presentation on computer education

How technology is reinventing education

Stanford Graduate School of Education Dean Dan Schwartz and other education scholars weigh in on what's next for some of the technology trends taking center stage in the classroom.

Image credit: Claire Scully

New advances in technology are upending education, from the recent debut of new artificial intelligence (AI) chatbots like ChatGPT to the growing accessibility of virtual-reality tools that expand the boundaries of the classroom. For educators, at the heart of it all is the hope that every learner gets an equal chance to develop the skills they need to succeed. But that promise is not without its pitfalls.

“Technology is a game-changer for education – it offers the prospect of universal access to high-quality learning experiences, and it creates fundamentally new ways of teaching,” said Dan Schwartz, dean of Stanford Graduate School of Education (GSE), who is also a professor of educational technology at the GSE and faculty director of the Stanford Accelerator for Learning . “But there are a lot of ways we teach that aren’t great, and a big fear with AI in particular is that we just get more efficient at teaching badly. This is a moment to pay attention, to do things differently.”

For K-12 schools, this year also marks the end of the Elementary and Secondary School Emergency Relief (ESSER) funding program, which has provided pandemic recovery funds that many districts used to invest in educational software and systems. With these funds running out in September 2024, schools are trying to determine their best use of technology as they face the prospect of diminishing resources.

Here, Schwartz and other Stanford education scholars weigh in on some of the technology trends taking center stage in the classroom this year.

AI in the classroom

In 2023, the big story in technology and education was generative AI, following the introduction of ChatGPT and other chatbots that produce text seemingly written by a human in response to a question or prompt. Educators immediately worried that students would use the chatbot to cheat by trying to pass its writing off as their own. As schools move to adopt policies around students’ use of the tool, many are also beginning to explore potential opportunities – for example, to generate reading assignments or coach students during the writing process.

AI can also help automate tasks like grading and lesson planning, freeing teachers to do the human work that drew them into the profession in the first place, said Victor Lee, an associate professor at the GSE and faculty lead for the AI + Education initiative at the Stanford Accelerator for Learning. “I’m heartened to see some movement toward creating AI tools that make teachers’ lives better – not to replace them, but to give them the time to do the work that only teachers are able to do,” he said. “I hope to see more on that front.”

He also emphasized the need to teach students now to begin questioning and critiquing the development and use of AI. “AI is not going away,” said Lee, who is also director of CRAFT (Classroom-Ready Resources about AI for Teaching), which provides free resources to help teach AI literacy to high school students across subject areas. “We need to teach students how to understand and think critically about this technology.”

Immersive environments

The use of immersive technologies like augmented reality, virtual reality, and mixed reality is also expected to surge in the classroom, especially as new high-profile devices integrating these realities hit the marketplace in 2024.

The educational possibilities now go beyond putting on a headset and experiencing life in a distant location. With new technologies, students can create their own local interactive 360-degree scenarios, using just a cell phone or inexpensive camera and simple online tools.

“This is an area that’s really going to explode over the next couple of years,” said Kristen Pilner Blair, director of research for the Digital Learning initiative at the Stanford Accelerator for Learning, which runs a program exploring the use of virtual field trips to promote learning. “Students can learn about the effects of climate change, say, by virtually experiencing the impact on a particular environment. But they can also become creators, documenting and sharing immersive media that shows the effects where they live.”

Integrating AI into virtual simulations could also soon take the experience to another level, Schwartz said. “If your VR experience brings me to a redwood tree, you could have a window pop up that allows me to ask questions about the tree, and AI can deliver the answers.”

Gamification

Another trend expected to intensify this year is the gamification of learning activities, often featuring dynamic videos with interactive elements to engage and hold students’ attention.

“Gamification is a good motivator, because one key aspect is reward, which is very powerful,” said Schwartz. The downside? Rewards are specific to the activity at hand, which may not extend to learning more generally. “If I get rewarded for doing math in a space-age video game, it doesn’t mean I’m going to be motivated to do math anywhere else.”

Gamification sometimes tries to make “chocolate-covered broccoli,” Schwartz said, by adding art and rewards to make speeded response tasks involving single-answer, factual questions more fun. He hopes to see more creative play patterns that give students points for rethinking an approach or adapting their strategy, rather than only rewarding them for quickly producing a correct response.

Data-gathering and analysis

The growing use of technology in schools is producing massive amounts of data on students’ activities in the classroom and online. “We’re now able to capture moment-to-moment data, every keystroke a kid makes,” said Schwartz – data that can reveal areas of struggle and different learning opportunities, from solving a math problem to approaching a writing assignment.

But outside of research settings, he said, that type of granular data – now owned by tech companies – is more likely used to refine the design of the software than to provide teachers with actionable information.

The promise of personalized learning is being able to generate content aligned with students’ interests and skill levels, and making lessons more accessible for multilingual learners and students with disabilities. Realizing that promise requires that educators can make sense of the data that’s being collected, said Schwartz – and while advances in AI are making it easier to identify patterns and findings, the data also needs to be in a system and form educators can access and analyze for decision-making. Developing a usable infrastructure for that data, Schwartz said, is an important next step.

