines insights from instructional design theory and self-determination theory (SDT, Deci & Ryan, 2000 ), in order to investigate the cognitive and motivational effects of providing psychological need support (support for the need for autonomy, competence and relatedness) in a 4C/ID based (van Merriënboer & Kirschner, 2018 ) online learning environment fostering upper secondary schools students’ research skills. In the following section, we elaborate on the definition of research skills in the understudied domain of behavioral sciences; on 4C/ID (van Merriënboer & Kirschner, 2018 ) as an instructional design model for complex learning; and on self-determination theory and its related need theory (Deci & Ryan, 2000 ). In addition, the research questions addressed in the current study are outlined.

Conceptual framework

Research skills.

As described by Fischer et al., ( 2014 , p. 29), we define research skills 1 as a broad set of skills used “to understand how scientific knowledge is generated in different scientific disciplines, to evaluate the validity of science-related claims, to assess the relevance of new scientific concepts, methods, and findings, and to generate new knowledge using these concepts and methods”. Furthermore, eight scientific activities learners engage in while performing research are distinguished, namely: (1) problem identification, (2) questioning, (3) hypothesis generation, (4) construction and redesign of artefacts, (5) evidence generation, (6) evidence evaluation, (7) drawing conclusions, and (8) communicating and scrutinizing (Fischer et al., 2014 ). Fischer et al. ( 2014 ) argue that both the nature of, and the weights attributed to each of these activities, differ between domains. Intervention studies aiming to foster research skills are almost exclusively situated in natural sciences domains (Engelmann et al., 2016 ), leaving behavioral sciences domains largely understudied. The current study focuses on research skills in the understudied domain of behavioral sciences. We refer to the domain of behavioral sciences as the study of questions related to how people behave, and why they do so. Human behavior is understood in its broadest sense, and is the study of object in fields of psychology, educational sciences, cultural and social sciences.

The design of the learning environments used in this study is based on an existing instructional design model, namely the 4C/ID model (van Merriënboer & Kirschner, 2018 ). The 4C/ID model has been proven repeatedly effective in fostering complex skills (Costa et al., 2021 ), and thus drew our attention for the case of research skills, as research skills can be considered complex skills (it requires learners to integrate knowledge, skills and attitudes while performing complex learning tasks). Since the 4C/ID model focusses on supporting students’ cognitive outcomes, it might not be considered as relevant from a motivational point of view. However, since we argue that a deliberately designed learning environment from a cognitive point of view is an important prerequisite to provide qualitative motivational support, we briefly sketch the 4C/ID model and its characteristics. The 4C/ID model has a comprehensive character, integrating insights from different theories and models (Merrill, 2002 ), and highlights the relevance of four crucial components: learning tasks, supportive information, part task-practice, and just-in-time information. Central characteristics of these four components are that (a) high variability in authentic learning tasks is needed in order to deal with the complexity of the task; (b) supportive information is provided to the students in order to help them build mental models and strategies for solving the task under study (Cook & McDonald, 2008 ); (c) part-task practice is provided for recurrent skills that need to be automated; and (d) just-in-time (procedural) information is provided for recurrent skills.

Taking into account students’ cognitive struggles regarding research skills, and the existing research on the role of support in fostering research skills (see for example de Jong & van Joolingen, 1998 ), the 4C/ID model was found suitable to design a learning environment for research skills. This is partly because of its inclusion of (almost) all of the support found effective in the literature on research skills, such as providing direct access to domain information at the appropriate moment, providing learners with assignments, including model progression, the importance of students’ involvement in authentic activities, and so on (Chi, 2009 ; de Jong, 2006 ; de Jong & van Joolingen, 1998 ; Engelmann et al., 2016 ). While mainly implemented in vocational oriented programs, the 4C/ID model has been proposed as a good model to design learning environments aiming to foster research skills as well (Bastiaens et al., 2017 ; Maddens et al., 2020b ). Indeed, acquiring research skills requires complex learning processes (such as coordinating different constituent skills). Overall, the 4C/ID model can be considered to be highly suitable for designing learning environments aiming to foster research skills. Given its holistic design approach, it helps “to deal with complexity without losing sight of the interrelationships between the elements taught” (van Merriënboer & Kirschner, 2018 , p. 5).

Although the 4C/ID model has been used widely to construct learning environments enhancing students’ cognitive outcomes (see for example Fischer, 2018 ), research focusing on students’ motivational outcomes related to the 4C/ID model is scarce (van Merriënboer & Kirschner, 2018 ). Van Merriënboer and Kirschner ( 2018 ) suggest self-determination theory (SDT; Deci & Ryan, 2000 ) and its related need theory as a sound theoretical framework to investigate motivation in relation to 4C/ID.

Self-determination theory

Self-determination theory (SDT; Deci & Ryan, 2000 ) provides a broad framework for the study of motivation and distinguishes three types of motivation: amotivation (a lacking ability to self-regulate with respect to a behaviour), extrinsic motivation (extrinsically motivated behaviours, be they self-determined versus controlled), and intrinsic motivation (the ‘highest form’ of self-determined behaviour) (Deci & Ryan, 2000 ). According to Deci and Ryan ( 2000 , p. 237), intrinsic motivation can be considered “a standard against which the qualities of an extrinsically motivated behavior can be compared to determine its degree of self-determination”. Moreover, the authors (Deci & Ryan, 2000 , p. 237) argue that “extrinsic motivation does not typically become intrinsic motivation”. As the current study focuses on research skills in an academic context in which students did not voluntary chose to learn research skills, and thus learning research skills can be considered instrumental (directed to attaining a goal), the current study focuses on students’ amotivation, and students’ extrinsic motivation, realistically striving for the most self-determined types of extrinsic motivation.

Four types of extrinsic motivation are distinguished by SDT (external regulation, introjection, identification, and integration). These types can be categorized in two overarching types of motivation (autonomous and controlled motivation). Autonomous motivation contains the integrated and identified regulation towards a task (be it because the task is considered interesting, or because the task is considered personally relevant respectively). Controlled motivation refers to the external and introjected regulation towards the task (as a consequence of external or internal pressure respectively) (Vansteenkiste et al., 2009 ). More autonomous types of motivation have been found to be related to more positive cognitive and motivational outcomes (Deci & Ryan, 2000 ).

SDT further maintains that one should consider three innate psychological needs related to students’ motivation. These needs are the need for autonomy, the need for competence, and the need for relatedness. The need for autonomy can be described as the need to experience activities as being “concordant with one’s integrated sense of self” (Deci & Ryan, 2000 , p. 231). The need for competence refers to the need to feel effective when dealing with the environment (Deci & Ryan, 2000 ). The need for relatedness contains the need to have close relationships with others, including peers and teachers (Deci & Ryan, 2000 ). The satisfaction of these needs is hypothesized to be related to more internalization, and thus to more autonomous types of motivation (Deci & Ryan, 2000 ). This relationship has been studied frequently (for a recent overview, see Vansteenkiste et al., 2020 ). Indeed, research established the positive relationships between perceived autonomy (see for example Deci et al., 1996 ), perceived competence (see for example Vallerand & Reid, 1984 ), and perceived relatedness (see for example Ryan & Grolnick, 1986 for a self-report based study) with students’ more positive motivational outcomes. Apart from students’ need satisfaction, several scholars also aim to investigate need frustration as a different notion, as “it involves an active threat of the psychological needs (rather than a mere absence of need satisfaction)” (Vansteenkiste et al., 2020 , p. 9). In what follows, possible operationalizations are defined for the three needs.

Possible operationalizations of autonomy need support found in the literature are: teachers accepting irritation or negative feelings related to aspects of a task perceived as “uninteresting” (Reeve, 2006 ; Reeve & Jang, 2006 ; Reeve et al., 2002 ); providing a meaningful rationale in order to explain the value/usefulness of a certain task and stressing why involving in the task is important or why a rule exists (Deci & Ryan, 2000 ); using autonomy-supportive, inviting language (Deci et al., 1996 ); and allowing learners to regulate their own learning and to work at their own pace (Martin et al., 2018 ). Related to competence support, possible operationalizations are: providing a clear task rationale and providing structure (Reeve, 2006 ; Vansteenkiste et al., 2012 ); providing informational positive feedback after a learning activity (Deci et al., 1996 ; Martin et al., 2018 ; Vansteenkiste et al., 2012 ); providing an indication of progress and dividing content into manageable blocks (Martin et al., 2018 ; Schunk, 2003 ); and evaluating performance by means of previously introduced criteria (Ringeisen & Bürgermeister, 2015 ). Possible operationalizations concerning relatedness support are: teacher’s relational supports (Ringeisen & Bürgermeister, 2015 ); encouraging interaction between course participants and providing opportunities for learners to connect with each other (Butz & Stupnisky, 2017 ; van Merriënboer & Kirschner, 2018 ); using a warm and friendly approach or welcoming learners personally into a course (Martin et al., 2018 ); and offering a platform for learners to share ideas and to connect (Butz & Stupnisky, 2017 ; Martin et al., 2018 ).

In the current research, SDT is selected as a theoretical framework to investigate students’ motivation towards learning research skills, as, in contrast to other more purely goal-directed theories, it includes the concept of innate psychological needs or the Basic Psychological Need Theory (Deci & Ryan, 2000 ; Ryan, 1995 ; Vansteenkiste et al., 2020 ), and it describes the relation between these perceived needs and students’ autonomous motivation: higher levels of perceived needs relate to more autonomous forms of motivation. The inclusion of this need theory is considered an advantage in the case of research skills because research revealed problems of students with respect to both their feelings of competence in relation to research skills (Murtonen, 2005 ), as their feelings of autonomy in relation to research skills (Martin et al., 2018 ), as was indicated in the introduction. As such, fostering students’ psychological needs while learning research skills seems a promising way of fostering students’ motivation towards learning research skills.

4C/ID and SDT

One study (Bastiaens et al., 2017 ) was found to implement need support in 4C/ID based learning environments, comparing a traditional module, a 4C/ID based module and an autonomy supportive 4C/ID based module in a vocational undergraduate education context. Autonomy support was operationalized by means of providing choice to the learners. No main effect of the conditions was found on students’ motivation. Surprisingly, providing autonomy support did also not lead to an increase in students’ autonomy satisfaction. Similarly, no effects were found on students’ relatedness and competence satisfaction. Remarkably, students did qualitatively report positive experiences towards the need support, but this did not reflect in their quantitatively reported need experiences. In a previous study performed in the current research trajectory, Maddens et al. ( under review ) investigated the motivational effects of providing autonomy support in a 4C/ID based online learning environment fostering students’ research skills, compared to a learning environment not providing such support. Autonomy support was operationalized as stressing task meaningfulness to the students. Based on insights from self-determination theory, it was hypothesized that students in the autonomy condition would show more positive motivational outcomes compared to students in the baseline condition. However, results showed that students’ motivational outcomes appeared to be unaffected by the autonomy support. One possible explanation for this unexpected finding was that optimal circumstances for positive motivational outcomes are those that allow satisfaction of autonomy, competence, ánd relatedness support (Deci & Ryan, 2000 ; Niemiec & Ryan, 2009 ), and thus, that the intervention was insufficiently powerful for effects to occur. Autonomy support has often been manipulated in experimental research (Deci et al., 1994 ; Reeve et al., 2002 ; Sheldon & Filak, 2008 ). However, the three needs are rarely simultaneously manipulated (Sheldon & Filak, 2008 ).

Integrated need support

Although not making use of 4C/ID based learning environments, some scholars have focused on the impact of integrated (autonomy, competence and relatedness) need support on learners’ motivation. For example, Raes and Schellens ( 2015 ) found differential effects of a need supportive inquiry environment on upper secondary school students’ motivation: positive effects on autonomous motivation were only found in students in a general track, and not in students in a science track. This indicates that motivational effects of need-supportive environments might differ between tracks and disciplines. However, Raes and Schellens ( 2015 ) did not experimentally manipulate need support, as the learning environment was assumed to be need-supportive and was not compared to a non-need supportive learning environment. Pioneers in manipulating competence, relatedness and autonomy support in one study are Sheldon and Filak ( 2008 ), predicting need satisfaction and motivation based on a game-learning experience with introductory psychology students. Relatedness support (mainly operationalized by emphasizing interest in participants’ experiences in a caring way) had a significant effect on intrinsic motivation. Competence support (mainly operationalized by means of explicating positive expectations) had a marginal significant effect on intrinsic motivation. No main effects on intrinsic motivation were found regarding autonomy support (mainly operationalized by means of emphasizing choice, self-direction and participants’ perspective upon the task). However, as is often the case in motivational research based on SDT, the task at hand was quite straight forward (a timed task in which students try to form as many words as possible from a 4 × 4 letter grid), and thus, the applicability of the findings for providing need support in 4C/ID based learning environments for complex learning might be limited.

In the preceding section, several operationalizations of need support were discussed. Deci and Ryan ( 2000 ) argue that optimal circumstances for positive motivational outcomes are those that allow satisfaction of autonomy, competence, ánd relatedness support. However, such integrated need support has rarely been empirically studied (Sheldon & Filak, 2008 ). In addition, research investigating how need support can be implemented in learning environments based on the 4C/ID model is particularly scarce (van Merriënboer & Kirschner, 2018 ). This study aims to combine insights from instructional design theory for complex learning (van Merriënboer & Kirschner, 2018 ) and self-determination theory (Deci & Ryan, 2000 ) in order to investigate the motivational effects of providing need support in a 4C/ID based learning environment for students’ research skills. A pretest-intervention-posttest design is set up in order to compare 233 upper secondary school behavioral sciences students’ cognitive and motivational outcomes among two conditions: (1) a 4C/ID based online learning environment condition, and (2) an identical condition additively providing support for students’ need satisfaction. The following research questions are answered based on a combination of quantitative and qualitative data (see ‘method’): (1) Does a deliberately designed (4C/ID-based) learning environment improve students’ research skills, as measured by a research skills test and a research skills task? ; ( 2) What is the effect of providing autonomy, competence and relatedness support in a deliberately designed (4C/ID-based) learning environment fostering students’ research skills, on students’ motivational outcomes (i.e. students’ amotivation, autonomous motivation, controlled motivation, students’ perceived value/usefulness, and students’ perceived needs of competence, relatedness and autonomy)? ; (3) What are the relationships between students’ need satisfaction, students’ need frustration, students’ autonomous and controlled motivation and students’ cognitive outcomes (research skills test and research skills task)? ; (4) How do students experience need satisfaction and need frustration in a deliberately designed (4C/ID-based) learning environment? .

The first three questions are answered by means of quantitative data. Since the learning environment is constructed in line with existing instructional design principles for complex learning, we hypothesize that both learning environments will succeed in improving students’ research skills (RQ1). Relying on insights from self-determination theory (Deci & Ryan, 2000 ), we hypothesize that providing need support will enhance students’ autonomous motivation (RQ2). In addition, we hypothesize students’ need satisfaction to be positively related to students’ autonomous motivation (RQ3). These hypotheses on the relationship between students’ needs and students’ motivation rely on Vallerands’ ( 1997 ) finding that changes in motivation can be largely explained by students’ perceived competence, autonomy and relatedness (as psychological mediators). More specifically, Vallerand ( 1997 ) argues that environmental factors (in this case the characteristics of a learning environment) influence students’ perceptions of competence, autonomy, and relatedness, which, in turn, influence students’ motivation and other affective outcomes. In addition, based on the self-determination literature (Deci & Ryan, 2000 ), we expect students’ motivation to be positively related to students’ cognitive outcomes. In order to answer the fourth research question, qualitative data (students’ qualitative feedback on the learning environments) is analysed and categorized based on the need satisfaction and need frustration concepts (RQ4) in order to thoroughly capture the meaning of the quantitative results collected in light of RQ1–3. No hypotheses are formulated in this respect.

Methodology

Participants.

The study took place in authentic classroom settings in upper secondary behavioral sciences classes. In total, 233 students from 12 classes from eight schools in Flanders participated in the study. All participants are 11th or 12th grade students in a behavioral sciences track 2 in general upper secondary education in Flanders (Belgium). Classes were randomly assigned to one out of two experimental conditions. Of all 233 students, 105 students (with a mean age of 16.32, SD 0.90) worked in the baseline condition (of which 62% 11th grade students, 36% 12th grade students, and 2% not determined; and of which 31% male, 68% female, and 1% ‘other’), and 128 students (with a mean age of 16.02, SD 0.59) worked in the need supportive condition (of which 80% 11th grade students, and 20% 12th grade students; and of which 19% male, and 81% female). As the current study did not randomly assign students within classes to one out of the two conditions, this study should be considered quasi-experimental. Full randomization was considered but was not feasible as students worked in the learning environments in class, and would potentially notice the experimental differences when observing their peers working in the learning environment. As such, we argued that this would potentially cause bias in the study. By taking into account students’ pretest scores on the relevant variables (cognitive and motivational outcomes) as covariates, we aimed to adjust for inter-conditional differences. No such differences were found for students’ autonomous motivation t (226) =  − 0.115, p  < 0.909, d  = 0.015, and students’ amotivation t (226) =  − 0.658, p  < 0.511, d  =  − 0.088. However, differences were observed for students’ controlled motivation t (226) =  − 2.385, p  < 0.018, d  =  − 0.318, and students’ scores on the LRST pretest t (225) = − 5.200, p  < 0.001, d  =  − 0.695.

