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What 126 studies say about education technology

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In recent years, there has been widespread excitement around the transformative potential of technology in education. In the United States alone, spending on education technology has now exceeded $13 billion . Programs and policies to promote the use of education technology may expand access to quality education, support students’ learning in innovative ways, and help families navigate complex school systems.

However, the rapid development of education technology in the United States is occurring in a context of deep and persistent inequality . Depending on how programs are designed, how they are used, and who can access them, education technologies could alleviate or aggravate existing disparities. To harness education technology’s full potential, education decision-makers, product developers, and funders need to understand the ways in which technology can help — or in some cases hurt — student learning.

To address this need, J-PAL North America recently released a new publication summarizing 126 rigorous evaluations of different uses of education technology. Drawing primarily from research in developed countries, the publication looks at randomized evaluations and regression discontinuity designs across four broad categories: (1) access to technology, (2) computer-assisted learning or educational software, (3) technology-enabled nudges in education, and (4) online learning.

This growing body of evidence suggests some areas of promise and points to four key lessons on education technology.

First, supplying computers and internet alone generally do not improve students’ academic outcomes from kindergarten to 12th grade, but do increase computer usage and improve computer proficiency. Disparities in access to information and communication technologies can exacerbate existing educational inequalities. Students without access at school or at home may struggle to complete web-based assignments and may have a hard time developing digital literacy skills.

Broadly, programs to expand access to technology have been effective at increasing use of computers and improving computer skills. However, computer distribution and internet subsidy programs generally did not improve grades and test scores and in some cases led to adverse impacts on academic achievement. The limited rigorous evidence suggests that distributing computers may have a more direct impact on learning outcomes at the postsecondary level.

Second, educational software (often called “computer-assisted learning”) programs designed to help students develop particular skills have shown enormous promise in improving learning outcomes, particularly in math. Targeting instruction to meet students’ learning levels has been found to be effective in improving student learning, but large class sizes with a wide range of learning levels can make it hard for teachers to personalize instruction. Software has the potential to overcome traditional classroom constraints by customizing activities for each student. Educational software programs range from light-touch homework support tools to more intensive interventions that re-orient the classroom around the use of software.

Most educational software that have been rigorously evaluated help students practice particular skills through personalized tutoring approaches. Computer-assisted learning programs have shown enormous promise in improving academic achievement, especially in math. Of all 30 studies of computer-assisted learning programs, 20 reported statistically significant positive effects, 15 of which were focused on improving math outcomes.

Third, technology-based nudges — such as text message reminders — can have meaningful, if modest, impacts on a variety of education-related outcomes, often at extremely low costs. Low-cost interventions like text message reminders can successfully support students and families at each stage of schooling. Text messages with reminders, tips, goal-setting tools, and encouragement can increase parental engagement in learning activities, such as reading with their elementary-aged children.

Middle and high schools, meanwhile, can help parents support their children by providing families with information about how well their children are doing in school. Colleges can increase application and enrollment rates by leveraging technology to suggest specific action items, streamline financial aid procedures, and/or provide personalized support to high school students.

Online courses are developing a growing presence in education, but the limited experimental evidence suggests that online-only courses lower student academic achievement compared to in-person courses. In four of six studies that directly compared the impact of taking a course online versus in-person only, student performance was lower in the online courses. However, students performed similarly in courses with both in-person and online components compared to traditional face-to-face classes.

The new publication is meant to be a resource for decision-makers interested in learning which uses of education technology go beyond the hype to truly help students learn. At the same time, the publication outlines key open questions about the impacts of education technology, including questions relating to the long-term impacts of education technology and the impacts of education technology on different types of learners.

To help answer these questions, J-PAL North America’s Education, Technology, and Opportunity Initiative is working to build the evidence base on promising uses of education technology by partnering directly with education leaders.

Education leaders are invited to submit letters of interest to partner with J-PAL North America through its  Innovation Competition . Anyone interested in learning more about how to apply is encouraged to contact initiative manager Vincent Quan .

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Digital homework tools should be more than just the textbook as an app

Academic and Lecturer , CQUniversity Australia

Senior Lecturer in Educational Technology, CQUniversity Australia

Assistant researcher, CQUniversity Australia

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Schools are increasingly incorporating digital technologies into their teaching practice, raising questions about whether these technologies actually enhance the learning process.

We’re particularly interested the role of technology in homework. Is homework – particularly in digitally aligned STEM areas such as mathematics – any different on a digital device? And, if not, should it be?

We have found that the range of educational websites and apps currently available fail to capitalise on the unique opportunities of digital technology. Working together, technologists and educators could design tools for digital homework that are interactive, instructive, and allow teachers to monitor their students’ progress – leading to better learning outcomes for all.

Read more: Technology in the classroom can improve primary mathematics

The (negligible) value of homework

Despite the prevalence of homework in many schools, the research community is still unsure whether homework actually provides a benefit for students . Recent research from CQUniversity indicates that homework for primary school students is of negligible value, and students are better served by spending this time engaged in structured play or improving their reading abilities.

Even for students in high school, the traditional write-and-check style of homework has shown very little benefit for students . After all, if you don’t know how to do a problem, then how is more practice going to help?

But shouldn’t the interactive and intelligent nature of digital devices make mathematics homework more beneficial for students?

More than a practice problem book

We started reviewing different educational sites and apps addressing mathematics and found they fell into three groups:

• traditional tutorials
• minimally digital tutorials
• digitally enhanced tutorials.

The more traditionally designed online maths tutorials, such as Basic Mathematics and Ezy Math Tutoring , provide a decent amount of depth in their instructions, but they lack a proper curriculum, and any sort of video tutorial or feedback mechanism.

The minimally digital tutorials, such as Study Ladder and Mathletics , have a well-designed curriculum, but lack quality tutorial videos and feedback on the work students do.

The digitally enhanced, such as Khan Academy and Maths Online , provide a well-designed curriculum for any age or grade level, comprehensive instructions, videos, and feedback on student work. They still, however, lack any sort of tutorial prompts during the quizzes.

Enhancing the ‘e’ in e-homework

As you can see, even the best mathematics technologies are not really technological at all – apart from the fact that students use them on a computer or a pad. All the different websites or apps aimed at helping student in mathematics are missing the technological components of technology.

The tools are not interactive. Questions do not increase or decrease in difficulty based on the student’s response to the last question. It would be useful if the practice questions students worked on intuitively increased in difficulty based on the success the student has on the previous question.

Read more: Why digital apps can be good gifts for young family members

None of the tools provide instructive cues to remind students of steps and procedures. And they don’t provide cognitive scaffolding when students are struggling, such as instant instructional advice if a student misses a question.

The tools also fail to provide teachers with data collected about the reason for errors. If they did, teachers could create a learning analysis overviews and specialised learning programs for each student they teach.

It’s clear we need better digital design in our education apps, and particularly those used without a teacher present. But how do we do that?

Bringing educators and technologists together

What need to establish a closer connection between the technologists and the educators.

The tech people need help designing the technology, and they need to design more than just the textbook as an app. Educators can help technologists envision what instruction could look like if the digital device had to do the teaching (and not just the practice) – and then build apps and sites that are innovative and interactive.

Read more: Online learning can prepare students for a fast-changing future – wherever they are

Educators also need to learn from the technologists so they can maximise the use of the devices in their classes. Many educators lack training to use the technological devices to their full potential.

Finally, digital technology designers must consult with educational psychology specialists who provide training for teachers.

We need new technology that isn’t just a copy of educational tools that already exist. Only then will we see the benefits of true digital homework.

Program Manager, Teaching & Learning Initiatives

Lecturer/Senior Lecturer, Earth System Science (School of Science)

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Is technology good or bad for learning?

Subscribe to the brown center on education policy newsletter, saro mohammed, ph.d. smp saro mohammed, ph.d. partner - the learning accelerator @edresearchworks.

May 8, 2019

I’ll bet you’ve read something about technology and learning recently. You may have read that device use enhances learning outcomes . Or perhaps you’ve read that screen time is not good for kids . Maybe you’ve read that there’s no link between adolescents’ screen time and their well-being . Or that college students’ learning declines the more devices are present in their classrooms .

If ever there were a case to be made that more research can cloud rather than clarify an issue, technology use and learning seems to fit the bill. This piece covers what the research actually says, some outstanding questions, and how to approach the use of technology in learning environments to maximize opportunities for learning and minimize the risk of doing harm to students.

In my recent posts , I have frequently cited the mixed evidence about blended learning, which strategically integrates in-person learning with technology to enable real-time data use, personalized instruction, and mastery-based progression. One thing that this nascent evidence base does show is that technology can be linked to improved learning . When technology is integrated into lessons in ways that are aligned with good in-person teaching pedagogy, learning can be better than without technology.

A 2018 meta-analysis of dozens of rigorous studies of ed tech , along with the executive summary of a forthcoming update (126 rigorous experiments), indicated that when education technology is used to individualize students’ pace of learning, the results overall show “ enormous promise .” In other words, ed tech can improve learning when used to personalize instruction to each student’s pace.

Further, this same meta-analysis, along with other large but correlational studies (e.g., OECD 2015 ), also found that increased access to technology in school was associated with improved proficiency with, and increased use of, technology overall. This is important in light of the fact that access to technology outside of learning environments is still very unevenly distributed across ethnic, socio-economic, and geographic lines. Technology for learning, when deployed to all students, ensures that no student experiences a “21st-century skills and opportunity” gap.

More practically, technology has been shown to scale and sustain instructional practices that would be too resource-intensive to work in exclusively in-person learning environments, especially those with the highest needs. In multiple , large-scale studies where technology has been incorporated into the learning experiences of hundreds of students across multiple schools and school systems, they have been associated with better academic outcomes than comparable classrooms that did not include technology. Added to these larger bodies of research are dozens, if not hundreds, of smaller , more localized examples of technology being used successfully to improve students’ learning experiences. Further, meta-analyses and syntheses of the research show that blended learning can produce greater learning than exclusively in-person learning.

All of the above suggest that technology, used well, can drive equity in learning opportunities. We are seeing that students and families from privileged backgrounds are able to make choices about technology use that maximize its benefits and minimize its risks , while students and families from marginalized backgrounds do not have opportunities to make the same informed choices. Intentional, thoughtful inclusion of technology in public learning environments can ensure that all students, regardless of their ethnicity, socioeconomic status, language status, special education status, or other characteristics, have the opportunity to experience learning and develop skills that allow them to fully realize their potential.

On the other hand, the evidence is decidedly mixed on the neurological impact of technology use. In November 2016, the American Association of Pediatrics updated their screen time guidelines for parents, generally relaxing restrictions and increasing the recommended maximum amount of time that children in different age groups spend interacting with screens. These guidelines were revised not because of any new research, but for two far more practical reasons. First, the nuance of the existing evidence–especially the ways in which recommendations change as children get older–was not adequately captured in the previous guidelines. Second, the proliferation of technology in our lives had made the previous guidelines almost impossible to follow.

The truth is that infants, in particular, learn by interacting with our physical world and with other humans, and it is likely that very early (passive) interactions with devices–rather than humans–can disrupt or misinform neural development . As we grow older, time spent on devices often replaces time spent engaging in physical activity or socially with other people, and it can even become a substitute for emotional regulation, which is detrimental to physical, social, and emotional development.

In adolescence and young adulthood, the presence of technology in learning environments has also been associated with (but has not been shown to be the cause of) negative variables such as attention deficits or hyperactivity , feeling lonely , and lower grades . Multitasking is not something our brains can do while learning , and technology often represents not just one more “task” to have to attend to in a learning environment, but multiple additional tasks due to the variety of apps and programs installed on and producing notifications through a single device.

The pragmatic

The current takeaway from the research is that there are potential benefits and risks to deploying technology in learning environments. While we can’t wrap this topic up with a bow just yet–there are still more questions than answers–there is evidence that technology can amplify effective teaching and learning when in the hands of good teachers. The best we can do today is understand how technology can be a valuable tool for educators to do the complex, human work that is teaching by capitalizing on the benefits while remaining fully mindful of the risks as we currently understand them.

We must continue to build our understanding of both the risks and benefits as we proceed. With that in mind, here are some “Dos” and “Don’ts” for using technology in learning environments:

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How technology is shaping learning in higher education

About the authors.

This article is a collaborative effort by Claudio Brasca, Charag Krishnan , Varun Marya , Katie Owen, Joshua Sirois, and Shyla Ziade, representing views from McKinsey’s Education Practice.