With the accumulation of student data comes privacy concerns: How is the data being collected? Are there regulations or guidelines around its use in decision-making? What steps are being taken to prevent unauthorized access? In 2023 K-12 schools experienced a rise in cyberattacks, underscoring the need to implement strong systems to safeguard student data.

Technology is “requiring people to check their assumptions about education,” said Schwartz, noting that AI in particular is very efficient at replicating biases and automating the way things have been done in the past, including poor models of instruction. “But it’s also opening up new possibilities for students producing material, and for being able to identify children who are not average so we can customize toward them. It’s an opportunity to think of entirely new ways of teaching – this is the path I hope to see.”

What do we know about the expansion of K-12 computer science education?

Subscribe to the center for universal education bulletin, a review of the evidence, emiliana vegas and emiliana vegas former co-director - center for universal education , former senior fellow - global economy and development @emivegasv brian fowler brian fowler former research analyst - center for universal education.

August 4, 2020

15 min read

Introduction

Over the past decade, there has been substantial progress in increasing access to schooling for children and youth, but few are mastering the foundational skills and competencies needed for their futures. Confronted with this challenge, education systems are now increasingly strengthening existing learning models while simultaneously reorienting students for a world where technology is omnipresent.

Computer science (CS) is an important element in strengthening existing education models and preparing students for the future. Building on previous work, we define CS as the study of both computer hardware and software design including theoretical algorithms, artificial intelligence, and programming ( Technopedia ). 1 CS education can also include elements of computational thinking: a problem-solving approach that involves decomposition, use of algorithms, abstraction, and automation ( Wing, 2006 ). CS is distinct from computer literacy in that it is more concerned with computer design than with computer use . For example, coding is a skill one would learn in a CS course, while creating a document or slideshow presentation using an existing program is a skill one would learn in a computer literacy course.

Multiple studies indicate that CS education can help students beyond computing. CS education has been linked with higher rates of college enrollment and improved problem-solving abilities ( Brown & Brown, 2020 ; Salehi et al., 2020 ). A recent randomized control trial also showed that lessons in computational thinking improved student response inhibition, planning, and coding skills ( Arfé et al., 2020 ). As these skills take preeminence in the rapidly changing 21st century, CS education promises to significantly enhance student preparedness for the future of work and active citizenship.

CS education is expanding around the globe as more education systems recognize its importance. Yet, most countries have been slow to adopt it. We searched for online evidence of in-school CS education, and found that out of 219 countries: 44 (around 20 percent) mandate that schools offer it as an elective or required course; 15 (around 7 percent) offer CS in select schools and some subnational jurisdictions (states, provinces, etc.); and 160 (73 percent) are only piloting CS education programs or had no available evidence of in-school CS education (Figure 1). Few countries have offered CS education long enough to properly evaluate the effectiveness of their CS instruction and activities.

Figure 1 computer science education around the world

Though necessary for 21st century skills, providing quality CS education to the world’s students is no small feat. Many countries are still trying to ensure that all students learn basic literacy and numeracy. In the latest Trends in International Mathematics and Science Study (TIMMS) and Progress in International Reading Literacy Study (PIRLS) assessments, only 14 percent of students in low-income countries had achieved proficient levels in math, and less than 5 percent in reading ( World Bank, 2018 ). Under such prevailing environments, offering quality CS education to students around the world remains a challenge.

School systems face challenges in their endeavor to offer CS education to all students. First, some countries do not have sufficient numbers of teachers who are qualified to teach CS. Second, even though there is a growing interest among students, few of them pursue CS testing certifications ( U.K. government ) or consider CS as an undergraduate major compared to other STEM (science, technology, engineering, and mathematics) fields like engineering or biology ( Code.org, 2019 ). This is especially true for girls and underrepresented minorities, who generally have fewer opportunities to develop interest in CS and STEM more broadly ( Code.org & CSTA, 2018 ).

In response to these implementation challenges, some education systems have:

Introduced teacher qualification and preparation programs;
Made efforts to increase student interest and engagement in CS; and
Invested in research and development of new methods of instruction for CS education.

Though these efforts address core challenges in expanding CS education, there is a dearth of credible studies that rigorously evaluate CS education effectiveness. As part of a larger ongoing research project led by the Center for Universal Education at Brookings on global advances in CS education, this policy brief reviews various efforts around the world to improve and scale CS education.

Teacher qualification and preparation

A well-prepared and knowledgeable teacher is the most important school-side factor in student learning ( Chetty et al. 2005 ; Chetty, 2014 ; Rivkin et al., 2005 ). This is also true for CS education. Yet, several recent studies indicate that education systems have shortages of qualified CS teachers. For example, in a survey of pre-service elementary school teachers in the United States, only 10 percent responded that they understood the concept of computational thinking ( Campbell & Heller, 2019 ). Another study found that 75 percent of teachers in the U.S. incorrectly considered “creating documents or presentations on the computer” as a topic one would learn in a CS course ( Google/Gallup, 2015 ), demonstrating a poor understanding of the distinction between CS and computer literacy. Other case studies, surveys, and interviews have found that teachers in India, Saudi Arabia, the U.K., and Turkey self-report low confidence in their understanding of CS ( Ramen et al., 2015 ; Alfayez & Lambert, 2019 ; Royal Society, 2017 , Gülbahar & Kalelioğlu 2017 ). Indeed, in many of the world’s education systems, teacher training remains a challenge to develop the necessary skills and confidence levels for effective CS teaching and learning.