Study design and procedure

In a pretest session of maximum two lesson hours, the Leuven Research Skills Test (LRST, Maddens et al., 2020a ), the Academic Self-Regulation Scale (ASRS, Vansteenkiste et al., 2009 ), and four items related to students’ amotivation (Aydin et al., 2014 ) were administered in class via an online questionnaire, under supervision of the teacher. In the subsequent eight weeks, participants worked in the online learning environment, one hour a week. Out of the 233 participating students, 105 students studied in a baseline online learning environment. The baseline online learning environment 3 is systematically designed using existing instructional design principles for complex learning based on the 4C/ID model (van Merriënboer & Kirschner, 2018 ). All four components of the 4C/ID model were taken into account in the design process: regarding the first component, the learning tasks included real-life, authentic cases. More specifically, tasks were selected from the domains of psychology, educational sciences and sociology. As such, there was a large variety in the cases used in the learning tasks. This large variety in learning tasks is expected to facilitate transfer of learners’ research skills in a wide range of contexts. Furthermore, the tasks were ill-structured and required learners to make judgments, in order to provoke deep learning processes. Regarding the second component, supportive information was provided for complex tasks in the learning environment, such as formulating a research question, where students can consult general information on what constitutes a good research question, can consult examples or demonstrations of this general information, and can receive cognitive feedback on their answers (for example by means of example answers). Examples of the implementation of the third component (procedural information) are the provision of information on how to recognize a dependent and an independent variable by means of on-demand (just-in-time) presentation by means of pop-ups; information on how to use Boolean operators; and information on how to read a graph. To avoid split attention, this kind of information was integrated with the task environment itself (van Merriënboer & Kirschner, 2018 ). Finally, the fourth component, part-task-practice (by means of short tests) was implemented for routine aspects of research skills that should be automated, for example the formulation of a search query.

The remaining participating students ( n  = 128) completed an adapted version of the baseline online learning environment, in which autonomy, relatedness and competence support are provided. In total, need support consisted of 12 implementations (four implementations for each need), based on existing research on need support. An overview of these adaptations can be found in Tables ​ Tables1 1 and ​ and2. 2 . Although, ideally, students would work in class, under supervision of their teacher, this was not possible for all classes, due to the COVID-19 restrictions. 4 As a consequence, some students completed the learning environment partly at home. All students were supervised by their teachers (be it virtually or in class), and the researcher kept track of students’ overall activities in order to be able to contact students who did not complete the main activities. During the last two sessions of the intervention, participants submitted a two-pages long research proposal (“two-pager”). One week after the intervention, the LRST (Maddens et al., 2020a ), the ASRS (Vansteenkiste et al., 2009 ), four items related to students’ amotivation (Aydin et al., 2014 ), the value/usefulness scale (Ryan, 1982 ) and the Basic Psychological Need Satisfaction and Frustration Scale (BPNSNF, Chen et al., 2015 ) were administered in a posttest session of maximum two hours. Although most classes succeeded in organizing this posttest session in class, for some classes this posttest was administered at home. However, all classes were supervised by the teacher (be it virtually or in class). These contextual differences at the test moments will be reflected upon in the discussion section.

Adaptations online learning environment

Overview instruments

a When administered at both pretest and posttest level (see ‘procedure’), the internal consistency values are reported respectively

Instruments

In this section, we elaborate on the tests used during the pretest and the posttest. Example items for each scale are presented in Appendix 1.

Motivational outcomes

In the current study, two groups of motivational outcomes are assessed: (1) students’ need satisfaction and frustration, and students’ experiences of value/usefulness; and (2) students’ level of autonomous motivation, controlled motivation, and amotivation. When administered at both pretest and posttest level (see ‘procedure’), the internal consistency values are reported respectively.

The BPNSNF-training scale (The Basic Psychological Need Satisfaction and Frustration Scale, Chen et al., 2015 ; translated version Aelterman et al., 2016 5 ) measured students’ need satisfaction and need frustration while working in the learning environment, and consists of 24 items (four items per scale): (autonomy satisfaction, α  = 0.67; ω = 0.67; autonomy frustration, α  = 0.76; ω = 0.76; relatedness satisfaction, α  = 0.79; ω = 0.79; relatedness frustration, α  = 0.60; ω = 0.61; competence satisfaction, α  = 0.72; ω = 0.73; competence frustration, α  = 0.68; ω = 0.67). The items are Likert-type items ranging from one (not at all true) to five (entirely true). Although the current study focusses mainly on students’ need satisfaction, the scales regarding students’ need frustration are included in order to be able to also detect students’ potential ill-being and in order to detect potential critical issues regarding students’ needs. In addition to the BPNSNF, by means of seven Likert-type items ranging from one (not at all true) to seven (entirely true), the (for the purpose of this research translated) value/usefulness scale of the Intrinsic Motivation Inventory (IMI, Ryan, 1982 ) measured to what extent students valued the activities of the online learning environment ( α  = 0.92; ω = 0.92). Since in the research skills literature problems have been observed related to students’ perceived value/usefulness of research skills (Earley, 2014 ; Murtonen, 2005 ), and this concept is not sufficiently stressed in the BPNSNF-scale, we found it useful to include this value/usefulness scale to the study. The difference in the range of the answer possibilities (one to five vs one to seven) exists because we wanted to keep the range as initially prescribed by the authors of each instrument. All motivational measures are calculated by adding the scores on every item, and dividing this sum score by the number of items on a scale, leading to continuous outcomes. Although the IMI and the BPNSNF targeted students’ experiences while completing the online learning environment, these measures were administered during the posttest. Thus, students had to think retrospectively about their experiences. In order to prevent cognitive overload while completing the online learning environment, these measures were not administered during the intervention itself.

Students’ autonomous and controlled motivation towards learning research skills was measured by means of the Dutch version of the Academic Self-Regulation Scale (ASRS; Vansteenkiste et al., 2009 ), adapted to ‘ research skills ’. The ASRS consists of Likert-type items ranging from one (do not agree at all) to five (totally agree), and contains eight items per subscale (autonomous and controlled motivation). In the autonomous motivation scale, four items are related to identified regulation, and four items are related to intrinsic motivation. 6 In the controlled motivation scale, four items are related to external regulation, and four items are related to introjected regulation. Both scales (autonomous motivation and controlled motivation) indicated good internal consistency for the study’s data (autonomous motivation: α  = 0.91; 0.92; ω = 0.90; 0.92; controlled motivation: α  = 0.83; 0.86; ω = 0.82; 0.85). The items were adapted to the domain under study (motivation to learn about research skills). Based on students’ motivational issues related to research skills, we found it useful to also include a scale to assess students’ amotivation. This was measured with (for the purpose of the current research translated) four items related to students’ amotivation regarding learning research skills, adapted from Academic Motivation Scale for Learning Biology (Aydin et al., 2014 ) ( α  = 0.80; 0.75; ω = 0.81; 0.75). Also this measure consist of Likert-type items ranging from one (do not agree at all) to five (totally agree).

Cognitive outcomes

Students’ research skills proficiency was measured by means of a research skills test (Maddens et al., 2020a ) and a research skills task.

The research skills test used in this study is the LRST (Maddens et al., 2020a ) consisting of a combination of 37 open ended and close ended items ( α  = 0.79; 0.82; ω = 0.78; ω = 0.80 for this data set), administered via an online questionnaire. Each item of the LRST is related to one of the eight epistemic activities regarding research skills as mentioned in the introduction (Fischer et al., 2014 ), and is scored as 0 or 1. The total score on the LRST is calculated by adding the mean subscale scores (related to the eight epistemic activities), and dividing them by eight (the number of scales). In a previous study (Maddens et al., 2020a ), the LRST was checked and found suitable in light of interrater reliability ( κ  = 0.89). As the same researchers assessed the same test with a similar cohort in the current study, the interrater reliability was not calculated for this study.

In the research skills task (“two pager task”), students were asked to write a research proposal of maximum two pages long. The concrete instructions for this research proposal are given in Appendix 1. In this research proposal, students were asked to formulate a research question and its relevance; to explain how they would tackle this research question (method and participants); to explain their hypotheses or expectations; and to explain how they would communicate their results. The two-pager task was analyzed using a pairwise comparison technique, in which four evaluators (i.e. the four authors of this paper) made comparative judgements by comparing two two-pagers at a time, and indicating which two-pager they think is best. All four evaluators are researchers in educational sciences and are familiar with the research project and with assessing students’ texts. This shared understanding and expertise is a prerequisite for obtaining reliable results (Lesterhuis et al., 2018 ). The comparison technique is performed by means of the Comproved tool ( https://comproved.com ). As described by Lesterhuis et al. ( 2018 , p. 18), “the comparative judgement method involves assessing a text on its overall quality. However, instead of requiring an assessor to assign an absolute score to a single text, comparative judgement simplifies the process to a decision about which of two texts is better”. In total, 1635 comparisons were made (each evaluator made 545 comparisons), and this led to a (interrater)reliability score of 0.79. In a next step, these comparative judgements were used to rank the 218 products (15 students did not submit a two-pager) on their quality; and the products were graded based on their ranking. This method was used to grade the two-pagers because it facilitates the holistic evaluation of the tasks, based on the judgement of multiple experts (interrater reliability).

Qualitative feedback

Students’ experiences with the online learning environment were investigated in the online learning environment itself. After completing the learning environment, students were asked how they experienced the tasks, the theory, the opportunity to post answers in the forum and to ask questions via the chat, what they liked or disliked in the online learning environment, and what they disliked in the online learning environment (Fig.  1 ).

Study overview

The first research question (” Does a deliberately designed (4C/ID-based) learning environment improve students’ research skills, as measured by a research skills test and a research skills task?” ) is answered by means of a paired samples t -test in order to look for overall improvements in order to detect potential general trends, followed by a full factorial MANCOVA, as this allows us to investigate the effectiveness for both conditions taking into account students’ pretest scores. Hence, the condition is included as an experimental factor, and students’ scores on the LRST and the two-pager task are included as continuous outcome variables. Students’ pretest scores on the LRST are included as a covariate. Prior to the analysis, a MANCOVA model is defined taking into account possible interaction effects between the experimental factor and the covariate.

The second research question (“ What is the effect of providing autonomy, competence and relatedness support in a deliberately designed (4C/ID-based) learning environment fostering students’ research skills, on students’ motivational outcomes, i.e. students’ amotivation, autonomous motivation, controlled motivation, students’ perceived value/usefulness, and students’ perceived needs of competence, relatedness and autonomy)?”) ;) is answered by means of a full factorial MANCOVA. The condition (need satisfaction condition versus baseline condition) is included as an experimental factor, and students’ responses on the value/usefulness, autonomous and controlled motivation, amotivation, and need satisfaction scales are included as continuous outcome variables. ASRS pretest scores (autonomous and controlled motivation) are included as covariates in order to test the differences between group means, adjusted for students’ a priori motivation. Prior to the analysis, a MANCOVA model is defined taking into account possible interaction effects between the experimental factor and the covariates, and assumptions to be met to perform a MANCOVA are checked. 7

The third research question ( “ What are the relationships between students’ need satisfaction, students’ need frustration, students’ autonomous and controlled motivation and students’ cognitive outcomes (research skills test and research skills task)?” ), is initially answered by means of five multiple regression analyses. The first three regressions include the need satisfaction and frustration scales, and students’ value/usefulness as independent variables, and students’ (1) autonomous motivation, (2) controlled motivation, and (3) amotivation as dependent variables. The fourth and fifth regressions include students’ autonomous motivation, controlled motivation, and amotivation as independent variables, and students’ (4) LRST scores, and (5) scores on the two-pager task as dependent variables. As a follow-up analysis (see ‘ results ’) two additional regression analyses are performed to look into the direct relationships between students’ perceived needs and students’ experienced value/usefulness, with students’ cognitive outcomes (LRST (6) and two-pager (7)). As the goal of this analysis is to investigate the relationships between variables as described in SDT research, this analysis focuses on the full sample, rather than distinguishing between the two conditions. An ‘Enter’ method (Field, 2013 ) is used in order to enter the independent variables simultaneously (in line with Sheldon et al., 2008 ).

The fourth research question (“ How do students experience need satisfaction and need frustration in a deliberately designed (4C/ID-based) learning environment?” ) is analyzed by means of the knowledge management tool Citavi. Based on the theoretical framework, students’ experiences are labeled by the codes ‘autonomy satisfaction, autonomy frustration, competence satisfaction, competence frustration, relatedness satisfaction, and relatedness frustration’. For example, students’ quotes referring to the value/usefulness of the learning environment, are labeled as ‘autonomy satisfaction’ or ‘autonomy frustration’. Students’ references towards their feelings of mastery of the learning content are labeled as ‘competence satisfaction’ or ‘competence frustration’. Students’ quotes regarding their relationships with peers and teachers are labeled as ‘relatedness satisfaction’ or ‘relatedness frustration’ (Fig.  2 ).

Overview variables

Does the deliberately designed (4C/ID based) learning environments improve students’ research skills, as measured by a research skills test and a research skills task?

Paired samples t -test. A paired samples t -test reveals that, in general, students ( n  = 210) improved on the LRST-posttest ( M  = 0.57, SD  = 0.16) compared to the pretest ( M  = 0.51, SD  = 0.15) (range 0–1). The difference between the posttest and the pretest is significant t (209) =  − 8.215, p  < 0.001, d 8  =  − 0.567. The correlation between the LRST pretest and posttest is 0.70 ( p  < 0.010).

MANCOVA. A MANCOVA model ( n  = 196) was defined checking for possible interaction effects between the experimental factor and the covariate in order to control for the assumption of ‘independence of the covariate and treatment effect’ (Field, 2013 ). The covariate LRST pretest did not show significant interaction effects for the two outcome variables LRST post ( p  = 0.259) and the two-pager task ( p  = 0.702). The correlation between the outcome variables (LRST post and two-pager), is 0.28 ( p  < 0.050).

Of all 233 students, 36 students were excluded from the main analysis because of missing data (for example, because they were absent during a pretest or posttest moment). These students were excluded by means of a listwise deletion method because we found it important to use a complete dataset, since, in a lot of cases, students who did not complete the pretest or posttest, did also not complete the entire learning environment. Including partial data for these students could bias the results. The baseline condition counted 86 students, and the need satisfaction condition counted 111 students. Using Pillai’s Trace [ V  = 0.070, F (2,193) = 7.285, p  ≤ 0.001], there was a significant effect of the condition on the cognitive outcome variables, taking into account students’ LRST pretest scores. Separate univariate ANOVAs on the outcome variables revealed no significant effect of the condition on the LRST posttest measure, F (1,194) = 2.45, p  = 0.120. However, a significant effect of condition was found on the two-pager scores, F (1,194) = 13.69, p  < 0.001 (in the baseline group, the mean score was 6,6/20; in the need condition group, the mean score was 7,6/20). It should be mentioned that both scores are rather low.

What is the effect of providing autonomy, competence and relatedness support in a deliberately designed (4C/ID based) learning environment fostering students’ research skills, on students’ motivational outcomes (students’ amotivation, autonomous motivation, controlled motivation, students’ perceived value/usefulness, and students’ perceived needs of competence, relatedness and autonomy)?

Paired samples t -tests. The correlations between students’ pretest and posttestscores for the motivational measures are 0.67 ( p  < 0.010) for autonomous motivation; 0.44 ( p  < 0.010) for controlled motivation, and 0.38 for amotivation ( p  < 0.010). Regarding the differences in students’ motivation, three unexpected findings were observed. Overall, students’ ( n  = 215) amotivation was higher on the posttest ( M  = 2.26, SD  = 0.89) compared to the pretest ( M  = 1.77, SD  = 0.79) (based on a score between 1 and 5). The difference between the posttest and the pretest is significant t (214) =  − 7.69, p  < 0.001, d  =  − 0.524. Further analyses learn that the amotivation means in the baseline group increased with 0.65, and the amotivation in the need support group increased with 0.37. In addition, students’ ( n  = 215) autonomous motivation was higher on the pretest ( M  = 2.81, SD  = 0.81) compared to the posttest ( M  = 2.64, SD  = 0.82). The difference between the posttest and the pretest is significant t (214) = 3.72, p  < 0.001, d  = 0.254. Students’ mean scores on autonomous motivation in the baseline condition decreased with 0.19, and students’ autonomous motivation in the need support condition decreased with 0.15. Students’ ( n  = 215) controlled motivation was higher on the posttest ( M  = 2.33, SD  = 0.75) compared to the pretest ( M  = 1.93, SD  = 0.67). The difference between the posttest and the pretest is significant t (214) =  − 07.72, p  < 0.001, d  =  − 0.527. Students’ controlled motivation in the baseline group increased with 0.36, and students’ controlled motivation in the need support group increased with 0.43. However, overall, all mean scores are and stay below neutral score (below 3), indicating robust low autonomous, controlled and amotivation scores (see Table ​ Table3). 3 ). An independent samples T -test on the mean differences between these measures shows that the increases/decreases on autonomous motivation [ t (213) =  − 0.506, p  = 0.613, d  =  − 0.069] and controlled motivation [ t (213) =  − 0.656, p  = 0.513, d  =  − 0.090] did not differ between the two groups. However, the increases in amotivation [ t (213) = 2.196, p  = 0.029, d  = 0.301] does differ significantly between the two conditions. More specifically, the increase was lower in the need supportive condition compared to the baseline condition.

Mean scores and standard deviations motivational variables

a Overall, students’ ( n  = 215) autonomous motivation was significantly higher on the pretest compared to the posttest ( t (214) 3.72, p  ≤ 0.001, d  = 0.254

b Students’ (n = 215) controlled motivation was significantly higher on the posttest compared to the pretest ( t (214) =  − 7.72, p  ≤ 0.001, d  =  − 0.527

c Students’ ( n  = 215) amotivation was significantly higher on the posttest compared to the pretest ( t (214) =  − 07,69, p  ≤ 0.001, d  =  − 0.534)

MANCOVA. Of all 233 students, 18 students were excluded from the analysis because of missing data (for example, because they were absent during a pretest or posttest moment). Compared to the cognitive analyses, the amount of missing data is lower concerning motivational outcomes since, concerning the cognitive outcomes, some students did not complete the two-pager task. However, we found it important to use all relevant data and chose to report this is in a clear way. In total, the baseline condition counted 97 students, and the experimental condition counted 118 students. Similar to the analysis for the cognitive outcomes, a MANCOVA model was defined to check for possible interaction effects between the experimental factor and the covariate in order to control for the assumption of ‘independence of the covariate and treatment effect’ (Field, 2013 ). The covariates did not show significant interaction effects for the outcome variables. 9

Using Pillai’s Trace [ V  = 0.113, F (10,201) = 2.558, p  = 0.006], there was a significant effect of condition on the motivational variables, taking into account students’ autonomous and controlled pretest scores, and students’ a priori amotivation. Separate univariate ANOVAs on the outcome variables revealed a significant effect of the condition on the outcome variables amotivation, F (1,210) = 3.98, p  = 0.047; and relatedness satisfaction F (1,210) = 6.41, p  = 0.012. As was hypothesized, students in the need satisfaction group reported less amotivation ( M  = 2.38), compared to students in the baseline group ( M  = 2.18). In contrast to what was hypothesized, students in the need satisfaction group reported less relatedness satisfaction ( M  = 2.43) compared to students in the baseline group ( M  = 2.73), and no significant effects of condition were found on the outcome variables autonomous motivation post, controlled motivation post, value/usefulness, autonomy satisfaction, autonomy frustration, competence satisfaction, competence frustration, and relatedness frustration. Table ​ Table4 4 shows the correlations between the motivational outcome variables.