The COVID-19 pandemic forced a shift to remote learning overnight for most higher-education students, starting in the spring of 2020. To complement video lectures and engage students in the virtual classroom, educators adopted technologies that enabled more interactivity and hybrid models of online and in-person activities. These tools changed learning, teaching, and assessment in ways that may persist after the pandemic. Investors have taken note. Edtech start-ups raised record amounts of venture capital in 2020 and 2021, and market valuations for bigger players soared.

A study conducted by McKinsey in 2021 found that to engage most effectively with students, higher-education institutions can focus on eight dimensions  of the learning experience. In this article, we describe the findings of a study of the learning technologies that can enable aspects of several of those eight dimensions (see sidebar “Eight dimensions of the online learning experience”).

Eight dimensions of the online learning experience

Leading online higher-education institutions focus on eight key dimensions of the learning experience across three overarching principles.

Seamless journey

Clear education road map: “My online program provides a road map to achieve my life goals and helps me structure my day to day to achieve steady progress.”

Seamless connections: “I have one-click access to classes and learning resources in the virtual learning platform through my laptop or my phone.”

Engaging teaching approach

Range of learning formats: “My program offers a menu of engaging courses with both self-guided and real-time classes, and lots of interaction with instructors and peers.”

Captivating experiences: “I learn from the best professors and experts. My classes are high quality, with up-to-date content.”

Adaptive learning: “I access a personalized platform that helps me practice exercises and exams and gives immediate feedback without having to wait for the course teacher.”

Real-world skills application: “My online program helps me get hands-on practice using exciting virtual tools to solve real-world problems.”

Caring network

Timely support: “I am not alone in my learning journey and have adequate 24/7 support for academic and nonacademic issues.”

Strong community: “I feel part of an academic community and I’m able to make friends online.”

In November 2021, McKinsey surveyed 600 faculty members and 800 students from public and private nonprofit colleges and universities in the United States, including minority-serving institutions, about the use and impact of eight different classroom learning technologies (Exhibit 1). (For more on the learning technologies analyzed in this research, see sidebar “Descriptions of the eight learning technologies.”) To supplement the survey, we interviewed industry experts and higher-education professionals who make decisions about classroom technology use. We discovered which learning tools and approaches have seen the highest uptake, how students and educators view them, the barriers to higher adoption, how institutions have successfully adopted innovative technologies, and the notable impacts on learning (for details about our methodology, see sidebar “About the research”).

Double-digit growth in adoption and positive perceptions

Descriptions of the eight learning technologies.

• Classroom interactions: These are software platforms that allow students to ask questions, make comments, respond to polls, and attend breakout discussions in real time, among other features. They are downloadable and accessible from phones, computers, and tablets, relevant to all subject areas, and useful for remote and in-person learning.
• Classroom exercises: These platforms gamify learning with fun, low-stakes competitions, pose problems to solve during online classes, allow students to challenge peers to quizzes, and promote engagement with badges and awards. They are relevant to all subject areas.
• Connectivity and community building: A broad range of informal, opt-in tools, these allow students to engage with one another and instructors and participate in the learning community. They also include apps that give students 24/7 asynchronous access to lectures, expanded course materials, and notes with enhanced search and retrieval functionality.
• Group work: These tools let students collaborate in and out of class via breakout/study rooms, group preparation for exams and quizzes, and streamlined file sharing.
• Augmented reality/virtual reality (AR/VR): Interactive simulations immerse learners in course content, such as advanced lab simulations for hard sciences, medical simulations for nursing, and virtual exhibit tours for the liberal arts. AR can be offered with proprietary software on most mobile or laptop devices. VR requires special headsets, proprietary software, and adequate classroom space for simultaneous use.
• AI adaptive course delivery: Cloud-based, AI-powered software adapts course content to a student’s knowledge level and abilities. These are fully customizable by instructors and available in many subject areas, including business, humanities, and sciences.
• Machine learning–powered teaching assistants: Also known as chatbot programs, machine learning–powered teaching assistants answer student questions and explain course content outside of class. These can auto-create, deliver, and grade assignments and exams, saving instructors’ time; they are downloadable from mobile app stores and can be accessed on personal devices.
• Student progress monitoring: These tools let instructors monitor academic progress, content mastery, and engagement. Custom alerts and reports identify at-risk learners and help instructors tailor the content or their teaching style for greater effectiveness. This capability is often included with subscriptions to adaptive learning platforms.

Survey respondents reported a 19 percent average increase in overall use of these learning technologies since the start of the COVID-19 pandemic. Technologies that enable connectivity and community building, such as social media–inspired discussion platforms and virtual study groups, saw the biggest uptick in use—49 percent—followed by group work tools, which grew by 29 percent (Exhibit 2). These technologies likely fill the void left by the lack of in-person experiences more effectively than individual-focused learning tools such as augmented reality and virtual reality (AR/VR). Classroom interaction technologies such as real-time chatting, polling, and breakout room discussions were the most widely used tools before the pandemic and remain so; 67 percent of survey respondents said they currently use these tools in the classroom.

About the research

In November 2021, McKinsey surveyed 634 faculty members and 818 students from public, private, and minority-serving colleges and universities over a ten-day period. The survey included only students and faculty who had some remote- or online-learning experience with any of the eight featured technologies. Respondents were 63 percent female, 35 percent male, and 2 percent other gender identities; 69 percent White, 18 percent Black or African American, 8 percent Asian, and 4 percent other ethnicities; and represented every US region. The survey asked respondents about their:

• experiences with technology in the classroom pre-COVID-19;
• experiences with technology in the classroom since the start of the COVID-19 pandemic; and
• desire for future learning experiences in relation to technology.

The shift to more interactive and diverse learning models will likely continue. One industry expert told us, “The pandemic pushed the need for a new learning experience online. It recentered institutions to think about how they’ll teach moving forward and has brought synchronous and hybrid learning into focus.” Consequently, many US colleges and universities are actively investing to scale up their online and hybrid program offerings .

Differences in adoption by type of institution observed in the research

• Historically Black colleges and universities (HBCUs) and tribal colleges and universities made the most use of classroom interactions and group work tools (55 percent) and the least use of tools for monitoring student progress (15 percent).
• Private institutions used classroom interaction technologies (84 percent) more than public institutions (63 percent).
• Public institutions, often associated with larger student populations and course sizes, employed group work and connectivity and community-building tools more often than private institutions.
• The use of AI teaching-assistant technologies increased significantly more at public institutions (30 percent) than at private institutions (9 percent), though overall usage remained comparatively higher at private institutions.
• The use of tools for monitoring student progress increased by 14 percent at private institutions, versus no growth at public institutions.

Some technologies lag behind in adoption. Tools enabling student progress monitoring, AR/VR, machine learning–powered teaching assistants (TAs), AI adaptive course delivery, and classroom exercises are currently used by less than half of survey respondents. Anecdotal evidence suggests that technologies such as AR/VR require a substantial investment in equipment and may be difficult to use at scale in classes with high enrollment. Our survey also revealed utilization disparities based on size. Small public institutions use machine learning–powered TAs, AR/VR, and technologies for monitoring student progress at double or more the rates of medium and large public institutions, perhaps because smaller, specialized schools can make more targeted and cost-effective investments. We also found that medium and large public institutions made greater use of connectivity and community-building tools than small public institutions (57 to 59 percent compared with 45 percent, respectively). Although the uptake of AI-powered tools was slower, higher-education experts we interviewed predict their use will increase; they allow faculty to tailor courses to each student’s progress, reduce their workload, and improve student engagement at scale (see sidebar “Differences in adoption by type of institution observed in the research”).

While many colleges and universities are interested in using more technologies to support student learning, the top three barriers indicated are lack of awareness, inadequate deployment capabilities, and cost (Exhibit 3).

Students want entertaining and efficient tools

More than 60 percent of students said that all the classroom learning technologies they’ve used since COVID-19 began had improved their learning and grades (Exhibit 4). However, two technologies earned higher marks than the rest for boosting academic performance: 80 percent of students cited classroom exercises, and 71 percent cited machine learning–powered teaching assistants.

Although AR/VR is not yet widely used, 37 percent of students said they are “most excited” about its potential in the classroom. While 88 percent of students believe AR/VR will make learning more entertaining, just 5 percent said they think it will improve their ability to learn or master content (Exhibit 5). Industry experts confirmed that while there is significant enthusiasm for AR/VR, its ability to improve learning outcomes is uncertain. Some data look promising. For example, in a recent pilot study, 1 “Immersive biology in the Alien Zoo: A Dreamscape Learn software product,” Dreamscape Learn, accessed October 2021. students who used a VR tool to complete coursework for an introductory biology class improved their subject mastery by an average of two letter grades.

Faculty embrace new tools but would benefit from more technical support and training

Faculty gave learning tools even higher marks than students did, for ease of use, engagement, access to course resources, and instructor connectivity. They also expressed greater excitement than students did for the future use of technologies. For example, while more than 30 percent of students expressed excitement for AR/VR and classroom interactions, more than 60 percent of faculty were excited about those, as well as machine learning–powered teaching assistants and AI adaptive technology.

Eighty-one percent or more of faculty said they feel the eight learning technology tools are a good investment of time and effort relative to the value they provide (Exhibit 6). Expert interviews suggest that employing learning technologies can be a strain on faculty members, but those we surveyed said this strain is worthwhile.

While faculty surveyed were enthusiastic about new technologies, experts we interviewed stressed some underlying challenges. For example, digital-literacy gaps have been more pronounced since the pandemic because it forced the near-universal adoption of some technology solutions, deepening a divide that was unnoticed when adoption was sporadic. More tech-savvy instructors are comfortable with interaction-engagement-focused solutions, while staff who are less familiar with these tools prefer content display and delivery-focused technologies.

According to experts we interviewed, learning new tools and features can bring on general fatigue. An associate vice president of e-learning at one university told us that faculty there found designing and executing a pilot study of VR for a computer science class difficult. “It’s a completely new way of instruction. . . . I imagine that the faculty using it now will not use it again in the spring.” Technical support and training help. A chief academic officer of e-learning who oversaw the introduction of virtual simulations for nursing and radiography students said that faculty holdouts were permitted to opt out but not to delay the program. “We structured it in a ‘we’re doing this together’ way. People who didn’t want to do it left, but we got a lot of support from vendors and training, which made it easy to implement simulations.”

Reimagining higher education in the United States

Takeaways from our research.

Despite the growing pains of digitizing the classroom learning experience, faculty and students believe there is a lot more they can gain. Faculty members are optimistic about the benefits, and students expect learning to stay entertaining and efficient. While adoption levels saw double-digit growth during the pandemic, many classrooms have yet to experience all the technologies. For institutions considering the investment, or those that have already started, there are several takeaways to keep in mind.

• It’s important for administration leaders, IT, and faculty to agree on what they want to accomplish by using a particular learning technology. Case studies and expert interviews suggest institutions that seek alignment from all their stakeholders before implementing new technologies are more successful. Is the primary objective student engagement and motivation? Better academic performance? Faculty satisfaction and retention? Once objectives are set, IT staff and faculty can collaborate more effectively in choosing the best technology and initiating programs.
• Factor in student access to technology before deployment. As education technology use grows, the digital divide for students puts access to education at risk. While all the institution types we surveyed use learning technologies in the classroom, they do so to varying degrees. For example, 55 percent of respondents from historically Black colleges and universities and tribal colleges and universities use classroom interaction tools. This is lower than public institutions’ overall utilization rate of 64 percent and private institutions’ utilization rate of 84 percent. Similarly, 15 percent of respondents from historically Black colleges and universities and tribal colleges and universities use tools for monitoring student progress, while the overall utilization rate for both public and private institutions is 25 percent.
• High-quality support eases adoption for students and faculty. Institutions that have successfully deployed new learning technologies provided technical support and training for students and guidance for faculty on how to adapt their course content and delivery. For example, institutions could include self-service resources, standardize tools for adoption, or provide stipend opportunities for faculty who attend technical training courses. One chief academic officer told us, “The adoption of platforms at the individual faculty level can be very difficult. Ease of use is still very dependent upon your IT support representative and how they will go to bat to support you.”
• Agree on impact metrics and start measuring in advance of deployment. Higher-education institutions often don’t have the means to measure the impact of their investment in learning technologies, yet it’s essential for maximizing returns. Attributing student outcomes to a specific technology can be complex due to the number of variables involved in academic performance. However, prior to investing in learning technologies, the institution and its faculty members can align on a core set of metrics to quantify and measure their impact. One approach is to measure a broad set of success indicators, such as tool usage, user satisfaction, letter grades, and DFW rates (the percentage of students who receive a D, F, or Withdraw) each term. The success indicators can then be correlated by modality—online versus hybrid versus in-class—to determine the impact of specific tools. Some universities have offered faculty grants of up to $20,000 for running pilot programs that assess whether tools are achieving high-priority objectives. “If implemented properly, at the right place, and with the right buy-in, education technology solutions are absolutely valuable and have a clear ROI,” a senior vice president of academic affairs and chief technology officer told us.