To address these challenges, school systems have introduced continuous professional development (PD), certification programs, and CS credentials issued by teaching degree programs for pre-service teachers.

Professional development and formal networks

Given a lack of knowledgeable CS teachers, several education systems have engaged teachers in PD. They range from one-week summer computing workshops focusing on block-based programming languages to multiday seminars meant to familiarize teachers with CS and train them to help students learn programming skills ( Liu et al., 2011 ). Teacher-led professional development groups have shown potential to foster collaborative learning among CS teachers ( Cutts et al., 2017 ; Alkaria & Alhassan, 2017 ; Goode et al., 2014 ). Still, more rigorous evaluation is needed to understand their effectiveness.

Teacher certification

Certification schemes serve the dual purpose of testing CS teachers’ subject matter expertise and signaling their unique qualifications to prospective employers. This in turn incentivizes teachers to pursue training, to set forth a cycle of developing better CS education teachers.

Advocates of CS education have recommended that education systems initiate certification schemes quickly and improve them over time ( Code.org, 2017 ; CSTA, 2013 ). Short-term recommendations involve temporary licenses to teachers who meet minimum content and knowledge requirements. Longer-term recommendations encourage pre-service teachers to take CS courses as part of their teaching degree programs, 2 to earn a CS endorsement or certificate.

Demand for CS education

Due to a high demand for their skills, CS professionals enjoy stable, high-income careers. According to the Bureau of Labor Statistics , the median annual salary for CS occupations was $88,240 in 2019, about $48,000 greater than the median wage for all occupations in the U.S. The Bureau has also projected that the market for CS professionals will continue to grow at twice the speed of the rest of the labor market between 2014 and 2024 ( National Academies of Sciences, 2018). Despite these benefits, the tech industry has not been able to attract diverse talent into its ranks.

To meet the demand for CS professionals, state and philanthropic organizations have implemented programs that introduce students to CS. By increasing awareness and interest among K-12 students regarding CS professions, the well-documented lack of diversity in the tech industry could be addressed ( Harrison, 2019 ; Ioannou, 2018 ).

Student and parental interest in CS education

Despite a clear economic incentive to study CS, relatively few K-12 students express interest in CS education. One reason may be that learning CS comes with a fair amount of social stigma for students. This stigma could be attributed to the commonly held belief that CS is a male-oriented field that involves social isolation and a focus on machinery rather than people ( Cheryan et al. 2015) .

Parents see CS education favorably, but also hold misconceptions around who can learn it. More than 80 percent of U.S. parents surveyed in a 2016 Google/Gallup stud y reported that they think CS is as important as any other discipline. Nevertheless, the same parents indicated that they hold biases around who should take CS courses: 57 percent of U.S. parents surveyed expressed that one needs to be “very smart” to learn CS ( Google, 201 5). It is a common misbelief that some people are inherently talented for CS, otherwise known as the “geek gene,” while others are inherently inept at CS ( McCartney, 2017 ). This belief discourages some students from developing an interest in CS. On the contrary, statistical evidence indicates that students learn CS through studying and practicing core concepts and, thus, the “geek gene” is more likely myth than reality ( Patitsas et al. 2019 ).

CS education for girls and underrepresented minorities (URMs)

Girls and racial minorities have been historically underrepresented in CS education ( Sax et al., 2016 ). This lack of diversity has become a barrier to entry for other prospective students who might have pursued career paths and highly paid jobs in the field of CS and technology. Research indicates that the diversity gap in CS professions and education is not due to innate talent differences among demographic groups ( Sullivan & Bers, 2012 ; Cussó-Calabuig et al., 2017 ), but rather a disparity of access to CS content ( Google/Gallup (2016); Code.org & CSTA, 2018 ; Du & Wimmer, 2019 ), widely held cultural perceptions, and poor representation of women and URMs in media depictions ( Google, 2015 ; Ayebi-Arthur, 2011 ; Downes & Looker, 2011 ; Du & Wimmer, 2019 ).

Interventions for improving student interest

Education systems and advocacy groups have used short, one-time lessons in coding to reduce student anxiety around CS. Hour of Code, designed by Code.org, is perhaps the best known of these programs. In multiple surveys, students indicated better confidence after exposure to this program ( Phillips & Brooks, 2017 ; Doukaki et al., 2013 ; Lang et al., 2016 ). It is not clear, however, whether these programs make students more likely to consider semester-long CS courses ( Phillips & Brooks, 2017 ; Lang et al., 2016 ).

Time-intensive programs aimed at improving students’ interest in CS have been attempted as well. The U.S. state of Georgia, for example, implemented a program involving after-school, weekend, and summer workshops over a six-year period. During the duration of the program, Georgia saw an increase in participation in the Advanced Placement (AP) CS exam, especially among girls and URMs ( Guzdial et al., 2014) . Some states have introduced similar programs, setting up summer camps and weekend workshops in universities to help high school students become familiar with CS ( Best College Reviews ).