Correlations motivational outcome variables

AM autonomous motivation, CM controlled motivation, AMOT amotivation, VU value/usefulness, AS autonomy satisfaction, AF autonomy frustration, CS competence satisfaction, CF competence frustration, RS relatedness satisfaction, RF relatedness frustration

**Correlation is significant at the 0.010 level (2-tailed)

*Correlation is significant at the 0.050 level (2-tailed)

What are the relationships between students’ need satisfaction, students’ need frustration, students’ autonomous and controlled motivation and students’ cognitive outcomes (research skills test and research skills task)?

The third research question (investigating the relationships between students’ need satisfaction, students’ motivation and students’ cognitive outcomes), is answered by means of five multiple regression analyses. The first three regressions include the need satisfaction and frustration scales, and students value/usefulness as independent variables, and students’ (1) autonomous motivation, (2) controlled motivation, and (3) amotivation as dependent variables ( n  = 219). The fourth and fifth regressions include students’ autonomous motivation, controlled motivation, and amotivation as independent variables, and students’ (4) LRST scores ( n  = 215), and (5) scores on the two-pager task as dependent variables ( n  = 206). Table ​ Table4 4 depicts the correlations for the first three analyses. Table ​ Table5 5 depicts the correlations for the last two analyses.

Correlations motivational and cognitive outcome variables

AM  autonomous motivation, CM  controlled motivation, AMOT  amotivation, LRST  score on LRST, Twopager  score on Twopager

In Table ​ Table3, 3 , we can see that students in both conditions experience average competence and autonomy satisfaction. However, students’ relatedness satisfaction seems low in both conditions. This finding will be further discussed in the discussion section. For autonomous motivation, a significant regression equation was found F (7,211) = 37.453, p  < 0.001. The regression analysis (see Table ​ Table5) 5 ) further reveals that all three satisfaction scores (competence satisfaction, relatedness satisfaction and autonomy satisfaction) contribute positively to students’ autonomous motivation, as does students’ experienced value/usefulness. Also for students’ controlled motivation a significant regression equation was found F (7,211) = 8.236, p  < 0.001, with students’ autonomy frustration and students’ relatedness satisfaction contributing to students’ controlled motivation. The aforementioned relationships are in line with the expectations. However, we noticed that relatedness satisfaction contributed to students’ controlled motivation in the opposite direction of what was expected (the higher students’ relatedness satisfaction, the lower students’ controlled motivation). This finding will be reflected upon in the discussion section. Also for students’ amotivation, a significant regression equation was found F (7,211) = 7.913, p  < 0.001. Students’ autonomy frustration, competence frustration and students’ value/usefulness contributed to students’ amotivation in an expected way. Also for cognitive outcomes related to the research skills test, a significant regression equation was found F (3,211) = 8.351, p  < 0.001. In line with the expectations, the regression analysis revealed that the higher students’ amotivation, the lower students’ scores on the research skills test. No significant regression equation was found for the outcome variable related to the research skills task F (3,202) = 0.954, p  < 0.416. For all regression equations, the R 2 and the exact regression weights are presented in Table ​ Table6 6 .

Linear model of predictors of autonomous motivation, controlled motivation, amotivation, LRST scores, and two-pager scores with beta values, standard errors, standardized beta values and significance values

*Significant at .050 level

As a follow-up analysis and in order to better understand the outcomes, we decided to also look into the direct relationships between students’ perceived needs and students’ experienced value/usefulness, with students’ cognitive outcomes (LRST and two-pager) by means of two additional regression analyses. The motivation behind this decision relates to possible issues regarding the motivational measures used, which might complicate the investigation of indirect relationships (see discussion). The results are provided in Table ​ Table7, 7 , and show that both for the LRST and the two-pager, respectively, a significant [ F (7,207) = 4.252, p  < 0.001] and marginally significant regression weight [ F (7,199) = 2.029, p  = 0.053] was found. More specifically, students’ relatedness satisfaction and students’ perceived value/usefulness contribute to students’ scores on the two-pager and on the research skills test. As one would expect, we see that the higher students’ value/usefulness, the higher students’ scores on both cognitive outcomes. In contrast to one would expect, we found that the higher students’ relatedness satisfaction, the lower students’ scores on the cognitive outcomes. These findings are reflected upon in the discussion section.

Linear model of predictors of LRST scores, and two-pager scores with beta values, standard errors, standardized beta values and significance values

How do students experience need satisfaction and need frustration in a deliberately designed (4C/ID based) learning environment?

As was mentioned in the method section, the fourth research question was analysed by labelling students’ qualitative feedback by the codes ‘autonomy satisfaction, autonomy frustration, competence satisfaction, competence frustration, relatedness satisfaction, and relatedness frustration’. By means of this approach, we could analyse students’ need experiences in a fine grained manner. When students’ quotes were applicable to more than one code, they were labelled with different codes. In what follows, students’ quotes are indicated with the codes “BC” (baseline condition) or “NSC” (need satisfaction condition) in order to indicate which learning environment the student completed. Of all 233 students, 124 students provided qualitative feedback (44 in BC and 80 in NSC). In total, 266 quotes were labeled. Autonomy satisfaction was coded 40 times BC and 41 times in NSC; autonomy frustration was coded 13 times in BC and four times in NSC; competence satisfaction was coded 28 times in BC and 34 times in NSC; competence frustration was coded 31 times in BC and 27 times in NSC; relatedness satisfaction was coded 10 times in BC and 16 times in NSC; and relatedness frustration was coded five times in BC and 17 times in NSC. Several observations could be drawn from the qualitative data.

Related to autonomy satisfaction , in both conditions, several students explicitly mentioned the personal value and usefulness of what they had learned in the learning environment. While in the baseline condition, these references were often vague (“Now I know what people expect from me next year ”; “I think I might use this information in the future ”); some references appeared to be more specific in the need support condition (“I want to study psychology and I think I can use this information!”; “This is a good preparation for higher education and university ”; “I can use this information to write an essay ”; “I think the theory was interesting, because you are sure you will need it once. I don’t always have that feeling during a normal lesson in school”). In addition, students in both conditions mentioned that they found the material interesting, and that they appreciated the online format: “It’s different then just listening to a teacher, I kept interested because of the large variety in exercises and overall, I found it fun” (NSC).

Several comments were coded as ‘ autonomy frustration’ in both conditions. Some students indicated that they found the material “useless” (BC), or that “they did not remember that much” (BC). Others found the material “uninteresting” (BC), “heavy and boring” (NSC) or “not fun” (BC). In addition, some students “did not like to complete the assignments” (NSC), or “prefer a book to learn theory” (NSC).

Related to competence satisfaction , students in both conditions found the material “clear” (BC, NSC). In addition, students’ appreciated the example answers, the difficulty rate (“Some exercises were hard, but that is good. That’s a sign you’re learning something new” (NSC)), and the fact that the theory was segmented in several parts. In addition, students recognized that the material required complex skills: “I learned a lot, you had to think deeper or gain insights in order to solve the exercises” (NSC), “you really had to think to complete the exercises” (NSC). In the need satisfaction group, several quotes were labelled related to the specific need support provided. For example, students indicated that they appreciated the forum option: “If something was not clear, you could check your peer’s answers” (NSC). Students also valued the fact that they could work at their own pace: “I found it very good that we could solve everything at our own pace” (NSC); “good that you could choose your own pace, and if something was not clear to you, you could reread it at your own pace” (NSC). In addition, students appreciated the immediate feedback provided by the researcher “I found it very good that we received personal feedback from xxx (name researcher). That way, I knew whether I understood the theory correctly” (NSC); and the fact that they could indicate their progress “It was good that you could see how far you proceeded in the learning environment” (NSC).

In both the baseline and the need supportive condition, there were also several comments related to competence frustration . For example, students found exercises vague, unclear or too difficult. While students, overall, understood the theory provided, applying the theory to an integrative assignment appears to be very difficult: “I did understand the several parts of the learning environment, but I did not succeed in writing a research proposal myself” (NSC). “I just found it hard to respond to questions. When I had to write my two-pager research proposal, I really struggled. I really felt like I was doing it entirely wrong” (NSC)). In addition, a lot comments related to the fact that the theory was a lot to process in a short time frame, and therefore, students indicated that it was hard to remember all the theory provided. In addition, this led pressure in some students: “Sometimes, I experiences pressure. When you see that your peers are finished, you automatically start working faster.” (BC).

Concerning relatedness satisfaction , in the baseline condition, students appreciated the chat function “you could help each other and it was interesting to hear each other’s opinions about the topics we were working on” (BC). However, most students indicated that they did not make use of the chat or forum options. In the need satisfaction condition, students appreciated the forum and the chat function: “You knew you could always ask questions. This helped to process the learning material” (NSC), “My peers’ answers inspired me” (NSC), “Thanks to the chat function, I felt more connected to my peers” (NSC). In addition, students in the need satisfaction condition appreciated the fact that they could contact the researcher any time.

Several students made comments related to relatedness frustration . In both groups, students missed the ‘live teaching’: “I tried my best, but sometimes I did not like it, because you do not receive the information in ‘real time’, but through videos” (BC). In addition, students missed their peers: “We had to complete the environment individually” (BC). While some students appreciated the opportunity of a forum, other students found this possibility stressful: “I think the forum is very scary. I posted everything I had to, but I found it very scary that everyone can see what you post” (NSC). Others did not like the fact that they needed to work individually: “Sometimes I lost my attention because no one was watching my screen with me” (NSC); “I found it hard because this was new information and we could not discuss it with each other” (NSC); “I felt lonely” (NSC); “It is hard to complete exercises without the help of a teacher. In the future this will happen more often, so I guess I will have to get used to it” (NSC); “When I see the teacher physically, I feel less reluctant to ask questions” (NSC).

The current intervention study aimed at exploring the motivational and cognitive effects of providing need support in an online learning environment fostering upper secondary school students’ research skills. More specifically, we investigated the impact of autonomy, competence and relatedness support in an online learning environment on students’ scores on a research skills test, a research skills task, students’ autonomous motivation, controlled motivation, amotivation, need satisfaction, need frustration, and experienced value/usefulness. Adopting a pretest-intervention-posttest design approach, 233 upper secondary school behavioral sciences students’ motivational outcomes were compared among two conditions: (1) a 4C/ID inspired online learning environment condition (baseline condition), and (2) a condition with an identical online learning environment additively providing support for students’ autonomy, relatedness and competence need satisfaction (need supportive condition). This study aims to contribute to the literature by exploring the integration of need support for all three needs (the need for competence, relatedness and autonomy) in an ecologically valid setting. In what follows, the findings are discussed taking into account the COVID-19 affected circumstances in which the study took place.

As was hypothesized based on existing research (Costa et al., 2021 ), results showed significant learning gains on the LRST cognitive measure in both conditions, pointing out that the learning environments in general succeeded in improving students’ research skills. The current study did not find any significant differences in these learning gains between both conditions. Controlling for a priori differences between the conditions on the LRST pretest measure, students in the need support condition did exceed students in the baseline condition on the two-pager task. However, overall, the scores on the research skills task were quite low, pointing to the fact that students still seem to struggle in writing a research proposal. This task can be considered more complex (van Merriënboer & Kirschner, 2018 ) than the research skills test, as students are required to combine their conceptual and procedural knowledge in one assignment. Indeed, in the qualitative feedback, students indicate that they understand the theory and are able to apply the theory in basic exercises, but that they struggle in integrating their knowledge in a research proposal. Future research could set up more extensive interventions explicitly targeting students’ progress while writing a research proposal, for example using development portfolios (van Merriënboer et al., 2006 ).

The effect of the intervention on the motivational outcome measures was investigated. Since we experimentally manipulated need support, this study hypothesized that students in the need supportive condition would show higher scores for autonomous motivation, value/usefulness and need satisfaction; and lower scores for controlled motivation, amotivation and need frustration compared to students in the baseline condition (Deci & Ryan, 2000 ). However, the analyses showed that students in the conditions did not differ on the value/usefulness, autonomy satisfaction, autonomy frustration, competence satisfaction, competence frustration and relatedness frustration measures. In contrast to what was hypothesized, students’ in the baseline condition reported higher relatedness satisfaction compared to students in the need supportive condition. No differences were found in students’ autonomous motivation and controlled motivation. However, as was expected, students in the need supportive conditions did report lower levels of amotivation compared to students in the baseline condition. Still, for the current study, one could question the role of the need support in this respect, as the current intervention did not succeed in manipulating students’ need experiences. In what follows, possible explanations for these findings are outlined in light of the existing literature.

Need experiences

A first observation based on the findings as described above is that the intervention did not succeed in manipulating students’ need satisfaction, need frustration and value/usefulness in an expected way. One effect was found of condition on relatedness satisfaction, but in the opposite direction of what was expected. We did not find a conclusive explanation for this unanticipated finding, but we do argue that the COVID-19 related measures at play during the intervention could have impacted this result. This will be reflected upon later in this discussion (limitations). In both conditions, students seem to be averagely satisfied regarding autonomy and competence in the 4C/ID based learning environments. This might be explained by the fact that 4C/ID based learning environments inherently foster students’ perceived competence because of the attention for structure and guidance, and the fact that the use of authentic tasks can be considered autonomy supportive (Bastiaens & Martens, 2007). However, we see that students experience low relatedness satisfaction in both conditions. The fact that the learning environment was organized entirely online might have influenced this result. While one might also partly address this low relatedness satisfaction to the COVID-19 circumstances at play during the study, this hypothetical explanation does not hold entirely since also in a previous non COVID-affected study in this research trajectory (Maddens et al., under review ), students’ relatedness satisfaction was found to be low. This finding, combined with findings from students’ qualitative feedback clearly indicating relatedness frustration, we argue that future research could focus on the question as how to provide need for relatedness support in 4C/ID based learning environments. On a more general level, this raises the question how opportunities for discussions and collaboration can be included in 4C/ID based learning environments. For example, organizing ‘real classroom interactions’ or performing assignments in groups (see also the suggestion of van Merriënboer & Kirschner, 2018 ), might be important in fostering students’ relatedness satisfaction (Salomon, 2002 ) . As argued by Wang et al. ( 2019 ), relatedness support is clearly understudied, for a long time often even ignored, in the SDT literature. Recently, relatedness is beginning to receive more attention, and has been found a strong predictor of autonomous motivation in the classroom (Wang et al., 2019 ).

Possibly, the need support provided in the learning environment was insufficient or inadequate to foster students’ need experiences. However, as the implementations were based on the existing literature (Deci & Ryan, 2000 ), this finding can be considered surprising. In addition, we derive from the qualitative feedback that students seem to value the need support provided in the learning environment. These contradictory observations are in line with previous research (Bastiaens et al., 2017 ), and call for further investigation.

Autonomous motivation, controlled motivation, amotivation

A second observation is that, in both conditions, students seem to hold low autonomous motivation and low controlled motivation towards learning research. On average, also students’ amotivation is low. The fact that students are not amotivated to learn about research can be considered reassuring. However, the fact that students experience low autonomous motivation causes concerns, as we know this might negatively impact their learning behavior and intentions to learn (Deci & Ryan, 2000 ; Wang et al., 2019 ). However, this result is based on mean scores. Future research might look at these results at student level, in order to identify individual motivational profiles (Vansteenkiste et al., 2009 ) and their prevalence in upper secondary behavioral sciences education.

A third observation is that students’ autonomous and controlled motivation were not affected by the intervention. Since the intervention did not succeed in manipulating students’ need experiences, this finding is not surprising. In addition, this is in line with Bastiaens et al.’ ( 2017 ) study, not finding motivational effects of providing need support in 4C/ID based learning environments. However, the current study did confirm that—although still higher than at pretest level, see below—students in the need supportive condition reported lower amotivation compared to students in the baseline condition. As no amotivational differences were observed at pretest level, this might indicate that students’ self-reported motivation (autonomous and controlled motivation) and/or needs do not align with students’ experienced motivation and needs. As was mentioned, this calls for further research.

Theoretical relationships

In line with previous research (Wang et al., 2019 ), multiple regression analyses revealed that students’ need satisfaction (on all three measures) contributed positively to students’ autonomous motivation. In addition, also students’ perceived value/usefulness contributed positively to students’ autonomous motivation. Students’ competence frustration and autonomy frustration contributed positively to students’ amotivation, and students’ value/usefulness contributed negatively to students’ amotivation. Students’ autonomy frustration contributed positively to students’ controlled motivation. While all the aforementioned relationships are in line with the expectations (Deci & Ryan, 2000 ; Wang et al., 2019 ), an unexpected finding is that students’ relatedness satisfaction contributed positively to students’ controlled motivation. This contradicts previous research (Wang et al., 2019 ), reporting that relatedness contributes to controlled motivation negatively. However, previous research (Wang et al., 2019 ) did find controlled motivation to be positively related to pressure . Although we did not find a conclusive explanation for this unanticipated finding, one possible reason thus is that students who contacted their peers in the online learning environment (and thus felt more related to their peers), might have experienced pressure because they felt like their peers worked faster or in a different way. Indeed, in the qualitative feedback, we noticed that some students indicated they ‘rushed’ through the online learning environment because they noticed a peer working faster. This finding calls for further research.