In an earlier article , we looked at the broader changes in higher education that have been prompted by the pandemic. But perhaps none has advanced as quickly as the adoption of digital learning tools. Faculty and students see substantial benefits, and adoption rates are a long way from saturation, so we can expect uptake to continue. Institutions that want to know how they stand in learning tech adoption can measure their rates and benchmark them against the averages in this article and use those comparisons to help them decide where they want to catch up or get ahead.

Claudio Brasca is a partner in McKinsey’s Bay Area office, where Varun Marya is a senior partner; Charag Krishnan is a partner in the New Jersey office; Katie Owen is an associate partner in the St. Louis office, where Joshua Sirois is a consultant; and Shyla Ziade is a consultant in the Denver office.

The authors wish to thank Paul Kim, chief technology officer and associate dean at Stanford School of Education, and Ryan Golden for their contributions to this article.

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Education Technology: What Is Edtech? A Guide.

Edtech, or education technology, is the combination of IT tools and educational practices aimed at facilitating and enhancing learning.

What Is Edtech?

Edtech, or education technology, is the practice of introducing information and communication technology tools into the classroom to create more engaging, inclusive and individualized learning experiences.

Today’s classrooms have moved beyond the clunky desktop computers that were once the norm and are now tech-infused with tablets, interactive online courses and even robots that can take notes and record lectures for absent students.

The influx of edtech tools are changing classrooms in a variety of ways. For instance, edtech robots , virtual reality lessons and gamified classroom activities make it easier for students to stay engaged through fun forms of learning. And edtech IoT devices are hailed for their ability to create digital classrooms for students, whether they’re physically in school, on the bus or at home. Even machine learning and blockchain tools are assisting teachers with grading tests and holding students accountable for homework.

The potential for scalable individualized learning has played an important role in the edtech industry’s ascendance . The way we learn, how we interact with classmates and teachers, and our overall enthusiasm for the same subjects is not a one-size-fits-all situation. Everyone learns at their own pace and in their own style. Edtech tools make it easier for teachers to create individualized lesson plans and learning experiences that foster a sense of inclusivity and boost the learning capabilities of all students, no matter their age or learning abilities.

And it looks like technology in the classroom is here to stay. In a 2018 study , 86 percent of eighth-grade teachers agreed that using technology to teach students is important. And 75 percent of the study’s teachers said technology use improved the academic performance of students. For that reason, many would argue it’s vital to understand the benefits edtech brings in the form of increased communication, collaboration and overall quality of education.

Related Reading 13 Edtech Examples You Should Know

How Does Edtech Help Students and Teachers?

Benefits of edtech for students.

An influx of technology is opening up new avenues of learning for students of all ages, while also promoting collaboration and inclusivity in the classroom. Here are five major ways edtech is directly impacting the way students learn.

Increased Collaboration

Cloud-enabled tools and tablets are fostering collaboration in the classroom. Tablets loaded with learning games and online lessons give children the tools to solve problems together. Meanwhile, cloud-based apps let students upload their homework and digitally converse with one another about their thought processes and for any help they may need.

24/7 Access to Learning

IoT devices are making it easier for students to have full access to the classroom in a digital environment. Whether they’re at school, on the bus or at home, connected devices are giving students Wi-Fi and cloud access to complete work at their own pace — and on their own schedules — without being hampered by the restriction of needing to be present in a physical classroom.

Various apps also help students and teachers stay in communication in case students have questions or need to alert teachers to an emergency.

“Flipping” the Classroom

Edtech tools are flipping the traditional notion of classrooms and education. Traditionally, students have to listen to lectures or read in class then work on projects and homework at home. With video lectures and learning apps, students can now watch lessons at home at their own pace, using class time to collaboratively work on projects as a group. This type of learning style helps foster self-learning, creativity and a sense of collaboration among students.

Personalized Educational Experiences

Edtech opens up opportunities for educators to craft personalized learning plans for each of their students. This approach aims to customize learning based on a student’s strengths, skills and interests.

Video content tools help students learn at their own pace and because students can pause and rewind lectures, these videos can help students fully grasp lessons. With analytics, teachers can see which students had trouble with certain lessons and offer further help on the subject.

Instead of relying on stress-inducing testing to measure academic success, educators are now turning to apps that consistently measure overall aptitude . Constant measurements display learning trends that teachers can use to craft specialized learning plans based on each student’s strengths and weaknesses or, more importantly, find negative trends that can be proactively thwarted with intervention.

Attention-Grabbing Lessons

Do you remember sitting in class, half-listening, half-day dreaming? Now, with a seemingly infinite number of gadgets and outside influences vying for a student’s attention, it’s imperative to craft lesson plans that are both gripping and educational. Edtech proponents say technology is the answer. Some of the more innovative examples of students using tech to boost classroom participation include interacting with other classrooms around the world via video, having students submit homework assignments as videos or podcasts and even gamifying problem-solving .

Benefits of Edtech

• Personalized education caters to different learning styles.
• On-demand video lectures allow classroom time to focus on collaboration.
• Gamified lessons engage students more deeply.
• Cloud computing with 24/7 access lets students work from anywhere.
• Automated grading and classroom management tools help teachers balance responsibilities.

Benefits of Edtech for Teachers

Students aren’t the only group benefitting from edtech. Teachers are seeing educational tech as a means to develop efficient learning practices and save time in the classroom. Here are four ways edtech is helping teachers get back to doing what they do — teaching.

Automated Grading

Artificially intelligent edtech tools are making grading a breeze. These apps use machine learning to analyze and assess answers based on the specifications of the assignment. Using these tools, especially for objective assignments like true/false or fill-in-the-blank assessments, frees up hours that teachers usually spend grading assignments. Extra free time for teachers provides more flexibility for less prep and one-on-one time with both struggling and gifted students.     

Classroom Management Tools

Let’s face it, trying to get a large group of kids to do anything can be challenging. Educational technology has the potential to make everything — from the way teachers communicate with their students to how students behave — a little easier. There are now apps that help send parents and students reminders about projects or homework assignments, as well as tools that allow students to self-monitor classroom noise levels. The addition of management tools in the classroom brings forth a less-chaotic, more collaborative environment.

Read Next Assistive Technology in the Classroom Is Reimagining the Future of Education

Paperless Classrooms

Printing budgets, wasting paper and countless time spent at the copy machine are a thing of the past thanks to edtech. Classrooms that have gone digital bring about an easier way to grade assignments, lessen the burden of having to safeguard hundreds of homework files and promote overall greener policies in the classroom.   

Eliminating Guesswork

Teachers spend countless hours attempting to assess the skills or areas of improvement of their students. Edtech can change all of that. There are currently myriad tools, data platforms and apps that constantly assess student’s skills and needs, and they relay the data to the teacher.

Sometimes harmful studying trends aren’t apparent to teachers for months, but some tools that use real-time data can help teachers discover a student’s strengths, weaknesses and even signs of learning disabilities, setting in motion a proactive plan to help.

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Why the “homework gap” is key to America’s digital divide

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When the pandemic hit, parents scrambled to get enough devices to get their kids for online schooling. But even when they did, not everything went smoothly. Getting multiple people online for hours at a time in a home was one big obstacle; making sure entire communities were able to sign on was another.

Jessica Rosenworcel, the senior Democrat on the Federal Communications Commission, wasn’t surprised. For years, Rosenworcel has talked about the “homework gap,” the term she coined to describe a problem facing communities where kids can’t access the internet because infrastructure is inadequate, their families can’t afford it, or both. 

People are now paying attention—not least because rumors are swirling that if Joe Biden is elected president, she could be appointed chairperson of the FCC. (Rosenworcel would not confirm these rumors, citing the Hatch Act.)

The FCC’s current broadband standard is a download speed of at least 25 megabits per second—the minimum for a single 4K Netflix stream. But in rural areas, where a Pew study estimates that one-third of Americans don’t have access to broadband, those speeds are unheard of. And while the Pew data indicates that about three-quarters of urban and suburban households have access to broadband, take that claim with a huge grain of salt: in current FCC mapping, a zip code is considered to be served with broadband if a single household has access .

In light of these problems, Rosenworcel is passionate about getting the FCC to update the E-Rate program , a federal education technology service created in 1996 that offers schools and libraries discounted internet access. 

I spoke to Rosenworcel about her plans to use the program to address the homework gap. This interview has been edited and condensed for length.

How did you come up with the term “homework gap”?

When I joined the FCC, I decided that I would visit some schools that were E-Rate beneficiaries when I was traveling for work. And something struck me: I wound up in big cities and in small towns, in urban America and rural America, but I heard the very same things from teachers and administrators no matter where I went: “The E-Rate program is great. We now have these devices we can use in all of our classrooms. But when our students go home at night, not all of them have reliable internet access at home. It’s hard for our teachers to assign homework if we don’t have the confidence that every student has reliable access outside of school.”

The more that I talked to teachers, the more I heard the same stories over and over again: Kids sitting in the school parking lot with school laptops they had borrowed late into the evening, trying to peck away at homework because that was the only place they could actually get online. Or kids sitting in fast food restaurants and doing their homework with a side of fries.

I looked at the data and I found that seven in 10 teachers would assign homework that requires internet access. But FCC data consistently shows that one in three households don’t have broadband at home. I started calling where those numbers overlap the “homework gap” because I felt that this portion of the digital divide really needed a phrase or a term to describe it because it’s so important.

It’s becoming apparent that every student needs this to complete schoolwork now. And then enter the pandemic, right? We sent millions and millions of kids home. We told so many of them to go to online class, but the data suggests that as many as 17 million of them can’t make it there, so now this homework gap is becoming an education gap—and I worry it can become a long-term opportunity gap if we don’t correct it.

Why does the US have such digital inequity?

Well, we’re really a diverse country. We’re also diverse geographically, and that has wonderful qualities but it also has consequences. It takes some work to make sure everyone is connected. But we’ve done it before. We did it with electricity following the Rural Electrification Act. We did it with basic telephony. We can do it again with broadband. 

Early in the pandemic I spoke to immigrant families and people who don’t have access to the internet unless they go to a public space. A lot of them were told they could get reduced-rate internet, but that was difficult in terms of documentation and being able to pay those rates. How has the FCC addressed this issue, and do you think there is a way to move forward here?

I’m one of five people at the FCC. I’m the senior Democrat. I’m not in the majority. I can be noisy and I can be relentless, but I don’t always convince my colleagues.

I am convinced that we can update the E-Rate program using existing law and support schools—loaning out Wi-Fi hot spots, for instance. I think we can do that today with the E-Rate program.

And shame on us for not doing it. Because we’re not doing it, what you see are pictures like the one that went viral of two girls sitting outside of a Taco Bell in Salinas, California, not for lunch—they were there because they were using the free Wi-Fi signal. And what you now see is Wi-Fi in parking lots across this country in places that have been closed down because there’s this cruel virus and students are sitting in hot cars attending class and doing their schoolwork. And then other students are entirely locked out of the virtual classrooms, because they just don’t have a way to get online.

So shame on the FCC for not making it a priority to update E-Rate to address this crisis, because it’s within our power to help right now. I am saddened that my agency keeps looking the other way.

What is the demographic of kids most affected by the homework gap?

It has a disproportionate impact on communities of color. It’s disproportionately harmful to rural America and disproportionately harms low-income households. What’s most cruel to me about this is that we have a program we could update and help fix this, but we keep looking the other way. So many students are unable to attend class in person right now. And if they can’t make it into online classrooms and they’re out of schools for months, it’s going to have a long-term impact on their education. 

Is implementing the E-Rate program even feasible right now?

One of the beauties of the E-Rate program is that it’s set up in a way so that more support goes to schools with greater numbers of students on free or reduced-price lunch programs. In other words, it’s almost a perfect map of where the demand is most likely. We could use that to really figure out how to get devices or wireless hot spots out to students—things that could make a meaningful difference. I mean, it wasn’t that long ago that every student didn’t always get textbooks or a grammar workbook. We have to start recognizing that for students who don’t have internet access at home, having the school loan out a wireless hot spot is the difference between keeping up in class and falling behind. We can do something to fix this. 