These initiatives, whether one-off introductions to CS or time-intensive programs, typically share the explicit goal of encouraging participation in CS education among all students, and especially girls and URMs. While studies indicate that Hour of Code and summer camps might improve student enthusiasm for CS, they do not provide the kind of rigorous impact assessment one would need to make a definitive conclusion of their effectiveness. For instance, in the case of Georgia, it cannot be confirmed if the after-school clubs can be directly credited for the increase in girls and URMs taking CS.

Instructional methods, core competencies, and research

Though great strides have been made to create engaging learning environments, as in other areas discussed here, there is a dearth of research that credibly evaluates the effectiveness of different curricula and instructional methods for developing CS skills ( Saeli et al., 2011 ; Hubwieser et al., 2013 ). Indeed, our review of the evidence suggests that expanding CS education globally will require a consensus on assessment strategies of students’ understanding of core CS competencies and quality evidence on effective curricula and instructional methods.

Curricula and core competencies

There is no one-size-fits all CS curriculum for all education systems, schools, or classrooms. Regional contexts, school infrastructure, prior access, and exposure to CS need to be considered when developing CS curricula and competencies. Some CS skills, such as programming languages, require access to computer infrastructure that may be absent in some contexts ( Lockwood & Cornell, 2013 ). According to participants at the International Olympiad In Informatics Workshop on Creating an International Informatics Curriculum for Primary and High School Education, specific circumstances should be considered when developing curricula ( Ackovska, 2015 ).

Rather than prescribing a curriculum, the K–12 Computer Science Framework recommends foundational computer science concepts and competencies for education systems to consider. This framework encourages curriculum developers and educators to create learning experiences that extend beyond the framework to encompass student interests and abilities.

Core competencies that students may learn by the end of primary school include: (1) abstraction (creating a model to solve a problem); (2) generalization (remixing and reusing resources that were previously created); (3) decomposition (breaking a complex task into simpler subtasks); (4) algorithmic thinking (defining a series of steps for a solution, putting instructions in the correct sequence, and formulating mathematical and logical expressions); and (5) debugging (recognizing when instructions do not correspond to actions and then removing or fixing errors) ( Angeli, 2016 ).

Competencies that older students may learn in CS courses, as practiced in Poland, include: (1) logical and abstract thinking; (2) representations of data; (3) problem-solving by designing and programming algorithms using digital devices; (4) performing calculations and executing programs; (5) collaboration; and (6) ethics such as privacy and data security ( Syslo & Kwiatkowska, 2015 ).

Commonly used instructional methods

A number of studies have described various methods for teaching CS core competencies. Integrated development environments are recommended especially for teaching coding skills (Florez et al., 2017 ; Saez-Lopez et al., 2016 ). 3 These environments teach block-based programming languages that encourage novice programmers to engage with programming, in part by alleviating the burden of syntax on learners ( Weintrop & Wilensky, 2017; Repenning, 1993 ). Others recommended a variety of teaching methods that blend computerized lessons with offline activities ( Taub et al. 2009 ; Curzon et al, 2009 , Ackovska, 2015 ). This approach is meant to teach core concepts of computational thinking while keeping students engaged in physical, as well as digital, environments ( Nishida et al., 2009). CS Unplugged, for example, provides kinesthetic lesson plans that include games and puzzles that teach core CS concepts like decomposition and algorithmic thinking.

Various studies have also attempted to measure traditional lecture-based instruction for CS ( Alhassan 2017 ; Cicek & Taspinar, 2016 ). 4 These studies, however, rely on small sample sizes wherein the experiment and control group each comprised individual classes. More rigorous research is required to understand the effectiveness of teaching strategies for CS.

Lack of consensus on assessment

Even though various methods—standardized tests, digital environments, classical cognitive tests, and CS Unplugged activity tests—are used to assess student competency in core CS concepts, there is no consensus around the best method for doing so ( So et al., 2019 ; Djambong & Freiman, 2016 ). Though these methods are widely available, there is still a lack of comparable assessments that researchers can use to evaluate various curricula or instructional methods in CS. Without assessment data, it is not feasible to assess curriculum or teaching strategies across classes or schools ( Webb et al., 2016 ; Tew, 2010 ). The lack of resulting evidence, in turn, makes it difficult for education systems to improve their CS programs.

The good news is that a growing number of organizations are developing standardized tests in CS and computational thinking. The International Computer and Information Literacy Study included examinations in computational thinking in 2018 that had two 25-minute modules, where students were asked to develop a sequence of tasks in a program that related to a unified theme ( Fraillon et al., 2018 ). The OECD’s PISA will include questions in 2021 to assess computational thinking. The AP CS exam has also yielded useful comparisons that have been used to evaluate teacher training programs ( Brown, 2018 ).

Education systems around the world are increasingly addressing the need to integrate CS into their standard curricula. Yet, many challenges have emerged. There are shortages of qualified teachers in many education systems who understand CS concepts and instructional methods. Despite the high demand for CS professionals, relatively few students show interest in CS compared to other STEM subjects. Development of core competencies, curricula, and assessments that are all tailored to the contexts of different educational systems remains a work in progress.