Overall, the results indicate that the observed need variables contributed most to students’ autonomous motivation, compared to (reversed relationships in) students’ amotivation and students’ controlled motivation. As such, when targeting students’ motivation, fostering students’ autonomous motivation based on students’ need experiences seems most promising. This is in line with previous research (Wang et al., 2019 ) reporting high correlations between students’ needs and students’ autonomous motivation, compared to students’ controlled motivation. We also investigated the relationships between students’ motivation and students’ cognitive outcomes. In line with a previously conducted study in this research trajectory (Maddens et al., under review ), but in contrast to what was hypothesized based on the existing literature (Deci & Ryan, 2000 ; Grolnick et al., 1991 ; Reeve, 2006 ) we found that nor students’ autonomous motivation, nor students’ controlled motivation contributed to students’ scores on the research skills test. However, we did find that students’ amotivation contributed negatively to students’ LRST scores. As such, when targeting students’ cognitive outcomes in educational programs, one might pay explicit attention to preventing amotivation. This is in line with previous research conducted in other domains, reporting that amotivation plays an important role in predicting mathematics achievement (Leroy & Bressoux, 2016 ), while this relationship was not found in other motivation types. Related to research skills, the current research suggests that preventing competence frustration and autonomy frustration, and fostering students’ experiences of value/usefulness might be especially promising to reach this goal.

Initially, we did not plan any analyses investigating the direct relationships between students’ needs and students’ cognitive outcomes, partly because previous research (Vallerand & Losier, 1999 ) suggests that the relationships between need satisfaction and (cognitive) outcomes are mediated by the types of motivation. To this end, we investigated the relationships between students’ needs and students’ motivation, separately from the relationships between students’ motivation and students’ cognitive outcomes. However, because of potential issues with the motivational measures (see earlier), which possibly hampers the interpretation of the relationships between students’ needs, students’ motivation, and students’ cognitive outcomes, we decided to also directly assess the regression weights of students’ needs and students’ perceived value/usefulness, on students’ cognitive outcomes. Results revealed that, in line with the expectations, students’ perceived value/usefulness contributed positively to students’ LRST scores and two-pager scores, which potentially stresses the importance of value/usefulness, not only for motivational purposes, but also for cognitive purposes. This is in line with previous research (Assor et al., 2002 ), establishing relationships between fostering relevance and students’ behavioral and cognitive engagement (which potentially leads to better cognitive outcomes). In contrast to the expectations, students’ relatedness satisfaction was found to be negatively related to students’ scores on the LRST and the two-pager. However, again, this surprising finding is best interpreted in light of the COVID-10 pandemic (see earlier).

Limitations

This study faced some reliability issues given the time frame in which the study took place. Due to the COVID-19-restrictions at play at the time of study, the study plan needed to be revised several times in collaboration with teachers in order to be able to complete the interventions. In addition, it is very likely that students’ motivation (and relatedness satisfaction) was influenced by the COVID 19-restrictions. For example, due to the restrictions, in the last phase of the intervention, students could only be present at school halftime, and therefore, some students worked from home while others worked in the classroom. In the qualitative feedback, students reported several COVID-19 related frustrations (it was too cold in class because teachers were obligated to open the windows; students needed to frequently disinfect their computers…). Also the teachers mentioned that students suffered from low well-being during the COVID-19 time frame (see further), and as such, this affected their motivation. Although all efforts were undertaken in order for the study to take place as controlled as possible, results should be interpreted in light of this time frame. The impact of the COVID-19 pandemic on students’ self-reported motivation has been established in recent research (Daniels et al., 2021 ). Overall, one could question to what extent we can expect an intervention at microlevel (manipulating need support in learning environments) to work, when the study takes place in a time frame where students’ need experiences are seriously threatened by the circumstances.

Decreasing motivation

Students’ motivation evolved in a non-desirable way in both conditions. This unexpected finding (decreasing motivation) might be explained by four possible reasons: a first explanation is that asking students to fill out the same questionnaire at posttest and pretest level might lead to frustration and lower reported motivation (Kosovich et al., 2017 ). Indeed, students spent a lot of time working in the online learning environment, so filling out another motivational questionnaire on top of the intervention might have added to the frustration (Kosovich et al., 2017 ). A second explanation is that students’ motivation naturally declines over time (which is a common finding in the motivational literature, Kosovich et al., 2017 ). A third explanation is that students, indeed, felt less motivated towards research skills after having completed the online learning environment. For example, the qualitative data indicated that a lot of students acknowledged the fact that the learning environment was useful, but that personally, they were not interested in learning the material. In addition, students indicated that the learning material was a lot to process in a short time frame, and was new to them, which might have negatively impacted their motivation. The latter (students indicating that the learning material was extensive) might indicate that students experienced high cognitive load (Paas & van Merriënboer, 1994; Sweller et al., 1994 ) while completing the learning environment. A fourth explanation is that, due to the COVID19-restrictions, students lost motivation during the learning process. A post-intervention survey in which we asked teachers about the impact of the COVID-19 restrictions on students’ motivation indicated that some students experienced low well-being during the COVID-19 pandemic, and thus, this might have hampered their motivation to learn. In addition, a teacher mentioned that COVID-19 in general was very demotivating for the students, and that students had troubles concentrating due to the fact they felt isolated. As was mentioned, the impact of COVID-19 on students’ motivation has been well described in the literature (Daniels et al., 2021 ). Although, in the current study, we cannot prove the impact of these measures on students’ motivation specifically towards learning research skills, it is important to take this context into account when interpreting the results.

Students’ learning behavior

Based on students’ qualitative feedback, we have reasons to believe that students did not always work in the learning environment as we would want them to do. Thus, students did not interact with the need support in the intended way (‘instructional disobedient behavior’: Elen, 2020 ). For example, several students reported that they did not always read all the material, did not make use of the forum, or did not notice certain messages from the researcher. However, the current research did not specifically look into students’ learning behavior in the learning environment. In learning environments organized online, future researchers might want to investigate students’ online behavior in order to gain insights in students’ interactions with the learning environment.

This study aims to contribute to theory and practice. Firstly, this study defines the 4C/ID model (van Merriënboer & Kirschner, 2018 ) as a good theoretical framework in order to design learning environments aiming to foster students’ research skills. However, this study also points to students’ struggling in writing a research proposal, which might lead to more specific intervention studies especially focussing on monitoring students’ progress while performing such tasks. Secondly, this study clearly elaborates on the operationalizations of need support used, and as such, might inform instructional designers in order to implement need support in an integrated manner (including competence, relatedness and autonomy support). Future interventions might want to track and monitor students’ learning behavior in order for students to interact with the learning environment as expected (Elen, 2020 ). Thirdly, this study established theoretical relationships between students’ needs, motivation and cognitive outcomes, which might be useful information for researchers aiming to investigate students’ motivation towards learning research skills in the future. Based on the findings, future researchers might especially involve in research fostering students’ autonomous motivation by means of providing need support; and avoiding students’ amotivation in order to enhance students’ cognitive outcomes. Suggestions are made based on the need support and frustration measures relating to these motivational and cognitive outcomes. For example, fostering students’ value/usefulness seems promising for both cognitive and motivational outcomes. Fourthly, although we did not succeed in manipulating students’ need experiences, we did gain insights in students’ experiences with the need support by means of the qualitative data. For example, the irreplaceable role of teachers in motivating students has been exposed. This study can be considered innovative because of its aim to inspect both students’ cognitive and motivational outcomes after completing a 4C/ID based educational program (van Merriënboer & Kirschner, 2018 ). In addition, this study implements integrated need support rather than focusing on a single need (Deci & Ryan, 2000 ; Sheldon & Filak, 2008 ).

Acknowledgements

This study was carried out within imec’s Smart Education research programme, with support from the Flemish government.

Appendix: Overview test instruments

• Instructions 2-pager (Maddens, Depaepe, Raes, & Elen, under review)

Write a research proposal for a fictional study.

In a Word-document of maximum two pages…

• You describe a research question and the importance of this research question
• You explain how you would answer this research question (manner of data collection and target group)
• You explain what your expectations are, and how you will report your results.

To do so, you receive 2 hours.

Post your research proposal here.

Good luck and thank you for your activity in the RISSC-environment!

Declarations

The authors declare that they have no conflict of interest.

All ethical and GDPR-related guidelines were followed as required for conducting human research and were approved by SMEC (Social and Societal Ethics Committee).

1 Fischer et al. ( 2014 ) refer to these research skills as scientific reasoning skills.

2 In Flanders, during the time of study, four different types of education are offered from the second stage of secondary education onwards (EACEA, 2018) (general secondary education, technical secondary education, secondary education in the arts and vocational secondary education). Behavioral sciences is a track in general secondary education.

3 For a complete overview on the design and the evaluation of this learning environment, see Maddens et al ( 2020b ).

4 During the time of study, the COVID-19 restrictions became more strict: students in upper secondary education could only come to school half of the time. Therefore, some students completed the last modules of the learning environment at home.

5 The BPNSNF-training scale is initially constructed to evaluate motivation related to workshops. The phrasing was adjusted slightly in order for the suitability for the current study. For example, we changed the wording ‘during the past workshop…’ to ‘while completing the online learning environment…’.

6 In the current study, we would label the items categorized as ‘intrinsic motivation’ in ASRS (finding something interesting, fun, fascinating or a pleasant activity) as ‘integration’. In SDT (Deci & Ryan, 2000 ; Deci et al., 2017 ), integration is described as being “fully volitional”, or “wholeheartedly engaged”, and it is argued that fully internalized extrinsic motivation does not typically become intrinsic motivation, but rather remains extrinsic even though fully volitional (because it is still instrumental). In the context of the current study, in which students learn about research skills because this is instructed (thus, out of instrumental motivations), we think that the term integration is more applicable than pure intrinsic motivation in self-initiated contexts (which can be observed for example in children’s play or in sports).

7 Levene’s test for homogeneity of variances was significant for the outcome “two-pager”. However, we continued with the analyses since the treatment group sizes are roughly equal, and thus, the assumption of homogeneity of variances does not need to be considered (Field, 2013 ). Levene’s test for homogeneity of variances was non-significant for all the other outcome measures.

8 Cohen’s D is calculated in SPSS by means of the formula: D = M 1 - M 2 Sp

Condition x autonomous motivation pretest Value/usefulness: p  = 0.251; autonomous motivation: p  = 0.269; controlled motivation: p  = 0.457; amotivation: p  = 0.219; autonomy satisfaction: p  = 0.794; autonomy frustration: p  = 0.096; competence satisfaction: p  = 0.682; competence frustration: p  = 0.699; relatedness satisfaction: p  = 0.943; relatedness frustration: p  = 0.870.

Condition x controlled motivation pretest Value/usefulness: p  = 0.882; autonomous motivation: p  = 0.270; controlled motivation: p  = 0.782; amotivation: p  = 0.940; autonomy satisfaction: p  = 0.815; autonomy frustration: p  = 0.737; competence satisfaction: p  = 0.649; competence frustration: p  = 0.505; relatedness satisfaction: p  = 0.625; relatedness frustration: p  = 0.741.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Top 10 Study Tips to Study Like a Harvard Student

Adjusting to a demanding college workload might be a challenge, but these 10 study tips can help you stay prepared and focused.

Lian Parsons

The introduction to a new college curriculum can seem overwhelming, but optimizing your study habits can boost your confidence and success both in and out of the classroom. 

Transitioning from high school to the rigor of college studies can be overwhelming for many students, and finding the best way to study with a new course load can seem like a daunting process. 

Effective study methods work because they engage multiple ways of learning. As Jessie Schwab, psychologist and preceptor at the Harvard College Writing Program, points out, we tend to misjudge our own learning. Being able to recite memorized information is not the same as actually retaining it. 

“One thing we know from decades of cognitive science research is that learners are often bad judges of their own learning,” says Schwab. “Memorization seems like learning, but in reality, we probably haven’t deeply processed that information enough for us to remember it days—or even hours—later.”

Planning ahead and finding support along the way are essential to your success in college. This blog will offer study tips and strategies to help you survive (and thrive!) in your first college class. 

1. Don’t Cram! 

It might be tempting to leave all your studying for that big exam up until the last minute, but research suggests that cramming does not improve longer term learning. 

Students may perform well on a test for which they’ve crammed, but that doesn’t mean they’ve truly learned the material, says an article from the American Psychological Association . Instead of cramming, studies have shown that studying with the goal of long-term retention is best for learning overall.   

2. Plan Ahead—and Stick To It! 

Having a study plan with set goals can help you feel more prepared and can give you a roadmap to follow. Schwab said procrastination is one mistake that students often make when transitioning to a university-level course load. 

“Oftentimes, students are used to less intensive workloads in high school, so one of my biggest pieces of advice is don’t cram,” says Schwab. “Set yourself a study schedule ahead of time and stick to it.”

3. Ask for Help

You don’t have to struggle through difficult material on your own. Many students are not used to seeking help while in high school, but seeking extra support is common in college.

As our guide to pursuing a biology major explains, “Be proactive about identifying areas where you need assistance and seek out that assistance immediately. The longer you wait, the more difficult it becomes to catch up.”

There are multiple resources to help you, including your professors, tutors, and fellow classmates. Harvard’s Academic Resource Center offers academic coaching, workshops, peer tutoring, and accountability hours for students to keep you on track.  

4. Use the Buddy System 

Your fellow students are likely going through the same struggles that you are. Reach out to classmates and form a study group to go over material together, brainstorm, and to support each other through challenges.

Having other people to study with means you can explain the material to one another, quiz each other, and build a network you can rely on throughout the rest of the class—and beyond. 

5. Find Your Learning Style

It might take a bit of time (and trial and error!) to figure out what study methods work best for you. There are a variety of ways to test your knowledge beyond simply reviewing your notes or flashcards. 

Schwab recommends trying different strategies through the process of metacognition. Metacognition involves thinking about your own cognitive processes and can help you figure out what study methods are most effective for you. 

Schwab suggests practicing the following steps:

• Before you start to read a new chapter or watch a lecture, review what you already know about the topic and what you’re expecting to learn.
• As you read or listen, take additional notes about new information, such as related topics the material reminds you of or potential connections to other courses. Also note down questions you have.
• Afterward, try to summarize what you’ve learned and seek out answers to your remaining questions. 

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6. Take Breaks

The brain can only absorb so much information at a time. According to the National Institutes of Health , research has shown that taking breaks in between study sessions boosts retention. 

Studies have shown that wakeful rest plays just as important a role as practice in learning a new skill. Rest allows our brains to compress and consolidate memories of what we just practiced. 

Make sure that you are allowing enough time, relaxation, and sleep between study sessions so your brain will be refreshed and ready to accept new information.

7. Cultivate a Productive Space

Where you study can be just as important as how you study. 

Find a space that is free of distractions and has all the materials and supplies you need on hand. Eat a snack and have a water bottle close by so you’re properly fueled for your study session. 

8. Reward Yourself

Studying can be mentally and emotionally exhausting and keeping your stamina up can be challenging.

Studies have shown that giving yourself a reward during your work can increase the enjoyment and interest in a given task.

According to an article for Science Daily , studies have shown small rewards throughout the process can help keep up motivation, rather than saving it all until the end. 

Next time you finish a particularly challenging study session, treat yourself to an ice cream or  an episode of your favorite show.

9. Review, Review, Review

Practicing the information you’ve learned is the best way to retain information. 

Researchers Elizabeth and Robert Bjork have argued that “desirable difficulties” can enhance learning. For example, testing yourself with flashcards is a more difficult process than simply reading a textbook, but will lead to better long-term learning. 

“One common analogy is weightlifting—you have to actually “exercise those muscles” in order to ultimately strengthen your memories,” adds Schwab.

10. Set Specific Goals

Setting specific goals along the way of your studying journey can show how much progress you’ve made. Psychology Today recommends using the SMART method:

• Specific: Set specific goals with an actionable plan, such as “I will study every day between 2 and 4 p.m. at the library.”  
• Measurable: Plan to study a certain number of hours or raise your exam score by a certain percent to give you a measurable benchmark.
• Realistic: It’s important that your goals be realistic so you don’t get discouraged. For example, if you currently study two hours per week, increase the time you spend to three or four hours rather than 10.
• Time-specific: Keep your goals consistent with your academic calendar and your other responsibilities.

Using a handful of these study tips can ensure that you’re getting the most out of the material in your classes and help set you up for success for the rest of your academic career and beyond. 

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About the Author

Lian Parsons is a Boston-based writer and journalist. She is currently a digital content producer at Harvard’s Division of Continuing Education. Her bylines can be found at the Harvard Gazette, Boston Art Review, Radcliffe Magazine, Experience Magazine, and iPondr.

Becoming Independent: Skills You’ll Need to Survive Your First Year at College

Are you ready? Here are a few ideas on what it takes to flourish on campus.

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Studying 101: Study Smarter Not Harder

Do you ever feel like your study habits simply aren’t cutting it? Do you wonder what you could be doing to perform better in class and on exams? Many students realize that their high school study habits aren’t very effective in college. This is understandable, as college is quite different from high school. The professors are less personally involved, classes are bigger, exams are worth more, reading is more intense, and classes are much more rigorous. That doesn’t mean there’s anything wrong with you; it just means you need to learn some more effective study skills. Fortunately, there are many active, effective study strategies that are shown to be effective in college classes.

This handout offers several tips on effective studying. Implementing these tips into your regular study routine will help you to efficiently and effectively learn course material. Experiment with them and find some that work for you.

Reading is not studying

Simply reading and re-reading texts or notes is not actively engaging in the material. It is simply re-reading your notes. Only ‘doing’ the readings for class is not studying. It is simply doing the reading for class. Re-reading leads to quick forgetting.

Think of reading as an important part of pre-studying, but learning information requires actively engaging in the material (Edwards, 2014). Active engagement is the process of constructing meaning from text that involves making connections to lectures, forming examples, and regulating your own learning (Davis, 2007). Active studying does not mean highlighting or underlining text, re-reading, or rote memorization. Though these activities may help to keep you engaged in the task, they are not considered active studying techniques and are weakly related to improved learning (Mackenzie, 1994).