How quickly can we expand the E-Rate program? 

The truth is that we should have started this at the start of the pandemic. Seven months in is too late, but today is better than tomorrow. We should be doing this immediately. And it’s not totally irrational. Years ago, the FCC years ago made some adjustments following Hurricane Katrina to a different program that helps low-income households get internet service, to make sure that everyone who got displaced was able to get phone service started again with a wireless line. 

We have a history of looking at a disaster, trying to assess what’s necessary to keep people connected, and updating our programs in response. We should be doing this right now with E-Rate for the homework gap.

I read that you’re a mom. 

I’m curious what you thought about homeschooling and being online during this time.

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How to effectively use technology to maximize homework outcomes

“Teachers’ Use of Technology for School and Homework Assignments: 2018–19 First Look” .  This report was generated in response to the enormous role technology is, and will increasingly be, playing in providing remote learning opportunities for students, whether in supporting part-time “school based” education or temporarily replacing it altogether.  The provides data on the access and availability of computers, smartphones, and the Internet to students at home, the impact that students’ access to technology outside of school has on teachers’ homework assignments, and ways that teachers provide assistance to their students who have limited access to technology and the Internet outside of school.  The following are some of the more important findings.

Teacher Awareness of Home Computer Availability and Use:   Teachers are on the front line of interfacing with students about their access to computers and the Internet at home.  Yet, they often have inexact information in this area.  Teachers reported that they get information by doing surveys of students or parents (51 percent), talking to students or parents individually (84 percent), and developing a sense while working with students.  Yet, among all teachers, a little over one in five reported being very knowledgeable and one in two reported being somewhat knowledgeable about their students’ access to computers and the Internet at home. School Support for Access to Computers and Internet:   Only twenty-six percent of teachers reported that their students have district- or school-provided computers for students to take home on a long-term basis during the school year. Thirty-six percent of teachers reported that the teachers estimated the percentage of their students who have access to a computer at home, including district- or school-provided computers for students who take them home. About two-thirds of teachers estimated that 75 percent or more of their students have access to a computer at home. While computers and Internet service might exist in students’ households, computer availability for homework and the reliability of computer connections to the Internet can vary considerably. About a third (35 percent) of teachers estimated that their students’ home computers were very available for school assignments. Twenty-nine percent of teachers thought it very likely that their students’ home computers had reliable Internet access.

Access to Technology and Homework Assignments:   About half of the teachers reported that their students’ access to technology and the Internet outside of school has a moderate (28 percent) or large (20 percent) influence on the homework they assign to them.  About a fifth (19 percent) of teachers reported that they often assign technology-based homework and an additional 28 percent reported doing so sometimes. The teachers who assign technology-based homework, at least rarely, were asked the extent that their students have difficulty completing this type of homework because they are not familiar with how to use technology. 

Among the 98 percent of teachers whose students are given online or computerized assessments by the state, district, or school, 44 percent reported that their students were very prepared and 39 percent reported students to be somewhat prepared to use the technology required for these assessments.

The overall conclusions of this survey is that, while there have been successes along the way to integrating technology into education, there is a long way to go in terms of data systems, resources, accountability, and ongoing support to meet the new needs for remote learning.

Citation(s):  Gray, L., and Lewis, L. (2020). Teachers’ Use of Technology for School and Homework Assignments: 2018–19 (NCES 2020-048). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved [date] from https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2020048

Link:  https://nces.ed.gov/pubs2020/2020048.pdf

Why Millions of Teens Can't Finish Their Homework

The push toward technology-focused education overlooks the students who lack the resources needed to complete their assignments.

In decades past, students needed little more than paper, pencils, and time to get their schoolwork done. For the vast majority of students, that's no longer the case. Most schoolwork these days necessitates a computer and an internet connection, and that includes work to be done at home. One federal survey found that 70 percent of American teachers  assign homework that needs to be done online; 90 percent of high schoolers say they have to do internet-based homework at least a few times a month. Nearly half of all students say they get such assignments daily or almost daily.

Yet despite the seemingly ever-growing embrace of digital learning in schools, access to the necessary devices remains unequal, with a new report from the Pew Research Center finding that 15 percent of U.S. households with school-age children lack high-speed internet at home. The problem is particularly acute for low-income families: One in three households that make below $30,000 a year lacks internet. This is despite an emerging reality in which poorer students are attending schools that evangelize technology-based learning while their more affluent counterparts, as The New York Times reported this past weekend, are “going back to wooden toys and the luxury of human interaction.”

It’s a glaring irony that’s also a major force behind class- and race-based discrepancies in academic achievement. In what’s often referred to as the “homework gap,” the unequal access to digital devices and high-speed internet prevents 17 percent of teens from completing their homework assignments, according to the new Pew analysis, which surveyed 743 students ages 13 through 17. Black teens are especially burdened by the homework gap: One in four of them at least sometimes struggle to complete assignments because of a lack of technology at home. And close to half of teenagers in the bottom income bracket have to do their homework on a cellphone occasionally or often.

Read: The futile resistance against classroom tech

From a history-class assignment on the political debate over immigration to required participation in an online discussion board for AP Environmental Science, access to a functioning computer and high-speed internet is all but a prerequisite for success in high school. This is becoming especially true as schools gravitate toward software where students file assignments and papers virtually, as well as schools that equip each student with a laptop or tablet ; one 2017 survey found that half of U.S. teachers have one device for each of their students, up 10 percentage points from the year prior. Close to two in three teachers use technology in their classroom daily, according to a separate 2017 survey .

The homework gap can have major consequences, with some studies suggesting that teens who lack access to a computer at home are less likely to graduate from high school than their more technologically equipped peers. The “challenge to complete homework in safe, predictable, and productive environments can have lifelong impacts on their ability to achieve their full potential,” wrote John Branam, who runs an initiative to provide lacking teens with internet access, in an op-ed for The Hechinger Report last year.

Although the big telecom providers offer subsidies to low-income families, these programs are generally underused . And while disadvantaged students can resort to public libraries and other venues that offer free Wi-Fi, such alternatives are still major obstacles to finishing homework every night. “Your aunt has internet access [at home] but she lives a 40-minute bus trip across town,” Branam wrote, illustrating the roadblocks for teens without internet access. “The public library does, but it has a 30-minute computer use limit and, as a young woman, you don’t feel comfortable there late at night. McDonald’s has free Wi-Fi but it’s noisy, you have to buy food and you can’t linger there forever.”

Read: When students can’t go online

With a team of researchers, the University of Texas at Austin professor S. Craig Watkins spent a year and a half observing and interacting with high schoolers to better understand the digital divide. The researchers’ forthcoming book, The Digital Edge: How Black and Latino Youth Navigate Digital Inequality , chronicles the ways low-income students of color get around not having access to the internet and a computer. In what Watkins calls “social hacking,” students often “reengineer their socioeconomic circumstances in order to get access to technology that they otherwise would not have access to.” For example, the researchers observed that students without such resources at home were adept at developing relationships with teachers who could, say, give them special weekend access to laptops and software for use at home. They also tended to rely on other needy classmates to find work-arounds, sharing with one another smartphones and tablets that more affluent students often take for granted, for instance. “It was an inventive way of cultivating social capital,” Watkins says, “but it also created a kind of sharing economy.”

Watkins says the digital divide is an “institutional blind spot” for many school leaders and policy makers. “I suspect that people a pay grade or two above teachers likely don’t understand the depth at which this access- and participation-gap divide still exists,” he says.

While embedding technology into the curriculum is all the rage in some schools, “oftentimes there’s a lack of clarity and vision in terms of what learning should look like with technology,” Watkins says. “There’s this assumption that just by providing access to technology you’re somehow creating a better learning future for kids, but that is not always the case.” After all, technology in schools is going to be of limited success if kids don’t have access to the internet and a computer once the final bell rings.

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Academic dishonesty when doing homework: How digital technologies are put to bad use in secondary schools

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The growth in digital technologies in recent decades has offered many opportunities to support students’ learning and homework completion. However, it has also contributed to expanding the field of possibilities concerning homework avoidance. Although studies have investigated the factors of academic dishonesty, the focus has often been on college students and formal assessments. The present study aimed to determine what predicts homework avoidance using digital resources and whether engaging in these practices is another predictor of test performance. To address these questions, we analyzed data from the Program for International Student Assessment 2018 survey, which contained additional questionnaires addressing this issue, for the Swiss students. The results showed that about half of the students engaged in one kind or another of digitally-supported practices for homework avoidance at least once or twice a week. Students who were more likely to use digital resources to engage in dishonest practices were males who did not put much effort into their homework and were enrolled in non-higher education-oriented school programs. Further, we found that digitally-supported homework avoidance was a significant negative predictor of test performance when considering information and communication technology predictors. Thus, the present study not only expands the knowledge regarding the predictors of academic dishonesty with digital resources, but also confirms the negative impact of such practices on learning.

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1 Introduction

Academic dishonesty is a widespread and perpetual issue for teachers made even more easier to perpetrate with the rise of digital technologies (Blau & Eshet-Alkalai, 2017 ; Ma et al., 2008 ). Definitions vary but overall an academically dishonest practices correspond to learners engaging in unauthorized practice such as cheating and plagiarism. Differences in engaging in those two types of practices mainly resides in students’ perception that plagiarism is worse than cheating (Evering & Moorman, 2012 ; McCabe, 2005 ). Plagiarism is usually defined as the unethical act of copying part or all of someone else’s work, with or without editing it, while cheating is more about sharing practices (Krou et al., 2021 ). As a result, most students do report cheating in an exam or for homework (Ma et al., 2008 ). To note, other research follow a different distinction for those practices and consider that plagiarism is a specific – and common – type of cheating (Waltzer & Dahl, 2022 ). Digital technologies have contributed to opening possibilities of homework avoidance and technology-related distraction (Ma et al., 2008 ; Xu, 2015 ).

The question of whether the use of digital resources hinders or enhances homework has often been investigated in large-scale studies, such as the Program for International Student Assessment (PISA), the Trends in International Mathematics and Science Study (TIMSS), and the Progress in International Reading Literacy Study (PIRLS). While most of the early large-scale studies showed positive overall correlations between the use of digital technologies for learning at home and test scores in language, mathematics, and science (e.g., OECD, 2015 ; Petko et al., 2017 ; Skryabin et al., 2015 ), there have been more recent studies reporting negative associations as well (Agasisti et al., 2020 ; Odell et al., 2020 ). One reason for these inconclusive findings is certainly the complex interplay of related factors, which include diverse ways of measuring homework, gender, socioeconomic status, personality traits, learning goals, academic abilities, learning strategies, motivation, and effort, as well as support from teachers and parents. Despite this complexity, it needs to be acknowledged that doing homework digitally does not automatically lead to productive learning activities, and it might even be associated with counter-productive practices such as digital distraction or academic dishonesty. Digitally enhanced academic dishonesty has mostly been investigated regarding formal assessment-related examinations (Evering & Moorman, 2012 ; Ma et al., 2008 ); however, it might be equally important to investigate its effects regarding learning-related assignments such as homework. Although a large body of research exists on digital academic dishonesty regarding assignments in higher education, relatively few studies have investigated this topic on K12 homework. To investigate this issue, we integrated questionnaire items on homework engagement and digital homework avoidance in a national add-on to PISA 2018 in Switzerland. Data from the Swiss sample can serve as a case study for further research with a wider cultural background. This study provides an overview of the descriptive results and tries to identify predictors of the use of digital technology for academic dishonesty when completing homework.