Governments and nonprofit organizations have been addressing these challenges in different ways. Teachers can engage in training and certification schemes while students can participate in short coding classes, after-school clubs, and summer camps. Education practitioners have innovated the design of instructional methods for CS education, ranging from block-based programming activities to kinesthetic lessons.

These activities and programs are often well run and may plausibly address the challenges they are designed to solve. Still, the Royal Society (2017) recommends more robust research for CS education for the following priorities: pedagogy, learning models and instructional techniques, classroom structure and physical resources, programming languages, student engagement, and assessment techniques. The resulting research would have the potential to help education systems initiate, scale, and improve their CS education.

The authors gratefully acknowledge Pat Yongpradit, Mark Guzdial, and Benson Neethipudi for their comments on earlier drafts of this policy brief.

The Brookings Institution is a nonprofit organization devoted to independent research and policy solutions. Its mission is to conduct high-quality, independent research and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the Institution, its management, or its other scholars.

Brookings gratefully acknowledges the support provided by Amazon, Atlassian Foundation International, Google, and Microsoft.

Brookings recognizes that the value it provides is in its commitment to quality, independence, and impact. Activities supported by its donors reflect this commitment.

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Information and communication technology (ICT) in education

Information and communications technology (ict) can impact student learning when teachers are digitally literate and understand how to integrate it into curriculum..

Schools use a diverse set of ICT tools to communicate, create, disseminate, store, and manage information.(6) In some contexts, ICT has also become integral to the teaching-learning interaction, through such approaches as replacing chalkboards with interactive digital whiteboards, using students’ own smartphones or other devices for learning during class time, and the “flipped classroom” model where students watch lectures at home on the computer and use classroom time for more interactive exercises.

When teachers are digitally literate and trained to use ICT, these approaches can lead to higher order thinking skills, provide creative and individualized options for students to express their understandings, and leave students better prepared to deal with ongoing technological change in society and the workplace.(18)

ICT issues planners must consider include: considering the total cost-benefit equation, supplying and maintaining the requisite infrastructure, and ensuring investments are matched with teacher support and other policies aimed at effective ICT use.(16)

Issues and Discussion

Digital culture and digital literacy: Computer technologies and other aspects of digital culture have changed the ways people live, work, play, and learn, impacting the construction and distribution of knowledge and power around the world.(14) Graduates who are less familiar with digital culture are increasingly at a disadvantage in the national and global economy. Digital literacy—the skills of searching for, discerning, and producing information, as well as the critical use of new media for full participation in society—has thus become an important consideration for curriculum frameworks.(8)

In many countries, digital literacy is being built through the incorporation of information and communication technology (ICT) into schools. Some common educational applications of ICT include:

One laptop per child: Less expensive laptops have been designed for use in school on a 1:1 basis with features like lower power consumption, a low cost operating system, and special re-programming and mesh network functions.(42) Despite efforts to reduce costs, however, providing one laptop per child may be too costly for some developing countries.(41)
Tablets: Tablets are small personal computers with a touch screen, allowing input without a keyboard or mouse. Inexpensive learning software (“apps”) can be downloaded onto tablets, making them a versatile tool for learning.(7)(25) The most effective apps develop higher order thinking skills and provide creative and individualized options for students to express their understandings.(18)
Interactive White Boards or Smart Boards : Interactive white boards allow projected computer images to be displayed, manipulated, dragged, clicked, or copied.(3) Simultaneously, handwritten notes can be taken on the board and saved for later use. Interactive white boards are associated with whole-class instruction rather than student-centred activities.(38) Student engagement is generally higher when ICT is available for student use throughout the classroom.(4)
E-readers : E-readers are electronic devices that can hold hundreds of books in digital form, and they are increasingly utilized in the delivery of reading material.(19) Students—both skilled readers and reluctant readers—have had positive responses to the use of e-readers for independent reading.(22) Features of e-readers that can contribute to positive use include their portability and long battery life, response to text, and the ability to define unknown words.(22) Additionally, many classic book titles are available for free in e-book form.
Flipped Classrooms: The flipped classroom model, involving lecture and practice at home via computer-guided instruction and interactive learning activities in class, can allow for an expanded curriculum. There is little investigation on the student learning outcomes of flipped classrooms.(5) Student perceptions about flipped classrooms are mixed, but generally positive, as they prefer the cooperative learning activities in class over lecture.(5)(35)

ICT and Teacher Professional Development: Teachers need specific professional development opportunities in order to increase their ability to use ICT for formative learning assessments, individualized instruction, accessing online resources, and for fostering student interaction and collaboration.(15) Such training in ICT should positively impact teachers’ general attitudes towards ICT in the classroom, but it should also provide specific guidance on ICT teaching and learning within each discipline. Without this support, teachers tend to use ICT for skill-based applications, limiting student academic thinking.(32) To support teachers as they change their teaching, it is also essential for education managers, supervisors, teacher educators, and decision makers to be trained in ICT use.(11)