Ideas for active studying include:

• Create a study guide by topic. Formulate questions and problems and write complete answers. Create your own quiz.
• Become a teacher. Say the information aloud in your own words as if you are the instructor and teaching the concepts to a class.
• Derive examples that relate to your own experiences.
• Create concept maps or diagrams that explain the material.
• Develop symbols that represent concepts.
• For non-technical classes (e.g., English, History, Psychology), figure out the big ideas so you can explain, contrast, and re-evaluate them.
• For technical classes, work the problems and explain the steps and why they work.
• Study in terms of question, evidence, and conclusion: What is the question posed by the instructor/author? What is the evidence that they present? What is the conclusion?

Organization and planning will help you to actively study for your courses. When studying for a test, organize your materials first and then begin your active reviewing by topic (Newport, 2007). Often professors provide subtopics on the syllabi. Use them as a guide to help organize your materials. For example, gather all of the materials for one topic (e.g., PowerPoint notes, text book notes, articles, homework, etc.) and put them together in a pile. Label each pile with the topic and study by topics.

For more information on the principle behind active studying, check out our tipsheet on metacognition .

Understand the Study Cycle

The Study Cycle , developed by Frank Christ, breaks down the different parts of studying: previewing, attending class, reviewing, studying, and checking your understanding. Although each step may seem obvious at a glance, all too often students try to take shortcuts and miss opportunities for good learning. For example, you may skip a reading before class because the professor covers the same material in class; doing so misses a key opportunity to learn in different modes (reading and listening) and to benefit from the repetition and distributed practice (see #3 below) that you’ll get from both reading ahead and attending class. Understanding the importance of all stages of this cycle will help make sure you don’t miss opportunities to learn effectively.

Spacing out is good

One of the most impactful learning strategies is “distributed practice”—spacing out your studying over several short periods of time over several days and weeks (Newport, 2007). The most effective practice is to work a short time on each class every day. The total amount of time spent studying will be the same (or less) than one or two marathon library sessions, but you will learn the information more deeply and retain much more for the long term—which will help get you an A on the final. The important thing is how you use your study time, not how long you study. Long study sessions lead to a lack of concentration and thus a lack of learning and retention.

In order to spread out studying over short periods of time across several days and weeks, you need control over your schedule . Keeping a list of tasks to complete on a daily basis will help you to include regular active studying sessions for each class. Try to do something for each class each day. Be specific and realistic regarding how long you plan to spend on each task—you should not have more tasks on your list than you can reasonably complete during the day.

For example, you may do a few problems per day in math rather than all of them the hour before class. In history, you can spend 15-20 minutes each day actively studying your class notes. Thus, your studying time may still be the same length, but rather than only preparing for one class, you will be preparing for all of your classes in short stretches. This will help focus, stay on top of your work, and retain information.

In addition to learning the material more deeply, spacing out your work helps stave off procrastination. Rather than having to face the dreaded project for four hours on Monday, you can face the dreaded project for 30 minutes each day. The shorter, more consistent time to work on a dreaded project is likely to be more acceptable and less likely to be delayed to the last minute. Finally, if you have to memorize material for class (names, dates, formulas), it is best to make flashcards for this material and review periodically throughout the day rather than one long, memorization session (Wissman and Rawson, 2012). See our handout on memorization strategies to learn more.

It’s good to be intense

Not all studying is equal. You will accomplish more if you study intensively. Intensive study sessions are short and will allow you to get work done with minimal wasted effort. Shorter, intensive study times are more effective than drawn out studying.

In fact, one of the most impactful study strategies is distributing studying over multiple sessions (Newport, 2007). Intensive study sessions can last 30 or 45-minute sessions and include active studying strategies. For example, self-testing is an active study strategy that improves the intensity of studying and efficiency of learning. However, planning to spend hours on end self-testing is likely to cause you to become distracted and lose your attention.

On the other hand, if you plan to quiz yourself on the course material for 45 minutes and then take a break, you are much more likely to maintain your attention and retain the information. Furthermore, the shorter, more intense sessions will likely put the pressure on that is needed to prevent procrastination.

Silence isn’t golden

Know where you study best. The silence of a library may not be the best place for you. It’s important to consider what noise environment works best for you. You might find that you concentrate better with some background noise. Some people find that listening to classical music while studying helps them concentrate, while others find this highly distracting. The point is that the silence of the library may be just as distracting (or more) than the noise of a gymnasium. Thus, if silence is distracting, but you prefer to study in the library, try the first or second floors where there is more background ‘buzz.’

Keep in mind that active studying is rarely silent as it often requires saying the material aloud.

Problems are your friend

Working and re-working problems is important for technical courses (e.g., math, economics). Be able to explain the steps of the problems and why they work.

In technical courses, it is usually more important to work problems than read the text (Newport, 2007). In class, write down in detail the practice problems demonstrated by the professor. Annotate each step and ask questions if you are confused. At the very least, record the question and the answer (even if you miss the steps).

When preparing for tests, put together a large list of problems from the course materials and lectures. Work the problems and explain the steps and why they work (Carrier, 2003).

Reconsider multitasking

A significant amount of research indicates that multi-tasking does not improve efficiency and actually negatively affects results (Junco, 2012).

In order to study smarter, not harder, you will need to eliminate distractions during your study sessions. Social media, web browsing, game playing, texting, etc. will severely affect the intensity of your study sessions if you allow them! Research is clear that multi-tasking (e.g., responding to texts, while studying), increases the amount of time needed to learn material and decreases the quality of the learning (Junco, 2012).

Eliminating the distractions will allow you to fully engage during your study sessions. If you don’t need your computer for homework, then don’t use it. Use apps to help you set limits on the amount of time you can spend at certain sites during the day. Turn your phone off. Reward intensive studying with a social-media break (but make sure you time your break!) See our handout on managing technology for more tips and strategies.

Switch up your setting

Find several places to study in and around campus and change up your space if you find that it is no longer a working space for you.

Know when and where you study best. It may be that your focus at 10:00 PM. is not as sharp as at 10:00 AM. Perhaps you are more productive at a coffee shop with background noise, or in the study lounge in your residence hall. Perhaps when you study on your bed, you fall asleep.

Have a variety of places in and around campus that are good study environments for you. That way wherever you are, you can find your perfect study spot. After a while, you might find that your spot is too comfortable and no longer is a good place to study, so it’s time to hop to a new spot!

Become a teacher

Try to explain the material in your own words, as if you are the teacher. You can do this in a study group, with a study partner, or on your own. Saying the material aloud will point out where you are confused and need more information and will help you retain the information. As you are explaining the material, use examples and make connections between concepts (just as a teacher does). It is okay (even encouraged) to do this with your notes in your hands. At first you may need to rely on your notes to explain the material, but eventually you’ll be able to teach it without your notes.

Creating a quiz for yourself will help you to think like your professor. What does your professor want you to know? Quizzing yourself is a highly effective study technique. Make a study guide and carry it with you so you can review the questions and answers periodically throughout the day and across several days. Identify the questions that you don’t know and quiz yourself on only those questions. Say your answers aloud. This will help you to retain the information and make corrections where they are needed. For technical courses, do the sample problems and explain how you got from the question to the answer. Re-do the problems that give you trouble. Learning the material in this way actively engages your brain and will significantly improve your memory (Craik, 1975).

Take control of your calendar

Controlling your schedule and your distractions will help you to accomplish your goals.

If you are in control of your calendar, you will be able to complete your assignments and stay on top of your coursework. The following are steps to getting control of your calendar:

• On the same day each week, (perhaps Sunday nights or Saturday mornings) plan out your schedule for the week.
• Go through each class and write down what you’d like to get completed for each class that week.
• Look at your calendar and determine how many hours you have to complete your work.
• Determine whether your list can be completed in the amount of time that you have available. (You may want to put the amount of time expected to complete each assignment.) Make adjustments as needed. For example, if you find that it will take more hours to complete your work than you have available, you will likely need to triage your readings. Completing all of the readings is a luxury. You will need to make decisions about your readings based on what is covered in class. You should read and take notes on all of the assignments from the favored class source (the one that is used a lot in the class). This may be the textbook or a reading that directly addresses the topic for the day. You can likely skim supplemental readings.
• Pencil into your calendar when you plan to get assignments completed.
• Before going to bed each night, make your plan for the next day. Waking up with a plan will make you more productive.

See our handout on calendars and college for more tips on using calendars as time management.

Use downtime to your advantage

Beware of ‘easy’ weeks. This is the calm before the storm. Lighter work weeks are a great time to get ahead on work or to start long projects. Use the extra hours to get ahead on assignments or start big projects or papers. You should plan to work on every class every week even if you don’t have anything due. In fact, it is preferable to do some work for each of your classes every day. Spending 30 minutes per class each day will add up to three hours per week, but spreading this time out over six days is more effective than cramming it all in during one long three-hour session. If you have completed all of the work for a particular class, then use the 30 minutes to get ahead or start a longer project.

Use all your resources

Remember that you can make an appointment with an academic coach to work on implementing any of the strategies suggested in this handout.

Works consulted

Carrier, L. M. (2003). College students’ choices of study strategies. Perceptual and Motor Skills, 96 (1), 54-56.

Craik, F. I., & Tulving, E. (1975). Depth of processing and the retention of words in episodic memory. Journal of Experimental Psychology: General, 104 (3), 268.

Davis, S. G., & Gray, E. S. (2007). Going beyond test-taking strategies: Building self-regulated students and teachers. Journal of Curriculum and Instruction, 1 (1), 31-47.

Edwards, A. J., Weinstein, C. E., Goetz, E. T., & Alexander, P. A. (2014). Learning and study strategies: Issues in assessment, instruction, and evaluation. Elsevier.

Junco, R., & Cotten, S. R. (2012). No A 4 U: The relationship between multitasking and academic performance. Computers & Education, 59 (2), 505-514.

Mackenzie, A. M. (1994). Examination preparation, anxiety and examination performance in a group of adult students. International Journal of Lifelong Education, 13 (5), 373-388.

McGuire, S.Y. & McGuire, S. (2016). Teach Students How to Learn: Strategies You Can Incorporate in Any Course to Improve Student Metacognition, Study Skills, and Motivation. Stylus Publishing, LLC.

Newport, C. (2006). How to become a straight-a student: the unconventional strategies real college students use to score high while studying less. Three Rivers Press.

Paul, K. (1996). Study smarter, not harder. Self Counsel Press.

Robinson, A. (1993). What smart students know: maximum grades, optimum learning, minimum time. Crown trade paperbacks.

Wissman, K. T., Rawson, K. A., & Pyc, M. A. (2012). How and when do students use flashcards? Memory, 20, 568-579.

If you enjoy using our handouts, we appreciate contributions of acknowledgement.

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Home › Study Tips › Research Skills: What They Are and How They Benefit You

Research Skills: What They Are and How They Benefit You

• Published May 23, 2024

Research skills give you the ability to gather relevant information from different sources and analyse it critically in order to develop a comprehensive understanding of a subject. Thus, research skills are fundamental to academic success.

Developing these skills will improve your studies, helping you understand subjects better and positioning you for academic success.

That said, how can you develop important research skills? This will explore what research skills are, identify the core ones, and explain how you can develop them.

What Are Research Skills?

Research skills are a set of abilities that allow individuals to find and gather reliable information and then evaluate the information to find answers to questions.

Good research skills are important in academic settings, as finding and critically evaluating relevant information can help you gain a deeper understanding of a subject.

These skills are also important in professional and personal settings. When you graduate and are working in a professional capacity, you’ll often need to analyse sets of data to identify issues and determine how to solve them.

In personal contexts, you’ll always need to assess relevant information to make an informed decision. Whether you’re deciding on a major purchase, choosing a healthcare provider, or planning to make an investment, you’ll need to evaluate options to ensure better decision outcomes.

Different Types of Research Skills

Research skills are categorised into different sub-skills. The most common types are:

Quantitative Skills

Quantitative skills refer to the ability to work with numerical data and perform mathematical and statistical analyses to extract meaningful insights and draw conclusions. 

When you have quantitative skills, you’ll be able to apply mathematical concepts and operations in research design and data analysis. 

You’ll also be proficient in using statistical methods to analyse data and interpreting numerical data to draw meaningful conclusions. 

Analytical Skills

Analytical skills refer to the ability to gather data, evaluate it, and draw sound conclusions. When you have analytical skills, you’ll be able to systematically analyse information to reach a reasonable conclusion. 

Analytical skills are important in problem-solving. They help you to break down complex problems into more manageable components, think critically about the information at hand, analyse root causes, and develop effective solutions.

Qualitative Skills

Qualitative skills refer to the ability to collect, analyse, and interpret non-numerical data. When you have qualitative skills, you’ll be proficient in observation, interviewing, and other methods for collecting qualitative research data. 

You’ll also be able to analyse non-numerical data, such as documents and images, to identify themes, patterns, and meanings.

Research Skills Examples

The core research skills you need for success in academic, professional, and personal contexts include:

Data Collection

Data is at the centre of every research, as data is what you assess to find the answers you seek. Thus, research starts with collecting relevant data.

Depending on the research, there are two broad categories of data you can collect: primary and secondary.

Primary data is generated by the researcher, like data from interviews, observations, or experiments. Secondary data is pre-existing data obtained from different existing databases, like published literature, government reports, etc. 

Thus, data collection is more than gathering information from the Internet. Depending on the research, it can require more advanced skills for conducting experiments to generate your own data.

Source Evaluation

When doing research on any subject (especially when using the Internet), you’ll be amazed at the volume of information you’ll find. And a lot is pure garbage that can compromise your research work.

Thus, an important research skill is being able to dig through the garbage to get to the real facts. This is where source evaluation comes in!

Good research skills call for being able to identify biases, assess the authority of the author, and determine the accuracy of information before using it.

Time Management Skills

Have you ever felt that there is not enough time in a day for all that you need to do? When you already have so much to do, adding research can be overwhelming.

Good time management skills can help you find the time to do all you need to do, including relevant research work, making it an essential research skill.

Time management allows you to plan and manage your research project effectively. It includes breaking down research tasks into more manageable parts, setting priorities, and allocating time to the different stages of the research.

Communication Skills

Communication is an important aspect of every research, as it aids in data collection and sharing research findings. 

Important communication skills needed in research include active listening, active speaking, interviewing, report writing, data visualisation, and presentation, etc.

For example, when research involves collecting primary data via interviews, you must have sound speaking and listening skills. 

When you conclude the research and need to share findings, you’ll need to write a research report and present key findings in easy-to-understand formats like charts. 

Attention to Detail

Attention to detail is the ability to achieve thoroughness and accuracy when doing something. It requires focusing on every aspect of the tasks, even small ones. 

Anything you miss during your research will affect the quality of your research findings. Thus, the ability to pay close attention to details is an important research skill.

You need attention to detail at every stage of the research process. During data collection, it helps you ensure reliable data. 

During analysis, it reduces the risk of error to ensure your results are trustworthy. It also helps you express findings precisely to minimise ambiguity and facilitate understanding.

Note-Taking

Note-taking is exactly what it sounds like—writing down key information during the research process.

Remember that research involves sifting through and taking in a lot of information. It’s impossible to take in all the information and recall it from memory. This is where note-taking comes in!

Note-taking helps you capture key information, making it easier to remember and utilise for the research later. It also involves writing down where to look for important information.

Critical Thinking

Critical thinking is the ability to think rationally and synthesise information in a thoughtful way. It is an important skill needed in virtually all stages of the research process.

For example, when collecting data, you need critical thinking to assess the quality and relevance of data. It can help you identify gaps in data to formulate your research question and hypothesis. 

It can also help you to identify patterns and make reasonable connections when interpreting research findings.

Data Analysis

Data may not mean anything until you analyse it qualitatively or quantitatively (using techniques like Excel or SPSS). For this reason, data analysis analysis is an important research skill.

Researchers need to be able to build hypotheses and test these using appropriate research techniques. This helps to draw meaningful conclusions and gain a comprehensive understanding of research data.

Problem-Solving Skills

Research often involves addressing specific questions and solving problems. For this reason, problem-solving skills are important skills when conducting research. 

Problem-solving skills refer to the ability to identify, analyse, and solve problems effectively. 

With problem-solving skills, you’ll be able to assess a situation, consider various solutions, and choose the most appropriate course of action toward finding a solution.

Benefits of Research Skills

Research skills have many benefits, including:

Enhances Critical Thinking

Research skills and critical thinking are intertwined such that developing one enhances the other.

Research requires people to question assumptions, evaluate evidence, analyse information, and draw conclusions. These activities require you to think critically about the information at hand. Hence, engaging in research enhances critical thinking.

Develops Problem-Solving Skills

Research helps you acquire a set of critical skills that are directly transferable to problem-solving. 

For example, research fosters creative thinking, as it often requires synthesising data from different sources and connecting different concepts. After developing creative thinking via research, you can apply the skill to generate innovative solutions in problem-solving situations. 

Helps in Knowledge Acquisition

Engaging in research is a powerful way to acquire knowledge. Research involves exploring new ideas, and this helps you expand your breadth of knowledge.

It also involves applying research methods and methodologies. So, you’ll acquire knowledge about research methods, enhancing your ability to design and conduct studies in your higher education or professional life.

Why Are Research Skills Important?

Strong research skills offer numerous benefits, especially for students’ academic learning and development. 

When you develop good research skills, you’ll reap great academic rewards that include:

In-Depth Understanding

Conducting research allows you to delve deep into specific topics, helping you gain a thorough understanding of the subject matter beyond what is covered in standard coursework.

Critical Thinking Development

Research involves critical evaluation of information and making informed decisions. This builds your ability to think critically.

This skill will not only help you solve academic problems better, but it’s also crucial to your personal and professional growth.

Encouragement of Independent Learning

Research encourages independent learning. When you engage in research, you seek answers independently. You take the initiative to find, retrieve, and evaluate information relevant to your research.