1.1 Prevalence and factors of digital academic dishonesty in schools

According to Pavela’s ( 1997 ) framework, four different types of academic dishonesty can be distinguished: cheating by using unauthorized materials, plagiarism by copying the work of others, fabrication of invented evidence, and facilitation by helping others in their attempts at academic dishonesty. Academic dishonesty can happen in assessment situations, as well as in learning situations. In formal assessments, academic dishonesty usually serves the purpose of passing a test or getting a better grade despite lacking the proper abilities or knowledge. In learning-related situations such as homework, where assignments are mandatory, cheating practices equally qualify as academic dishonesty. For perpetrators, these practices can be seen as shortcuts in which the willingness to invest the proper time and effort into learning is missing (Chow, 2021; Waltzer & Dahl,  2022 ). The interviews by Waltzer & Dahl ( 2022 ) reveal that students do perceive cheating as being wrong but this does not prevent them from engaging in at least one type of dishonest practice. While academic dishonesty is not a new phenomenon, it has been changing together with the development of new digital technologies (Anderman & Koenka, 2017 ; Ercegovac & Richardson, 2004 ). With the rapid growth in technologies, new forms of homework avoidance, such as copying and plagiarism, are developing (Evering & Moorman, 2012 ; Ma et al., 2008 ) summarized the findings of the 2006 U.S. surveys of the Josephson Institute of Ethics with the conclusion that the internet has led to a deterioration of ethics among students. In 2006, one-third of high school students had copied an internet document in the past 12 months, and 60% had cheated on a test. In 2012, these numbers were updated to 32% and 51%, respectively (Josephson Institute of Ethics, 2012 ). Further, 75% reported having copied another’s homework. Surprisingly, only a few studies have provided more recent evidence on the prevalence of academic dishonesty in middle and high schools. The results from colleges and universities are hardly comparable, and until now, this topic has not been addressed in international large-scale studies on schooling and school performance.

Despite the lack of representative studies, research has identified many factors in smaller and non-representative samples that might explain why some students engage in dishonest practices and others do not. These include male gender (Whitley et al., 1999 ), the “dark triad” of personality traits in contrast to conscientiousness and agreeableness (e.g., Cuadrado et al., 2021 ; Giluk & Postlethwaite, 2015 ), extrinsic motivation and performance/avoidance goals in contrast to intrinsic motivation and mastery goals (e.g., Anderman & Koenka,  2017 ; Krou et al., 2021 ), self-efficacy and achievement scores (e.g., Nora & Zhang,  2010 ; Yaniv et al., 2017 ), unethical attitudes, and low fear of being caught (e.g., Cheng et al., 2021 ; Kam et al., 2018 ), influenced by the moral norms of peers and the conditions of the educational context (e.g., Isakov & Tripathy,  2017 ; Kapoor & Kaufman, 2021 ). Similar factors have been reported regarding research on the causes of plagiarism (Husain et al., 2017 ; Moss et al., 2018 ). Further, the systematic review from Chiang et al. ( 2022 ) focused on factors of academic dishonesty in online learning environments. The analyses, based on the six-components behavior engineering, showed that the most prominent factors were environmental (effect of incentives) and individual (effect of motivation). Despite these intensive research efforts, there is still no overarching model that can comprehensively explain the interplay of these factors.

1.2 Effects of homework engagement and digital dishonesty on school performance

In meta-analyses of schools, small but significant positive effects of homework have been found regarding learning and achievement (e.g., Baş et al., 2017 ; Chen & Chen, 2014 ; Fan et al., 2017 ). In their review, Fan et al. ( 2017 ) found lower effect sizes for studies focusing on the time or frequency of homework than for studies investigating homework completion, homework grades, or homework effort. In large surveys, such as PISA, homework measurement by estimating after-school working hours has been customary practice. However, this measure could hide some other variables, such as whether teachers even give homework, whether there are school or state policies regarding homework, where the homework is done, whether it is done alone, etc. (e.g., Fernández-Alonso et al., 2015 , 2017 ). Trautwein ( 2007 ) and Trautwein et al. ( 2009 ) repeatedly showed that homework effort rather than the frequency or the time spent on homework can be considered a better predictor for academic achievement Effort and engagement can be seen as closely interrelated. Martin et al. ( 2017 ) defined engagement as the expressed behavior corresponding to students’ motivation. This has been more recently expanded by the notion of the quality of homework completion (Rosário et al., 2018 ; Xu et al., 2021 ). Therefore, it is a plausible assumption that academic dishonesty when doing homework is closely related to low homework effort and a low quality of homework completion, which in turn affects academic achievement. However, almost no studies exist on the effects of homework avoidance or academic dishonesty on academic achievement. Studies investigating the relationship between academic dishonesty and academic achievement typically use academic achievement as a predictor of academic dishonesty, not the other way around (e.g., Cuadrado et al., 2019 ; McCabe et al., 2001 ). The results of these studies show that low-performing students tend to engage in dishonest practices more often. However, high-performing students also seem to be prone to cheating in highly competitive situations (Yaniv et al., 2017 ).

1.3 Present study and hypotheses

The present study serves three combined purposes.

First, based on the additional questionnaires integrated into the Program for International Student Assessment 2018 (PISA 2018) data collection in Switzerland, we provide descriptive figures on the frequency of homework effort and the various forms of digitally-supported homework avoidance practices.

Second, the data were used to identify possible factors that explain higher levels of digitally-supported homework avoidance practices. Based on our review of the literature presented in Section 1.1 , we hypothesized (Hypothesis 1 – H1) that these factors include homework effort, age, gender, socio-economic status, and study program.

Finally, we tested whether digitally-supported homework avoidance practices were a significant predictor of test score performance. We expected (Hypothesis 2 – H2) that technology-related factors influencing test scores include not only those reported by Petko et al. ( 2017 ) but also self-reported engagement in digital dishonesty practices. .

2.1 Participants

Our analyses were based on data collected for PISA 2018 in Switzerland, made available in June 2021 (Erzinger et al., 2021 ). The target sample of PISA was 15-year-old students, with a two-phase sampling: schools and then students (Erzinger et al., 2019 , p.7–8, OECD, 2019a ). A total of 228 schools were selected for Switzerland, with an original sample of 5822 students. Based on the PISA 2018 technical report (OECD, 2019a ), only participants with a minimum of three valid responses to each scale used in the statistical analyses were included (see Section 2.2 ). A final sample of 4771 responses (48% female) was used for statistical analyses. The mean age was 15 years and 9 months ( SD  = 3 months). As Switzerland is a multilingual country, 60% of the respondents completed the questionnaires in German, 23% in French, and 17% in Italian.

2.2 Measures

2.2.1 digital dishonesty in homework scale.

This six-item digital dishonesty for homework scale assesses the use of digital technology for homework avoidance and copying (IC801 C01 to C06), is intended to work as a single overall scale for digital homework dishonesty practice constructed to include items corresponding to two types of dishonest practices from Pavela ( 1997 ), namely cheating and plagiarism (see Table  1 ). Three items target individual digital practices to avoid homework, which can be referred to as plagiarism (items 1, 2 and 5). Two focus more on social digital practices, for which students are cheating together with peers (items 4 and 6). One item target cheating as peer authorized plagiarism. Response options are based on questions on the productive use of digital technologies for homework in the common PISA survey (IC010), with an additional distinction for the lowest frequency option (6-point Likert scale). The scale was not tested prior to its integration into the PISA questionnaire, as it was newly developed for the purposes of this study.

2.2.2 Homework engagement scale

The scale, originally developed by Trautwein et al. (Trautwein, 2007 ; Trautwein et al., 2006 ), measures homework engagement (IC800 C01 to C06) and can be subdivided into two sub-scales: homework compliance and homework effort. The reliability of the scale was tested and established in different variants, both in Germany (Trautwein et al., 2006 ; Trautwein & Köller, 2003 ) and in Switzerland (Schnyder et al., 2008 ; Schynder Godel, 2015 ). In the adaptation used in the PISA 2018 survey, four items were positively poled (items 1, 2, 4, and 6), and two items were negatively poled (items 3 and 5) and presented with a 4-point Likert scale ranging from “Does not apply at all” to “Applies absolutely.” This adaptation showed acceptable reliability in previous studies in Switzerland (α = 0.73 and α = 0.78). The present study focused on homework effort, and thus only data from the corresponding sub-scale was analyzed (items 2 [I always try to do all of my homework], 4 [When it comes to homework, I do my best], and 6 [On the whole, I think I do my homework more conscientiously than my classmates]).

2.2.3 Demographics

Previous studies showed that demographic characteristics, such as age, gender, and socioeconomic status, could impact learning outcomes (Jacobs et al., 2002 ) and intention to use digital tools for learning (Tarhini et al., 2014 ). Gender is a dummy variable (ST004), with 1 for female and 2 for male. Socioeconomic status was analyzed based on the PISA 2018 index of economic, social, and cultural status (ESCS). It is computed from three other indices (OECD, 2019b , Annex A1): parents’ highest level of education (PARED), parents’ highest occupational status (HISEI), and home possessions (HOMEPOS). The final ESCS score is transformed so that 0 corresponds to an average OECD student. More details can be found in Annex A1 from PISA 2018 Results Volume 3 (OECD, 2019b ).

2.2.4 Study program

Although large-scale studies on schools have accounted for the differences between schools, the study program can also be a factor that directly affects digital homework dishonesty practices. In Switzerland, 15-year-old students from the PISA sampling pool can be part of at least six main study programs, which greatly differ in terms of learning content. In this study, study programs distinguished both level and type of study: lower secondary education (gymnasial – n  = 798, basic requirements – n  = 897, advanced requirements – n  = 1235), vocational education (classic – n  = 571, with baccalaureate – n  = 275), and university entrance preparation ( n  = 745). An “other” category was also included ( n  = 250). This 6-level ordinal variable was dummy coded based on the available CNTSCHID variable.

2.2.5 Technologies and schools

The PISA 2015 ICT (Information and Communication Technology) familiarity questionnaire included most of the technology-related variables tested by Petko et al. ( 2017 ): ENTUSE (frequency of computer use at home for entertainment purposes), HOMESCH (frequency of computer use for school-related purposes at home), and USESCH (frequency of computer use at school). However, the measure of student’s attitudes toward ICT in the 2015 survey was different from that of the 2012 dataset. Based on previous studies (Arpacı et al., 2021 ; Kunina-Habenicht & Goldhammer, 2020 ), we thus included INICT (Student’s ICT interest), COMPICT (Students’ perceived ICT competence), AUTICT (Students’ perceived autonomy related to ICT use), and SOIACICT (Students’ ICT as a topic in social interaction) instead of the variable ICTATTPOS of the 2012 survey.

2.2.6 Test scores

The PISA science, mathematics, and reading test scores were used as dependent variables to test our second hypothesis. Following Aparicio et al. ( 2021 ), the mean scores from plausible values were computed for each test score and used in the test score analysis.

2.3 Data analyses

Our hypotheses aim to assess the factors explaining student digital homework dishonesty practices (H1) and test score performance (H2). At the student level, we used multilevel regression analyses to decompose the variance and estimate associations. As we used data for Switzerland, in which differences between school systems exist at the level of provinces (within and between), we also considered differences across schools (based on the variable CNTSCHID).

Data were downloaded from the main PISA repository, and additional data for Switzerland were available on forscenter.ch (Erzinger et al., 2021 ). Analyses were computed with Jamovi (v.1.8 for Microsoft Windows) statistics and R packages (GAMLj, lavaan).

3.1 Additional scales for Switzerland

3.1.1 digital dishonesty in homework practices.

The digital homework dishonesty scale (6 items), computed with the six items IC801, was found to be of very good reliability overall (α = 0.91, ω = 0.91). After checking for reliability, a mean score was computed for the overall scale. The confirmatory factor analysis for the one-dimensional model reached an adequate fit, with three modifications using residual covariances between single items χ 2 (6) = 220, p  < 0.001, TLI = 0.969, CFI = 0.988, RMSEA (Root Mean Square Error of Approximation) = 0.086, SRMR = 0.016).

On the one hand, the practice that was the least reported was copying something from the internet and presenting it as their own (51% never did). On the other hand, students were more likely to partially copy content from the internet and modify it to present as their own (47% did it at least once a month). Copying answers shared by friends was rather common, with 62% of the students reporting that they engaged in such practices at least once a month.

When all surveyed practices were taken together, 7.6% of the students reported that they had never engaged in digitally dishonest practices for homework, while 30.6% reported cheating once or twice a week, 12.1% almost every day, and 6.9% every day (Table  1 ).

3.1.2 Homework effort

The overall homework engagement scale consisted of six items (IC800), and it was found to be acceptably reliable (α = 0.76, ω = 0.79). Items 3 and 5 were reversed for this analysis. The homework compliance sub-scale had a low reliability (α = 0.58, ω = 0.64), whereas the homework effort sub-scale had an acceptable reliability (α = 0.78, ω = 0.79). Based on our rationale, the following statistical analyses used only the homework effort sub-scale. Furthermore, this focus is justified by the fact that the homework compliance scale might be statistically confounded with the digital dishonesty in homework scale.

Descriptive weighted statistics per item (Table  2 ) showed that while most students (80%) tried to complete all of their homework, only half of the students reported doing those diligently (53.3%). Most students also reported that they believed they put more effort into their homework than their peers (77.7%). The overall mean score of the composite scale was 2.81 ( SD  = 0.69).