Ensuring benefits of ICT investments: To ensure the investments made in ICT benefit students, additional conditions must be met. School policies need to provide schools with the minimum acceptable infrastructure for ICT, including stable and affordable internet connectivity and security measures such as filters and site blockers. Teacher policies need to target basic ICT literacy skills, ICT use in pedagogical settings, and discipline-specific uses. (21) Successful implementation of ICT requires integration of ICT in the curriculum. Finally, digital content needs to be developed in local languages and reflect local culture. (40) Ongoing technical, human, and organizational supports on all of these issues are needed to ensure access and effective use of ICT. (21)

Resource Constrained Contexts: The total cost of ICT ownership is considerable: training of teachers and administrators, connectivity, technical support, and software, amongst others. (42) When bringing ICT into classrooms, policies should use an incremental pathway, establishing infrastructure and bringing in sustainable and easily upgradable ICT. (16) Schools in some countries have begun allowing students to bring their own mobile technology (such as laptop, tablet, or smartphone) into class rather than providing such tools to all students—an approach called Bring Your Own Device. (1)(27)(34) However, not all families can afford devices or service plans for their children. (30) Schools must ensure all students have equitable access to ICT devices for learning.

Inclusiveness Considerations

Digital Divide: The digital divide refers to disparities of digital media and internet access both within and across countries, as well as the gap between people with and without the digital literacy and skills to utilize media and internet.(23)(26)(31) The digital divide both creates and reinforces socio-economic inequalities of the world’s poorest people. Policies need to intentionally bridge this divide to bring media, internet, and digital literacy to all students, not just those who are easiest to reach.

Minority language groups: Students whose mother tongue is different from the official language of instruction are less likely to have computers and internet connections at home than students from the majority. There is also less material available to them online in their own language, putting them at a disadvantage in comparison to their majority peers who gather information, prepare talks and papers, and communicate more using ICT. (39) Yet ICT tools can also help improve the skills of minority language students—especially in learning the official language of instruction—through features such as automatic speech recognition, the availability of authentic audio-visual materials, and chat functions. (2)(17)

Students with different styles of learning: ICT can provide diverse options for taking in and processing information, making sense of ideas, and expressing learning. Over 87% of students learn best through visual and tactile modalities, and ICT can help these students ‘experience’ the information instead of just reading and hearing it. (20)(37) Mobile devices can also offer programmes (“apps”) that provide extra support to students with special needs, with features such as simplified screens and instructions, consistent placement of menus and control features, graphics combined with text, audio feedback, ability to set pace and level of difficulty, appropriate and unambiguous feedback, and easy error correction. (24)(29)

Plans and policies

India [ PDF ]
Detroit, USA [ PDF ]
Finland [ PDF ]
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Computers in Education

Apr 07, 2019

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Computers in Education. Week 8. What is the Perfect Classroom?. Clean white wall in front of the room Show video clips Project an computer screen image Write with special pens Touch sensitive Printing abilities Networked to each Student’s PDA. Young Children. Education needs to be

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Computers in Education Week 8

What is the Perfect Classroom? • Clean white wall in front of the room • Show video clips • Project an computer screen image • Write with special pens • Touch sensitive • Printing abilities • Networked to each Student’s PDA

Young Children • Education needs to be • visually stimulating • actively involved • Education starts at a very early age - 1 year • Programs to teach colors, ABC, even foreign languages stressing participatory learning

Young Children • Learn at their own pace • Turn abstract into concrete • money and stocks • Slightly older children benefit from edutainment • Benefit - learning is FUN

Literacy Requirements for Education • SOL of public education has a literacy requirement for technology that is different for each grade level • Is there a computer literacy requirement at ODU?

High School and Beyond • Intelligent tutoring programs • adapts based upon student responses • Computer based tutorial • Computer Simulation • Simulation games

High School and College • Research • Web searching • Distance Learning • Two way - IRI at ODU • Teletechnet • Virtual University

Administrative Uses • Instructors • testing • maintain grades • develop lesson plans • create homework assignments • research

Administrative Uses • Schools • maintain student records • assign students to classes and rooms • pay employees

Administrative Uses • Research studies • track students to determine graduation rates, job offers • Student performance and attitudes to improve the education process • Provide information for accountability reporting

Administrative Uses • Marketing • Web sites • CD-ROM tours • Virtual reality

Additional Uses by Students • Application software • Storage of information • Instrument of research • E-mail • On-line applications • Homework help • Plagiarism???

Uses by Parents • Monitor students courses, professors, activities, etc. • Email • Research tool to pick a university

Education Outside of the Classroom • Educational tools disguised as games • SimCity • Oceans Below • Reference material presented in video • pictorial atlas • body works

Advantages of Computers in Education • Accelerated learning due to tools and improved interest • High quality documents • Research facilitated • Improved monitoring of students • Remote education

Disadvantages • Inability of schools to keep pace with technology • Instructor/student involvement diminished • Haves and Have nots • Maintenance of machines • Promotes laziness

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Insights on the Distribution of Nonverbal and Verbal Oral Presentation Skills in an Educational Institution

Original Research
Published: 25 April 2024
Volume 5 , article number 491 , ( 2024 )

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Federico Domínguez ORCID: orcid.org/0000-0002-3655-2179 1 , 2 ,
Leonardo Eras 1 &
Adriana Collaguazo 2