That helps you develop self-directed study habits. You’ll be able to take ownership of your education and actively seek out information for a better understanding of the subject matter.

Intellectual Curiosity Development

Research skills encourage intellectual curiosity and a love of learning, as they’ll make you explore topics you find intriguing or important. Thus, you’ll be more motivated to explore topics beyond the scope of your coursework.

Enhanced Communication Skills

Research helps you build better interpersonal skills as well as report-writing skills.

Research helps you sharpen your communication skills when you interact with research subjects during data collection. Communicating research findings to an audience also helps sharpen your presentation skills or report writing skills.

Assistance in Career Preparation 

Many professions find people with good research skills. Whether you’ll pursue a career in academia, business, healthcare, or IT, being able to conduct research will make you a valuable asset.

So, researching skills for students prepares you for a successful career when you graduate.

Contribution to Personal Growth

Research also contributes to your personal growth. Know that research projects often come with setbacks, unexpected challenges, and moments of uncertainty. Navigating these difficulties helps you build resilience and confidence.

Acquisition of Time Management Skills

Research projects often come with deadlines. Such research projects force you to set goals, prioritise tasks, and manage your time effectively.

That helps you acquire important time management skills that you can use in other areas of academic life and your professional life when you graduate.

Ways to Improve Research Skills

The ways to improve your research skills involve a combination of learning and practice. 

You should consider enrolling in research-related programmes, learning to use data analysis tools, practising summarising and synthesising information from multiple sources, collaborating with more experienced researchers, and more. 

Looking to improve your research skills? Read our 11 ways to improve research skills article.

How Can I Learn Research Skills?

You can learn research skills using these simple three-point framework:

Clarifying the Objective

Start by articulating the purpose of your research. Identify the specific question you are trying to answer or the problem you are aiming to solve.

Then, determine the scope of your research to help you stay focused and avoid going after irrelevant information.

Cross-Referencing Sources

The next step is to search for existing research on the topic. Use academic databases, journals, books, and reputable online sources.

It’s important to compare information from multiple sources, taking note of consensus among studies and any conflicting findings. 

Also, check the credibility of each source by looking at the author’s expertise, information recency, and reputation of the publication’s outlet.

Organise the Research

Develop a note-taking system to document key findings as you search for existing research. Create a research outline, then arrange your ideas logically, ensuring that each section aligns with your research objective.

As you progress, be adaptable. Be open to refining your research plan as new understanding evolves.

Enrolling in online research programmes can also help you build strong research skills. These programmes combine subject study with academic research project development to help you hone the skills you need to succeed in higher education.

Immerse Education is a foremost provider of online research programmes.

Acquire Research Skills with Immerse Education 

Research skills are essential to academic success. They help you gain an in-depth understanding of subjects, enhance your critical thinking and problem-solving skills, improve your time management skills, and more. 

In addition to boosting you academically, they contribute to your personal growth and prepare you for a successful professional career.

Thankfully, you can learn research skills and reap these benefits. There are different ways to improve research skills, including enrolling in research-based programmes. This is why you need Immerse Education!

Immerse Education provides participants aged 13-18 with unparalleled educational experience. All our programmes are designed by tutors from top global universities and help prepare participants for future success.

Our online research programme expertly combines subject study with academic research projects to help you gain subject matter knowledge and the important research skills you need to succeed in higher education.  With one-on-one tutoring or group sessions from an expert academic from Oxford or Cambridge University and a flexible delivery mode, the programme is designed for you to succeed. Subsequently, enrolling in our accredited Online Research Programme will award students with 8 UCAS points upon completion.

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Ultimate Study Skills Guide: Tips, Tricks, and Strategies for Every Grade

Because they really do need to learn how to learn.

It’s not an exaggeration to say that study skills are life skills. Taking good notes, creating a focused workspace, managing distractions, making plans—any and all of these are skills people of all ages use every single day. Taking time to teach good study skills up front can equip students to succeed in school and beyond.

We’ve broken down many of the top study skills students need, including examples by grade level. Remember that there are a lot of different ways to study successfully. Offer students options and help them find the strategies that work best for them.

Study Spaces

Organization and time management study skills, learning styles, taking and using notes, effective reading study skills, completing assignments, test taking, finding help.

Choosing the right place to study is the first step to good study skills. Teach students to consider these elements.

Choose Your Space

For some students, this means a dedicated study space like a desk in their room. Others may prefer to curl up in a chair with a lap desk or work at a table in a common space. Whichever they choose, it should be an area that’s dedicated to study while they’re using it.

Source: organizeandarrangeit/Instagram

• Elementary School: Many students begin doing homework on the dining room or kitchen table, where parents can supervise. As students get older, encourage them to explore other spaces too, especially those where they can work independently.
• Middle School: By this age, kids will probably need a dedicated study space of their own, where they can keep supplies and works-in-progress. If that’s not possible, create a bin or box where they can store stuff while they’re not using it, then pull it out when it’s time to study.
• High School: Older students should be able to carve out a study space pretty much anywhere, since that’s something they’ll need to be able to do in the working world too. As long as they’re able to concentrate and get their work done, don’t be too picky about where they choose to do it.

Make Yourself Comfortable

“Comfortable” looks different for every person, so don’t assume all kids need to be sitting at a desk to work well. At the same time, they shouldn’t be so comfortable that they’ll fall asleep!

• Elementary School: When kids are doing independent reading, let them choose any spot they like. For other work, make sure they have a sturdy writing surface, like a table or lap desk. Ensure they have enough light to see what they’re doing, and teach them good posture if they’re sitting in a chair so they don’t develop stiff muscles.
• Middle and High School: Show them how to adjust the font size on screens so they’re not squinting to read. Encourage them to use blue light filters if they’re spending a lot of time on computers.

Manage Distractions

Learning to concentrate while ignoring distractions is a key life skill, and one that we all need to develop. Some students will have no trouble tuning things out, while others are going to need a lot of help with this one.

• Elementary School: Kids at this age are very easily distracted, so their study space should be as calm as possible. If a quiet room isn’t available, they might need noise-canceling headphones or even a white-noise machine to help them concentrate. Muting the TV isn’t enough—be sure it’s off completely. Remind friends and siblings to leave kids alone while they’re working.
• Middle School: These kids are old enough to recognize distractions but might still have trouble handling them. Encourage them to turn off phones and electronics (although some students are fine listening to music while they work). Students at this age are old enough to politely ask friends or family not to interrupt them while they work.
• High School: By this time, students know that the world is full of distractions and you can’t quiet them all. But you can teach them to mute their phone and messaging notifications, close all unnecessary windows on their laptops, and be firm about letting others know they need to be left alone to study.

Gather Your Supplies

One way to eliminate distractions is to ensure you have everything you need in place before you start. This includes books, notes, office supplies, and more. All kids should have water and some healthy snacks on hand too.

Source: jugglingactmama/Instagram

• Elementary School: Having a dedicated, well-stocked study space makes it much easier for kids to settle down to their work. Keep a supply of sharpened pencils, glue sticks, scissors, markers, and other items in a nearby drawer or a bin they can grab when they’re ready to get started.
• Middle School: Students this age likely keep just about everything they need in their backpacks, so they’ll want it nearby when they study. Remind them to restock their supplies once a week (including sharpening pencils in advance).
• High School: Depending on the assignment, these students may not need a lot of physical supplies, but they should still gather any books, notes, laptops, pens and highlighters, etc., they need before they settle in for a study session.

These two study skills are also vital life skills, so the sooner kids learn them, the better. They’ll be grateful later in life!

Use a Homework Planner

As soon as kids starting having any kind of homework, they need a planner. For younger students, this could be a daily take-home folder, while older kids will need a more sophisticated system. Either way, use it consistently so it becomes a habit.

• Elementary School: Take-home folders are perfect for organizing worksheets and other assignments. Put unfinished work on the left and finished work on the right. Use sticky notes on the worksheets or the front of the folder to write reminders about what needs to be done, including any due dates. Parents of younger students can review these folders each day, while upper elementary kids should mostly be able to keep track of things on their own.

Source: Busy Classroom

• Middle School: Use a planner notebook that includes calendars to help keep track of long-term assignments, with pages for daily notes and to-do lists. Teach students to make notes in them during class or immediately after, and start every study session by reviewing any current assignments and their due dates.

Source: Starts at Eight

• High School: Kids can continue using paper planners, or transition to online calendars or apps. Show them how to set useful reminders online, so things don’t slip through the cracks.

Source: LP Tutoring

Create a Daily Study Plan

When kids sit down to tackle the day’s work, encourage them to begin by making a plan. Assess what needs to be done, estimate the amount of time it will take, and decide what to do first.

Source: Beyond Booksmart

• Elementary School: Parents and young kids should sit down together to look over the day’s assignments and talk about what to work on first. Some students might like to get easy tasks out of the way before settling in to harder ones, while others prefer to handle more difficult things first. Help them find the method that works best for them.
• Middle School and High School: This age brings a higher amount of homework, so students should always start by determining how much time they’ll need to complete it. Let them experiment a bit—do they work best by completely finishing one assignment before moving on to the next, or do they like to do a little bit of each and take some breaks in between? Over time, they’ll find the methods they like best.

Chose the Best Study Time

Kids’ days are often jam-packed with activities, leaving homework and studying to get squeezed in whenever it fits. Take time to find out what time of day kids are at their best, and prioritize that time for study. For instance, if a student seems to learn better if they do their homework right after school, try to choose extracurriculars that meet in the evenings or weekends instead. Some students might even prefer to get up early in the morning and work, and that’s OK too as long as they’re getting enough sleep.

• Elementary School: Let kids try doing their homework at different times throughout the day, and see if there are times when they’re better at concentrating. If so, teach them to schedule their schoolwork during those times, and make extracurricular choices for them accordingly.
• Middle and High School: Students probably know by now when they work best, but busy schedules can make that more difficult to accommodate. Remind them to try to make smart choices and to tackle schoolwork when they’re feeling as fresh and alert as possible.

Keep Materials Neat and Organized

Some adults thrive in messy work spaces, and that’s OK. But kids should make an effort to keep their spaces and materials organized so they have fewer excuses for not getting things done.

Source: mywallpro/Instagram

• Elementary School: In early grades, parents should help kids go through their backpack each night, cleaning out trash and restocking supplies. Help them set up an organization system using the different pockets. Show them how to use different-color folders and notebooks for each subject, and clean out every folder regularly. Set the backpack by the front door each night so it’s ready to go in the morning. Upper grade students should gradually do some or all of these things on their own.
• Middle School: Transition to entirely managing backpacks and study spaces on their own. Parents might check in once a week or at the beginning of a school quarter to see if students need some assistance getting organized.
• High School: In addition to managing their physical study materials, ensure kids at this age know how to keep things organized online. Show them how to use files and folders, where to back things up, and how to manage their email and message inboxes. Encourage them to set aside a regular time to make sure everything is in order, and make improvements as needed.

Take Breaks

Students need both physical and mental brain breaks while they study! Remind kids to get up and move around regularly, rest their eyes, and give their brain a break for a few minutes every so often.

• Elementary School: Younger students should be able to work for about 15-20 minutes before taking a break, with upper grades going as long as 30 minutes. They usually won’t need reminders to take breaks, but they might need some help keeping those breaks to no more than 10 minutes or so.
• Middle School: These kids can work 30-45 minutes at a time and should learn to recognize the signs of needing a break on their own. When they start to get very fidgety, feel a headache coming on, squint while they’re reading, or feel hungry or thirsty, it’s time for a short break. Teach them to set a timer to know when the break is over and they need to get back to work.
• High School: By now, students can work an hour at a time but should be encouraged to take regular breaks all the same. In fact, just like adults, they should aim to get up and move for at least 5 minutes every hour. Physical activity like stretching, yoga, or even dancing to music will help refresh them so they can get back down to it. If they have trouble remembering to take breaks, have them set a timer to remind them.

All students use different learning methods to retain and understand the same information. Some like written words, some prefer to hear it and talk about it. Others need to do something with their hands or see images and diagrams. These are known as learning styles. While it’s important not to pigeonhole students into any one style, kids should be aware of any strengths they have and use them to create strong study skills.

Source:  Nnenna Walters

Know Your Style

There are four generally accepted styles: visual, auditory, read/write, and kinesthetic (movement). You can learn more about them here. It’s worth taking time to understand which (if any) style appeals to a student more.

• Elementary School: Most kids are exposed to a wide array of learning activities, strategies, and methods here and will slowly form preferences. If parents or teachers notice that kids aren’t learning well using one method (e.g., flash cards to learn math facts), have students try activities from different styles instead (like videos or songs).
• Middle School: At this age, students should have some idea of which study methods fit their learning styles. They should continue to experiment, especially in subjects where they struggle to master the material.
• High School: Kids in these grades who still don’t understand how they learn best may benefit from taking the VARK questionnaire . It will point them in the right direction and help them find the best study methods.

Choose Appropriate Study Materials

Here are some examples of study materials and activities that appeal to different learning styles, no matter the age or grade level.

Source: Elementary Shenanigans

• Visual: Diagrams; charts; graphs; maps; videos with or without sound; photos and other images; graphic organizers and sketchnotes
• Auditory: Lectures; audiobooks; videos with sound; music and songs; text-to-speech translation; discussion and debate; teaching others
• Read/Write: Reading textbooks, articles, and handouts; watching video with subtitles turned on; using speech-to-text translation and transcripts; making lists; writing answers to questions
• Kinesthetic: Hands-on practice; educational craft projects; experiments and demonstrations; trial and error; moving and playing games while learning

Study after study have shown the importance of actively taking notes rather than passively reading a handout later on. The act of writing engages different parts of the brain, forging new pathways that help students retain information in long-term memory. Taking good notes and using them properly are study skills every student needs to master.

Learn Different Note-Taking Strategies

There are a variety of good strategies, like outlines, the Cornell Method, sketchnotes, and more. There’s no one best method; it often depends on the material and the learner.

Source:  Think Insights

• Elementary School: Actively teach kids how to take notes in a variety of styles. Learn about seven top note-taking strategies here , and share them with your students. Teachers can start with handouts and graphic organizers but should slowly transition to more independent methods.
• Middle School: Students should be mastering the skill of taking their own notes, choosing a style that works best for them. They may need reminders of key points to capture but should now be able to isolate the important info.
• High School: Note-taking should be automatic by now, and many students will have developed preferred styles. Teachers should not insist on a specific note-taking strategy, but should ensure kids are capturing the information they need.

Organize and Review

Taking notes is just one part of the process. Students with good study skills also know how to use them effectively.

Source: The Mad Scientist

• Elementary School: Help students keep all notes from one subject or project in one notebook or folder. Show them how to place them in an order that makes sense, and use tabs, tables of contents, or other organizational methods. Encourage them to review each day’s notes when they go home at night, to reinforce the learning.
• Middle School: Students in these grades might want to reorganize their notes on their own when they get home, re-copying them or even typing them into a computer. They should be able to use effective organization strategies, to find the notes they need later on during a study session.
• High School: Students should plan to spend time after every class going over that day’s notes, reviewing and reinforcing what they learned. They should be able to rely heavily on their own notes when reviewing for a test or completing a project.

“Read chapter three for homework tonight.” Sounds simple enough, right? But there’s a big difference between skimming the material and actually learning from it. Here are the study skills students need to learn while they read.

Highlighting

Everybody loves a handful of colorful highlighters, but using them effectively is a study skill all on its own. Kids can highlight both texts and their own notes.

Source: cozmic_mae/Instagram

• Elementary School: Read material with students, showing them how to highlight key words and phrases instead of whole blocks of text. Show them color-coding strategies for organizing the information. Give them practice passages specifically for learning these skills.
• Middle School: Introduce students to online highlighting tools, since many of the texts they’ll be reading are digital. If necessary, they can print out reading material to highlight physically instead.
• High School: Kids should be pretty expert at highlighting by now, but watch for students who are still highlighting whole blocks without really knowing why, and show them the fundamentals.

Rereading and Taking Notes

In a lot of cases, reading something once simply isn’t enough. All students should learn to reread materials, using that time to highlight and take notes.

Source: SERC

• Elementary School: Reread passages together, pointing out key words, phrases, and ideas. Make notes while reading, both in the text and on separate paper. Try to complete review questions without referring to the text.
• Middle School: Students will know they’ve read thoroughly when they can complete review questions without looking back. Show students how to write their own review questions as they study (the Cornell Method of Note-Taking is perfect for this) so they’ll know they truly understand the material.
• High School: Continue to reinforce good reading study skills by giving students review questions to complete or asking them to make an outline or sketchnotes to sum up what they’ve learned.

Kids need to learn how to thoroughly complete an assignment, whether it’s a worksheet, an essay, or a term-long research project. These are the study skills they should know.

Understand the Assignment

Having a clear understanding of what’s being asked is so important. Otherwise, kids might wind up doing the wrong work, then having to tackle it all over again.

• Elementary School: Show kids how to carefully read directions at the beginning. Have them repeat back what they’re expected to do, and make notes if they need reminders. Teachers should provide instructions in writing whenever possible and make them clear and simple.
• Middle School: Encourage students to ask questions about assignments up front, or throughout if necessary. Continue to ensure they fully understand the directions before they start, especially when there are multiple steps.
• High School: By now, students should be able to make their own notes about expectations and can handle a series of more complicated steps. They should make a habit of reviewing all that information before they begin work.

Make a Plan

Once they know the expectations, students should plan how they’ll do the work.

• Elementary School: Help students evaluate the assignment and decide which parts they’ll do first. This is also a good time to estimate how long the work will take.
• Middle School: Encourage kids to think about how they like to approach assignments. Do they like doing easy problems first, then circling back around to harder stuff? Do they sometimes get stuck and frustrated? If so, how can they get “unstuck” and continue to make progress?
• High School: Many high school assignments are more complex, and students will need to lay out the steps to take. For instance, a research project might require choosing a topic, getting approval, starting research, planning a presentation, and giving the presentation, with multiple sub-steps in each. This all feels more manageable when you have a plan in place first.