3.2 Multilevel regression analysis: Predictors of digital dishonesty in homework (H1)

Mixed multilevel modeling was used to analyze predictors of digital homework avoidance while considering the effect of school (random component). Based on our first hypothesis, we compared several models by progressively including the following fixed effects: homework effort and personal traits (age, gender) (Model 2), then socio-economic status (Model 3), and finally, study program (Model 4). The results are presented in Table  3 . Except for the digital homework dishonesty and homework efforts scales, all other scales were based upon the scores computed according to the PISA technical report (OECD, 2019a ).

We first compared variance components. Variance was decomposed into student and school levels. Model 1 provides estimates of the variance component without any covariates. The intraclass coefficient (ICC) indicated that about 6.6% of the total variance was associated with schools. The parameter (b  = 2.56, SE b  = 0.025 ) falls within the 95% confidence interval. Further, CI is above 0 and thus we can reject the null hypothesis. Comparing the empty model to models with covariates, we found that Models 2, 3 and 4 showed an increase in total explained variance to 10%. Variance explained by the covariates was about 3% in Models 2 and 3, and about 4% in Model 4. Interestingly, in our models, student socio-economic status, measured by the PISA index, never accounted for variance in digitally-supported dishonest practices to complete homework.

Summary of the two-steps Model 4 (estimates - β, with standard errors and significance levels, *** p < 0.001)

Further, model comparison based on AIC indicates that Model 4, including homework effort, personal traits, socio-economic status, and study program, was the better fit for the data. In Model 4 (Table  3 ; Fig.  1 ), we observed that homework effort and gender were negatively associated with digital dishonesty. Male students who invested less effort in their homework were more prone to engage in digital dishonesty. The study program was positively but weakly associated with digital dishonesty. Students in programs that target higher education were less likely to engage in digital dishonesty when completing homework.

3.3 Multilevel regression analysis: Cheating and test scores (H2)

Our first hypothesis aimed to provide insights into characteristics of students reporting that they regularly use digital resources dishonestly when completing homework. Our second hypothesis focused on whether digitally-supported homework avoidance practices was linked to results of test scores. Mixed multilevel modeling was used to analyze predictors of test scores while considering the effect of school (random component). Based on the study by Petko et al. ( 2017 ), we compared several models by progressively including the following fixed effects ICT use (three measures) (Model 2), then attitude toward ICT (four measures) (Model 3), and finally, digital dishonesty in homework (single measure) (Model 4). The results are presented in Table  4 for science, Table  5 for mathematics, and Table  6 for reading.

Variance components were decomposed into student and school level. ICC for Model 1 indicated that 37.9% of the variance component without covariates was associated with schools.

Taking Model 1 as a reference, we observed an increase in total explained variance to 40.5% with factors related to ICT use (Model 2), to 40.8% with factors related to attitude toward ICT (Model 3), and to 41.1% with the single digital dishonesty factor. It is interesting to note that we obtained different results from those reported by Petko et al. ( 2017 ). In their study, they found significant effects on the explained variances of ENTUSE, USESCH, and ICTATTPOS but not of HOMESCH for Switzerland. In the present study (Model 3), HOMESCH and USESCH were significant predictors but not ENTUSE, and for attitude toward ICT, all but INTICT were significant predictors of the variance. However, factors corresponding to ICT use were negatively associated with test performance, as in the study by Petko et al. ( 2017 ). Similarly, all components of attitude toward ICT positively affected science test scores, except for students’ ICT as a topic in social interaction.

Based on the AIC values, Model 4, including ICT use, attitude toward ICT, and digital dishonesty, was the better fit for the data. The parameter ( b  = 498.00, SE b  = 3.550) shows that our sample falls within the 95% confidence interval and that we can reject the null hypothesis. In this model, all factors except the use of ICT outside of school for leisure were significant predictors of explained variance in science test scores. These results are consistent with those reported by Petko et al. ( 2017 ), in which more frequent use of ICT negatively affected science test scores, with an overall positive effect of positive attitude toward ICT. Further, we observed that homework avoidance with digital resources strongly negatively affected performance, with lower performance associated with students reporting a higher frequency of engagement in digital dishonesty practices.

For mathematics test scores, results from Models 2 and 3 showed a similar pattern than those for science, and Model 4 also explained the highest variance (41.2%). The results from Model 4 contrast with those found by Petko et al. ( 2017 ), as in this study, HOMESCH was the only significant variable of ICT use. Regarding attitudes toward ICT, only two measures (COMPICT and AUTICT) were significant positive factors in Model 4. As for science test scores, digital dishonesty practices were a significantly strong negative predictor. Students who reported cheating more frequently were more likely to perform poorly on mathematics tests.

The analyses of PISA test scores for reading in Model 2 was similar to that of science and mathematics, with ENTUSE being a non-significant predictor when we included only measures of ICT use as predictors. In Model 3, contrary to the science and mathematics test scores models, in which INICT was non-significant, all measures of attitude toward ICT were positively significant predictors. Nevertheless, as for science and mathematics, Model 4, which included digital dishonesty, explained the greater variance in reading test scores (42.2%). We observed that for reading, all predictors were significant in Model 4, with an overall negative effect of ICT use, a positive effect of attitude toward ICT—except for SOIAICT, and a negative effect of digital dishonesty on test scores. Interestingly, the detrimental effect of using digital resources to engage in dishonest homework completion was the strongest in reading test scores.

4 Discussion

In this study, we were able to provide descriptive statistics on the prevalence of digital dishonesty among secondary students in the Swiss sample of PISA 2018. Students from this country were selected because they received additional questions targeting both homework effort and the frequency with which they engaged in digital dishonesty when doing homework. Descriptive statistics indicated that fairly high numbers of students engage in dishonest homework practices, with 49.6% reporting digital dishonesty at least once or twice a week. The most frequently reported practice was copying answers from friends, which was undertaken at least once a month by more than two-thirds of respondents. Interestingly, the most infamous form of digital dishonesty, that is plagiarism by copy-pasting something from the internet (Evering & Moorman, 2012 ), was admitted to by close to half of the students (49%). These results for homework avoidance are close to those obtained by previous research on digital academic plagiarism (e.g., McCabe et al., 2001 ).

We then investigated what makes a cheater, based on students’ demographics and effort put in doing their homework (H1), before looking at digital dishonesty as an additional ICT predictor of PISA test scores (mathematics, reading, and science) (H2).

The goal of our first research hypothesis was to determine student-related factors that may predict digital homework avoidance practices. Here, we focused on factors linked to students’ personal characteristics and study programs. Our multilevel model explained about 10% of the variance overall. Our analysis of which students are more likely to digital resources to avoid homework revealed an increased probability for male students who did not put much effort into doing their homework and who were studying in a program that was not oriented toward higher education. Thus, our findings tend to support results from previous research that stresses the importance of gender and motivational factors for academic dishonesty (e.g., Anderman & Koenka,  2017 ; Krou et al., 2021 ). Yet, as our model only explained little variance and more research is needed to provide an accurate representation of the factors that lead to digital dishonesty. Future research could include more aspects that are linked to learning, such as peer-related or teaching-related factors. Possibly, how closely homework is embedded in the teaching and learning culture may play a key role in digital dishonesty. Additional factors might be linked to the overall availability and use of digital tools. For example, the report combining factors from the PISA 2018 school and student questionnaires showed that the higher the computer–student ratio, the lower students scored in the general tests (OECD, 2020b ). A positive association with reading disappeared when socio-economic background was considered. This is even more interesting when considering previous research indicating that while internet access is not a source of divide among youths, the quality of use is still different based on gender or socioeconomic status (Livingstone & Helsper, 2007 ). Thus, investigating the usage-related “digital divide” as a potential source of digital dishonesty is an interesting avenue for future research (Dolan, 2016 ).

Our second hypothesis considered that digital dishonesty in homework completion can be regarded as an additional ICT-related trait and thus could be included in models targeting the influence of traditional ICT on PISA test scores, such as Petko et al. ( 2017 ) study. Overall, our results on the influence of ICT use and attitudes toward ICT on test scores are in line with those reported by Petko et al. ( 2017 ). Digital dishonesty was found to negatively influence test scores, with a higher frequency of cheating leading to lower performance in all major PISA test domains, and particularly so for reading. For each subject, the combined models explained about 40% of the total variance.

4.1 Conclusions and recommendations

Our results have several practical implications. First, the amount of cheating on homework observed calls for new strategies for raising homework engagement, as this was found to be a clear predictor of digital dishonesty. This can be achieved by better explaining the goals and benefits of homework, the adverse effects of cheating on homework, and by providing adequate feedback on homework that was done properly. Second, teachers might consider new forms of homework that are less prone to cheating, such as doing homework in non-digital formats that are less easy to copy digitally or in proctored digital formats that allow for the monitoring of the process of homework completion, or by using plagiarism software to check homework. Sometimes, it might even be possible to give homework and explicitly encourage strategies that might be considered cheating, for example, by working together or using internet sources. As collaboration is one of the 21st century skills that students are expected to develop (Bray et al., 2020 ), this can be used to turn cheating into positive practice. There is already research showing the beneficial impact of computer-supported collaborative learning (e.g., Janssen et al., 2012 ). Zhang et al. ( 2011 ) compared three homework assignment (creation of a homepage) conditions: individually, in groups with specific instructions, and in groups with general instructions. Their results showed that computer supported collaborative homework led to better performance than individual settings, only when the instructions were general. Thus, promoting digital collaborative homework could support the development of students’ digital and collaborative skills.

Further, digital dishonesty in homework needs to be considered different from cheating in assessments. In research on assessment-related dishonesty, cheating is perceived as a reprehensible practice because grades obtained are a misrepresentation of student knowledge, and cheating “implies that efficient cheaters are good students, since they get good grades” (Bouville, 2010 , p. 69). However, regarding homework, this view is too restrictive. Indeed, not all homework is graded, and we cannot know for sure whether students answered this questionnaire while considering homework as a whole or only graded homework (assessments). Our study did not include questions about whether students displayed the same attitudes and practices toward assessments (graded) and practice exercises (non-graded), nor did it include questions on how assessments and homework were related. By cheating on ungraded practice exercises, students will primarily hamper their own learning process. Future research could investigate in more depth the kinds of homework students cheat on and why.

Finally, the question of how to foster engaging homework with digital tools becomes even more important in pandemic situations. Numerous studies following the switch to home schooling at the beginning of the 2020 COVID-19 pandemic have investigated the difficulties for parents in supporting their children (Bol, 2020 ; Parczewska, 2021 ); however, the question of digital homework has not been specifically addressed. It is unknown whether the increase in digital schooling paired with discrepancies in access to digital tools has led to an increase in digital dishonesty practices. Data from the PISA 2018 student questionnaires (OECD, 2020a ) indicated that about 90% of students have a computer for schoolwork (OECD average), but the availability per student remains unknown. Digital homework can be perceived as yet another factor of social differences (see for example Auxier & Anderson,  2020 ; Thorn & Vincent-Lancrin, 2022 ).

4.2 Limitations and directions

The limitations of the study include the format of the data collected, with the accuracy of self-reports to mirror actual practices restricted, as these measures are particularly likely to trigger response bias, such as social desirability. More objective data on digital dishonesty in homework-related purposes could, for example, be obtained by analyzing students’ homework with plagiarism software. Further, additional measures that provide a more complete landscape of contributing factors are necessary. For example, in considering digital homework as an alternative to traditional homework, parents’ involvement in homework and their attitudes toward ICT are factors that have not been considered in this study (Amzalag, 2021 ). Although our results are in line with studies on academic digital dishonesty, their scope is limited to the Swiss context. Moreover, our analyses focused on secondary students. Results might be different with a sample of younger students. As an example, Kiss and Teller ( 2022 ) measured primary students cheating practices and found that individual characteristics were not a stable predictor of cheating between age groups. Further, our models included school as a random component, yet other group variables, such as class and peer groups, may well affect digital homework avoidance strategies.