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Developing effective oral presentation skills is crucial for new graduates in today’s competitive job market. Consequently, procuring the effective development of these skills in students is an essential task for higher education institutions (HEIs). We developed a technological solution that facilitates basic oral presentation skills learning by providing automatic and immediate feedback using machine learning algorithms on audiovisual recordings of oral presentations. We have been using this tool since 2017 to measure and aid learning of verbal, nonverbal, and visual oral presentation skills at our university and, by using the resulting data corpus, developed a methodology to accurately detect and evaluate two key nonverbal features of an oral presentation: posture and gaze. This article presents this methodology and shares the insights gleaned by comparing it with verbal features (filled pauses and voice volume) from more than 2000 different students across all study programs at our university. Preliminary results provide a glimpse of the prevalence and distribution of verbal and nonverbal oral presentation skills across several demographic variables. Statistically significant patterns point to possible differences between genders in verbal communication skills and nonverbal oral communication deficiencies in engineering programs at our HEI, highlighting the potential of our methodology to serve as a diagnostic tool for communication skills learning strategies.

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Unedited, unprocessed recordings of oral presentations can not be disseminated or published in accordance with Ecuador’s Personal Data Protection Law. Anonymized, processed data (postures, number of filled pauses, etc.) may be shared upon request and after internal review.

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Peeters MJ, Sahloff EG, Stone GE. A standardized rubric to evaluate student presentations. Am J Pharm Educ. 2010;74(9):1–8. https://doi.org/10.5688/aj7409171 .

Audhkhasi K, Kandhway K, Deshmukh OD, Verma A. Formant-based technique for automatic filled-pause detection in spontaneous spoken english. In: 2009 IEEE international conference on acoustics, speech and signal processing. IEEE; 2009. pp. 4857–4860.

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Acknowledgements

We would like to thank Fernando Campaña, Karen Bermúdez, Kelly Castro, Karina Ortega, Ricardo Salazar, and Juan Francisco Quimi for their invaluable help during the execution of this project.

This study received no funding.

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Information Technology Center, Escuela Superior Politécnica Del Litoral, ESPOL, Guayaquil, Ecuador

Federico Domínguez & Leonardo Eras

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FD contributed with overall direction of the study, posture detection and classification methodology, and data analysis. LE contributed with technological infrastructure development and gaze detection and classification methodology. AC contributed with data analysis and discussion of insights.

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Correspondence to Federico Domínguez .

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On behalf of all authors, the corresponding author states that there is no Conflict of interest.

Research involving humans or animals

This research study was conducted retrospectively using data acquired prior to the enactment of Ecuador’s Personal Data Protection Law in 2021. Consequently, after consulting with ESPOL University’s ethical committee, it was determined that no ethical approval was required. This research did not involve any animals.

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Informed consent was obtained from all individual participants included in the study.

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This article is part of the topical collection “Recent Trends on Computer Supported Education” guest edited by James Uhomoibhi, Bruce M. McLaren, Jelena Jovanovic and Irene-Angelica Chounta.

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Domínguez, F., Eras, L. & Collaguazo, A. Insights on the Distribution of Nonverbal and Verbal Oral Presentation Skills in an Educational Institution. SN COMPUT. SCI. 5 , 491 (2024). https://doi.org/10.1007/s42979-024-02785-6

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What the New Overtime Rule Means for Workers

Collage shows four professionals in business casual clothing.

One of the basic principles of the American workplace is that a hard day’s work deserves a fair day’s pay. Simply put, every worker’s time has value. A cornerstone of that promise is the Fair Labor Standards Act ’s (FLSA) requirement that when most workers work more than 40 hours in a week, they get paid more. The Department of Labor ’s new overtime regulation is restoring and extending this promise for millions more lower-paid salaried workers in the U.S.

Overtime protections have been a critical part of the FLSA since 1938 and were established to protect workers from exploitation and to benefit workers, their families and our communities. Strong overtime protections help build America’s middle class and ensure that workers are not overworked and underpaid.

Some workers are specifically exempt from the FLSA’s minimum wage and overtime protections, including bona fide executive, administrative or professional employees. This exemption, typically referred to as the “EAP” exemption, applies when:

1. An employee is paid a salary,

2. The salary is not less than a minimum salary threshold amount, and

3. The employee primarily performs executive, administrative or professional duties.

While the department increased the minimum salary required for the EAP exemption from overtime pay every 5 to 9 years between 1938 and 1975, long periods between increases to the salary requirement after 1975 have caused an erosion of the real value of the salary threshold, lessening its effectiveness in helping to identify exempt EAP employees.

The department’s new overtime rule was developed based on almost 30 listening sessions across the country and the final rule was issued after reviewing over 33,000 written comments. We heard from a wide variety of members of the public who shared valuable insights to help us develop this Administration’s overtime rule, including from workers who told us: “I would love the opportunity to...be compensated for time worked beyond 40 hours, or alternately be given a raise,” and “I make around $40,000 a year and most week[s] work well over 40 hours (likely in the 45-50 range). This rule change would benefit me greatly and ensure that my time is paid for!” and “Please, I would love to be paid for the extra hours I work!”