Save Your Work

Such a basic study skill, and so extremely important!

• Elementary School: Help students ensure all assignments go back into the appropriate folders and all folders make it into their backpack when they’re done. Don’t leave things lying around where they can get lost.
• Middle and High School: In addition to keeping physical papers in order, be sure kids know how to save files online, including backing up their work. Many programs save automatically, but that’s not always the case. Show them how to keep backed-up files on an external drive or in the cloud, in case their hardware fails.

Review and Revise

Finishing the last problem on the page or typing the final word on a paper doesn’t mean you’re done. Good study skills means going back to review your work and make revisions.

Source: EnglishWritingTeacher.com

• Elementary School: Parents and younger kids should go back over completed homework together to make sure it’s complete and correct. Perform math problems “backwards” to see if the answers make sense. As kids get older, parents should remind them to review and check their answers on their own.
• Middle School: Students should regularly remember to check their answers before turning in an assignment. Advise them to make sure they’ve done everything they’ve been asked to, to the best of their ability.
• High School: Reviewing and revising should be automatic now. Writing assignments should include plans for multiple revisions. Teach students to use spell-check and grammar-check programs as needed, and encourage them to read their writing out loud to hear how it sounds.

Some kids naturally do well on tests, but others freeze up and forget everything they’ve learned . Fortunately, test-taking study skills are something kids can learn over time.

Source: Tammy DeShaw/The Owl Teacher

Review the Material

Kids should develop a variety of strategies for reviewing for a test, including review questions, flash cards, discussions, looking over notes, and more. It’s also important to follow a regular study schedule on any subject, instead of leaving all the review to the last minute.

• Elementary School: Whenever possible, adults should work with kids to help them study. Make flash cards, talk over the material together, sing spelling word songs—model good study skills for them to help them learn.
• Middle School: Help students continue to use a variety of review strategies. Teachers can provide review questions, set up study groups, and create online materials for them to use, just to name a few.
• High School: Kids should be coordinating their own review by now, whether independently or in groups. Make sure they know how to contact you if they have questions while they’re studying.

Get Rest and Eat Well

At any age, feeling your best is key to acing a test. Discourage students from staying up late to cram, and see that they have healthy meals and snacks on the day of the test. If they’re allowed, be sure they have bottled water on hand to stay hydrated before and during the test itself.

Tackle Easy Questions First

This one is especially important for students who have difficulty managing their time, or those who get incredibly nervous about tests. Focus on showing what you know, and build confidence as you go along.

• Elementary School: Teach kids to look over the entire test first so they can see what they’ll be expected to do. Tell them to ask questions right away if they have any. On the second run-through, they should answer any questions or problems they’re certain about. Finally, they can go back and handle more challenging questions, one at a time. In younger grades, practice this skill by using guided test-taking sessions.
• Middle School: Before a test, remind students of the process. Have them look the whole thing over first, and ask if anyone has any general questions before they begin. Monitor kids as they complete the test, and nudge along any who seem stuck on one particular question or section.
• High School: By now, kids should have the process down pat, but teachers should be aware of nervous test-takers and quietly remind them to focus on what they know.

Watch the Time

It’s a simple skill but a valuable one. Get kids used to glancing at the clock, but not obsessing over how much time is left.

• Elementary School: Tell kids how much time they have up front. Offer reminders several times, especially toward the end, but don’t do it in a way that amps up anxiety.
• Middle School: Make time expectations clear up front, and remind students once or twice of the remaining time as they work. Students should be glancing at the clock occasionally as they work; at the end of every page or section is a good rule of thumb. If they feel like they’re running out of time, remind them to use the “easy questions first” strategy.
• High School: Older students should be able to look over a test and compare it to the amount of time they have, so they know they’re working at the right pace. Teachers can offer a reminder halfway through and five minutes before the end.

Review Before Submitting

Just like with assignments, students should try to make time to review test answers before they turn it in. (And to make sure they put their names on their paper!)

• Elementary School: Actively ask students who are turning in their papers to go back to their seats and review their answers first. Build in a little extra test time so every student has a chance to review their work.
• Middle School: Remind students to review their work before submitting it when you pass out the tests. Offer additional reminders to those who regularly turn in work that needed another look.
• High School: Students should remember to build in time to look things over at the end as they start taking the test. The five-minute reminder toward the end is their cue to look over what they’ve done.

Even when you have terrific study skills, sometimes you need some assistance. Asking for help when you need it is something everyone needs to be able to do. While kids can’t expect adults to walk them through every step of the process, they should feel free to reach out for guidance when they need it.

Know How and When To Contact Teachers

Help students keep contact information handy and know the appropriate ways to contact their teachers as needed.

Source: StudentSavvy/Teachers Pay Teachers

• Elementary School: Most outside-school communication is between parents and teachers at this point, but kids should be encouraged to ask their own questions during the school day whenever possible. As they get older, parents should do their best to let kids take the lead.
• Middle School: Students should be almost entirely independent of parents when communicating with teachers now. They should know when teachers are available to chat in person (including before and after school, if possible). Adults can also show them how to write respectful emails or texts if teachers have made that contact information available.
• High School: At this point, students should be nearly 100% responsible for talking to their teachers when they need to. They should keep a contact list of email addresses, phone numbers, or other info. Additionally, they should recognize and respect preferred methods of contact.

Create Study Groups

While some kids work best on their own, many others thrive working with others to keep them on track and motivated. Setting up study buddies or groups enhances everyone’s study skills.

Source: MiddleWeb

• Elementary School: Parents will likely have to coordinate any in-person or online study sessions. Teachers can help by pairing students together as partners or for tutoring, and providing virtual study spaces when necessary.
• Middle School: As students get older, they should learn to seek out strong study partners. Help them recognize that their best friends may not always be the best choices when it comes to studying. Encourage them to have peers over to study, or to meet in public places like libraries.
• High School: Kids should be independently forming their own study support systems. However, they might ask teachers for help when they need one-on-one tutor recommendations. They may work together at school, at home, at the library, or online.

Use Resource Tools

There are more ways to learn and study than ever before. Help students find the right options to support their studies.

• Elementary School: Encourage students to look up answers in the right places: What does a word mean? Check the dictionary. When did the Civil War start? Here’s how to Google that. Help younger students use the resources to ensure they’re finding the information they need.
• Middle School: “Hey Google, how many moons does Jupiter have?” Kids this age know how to ask questions on the web. However, they need to learn how to make sure the answers are reliable. Teach them about primary sources (like following Wikipedia info back to its original source) and how to verify information in several different places.
• High School: A huge number of resources are online these days, so be sure students know where to find them and how to use them. Provide trusted online dictionaries and encyclopedias, show them how to seek out a thesaurus or rhyming dictionary, and guide them to video sites beyond YouTube, just to name a few.

How do you teach study skills in your classroom? Come share your ideas and ask for advice in the WeAreTeachers HELPLINE group on Facebook !

Plus, check out 15 life skills every teen should learn ..

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Research skills are the ability to find out accurate information on a topic. They include being able to determine the data you need, find and interpret those findings, and then explain that to others. Being able to do effective research is a beneficial skill in any profession, as data and research inform how businesses operate. Whether you’re unsure of your research skills or are looking for ways to further improve them, then this article will cover important research skills and how to become even better at research. Key Takeaways Having strong research skills can help you understand your competitors, develop new processes, and build your professional skills in addition to aiding you in finding new customers and saving your company money. Some of the most valuable research skills you can have include goal setting, data collection, and analyzing information from multiple sources. You can and should put your research skills on your resume and highlight them in your job interviews. In This Article    Skip to section What are research skills? Why are research skills important? 12 of the most important research skills How to improve your research skills Highlighting your research skills in a job interview How to include research skills on your resume Resume examples showcasing research skills Research skills FAQs References Sign Up For More Advice and Jobs Show More What are research skills?

Research skills are the necessary tools to be able to find, compile, and interpret information in order to answer a question. Of course, there are several aspects to this. Researchers typically have to decide how to go about researching a problem — which for most people is internet research.

In addition, you need to be able to interpret the reliability of a source, put the information you find together in an organized and logical way, and be able to present your findings to others. That means that they’re comprised of both hard skills — knowing your subject and what’s true and what isn’t — and soft skills. You need to be able to interpret sources and communicate clearly.

Why are research skills important?

Research skills are useful in any industry, and have applications in innovation, product development, competitor research, and many other areas. In addition, the skills used in researching aren’t only useful for research. Being able to interpret information is a necessary skill, as is being able to clearly explain your reasoning.

Research skills are used to:

Do competitor research. Knowing what your biggest competitors are up to is an essential part of any business. Researching what works for your competitors, what they’re doing better than you, and where you can improve your standing with the lowest resource expenditure are all essential if a company wants to remain functional.

Develop new processes and products. You don’t have to be involved in research and development to make improvements in how your team gets things done. Researching new processes that make your job (and those of your team) more efficient will be valued by any sensible employer.

Foster self-improvement. Folks who have a knack and passion for research are never content with doing things the same way they’ve always been done. Organizations need independent thinkers who will seek out their own answers and improve their skills as a matter of course. These employees will also pick up new technologies more easily.

Manage customer relationships. Being able to conduct research on your customer base is positively vital in virtually every industry. It’s hard to move products or sell services if you don’t know what people are interested in. Researching your customer base’s interests, needs, and pain points is a valuable responsibility.

Save money. Whether your company is launching a new product or just looking for ways to scale back its current spending, research is crucial for finding wasted resources and redirecting them to more deserving ends. Anyone who proactively researches ways that the company can save money will be highly appreciated by their employer.

Solve problems. Problem solving is a major part of a lot of careers, and research skills are instrumental in making sure your solution is effective. Finding out the cause of the problem and determining an effective solution both require accurate information, and research is the best way to obtain that — be it via the internet or by observation.

Determine reliable information. Being able to tell whether or not the information you receive seems accurate is a very valuable skill. While research skills won’t always guarantee that you’ll be able to tell the reliability of the information at first glance, it’ll prevent you from being too trusting. And it’ll give the tools to double-check .

12 of the most important research skills

Experienced researchers know that worthwhile investigation involves a variety of skills. Consider which research skills come naturally to you, and which you could work on more.

Data collection . When thinking about the research process, data collection is often the first thing that comes to mind. It is the nuts and bolts of research. How data is collected can be flexible.

For some purposes, simply gathering facts and information on the internet can fulfill your need. Others may require more direct and crowd-sourced research. Having experience in various methods of data collection can make your resume more impressive to recruiters.

Data collection methods include: Observation Interviews Questionnaires Experimentation Conducting focus groups

Analysis of information from different sources. Putting all your eggs in one source basket usually results in error and disappointment. One of the skills that good researchers always incorporate into their process is an abundance of sources. It’s also best practice to consider the reliability of these sources.

Are you reading about U.S. history on a conspiracy theorist’s blog post? Taking facts for a presentation from an anonymous Twitter account?

If you can’t determine the validity of the sources you’re using, it can compromise all of your research. That doesn’t mean just disregard anything on the internet but double-check your findings. In fact, quadruple-check. You can make your research even stronger by turning to references outside of the internet.

Examples of reliable information sources include: Published books Encyclopedias Magazines Databases Scholarly journals Newspapers Library catalogs

Finding information on the internet. While it can be beneficial to consulate alternative sources, strong internet research skills drive modern-day research.

One of the great things about the internet is how much information it contains, however, this comes with digging through a lot of garbage to get to the facts you need. The ability to efficiently use the vast database of knowledge that is on the internet without getting lost in the junk is very valuable to employers.

Internet research skills include: Source checking Searching relevant questions Exploring deeper than the first options Avoiding distraction Giving credit Organizing findings

Interviewing. Some research endeavors may require a more hands-on approach than just consulting internet sources. Being prepared with strong interviewing skills can be very helpful in the research process.

Interviews can be a useful research tactic to gain first-hand information and being able to manage a successful interview can greatly improve your research skills.

Interviewing skills involves: A plan of action Specific, pointed questions Respectfulness Considering the interview setting Actively Listening Taking notes Gratitude for participation

Report writing. Possessing skills in report writing can assist you in job and scholarly research. The overall purpose of a report in any context is to convey particular information to its audience.

Effective report writing is largely dependent on communication. Your boss, professor , or general reader should walk away completely understanding your findings and conclusions.

Report writing skills involve: Proper format Including a summary Focusing on your initial goal Creating an outline Proofreading Directness

Critical thinking. Critical thinking skills can aid you greatly throughout the research process, and as an employee in general. Critical thinking refers to your data analysis skills. When you’re in the throes of research, you need to be able to analyze your results and make logical decisions about your findings.

Critical thinking skills involve: Observation Analysis Assessing issues Problem-solving Creativity Communication

Planning and scheduling. Research is a work project like any other, and that means it requires a little forethought before starting. Creating a detailed outline map for the points you want to touch on in your research produces more organized results.

It also makes it much easier to manage your time. Planning and scheduling skills are important to employers because they indicate a prepared employee.

Planning and scheduling skills include: Setting objectives Identifying tasks Prioritizing Delegating if needed Vision Communication Clarity Time-management

Note-taking. Research involves sifting through and taking in lots of information. Taking exhaustive notes ensures that you will not neglect any findings later and allows you to communicate these results to your co-workers. Being able to take good notes helps summarize research.

Examples of note-taking skills include: Focus Organization Using short-hand Keeping your objective in mind Neatness Highlighting important points Reviewing notes afterward

Communication skills. Effective research requires being able to understand and process the information you receive, either written or spoken. That means that you need strong reading comprehension and writing skills — two major aspects of communication — as well as excellent listening skills.

Most research also involves showcasing your findings. This can be via a presentation. , report, chart, or Q&A. Whatever the case, you need to be able to communicate your findings in a way that educates your audience.

Communication skills include: Reading comprehension Writing Listening skills Presenting to an audience Creating graphs or charts Explaining in layman’s terms

Time management. We’re, unfortunately, only given 24 measly hours in a day. The ability to effectively manage this time is extremely powerful in a professional context. Hiring managers seek candidates who can accomplish goals in a given timeframe.

Strong time management skills mean that you can organize a plan for how to break down larger tasks in a project and complete them by a deadline. Developing your time management skills can greatly improve the productivity of your research.

Time management skills include: Scheduling Creating task outlines Strategic thinking Stress-management Delegation Communication Utilizing resources Setting realistic expectations Meeting deadlines

Using your network. While this doesn’t seem immediately relevant to research skills, remember that there are a lot of experts out there. Knowing what people’s areas of expertise and asking for help can be tremendously beneficial — especially if it’s a subject you’re unfamiliar with.

Your coworkers are going to have different areas of expertise than you do, and your network of people will as well. You may even know someone who knows someone who’s knowledgeable in the area you’re researching. Most people are happy to share their expertise, as it’s usually also an area of interest to them.

Networking involves: Remembering people’s areas of expertise Being willing to ask for help Communication Returning favors Making use of advice Asking for specific assistance

Attention to detail. Research is inherently precise. That means that you need to be attentive to the details, both in terms of the information you’re gathering, but also in where you got it from. Making errors in statistics can have a major impact on the interpretation of the data, not to mention that it’ll reflect poorly on you.

There are proper procedures for citing sources that you should follow. That means that your sources will be properly credited, preventing accusations of plagiarism. In addition, it means that others can make use of your research by returning to the original sources.

Attention to detail includes: Double checking statistics Taking notes Keeping track of your sources Staying organized Making sure graphs are accurate and representative Properly citing sources

How to improve your research skills

As with many professional skills, research skills serve us in our day to day life. Any time you search for information on the internet, you’re doing research. That means that you’re practicing it outside of work as well. If you want to continue improving your research skills, both for professional and personal use, here are some tips to try.

Differentiate between source quality. A researcher is only as good as their worst source. Start paying attention to the quality of the sources you use, and be suspicious of everything your read until you check out the attributions and works cited.

Be critical and ask yourself about the author’s bias, where the author’s research aligns with the larger body of verified research in the field, and what publication sponsored or published the research.

Use multiple resources. When you can verify information from a multitude of sources, it becomes more and more credible. To bolster your faith in one source, see if you can find another source that agrees with it.

Don’t fall victim to confirmation bias. Confirmation bias is when a researcher expects a certain outcome and then goes to find data that supports this hypothesis. It can even go so far as disregarding anything that challenges the researcher’s initial hunch. Be prepared for surprising answers and keep an open mind.

Be open to the idea that you might not find a definitive answer. It’s best to be honest and say that you found no definitive answer instead of just confirming what you think your boss or coworkers expect or want to hear. Experts and good researchers are willing to say that they don’t know.

Stay organized. Being able to cite sources accurately and present all your findings is just as important as conducting the research itself. Start practicing good organizational skills , both on your devices and for any physical products you’re using.

Get specific as you go. There’s nothing wrong with starting your research in a general way. After all, it’s important to become familiar with the terminology and basic gist of the researcher’s findings before you dig down into all the minutia.

Highlighting your research skills in a job interview

A job interview is itself a test of your research skills. You can expect questions on what you know about the company, the role, and your field or industry more generally. In order to give expert answers on all these topics, research is crucial.

Start by researching the company . Look into how they communicate with the public through social media, what their mission statement is, and how they describe their culture.

Pay close attention to the tone of their website. Is it hyper professional or more casual and fun-loving? All of these elements will help decide how best to sell yourself at the interview.

Next, research the role. Go beyond the job description and reach out to current employees working at your desired company and in your potential department. If you can find out what specific problems your future team is or will be facing, you’re sure to impress hiring managers and recruiters with your ability to research all the facts.

Finally, take time to research the job responsibilities you’re not as comfortable with. If you’re applying for a job that represents increased difficulty or entirely new tasks, it helps to come into the interview with at least a basic knowledge of what you’ll need to learn.

How to include research skills on your resume

Research projects require dedication. Being committed is a valuable skill for hiring managers. Whether you’ve had research experience throughout education or a former job, including it properly can boost the success of your resume .