The findings of this study suggest that academic dishonesty when doing homework needs to be addressed in schools. One way, as suggested by Chow et al. ( 2021 ) and Djokovic et al. ( 2022 ), is to build on students’ practices to explain which need to be considered cheating. This recommendation for institutions to take preventive actions and explicit to students the punishment faced in case of digital academic behavior was also raised by Chiang et al. ( 2022 ). Another is that teachers may consider developing homework formats that discourage cheating and shortcuts (e.g., creating multimedia documents instead of text-based documents, using platforms where answers cannot be copied and pasted, or using advanced forms of online proctoring). It may also be possible to change homework formats toward more open formats, where today’s cheating practices are allowed when they are made transparent (open-book homework, collaborative homework). Further, experiences from the COVID-19 pandemic have stressed the importance of understanding the factors related to the successful integration of digital homework and the need to minimize the digital “homework gap” (Auxier & Anderson, 2020 ; Donnelly & Patrinos, 2021 ). Given that homework engagement is a core predictor of academic dishonesty, students should receive meaningful homework in preparation for upcoming lessons or for practicing what was learned in past lessons. Raising student’s awareness of the meaning and significance of homework might be an important piece of the puzzle to honesty in learning.

Data availability

The data that support the findings of this study are openly available in SISS base at https://doi.org/10.23662/FORS-DS-1285-1 , reference number 1285.

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List of abbreviations related to PISA datasets

students’ perceived autonomy related to ICT use

students’ perceived ICT competence

frequency of computer use at home for entertainment purposes

index of economic, social, and cultural status (computed from PARED, HISEI and HOMEPOS)

parents’ highest occupational status

home possessions

frequency of computer use for school-related purposes at home

digital cheating for homework items for Switzerland

homework engagement items for Switzerland

positive attitude towards ICT as a learning tool

student’s ICT interest

parents’ highest level of education

students’ ICT as a topic in social interaction

frequency of computer use at school

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Désiron, J.C., Petko, D. Academic dishonesty when doing homework: How digital technologies are put to bad use in secondary schools. Educ Inf Technol 28 , 1251–1271 (2023). https://doi.org/10.1007/s10639-022-11225-y

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The ‘Homework Gap’ Is About to Get Worse. What Should Schools Do?

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A program that provides discounted broadband internet service to low-income households is expected to run out of funding by the end of April, a concerning development for school districts with families that relied on the subsidy.

With the Affordable Connectivity Program , eligible families can receive a discount of up to $30 per month toward internet service. For those on qualifying tribal lands, the discount is up to $75 per month. The program also provides a one-time discount to purchase a laptop, desktop computer, or tablet from participating providers.

Nearly 23 million households have enrolled in the program since it launched in 2021, according to the Federal Communications Commission, which runs the program. However, the agency stopped accepting new enrollments as of Feb. 8 and said it will disenroll all households from the program at the end of April, unless Congress provides additional funding.

Schools are increasingly relying on technology for teaching and learning, from learning management systems to multimedia curriculum to internet research. In some cases, schools are turning inclement weather days into remote learning days . So it’s even more imperative that students have sufficient internet connectivity and devices to access learning materials while at home.

‘It’s a huge equity problem’

Educators and advocates say the possible sunsetting of the Affordable Connectivity Program could worsen the so-called “ homework gap ”—a phrase used to describe the inequities between students who have digital devices and reliable internet connectivity at home, and those who don’t and struggle to complete online assignments as a result.

“My fear is that, with this funding running out, we’re going to have either more families not having access to those services, or more families having to go someplace with open Wi-Fi that maybe isn’t as secure as it should be,” said Chantell Manahan, the director of technology for Steuben County schools, a 2,600-student district in rural northeast Indiana. The program’s expiration could also mean more “families away from home, sitting in parking lots like they were during the pandemic, and that’s not a good place for our students and families to be.”

In 2024, [internet access is] not a luxury anymore. This is a necessity to participate in modern society.

The expiration of the Affordable Connectivity Program doesn’t just affect students, but parents, too.

“Many schools rely on online communications platforms to communicate with parents and guardians about their student’s progress, school activities, and other important information. If families lose affordable internet access, this [communication] channel may be compromised,” said Julia Fallon, the executive director of the State Educational Technology Directors Association.

Sometimes, a school-issued device is the only one available to use at home, so parents also use it to look for jobs, do online coursework, or attend telehealth appointments, Manahan said.

“It’s not just a K-12 education problem. It’s a community problem. It’s a huge equity problem,” she added.

Will Congress provide more funding for ACP?

The Affordable Connectivity Program first launched as the Emergency Broadband Benefit, which was part of a pandemic relief package signed by former President Donald Trump in 2020. The next year, the program was codified as part of the bipartisan infrastructure law signed by President Joe Biden.

But the program has run through much of the initial $17.4 billion allocated by Congress, including $14.2 billion from the infrastructure law and $3.2 billion from its emergency predecessor.

In January, a bipartisan group of lawmakers introduced a bill in the Senate and the House of Representatives that would provide $7 billion to keep the Affordable Connectivity Program operational.

It’s unclear how much traction the bill will receive, but several FCC commissioners and advocacy groups have applauded the bill and urged Congress to pass the measure.

Districts look for other solutions

In the meantime, district leaders are having tough conversations about how to provide adequate internet access to students and families who relied on the program.

In Steuben County, Manahan said the district might go back to solutions it used before the Affordable Connectivity Program, such as partnerships with local businesses and organizations that would let families come in and use their Wi-Fi for virtual learning.

The district has Wi-Fi hotspot devices it can lend to students, too, though Manahan is unsure how many of those devices the district can keep after funding runs out. The devices were originally funded through ESSER and the Emergency Connectivity Fund , both of which are also expiring this year.

Fortunately, Manahan said, the FCC’s E-rate funding will now cover putting Wi-Fi on school buses .

“It’ll be much more cost-effective for the district to be able to outfit all the buses,” she said. “We know there are some places where we might be able to park those buses and have internet access available.”

Along with school bus Wi-Fi, the district could also extend the reach of the Wi-Fi on school buildings so students, families, and staff can use it in the parking lot, she said.

“I can only hope that if we do see both ACP and ECF sunsetting that they’re going to divert those funds to other programs [that would provide] internet access into all our homes,” Manahan said. “In 2024, it’s not a luxury anymore. This is a necessity to participate in modern society.”

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Technology might be making education worse

Listen to the essay, as read by Antero Garcia, associate professor in the Graduate School of Education.

As a professor of education and a former public school teacher, I’ve seen digital tools change lives in schools.

I’ve documented the ways mobile technology like phones can transform student engagement in my own classroom.

I’ve explored how digital tools might network powerful civic learning and dialogue for classrooms across the country – elements of education that are crucial for sustaining our democracy today.

And, like everyone, I’ve witnessed digital technologies make schooling safer in the midst of a global pandemic. Zoom and Google Classroom, for instance, allowed many students to attend classrooms virtually during a period when it was not feasible to meet in person.

So I want to tell you that I think technologies are changing education for the better and that we need to invest more in them – but I just can’t.

Given the substantial amount of scholarly time I’ve invested in documenting the life-changing possibilities of digital technologies, it gives me no pleasure to suggest that these tools might be slowly poisoning us. Despite their purported and transformational value, I’ve been wondering if our investment in educational technology might in fact be making our schools worse.

Let me explain.

When I was a classroom teacher, I loved relying on the latest tools to create impressive and immersive experiences for my students. We would utilize technology to create class films, produce social media profiles for the Janie Crawfords, the Holden Caulfields, and other literary characters we studied, and find playful ways to digitally share our understanding of the ideas we studied in our classrooms.

As a teacher, technology was a way to build on students’ interests in pop culture and the world around them. This was exciting to me.

But I’ve continued to understand that the aspects of technology I loved weren’t actually about technology at all – they were about creating authentic learning experiences with young people. At the heart of these digital explorations were my relationships with students and the trust we built together.

“Part of why I’ve grown so skeptical about this current digital revolution is because of how these tools reshape students’ bodies and their relation to the world around them.”

I do see promise in the suite of digital tools that are available in classrooms today. But my research focus on platforms – digital spaces like Amazon, Netflix, and Google that reshape how users interact in online environments – suggests that when we focus on the trees of individual tools, we ignore the larger forest of social and cognitive challenges.

Most people encounter platforms every day in their online social lives. From the few online retail stores where we buy groceries to the small handful of sites that stream our favorite shows and media content, platforms have narrowed how we use the internet today to a small collection of Silicon Valley behemoths. Our social media activities, too, are limited to one or two sites where we check on the updates, photos, and looped videos of friends and loved ones.

These platforms restrict our online and offline lives to a relatively small number of companies and spaces – we communicate with a finite set of tools and consume a set of media that is often algorithmically suggested. This centralization of internet – a trend decades in the making – makes me very uneasy.

From willfully hiding the negative effects of social media use for vulnerable populations to creating tools that reinforce racial bias, today’s platforms are causing harm and sowing disinformation for young people and adults alike. The deluge of difficult ethical and pedagogical questions around these tools are not being broached in any meaningful way in schools – even adults aren’t sure how to manage their online lives.

You might ask, “What does this have to do with education?” Platforms are also a large part of how modern schools operate. From classroom management software to attendance tracking to the online tools that allowed students to meet safely during the pandemic, platforms guide nearly every student interaction in schools today. But districts are utilizing these tools without considering the wider spectrum of changes that they have incurred alongside them.

Antero Garcia, associate professor of education (Image credit: Courtesy Antero Garcia)

For example, it might seem helpful for a school to use a management tool like Classroom Dojo (a digital platform that can offer parents ways to interact with and receive updates from their family’s teacher) or software that tracks student reading and development like Accelerated Reader for day-to-day needs. However, these tools limit what assessment looks like and penalize students based on flawed interpretations of learning.

Another problem with platforms is that they, by necessity, amass large swaths of data. Myriad forms of educational technology exist – from virtual reality headsets to e-readers to the small sensors on student ID cards that can track when students enter schools. And all of this student data is being funneled out of schools and into the virtual black boxes of company databases.

Part of why I’ve grown so skeptical about this current digital revolution is because of how these tools reshape students’ bodies and their relation to the world around them. Young people are not viewed as complete human beings but as boxes checked for attendance, for meeting academic progress metrics, or for confirming their location within a school building. Nearly every action that students perform in schools – whether it’s logging onto devices, accessing buildings, or sharing content through their private online lives – is noticed and recorded. Children in schools have become disembodied from their minds and their hearts. Thus, one of the greatest and implicit lessons that kids learn in schools today is that they must sacrifice their privacy in order to participate in conventional, civic society.

The pandemic has only made the situation worse. At its beginnings, some schools relied on software to track students’ eye movements, ostensibly ensuring that kids were paying attention to the tasks at hand. Similarly, many schools required students to keep their cameras on during class time for similar purposes. These might be seen as in the best interests of students and their academic growth, but such practices are part of a larger (and usually more invisible) process of normalizing surveillance in the lives of youth today.

I am not suggesting that we completely reject all of the tools at our disposal – but I am urging for more caution. Even the seemingly benign resources we might use in our classrooms today come with tradeoffs. Every Wi-Fi-connected, “smart” device utilized in schools is an investment in time, money, and expertise in technology over teachers and the teaching profession.

Our focus on fixing or saving schools via digital tools assumes that the benefits and convenience that these invisible platforms offer are worth it.

But my ongoing exploration of how platforms reduce students to quantifiable data suggests that we are removing the innovation and imagination of students and teachers in the process.

Antero Garcia is associate professor of education in the Graduate School of Education .

In Their Own Words is a collaboration between the Stanford Public Humanities Initiative  and Stanford University Communications.

If you’re a Stanford faculty member (in any discipline or school) who is interested in writing an essay for this series, please reach out to Natalie Jabbar at [email protected] .

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Jessica Grose

Every tech tool in the classroom should be ruthlessly evaluated.

By Jessica Grose

Opinion Writer

Educational technology in schools is sometimes described as a wicked problem — a term coined by a design and planning professor, Horst Rittel, in the 1960s , meaning a problem for which even defining the scope of the dilemma is a struggle, because it has so many interconnected parts that never stop moving.

When you have a wicked problem, solutions have to be holistic, flexible and developmentally appropriate. Which is to say that appropriate tech use for elementary schoolers in rural Oklahoma isn’t going to be the same as appropriate tech use in a Chicago high school.

I spent the past few weeks speaking with parents, teachers, public school administrators and academics who study educational technology. And while there are certainly benefits to using tech as a classroom tool, I’m convinced that when it comes to the proliferation of tech in K-12 education, we need “ a hard reset ,” as Julia Freeland Fisher of the Christensen Institute put it, concurring with Jonathan Haidt in his call for rolling back the “phone-based childhood.” When we recently spoke, Fisher stressed that when we weigh the benefits of ed tech, we’re often not asking, “What’s happening when it comes to connectedness and well-being?”

Well said. We need a complete rethink of the ways that we’re evaluating and using tech in classrooms; the overall change that I want to see is that tech use in schools — devices and apps — should be driven by educators, not tech companies.