The department’s final rule, which will go into effect on July 1, 2024, will increase the standard salary level that helps define and delimit which salaried workers are entitled to overtime pay protections under the FLSA.

Starting July 1, most salaried workers who earn less than $844 per week will become eligible for overtime pay under the final rule. And on Jan. 1, 2025, most salaried workers who make less than $1,128 per week will become eligible for overtime pay. As these changes occur, job duties will continue to determine overtime exemption status for most salaried employees.

Who will become eligible for overtime pay under the final rule? Currently most salaried workers earning less than $684/week. Starting July 1, 2024, most salaried workers earning less than $844/week. Starting Jan. 1, 2025, most salaried workers earning less than $1,128/week. Starting July 1, 2027, the eligibility thresholds will be updated every three years, based on current wage data. DOL.gov/OT

The rule will also increase the total annual compensation requirement for highly compensated employees (who are not entitled to overtime pay under the FLSA if certain requirements are met) from $107,432 per year to $132,964 per year on July 1, 2024, and then set it equal to $151,164 per year on Jan. 1, 2025.

Starting July 1, 2027, these earnings thresholds will be updated every three years so they keep pace with changes in worker salaries, ensuring that employers can adapt more easily because they’ll know when salary updates will happen and how they’ll be calculated.

The final rule will restore and extend the right to overtime pay to many salaried workers, including workers who historically were entitled to overtime pay under the FLSA because of their lower pay or the type of work they performed.

We urge workers and employers to visit our website to learn more about the final rule.

Jessica Looman is the administrator for the U.S. Department of Labor’s Wage and Hour Division. Follow the Wage and Hour Division on Twitter at  @WHD_DOL and LinkedIn . Editor's note: This blog was edited to correct a typo (changing "administrator" to "administrative.")

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Create and add an email signature in Outlook

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On the View tab, select View Settings .

Select Accounts > Signatures .

Select New signature , then give it a distinct name.

In the editing box below the new name, type your signature, then format it with the font, color, and styles to get the appearance you want.

Select Save when you're done.

With your new signature selected from the list above the editing box, go to Select default signatures and choose whether to apply the signature to new messages and to replies and forwards.

Select Save again.

Note: If you have a Microsoft account, and you use Outlook and Outlook on the web or Outlook on the web for business, you need to create a signature in both products.

Create your signature and choose when Outlook adds a signature to your messages

If you want to watch how it's done, you can go directly to the video below .

Open a new email message.

Under Select signature to edit , choose New , and in the New Signature dialog box, type a name for the signature.

Under Edit signature , compose your signature. You can change fonts, font colors, and sizes, as well as text alignment. If you want to create a more robust signature with bullets, tables, or borders, use Word to create and format your signature text, then copy and paste it into the Edit signature box. You can also use a pre-designed template to create your signature. Download the templates in Word, customize with your personal information, and then copy and paste into the Edit signature box.

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You can also add social media icons and links in your signature or customize one of our pre-designed temlates. For more information, see Create a signature from a template .

To add images to your signature, see Add a logo or image to your signature .

Under Choose default signature , set the following options.

In the E-mail account drop-down box, choose an email account to associate with the signature. You can have different signatures for each email account.

You can have a signature automatically added to all new messages. Go to in the New messages drop-down box and select one of your signatures. If you don't want to automatically add a signature to new messages, choose (none). This option does not add a signature to any messages you reply to or forward.

You can select to have your signature automatically appear in reply and forward messages. In the Replies/forwards drop-down, select one of your signatures. Otherwise, accept the default option of (none).

Choose OK to save your new signature and return to your message. Outlook doesn't add your new signature to the message you opened in Step 1, even if you chose to apply the signature to all new messages. You'll have to add the signature manually to this one message. All future messages will have the signature added automatically. To add the signature manually, select Signature from the Message menu and then pick the signature you just created.

Add a logo or image to your signature

If you have a company logo or an image to add to your signature, use the following steps.

Open a new message and then select Signature > Signatures .

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When you're done, select OK , then select OK again to save the changes to your signature.

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If you don't choose to insert a signature for all new messages or replies and forwards, you can still insert a signature manually.

In your email message, on the Message tab, select Signature .

Choose your signature from the fly-out menu that appears. If you have more than one signature, you can select any of the signatures you've created.

See how it's done

Your browser does not support video. Install Microsoft Silverlight, Adobe Flash Player, or Internet Explorer 9.

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Note: Outlook on the web is the web version of Outlook for business users with a work or school account.

Automatically add a signature to a message

You can create an email signature that you can add automatically to all outgoing messages or add manually to specific ones.

Select Settings at the top of the page.

Select Mail > Compose and reply .

Under Email signature , type your signature and use the available formatting options to change its appearance.

Select the default signature for new messages and replies.

Manually add your signature to a new message

If you've created a signature but didn't choose to automatically add it to all outgoing messages, you can add it later when you write an email message.

In a new message or reply, type your message.

If you created multiple signatures, choose the signature you want to use for your new message or reply.

When your email message is ready, choose Send .

Note: Outlook.com is the web version of Outlook for users signing in with a personal Microsoft account such as an Outlook.com or Hotmail.com account.

Create and add an email signature in Outlook for Mac

Create an email signature from a template

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