Consider how extensive your research background is. If you’ve worked on multiple, in-depth research projects, it might be best to include it as its own section. If you have less research experience, include it in the skills section .

Focus on your specific role in the research, as opposed to just the research itself. Try to quantify accomplishments to the best of your abilities. If you were put in charge of competitor research, for example, list that as one of the tasks you had in your career.

If it was a particular project, such as tracking the sale of women’s clothing at a tee-shirt company, you can say that you “directed analysis into women’s clothing sales statistics for a market research project.”

Ascertain how directly research skills relate to the job you’re applying for. How strongly you highlight your research skills should depend on the nature of the job the resume is for. If research looks to be a strong component of it, then showcase all of your experience.

If research looks to be tangential, then be sure to mention it — it’s a valuable skill — but don’t put it front and center.

Resume examples showcasing research skills

Example #1: Academic Research

Simon Marks 767 Brighton Blvd. | Brooklyn, NY, 27368 | (683)-262-8883 | [email protected] Diligent and hardworking recent graduate seeking a position to develop professional experience and utilize research skills. B.A. in Biological Sciences from New York University. PROFESSIONAL EXPERIENCE Lixus Publishing , Brooklyn, NY Office Assistant- September 2018-present Scheduling and updating meetings Managing emails and phone calls Reading entries Worked on a science fiction campaign by researching target demographic Organizing calendars Promoted to office assistant after one year internship Mitch’s Burgers and Fries , Brooklyn, NY Restaurant Manager , June 2014-June 2018 Managed a team of five employees Responsible for coordinating the weekly schedule Hired and trained two employees Kept track of inventory Dealt with vendors Provided customer service Promoted to restaurant manager after two years as a waiter Awarded a $2.00/hr wage increase SKILLS Writing Scientific Research Data analysis Critical thinking Planning Communication RESEARCH Worked on an ecosystem biology project with responsibilities for algae collection and research (2019) Lead a group of freshmen in a research project looking into cell biology (2018) EDUCATION New York University Bachelors in Biological Sciences, September 2016-May 2020

Example #2: Professional Research

Angela Nichols 1111 Keller Dr. | San Francisco, CA | (663)-124-8827 |[email protected] Experienced and enthusiastic marketer with 7 years of professional experience. Seeking a position to apply my marketing and research knowledge. Skills in working on a team and flexibility. EXPERIENCE Apples amp; Oranges Marketing, San Francisco, CA Associate Marketer – April 2017-May 2020 Discuss marketing goals with clients Provide customer service Lead campaigns associated with women’s health Coordinating with a marketing team Quickly solving issues in service and managing conflict Awarded with two raises totaling $10,000 over three years Prestigious Marketing Company, San Francisco, CA Marketer – May 2014-April 2017 Working directly with clients Conducting market research into television streaming preferences Developing marketing campaigns related to television streaming services Report writing Analyzing campaign success statistics Promoted to Marketer from Junior Marketer after the first year Timberlake Public Relations, San Francisco, CA Public Relations Intern – September 2013–May 2014 Working cohesively with a large group of co-workers and supervisors Note-taking during meetings Running errands Managing email accounts Assisting in brainstorming Meeting work deadlines EDUCATION Golden Gate University, San Francisco, CA Bachelor of Arts in Marketing with a minor in Communications – September 2009 – May 2013 SKILLS Marketing Market research Record-keeping Teamwork Presentation. Flexibility

Research skills FAQs

What research skills are important?

Goal-setting and data collection are important research skills. Additional important research skills include:

Using different sources to analyze information.

Finding information on the internet.

Interviewing sources.

Writing reports.

Critical thinking.

Planning and scheduling.

Note-taking.

Managing time.

How do you develop good research skills?

You develop good research skills by learning how to find information from multiple high-quality sources, by being wary of confirmation bias, and by starting broad and getting more specific as you go.

When you learn how to tell a reliable source from an unreliable one and get in the habit of finding multiple sources that back up a claim, you’ll have better quality research.

In addition, when you learn how to keep an open mind about what you’ll find, you’ll avoid falling into the trap of confirmation bias, and by staying organized and narrowing your focus as you go (rather than before you start), you’ll be able to gather quality information more efficiently.

What is the importance of research?

The importance of research is that it informs most decisions and strategies in a business. Whether it’s deciding which products to offer or creating a marketing strategy, research should be used in every part of a company.

Because of this, employers want employees who have strong research skills. They know that you’ll be able to put them to work bettering yourself and the organization as a whole.

Should you put research skills on your resume?

Yes, you should include research skills on your resume as they are an important professional skill. Where you include your research skills on your resume will depend on whether you have a lot of experience in research from a previous job or as part of getting your degree, or if you’ve just cultivated them on your own.

If your research skills are based on experience, you could put them down under the tasks you were expected to perform at the job in question. If not, then you should likely list it in your skills section.

University of the People – The Best Research Skills for Success

Association of Internet Research Specialists — What are Research Skills and Why Are They Important?

MasterClass — How to Improve Your Research Skills: 6 Research Tips

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Sky Ariella is a professional freelance writer, originally from New York. She has been featured on websites and online magazines covering topics in career, travel, and lifestyle. She received her BA in psychology from Hunter College.

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Home > Blog > Tips for Online Students > The Best Research Skills For Success

Tips for Online Students , Tips for Students

The Best Research Skills For Success

Updated: June 19, 2024

Published: January 5, 2020

Every student is required to conduct research in their academic careers at one point or another. A good research paper not only requires a great deal of time, but it also requires complex skills. Research skills include the ability to organize, evaluate, locate, and extract relevant information.

Let’s learn how to develop great research skills for academic success.

What is Research?

We’ve all surely heard the term “research” endlessly. But do you really know what it means?

Research is a type of study that focuses on a specific problem and aims to solve it using scientific methods. Research is a highly systematic process that involves both describing, explaining, and predicting something.

Photo by  Startup Stock Photos  from  Pexels

What are research skills.

Research skills are what helps us answer our most burning questions, and they are what assist us in our solving process from A to Z, including searching, finding, collecting, breaking down, and evaluating the relevant information to the phenomenon at hand.

Research is the basis of everything we know — and without it, we’re not sure where we would be today! For starters, without the internet and without cars, that’s for sure.

Why are Research Skills Important?

Research skills come in handy in pretty much everything we do, and especially so when it comes to the workforce. Employers will want to hire you and compensate you better if you demonstrate a knowledge of research skills that can benefit their company.

From knowing how to write reports, how to notice competition, develop new products, identify customer needs, constantly learn new technologies, and improve the company’s productivity, there’s no doubt that research skills are of utter importance. Research also can save a company a great deal of money by first assessing whether making an investment is really worthwhile for them.

How to Get Research Skills

Now that you’re fully convinced about the importance of research skills, you’re surely going to want to know how to get them. And you’ll be delighted to hear that it’s really not so complicated! There are plenty of simple methods out there to gain research skills such as the internet as the most obvious tool.

Gaining new research skills however is not limited to just the internet. There are tons of books, such as Lab Girl by Hope Jahren, journals, articles, studies, interviews and much, much more out there that can teach you how to best conduct your research.

Utilizing Research Skills

Now that you’ve got all the tools you need to get started, let’s utilize these research skills to the fullest. These skills can be used in more ways than you know. Your research skills can be shown off either in interviews that you’re conducting or even in front of the company you’re hoping to get hired at .

It’s also useful to add your list of research skills to your resume, especially if it’s a research-based job that requires skills such as collecting data or writing research-based reports. Many jobs require critical thinking as well as planning ahead.

Career Paths that Require Research Skills

If you’re wondering which jobs actually require these research skills, they are actually needed in a variety of industries. Some examples of the types of work that require a great deal of research skills include any position related to marketing, science , history, report writing, and even the food industry.

Photo by  Abby Chung  from  Pexels

How students can improve research skills.

Perhaps you know what you have to do, but sometimes, knowing how to do it can be more of a challenge. So how can you as a student improve your research skills ?

1. Define your research according to the assignment

By defining your research and understanding how it relates to the specific field of study, it can give more context to the situation.

2. Break down the assignment

The most difficult part of the research process is actually just getting started. By breaking down your research into realistic and achievable parts, it can help you achieve your goals and stay systematic.

3. Evaluate your sources

While there are endless sources out there, it’s important to always evaluate your sources and make sure that they are reliable, based on a variety of factors such as their accuracy and if they are biased, especially if used for research purposes.

4. Avoid plagiarism

Plagiarism is a major issue when it comes to research, and is often misunderstood by students. IAs a student, it’s important that you understand what plagiarism really means, and if you are unclear, be sure to ask your teachers.

5. Consult and collaborate with a librarian

A librarian is always a good person to have around, especially when it comes to research. Most students don’t seek help from their school librarian, however, this person tends to be someone with a vast amount of knowledge when it comes to research skills and where to look for reliable sources.

6. Use library databases

There are tons of online library resources that don’t require approaching anyone. These databases are generally loaded with useful information that has something for every student’s specific needs.

7. Practice effective reading

It’s highly beneficial to practice effective reading, and there are no shortage of ways to do it. One effective way to improve your research skills it to ask yourself questions using a variety of perspectives, putting yourself in the mind of someone else and trying to see things from their point of view.

There are many critical reading strategies that can be useful, such as making summaries from annotations, and highlighting important passages.

Thesis definition

A thesis is a specific theory or statement that is to be either proved or maintained. Generally, the intentions of a thesis are stated, and then throughout, the conclusions are proven to the reader through research. A thesis is crucial for research because it is the basis of what we are trying to prove, and what guides us through our writing.

What Skills Do You Need To Be A Researcher?

One of the most important skills needed for research is independence, meaning that you are capable of managing your own work and time without someone looking over you.

Critical thinking, problem solving, taking initiative, and overall knowing how to work professionally in front of your peers are all crucial for effectively conducting research .

1. Fact check your sources

Knowing how to evaluate information in your sources and determine whether or not it’s accurate, valid or appropriate for the specific purpose is a first on the list of research skills.

2. Ask the right questions

Having the ability to ask the right questions will get you better search results and more specific answers to narrow down your research and make it more concise.

3. Dig deeper: Analyzing

Don’t just go for the first source you find that seems reliable. Always dig further to broaden your knowledge and make sure your research is as thorough as possible.

4. Give credit

Respect the rights of others and avoid plagiarizing by always properly citing your research sources.

5. Utilize tools

There are endless tools out there, such as useful websites, books, online videos, and even on-campus professionals such as librarians that can help. Use all the many social media networks out there to both gain and share more information for your research.

6. Summarizing

Summarizing plays a huge role in research, and once the data is collected, relevant information needs to be arranged accordingly. Otherwise it can be incredibly overwhelming.

7. Categorizing

Not only does information need to be summarized, but also arranged into categories that can help us organize our thoughts and break down our materials and sources of information.

Photo by  Noelle Otto  from  Pexels

What are different types of research, 1. qualitative.

This type of research is exploratory research and its aim is to obtain a better understanding of reasons for things. Qualitative research helps form an idea without any specific fixed pattern. Some examples include face-to-face interviews or group discussions.

2. Quantitative

Quantitative research is based on numbers and statistics. This type of research uses data to prove facts, and is generally taken from a large group of people.

3. Analytical

Analytical research has to always be done from a neutral point of view, and the researcher is intended to break down all perspectives. This type of research involves collecting information from a wide variety of sources.

4. Persuasive

Persuasive research describes an issue from two different perspectives, going through both the pros and cons of both, and then aims to prove their preference towards one side by exploring a variety of logical facts.

5. Cause & Effect

In this type of research, the cause and effects are first presented, and then a conclusion is made. Cause and effect research is for those who are new in the field of research and is mostly conducted by high school or college students.

6. Experimental Research

Experimental research involves very specific steps that must be followed, starting by conducting an experiment. It is then followed by sharing an experience and providing data about it. This research is concluded with data in a highly detailed manner.

7. Survey Research

Survey research includes conducting a survey by asking participants specific questions, and then analyzing those findings. From that, researchers can then draw a conclusion.

8. Problem-Solution Research

Both students and scholars alike carry out this type of research, and it involves solving problems by analyzing the situation and finding the perfect solution to it.

What it Takes to Become a Researcher

• Critical thinking

Research is most valuable when something new is put on the table. Critical thinking is needed to bring something unique to our knowledge and conduct research successfully.

• Analytical thinking

Analytical thinking is one of the most important research skills and requires a great deal of practice. Such a skill can assist researchers in taking apart and understanding a large amount of important information in a short amount of time.

• Explanation skills

When it comes to research skills, it’s not just about finding information, but also about how you explain it. It’s more than just writing it out, but rather, knowing how to clearly and concisely explain your new ideas.

• Patience is key

Just like with anything in life, patience will always take you far. It might be difficult to come by, but by not rushing things and investing the time needed to conduct research properly, your work is bound for success.

• Time management

Time is the most important asset that we have, and it can never be returned back to us. By learning time management skills , we can utilize our time in the best way possible and make sure to always be productive in our research.

What You Need to Sharpen Your Research Skills

Research is one of the most important tasks that students are given in college, and in many cases, it’s almost half of the academic grade that one is given.

As we’ve seen, there are plenty of things that you’ll need to sharpen your research skills — which mainly include knowing how to choose reliable and relevant sources, and knowing how to take them and make it your own. It’s important to always ask the right questions and dig deeper to make sure that you understood the full picture.

In this article

At UoPeople, our blog writers are thinkers, researchers, and experts dedicated to curating articles relevant to our mission: making higher education accessible to everyone. Read More

• StudySkills@Sheffield
• Research skills
• Research methods

How to manage your research data

When undertaking a dissertation or final project you may collect material to help you explore your research questions and which will inform your conclusions. This is your research data. Learn how to collect, store and manage this data in a secure and appropriate way.

Research Data Management  

Research data is any material used to inform or support your research conclusions. It can take many different forms including recordings, transcripts, questionnaires, photographs and code. While a taught course research project may be relatively limited in time and scope, it is important to collect, store and manage data in a secure and appropriate way.

Research Data Management for postgraduate taught course students

• How to identify your research methods
• How to plan a dissertation or final year project
• Searching for information

Use your mySkills portfolio to discover your skillset, reflect on your development, and record your progress.

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Health Research PGCert

Year of entry 2024, sign up for masters updates.

Receive the latest information on events, scholarships, important deadlines and subject information. Sign up now

Course overview

Our PGCert can be taken as a stand-alone qualification or as a stepping-stone to a Postgraduate Diploma.

Designed to fit around your personal and professional commitments, our course provides introductory research training for health professionals interested in health and healthcare research - most often undertaken within National Health Service settings.

• Receive teaching from active health researchers
• Study a range of topics such as quantitative and qualitative study design; critical appraisal of published papers; capturing and analysing data; analytic and intervention research; writing and disseminating research.
• Have access to our Health Sciences Library including computing facilities and a broad range of books and journals.

Develop and connect

You will register initially for the Postgraduate Certificate. Successful completion of the Certificate means you can apply to register for the Diploma.

All programmes are part-time. Most modules are taught in blocks which run over four consecutive days, with a gap of two or more weeks between modules. Typically, the Certificate can be gained after six months of study and the Diploma after a further year.

Course details

The Postgraduate Certificate is an introductory course in research skills and consists of four compulsory 15-credit modules.

Topics include quantitative and qualitative study design; critical appraisal of published papers; capturing and analysing data; analytic and intervention research; writing and disseminating research.

Course structure

The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.

For more information and a full list of typical modules available on this course, please read Health Research PGCert in the course catalogue

Year 1 compulsory modules

Learning and teaching

Learning about research skills in an effective and enjoyable way involves activity. On this course there is extensive use of problem-based scenarios, workbook exercises, hands-on computer sessions and group participation.

You’ll have access to electronic copies of all the teaching materials through our Virtual Learning Environment and to the library’s extensive collection of online journals.

On this course you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.

Assessments reflect teaching style and depend heavily on the assignments. They could typically involve completion of workbooks and the critical appraisal of published research.

Your results in all modules count towards the final qualification.

Entry requirements

Normally applicants should hold a degree in medicine, dentistry, nursing, a profession allied to medicine, health management, biological science or a social science at 2:2 or greater.

Non-graduates can undertake programmes leading to postgraduate awards with the University of Leeds if they have adequate and relevant professional qualifications. We welcome enquiries and applications from non-graduates with work experience in health research.

English language requirements

IELTS 6.5 overall, with no less than 6.0 in any component. For other English qualifications, read English language equivalent qualifications .

Improve your English

International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.

This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks)  and Language for Science: General Science (10 weeks) . 

We also offer online pre-sessionals alongside our on-campus pre-sessionals.  Find out more about our six week online pre-sessional .

You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses .

How to apply

Application deadlines

September intake

• 31 July 2024 (international applicants)
• 25 August 2024 (home applicants)

January intake

• 23 November 2024 (international)
• 21 December 2024 (home)

Applications are considered on the basis of the applicant’s qualifications and experience. Applications may close before the deadline date if numbers accepted reach capacity.

In your application you should demonstrate through the supporting statement how the course will be of direct benefit to your personal and professional development.

The ‘Apply’ link at the top of this page takes you to information on applying for taught programmes and to the University's online application system.

If you're unsure about the application process, contact the admissions team for help.

Read about visas, immigration and other information in International students . We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.

Admissions policy

School of Medicine Taught Postgraduate Policy 2024

This course is taught by

School of Medicine

School of Medicine Postgraduate Admissions

Email: [email protected] Telephone:

UK: £4,083 (Total)

International: £9,167 (Total)

Read more about paying fees and charges .

For fees information for international taught postgraduate students, read Masters fees .

Additional cost information

There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page .

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview .

Studying in the School of Medicine at Leeds is an amazing opportunity, but we know that the cost can be difficult for many people to meet. If you are keen to join us, a range of funding opportunities are available.

Career opportunities

Many of our successful graduates work in the UK National Health Service or in universities associated with the NHS and its research projects. Graduates of this course have gone on to research degrees, research fellowships and research posts within the NHS and the higher education sector.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more about Careers support .

Related courses

Health research pgdip (part time).