In recent years, tech companies have provided their products to schools either free or cheap , and then schools have tried to figure out how to use those products. Wherever that dynamic exists, it should be reversed: Districts and individual schools should first figure out what tech would be most useful to their students, and their bar for “useful” should be set by available data and teacher experience. Only then should they acquire laptops, tablets and educational software.

As Mesut Duran — a professor of educational technology at the University of Michigan, Dearborn, and the author of “Learning Technologies: Research, Trends and Issues in the U.S. Education System” — told me, a lot of the technology that’s used in classrooms wasn’t developed with students in mind. “Most of the technologies are initially created for commercial purposes,” he said, “and then we decide how to use them in schools.”

In many cases, there’s little or no evidence that the products actually work, and “work” can have various meanings here: It’s not conclusive that tech, as opposed to hard-copy materials, improves educational outcomes. And sometimes devices or programs simply don’t function the way they’re supposed to. For example, artificial intelligence in education is all the rage, but then we get headlines like this one, in February, from The Wall Street Journal: “ We Tested an A.I. Tutor for Kids. It Struggled With Basic Math. ”

Alex Molnar, one of the directors of the National Educational Policy Center at the University of Colorado, Boulder, said that every school should be asking if the tech it’s using is both necessary and good. “The tech industry’s ethos is: If it’s doable, it is necessary. But for educators, that has to be an actual question: Is this necessary?” Even after you’ve cleared the bar of necessary, he said, educators should be asking, “Is doing it this way good, or could we do it another way that would be better? Better in the ethical sense and the pedagogical sense.”

With that necessary and good standard in mind, here are some specific recommendations that I’ve taken away from several discussions and a lot of reading. It’s unrealistic — and considering that we’re in a tech-saturated world, not ideal — to get rid of every last bit of educational technology. But we’re currently failing too many children by letting it run rampant.

At the State and Federal Levels: Privacy Protections and Better Evaluation

A complaint I heard from many public school parents who responded to my March 27 questionnaire and wanted a lower-tech environment for their kids is that they’re concerned about their children’s privacy. They couldn’t opt out of things like Google Classroom, they said, because in many cases, all of their children’s homework assignments were posted there. Molnar has a radical but elegant solution for this problem: “All data gathered must be destroyed after its intended purpose has been accomplished.” So if the intended purpose of a platform or application is grading, for example, the data would be destroyed at the end of the school year; it couldn’t be sold to a third party or used to further enhance the product or as a training ground for artificial intelligence.

Another recommendation — from a recent paper by the University of Edinburgh’s Ben Williamson, Molnar and the University of Colorado, Boulder’s Faith Boninger outlining the risks of A.I. in the classroom — is for the creation of an “independent government entity charged with ensuring the quality of digital educational products used in schools” that would evaluate tech before it is put into schools and “periodically thereafter.” Because the technology is always evolving, our oversight of it needs to be, as well.

At the District Level: Centralize the Tech-Vetting Process

Stephanie Sheron is the chief of strategic initiatives for the Montgomery County Public Schools, the largest district in Maryland, and all the district’s technology departments report to her. She likened the tech landscape, coming out of the Covid-19 pandemic remote school period, to the “Wild West.” School districts were flooded with different kinds of ed tech in an emergency situation in which teachers were desperately trying to engage their students, and a lot of relief money was pouring in from the federal government. When the dust settled, she said, the question was, “Now what do we do? How do we control this? How do we make sure that we’re in alignment with FERPA and COPPA and all of those other student data privacy components?”

To address this, Sheron said, her district has secured grant funding to hire a director of information security, who will function as the hub for all the educational technology vending and evaluate new tech. Part of the standardization that the district has been undergoing is a requirement that to be considered, curriculum vendors must offer both digital and hard-copy resources. She said her district tried to look at tech as a tool, adding: “A pencil is a tool for learning, but it’s not the only modality. Same thing with technology. We look at it as a tool, not as the main driver of the educational experience.”

At the Classroom Level: Ruthlessly Evaluate Every Tool

In my conversations with teachers, I’ve been struck by their descriptions of the cascade of tech use — that more tech is often offered as a solution to problems created by tech. For example, paid software like GoGuardian, which allows teachers to monitor every child’s screen, has been introduced to solve the problem of students goofing off on their laptops. But there’s a simple, free, low-tech solution to this problem that Doug Showley, a high school English teacher in Indiana I spoke to, employs: He makes all his students face their computer screens in his direction.

Every teacher who is concerned about tech use in his or her classroom should do a tech audit. There are several frameworks ; I like the worksheet created by Beth Pandolpho and Katie Cubano, the authors of “Choose Your Own Master Class: Urgent Ideas to Invigorate Your Professional Learning.” In the chapter “Balancing Technology Use in the Classroom,” they suggest that teachers list every tech tool they are using and evaluate its specific functions, asking, “Are these novel or duplicative?” They also encourage teachers to write out a defense of the tool and the frequency of use.

I like these questions because they make clear that the solutions are not going to be one size fits all.

Students Deserve Authentic Connection

As I close out this series, I want to return to what Fisher said about the importance of student connection and well-being. Of course academic outcomes matter. I want our kids to learn as much about as many different topics as they can. I care about falling test scores and think they’re an important piece of data.

But test scores are only one kind of information. A key lesson we should have learned from 2020 and ’21 is that school is about so much more than just academics. It’s about socialization, critical thinking, community and learning how to coexist with people who are different from you. I don’t know that all of these are things that can be tracked in a scientific way, which brings me back to the idea of tech in schools as a wicked problem: These aren’t easily measurable outcomes.

Jeff Frank, a professor of education at St. Lawrence University, expresses a sense that I’ve had very well in a paper , “Sounding the Call to Teach in a Social Media Age: Renewing the Importance of Philosophy in Teacher Education.” He says students are “hungry for experiences that make them feel alive and authentically connected to other people and to deeper sources of value. Though filtering and managing life through technologies offers safety, predictability and a sense of control, it also leads to life that can feel extremely small, constraining and lonely. Teaching can offer a powerful way to pierce this bubble.”

Ultimately, I believe the only way kids will be able to find that deeper meaning is through human relationships with their peers and teachers, no matter how shiny an A.I. tutor appears to be at first blush.

Jessica Grose is an Opinion writer for The Times, covering family, religion, education, culture and the way we live now.

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About 1 in 5 U.S. teens who’ve heard of ChatGPT have used it for schoolwork

Roughly one-in-five teenagers who have heard of ChatGPT say they have used it to help them do their schoolwork, according to a new Pew Research Center survey of U.S. teens ages 13 to 17. With a majority of teens having heard of ChatGPT, that amounts to 13% of all U.S. teens who have used the generative artificial intelligence (AI) chatbot in their schoolwork.

Teens in higher grade levels are particularly likely to have used the chatbot to help them with schoolwork. About one-quarter of 11th and 12th graders who have heard of ChatGPT say they have done this. This share drops to 17% among 9th and 10th graders and 12% among 7th and 8th graders.

There is no significant difference between teen boys and girls who have used ChatGPT in this way.

The introduction of ChatGPT last year has led to much discussion about its role in schools , especially whether schools should integrate the new technology into the classroom or ban it .

Pew Research Center conducted this analysis to understand American teens’ use and understanding of ChatGPT in the school setting.

The Center conducted an online survey of 1,453 U.S. teens from Sept. 26 to Oct. 23, 2023, via Ipsos. Ipsos recruited the teens via their parents, who were part of its KnowledgePanel . The KnowledgePanel is a probability-based web panel recruited primarily through national, random sampling of residential addresses. The survey was weighted to be representative of U.S. teens ages 13 to 17 who live with their parents by age, gender, race and ethnicity, household income, and other categories.

This research was reviewed and approved by an external institutional review board (IRB), Advarra, an independent committee of experts specializing in helping to protect the rights of research participants.

Here are the  questions used for this analysis , along with responses, and its  methodology .

Teens’ awareness of ChatGPT

Overall, two-thirds of U.S. teens say they have heard of ChatGPT, including 23% who have heard a lot about it. But awareness varies by race and ethnicity, as well as by household income:

• 72% of White teens say they’ve heard at least a little about ChatGPT, compared with 63% of Hispanic teens and 56% of Black teens.
• 75% of teens living in households that make $75,000 or more annually have heard of ChatGPT. Much smaller shares in households with incomes between $30,000 and $74,999 (58%) and less than $30,000 (41%) say the same.

Teens who are more aware of ChatGPT are more likely to use it for schoolwork. Roughly a third of teens who have heard a lot about ChatGPT (36%) have used it for schoolwork, far higher than the 10% among those who have heard a little about it.

When do teens think it’s OK for students to use ChatGPT?

For teens, whether it is – or is not – acceptable for students to use ChatGPT depends on what it is being used for.

There is a fair amount of support for using the chatbot to explore a topic. Roughly seven-in-ten teens who have heard of ChatGPT say it’s acceptable to use when they are researching something new, while 13% say it is not acceptable.

However, there is much less support for using ChatGPT to do the work itself. Just one-in-five teens who have heard of ChatGPT say it’s acceptable to use it to write essays, while 57% say it is not acceptable. And 39% say it’s acceptable to use ChatGPT to solve math problems, while a similar share of teens (36%) say it’s not acceptable.

Some teens are uncertain about whether it’s acceptable to use ChatGPT for these tasks. Between 18% and 24% say they aren’t sure whether these are acceptable use cases for ChatGPT.

Those who have heard a lot about ChatGPT are more likely than those who have only heard a little about it to say it’s acceptable to use the chatbot to research topics, solve math problems and write essays. For instance, 54% of teens who have heard a lot about ChatGPT say it’s acceptable to use it to solve math problems, compared with 32% among those who have heard a little about it.

Note: Here are the  questions used for this analysis , along with responses, and its  methodology .

• Artificial Intelligence
• Technology Adoption
• Teens & Tech

Olivia Sidoti is a research assistant focusing on internet and technology research at Pew Research Center

Jeffrey Gottfried is an associate director focusing on internet and technology research at Pew Research Center

Many Americans think generative AI programs should credit the sources they rely on

Americans’ use of chatgpt is ticking up, but few trust its election information, q&a: how we used large language models to identify guests on popular podcasts, striking findings from 2023, what the data says about americans’ views of artificial intelligence, most popular.

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Creative Holiday Homework for Class 8 Science: Ideas and Exercises

• Updated on  
• Apr 23, 2024

Here are some interesting ideas for creative holiday homework for Class 8 Science. As educators, you should understand the importance of fostering curiosity and engagement, even during vacation periods. In this blog, we have curated a diverse range of activities, exercises, projects, and frequently asked questions to make learning science not only informative but also enjoyable and interactive. So, whether you are a student seeking inspiration or a teacher looking to infuse your curriculum with creativity, join us on this journey of exploration and discovery in the fascinating world of science!

Table of Contents

• 1.1 Experiments 
• 1.2 Creative Presentations
• 2.1 CBSE Class 8 Short Answer Questions
• 2.2 CBSE Class 8 MCQs
• 2.3 CBSE Class 8 Long Answer Questions
• 3 Creative Holiday Homework for Class 8 Science: Projects

Creative Holiday Homework for Class 8 Science: Ideas

To begin with, we have enlisted experiments and presentation ideas for creative holiday homework for class 8 science students.

Experiments 

• As teachers, you can ask students to choose a scientific concept they learned in class (like acids and bases, and chemical reactions) and design a fun and safe experiment around it. Tell students to prepare a presentation explaining the science behind the experiment. 
• In addition, you can ask Class 8 students to design a working model that demonstrates a sustainable practice (like a solar water heater or a rainwater collector). Suggest they use recycled materials whenever possible and explain the science behind how their model works, once the school reopens. 
• Moreover, ask your students, Is there a common science myth they have heard (like sugar makes you hyper)? Based on their answers, tell them to design an experiment to test the myth and creatively present their findings, like a comic strip or a video after the summer vacation. 

Creative Presentations

• Introduce a recent scientific breakthrough or discovery to your students. Now, ask them to create a news report (written, video, or even a mock radio broadcast) during the summer vacation. Once the classes resume, ask each one of them to explain the science behind it clearly and engagingly.
• Furthermore, you can suggest students write a short story about a future technology based on scientific concepts they have learned recently. Tell them to explain how the technology works and its potential benefits or drawbacks in their respective stories.
• Besides, you can ask your pupils to research the history of a scientific discovery or invention (like vaccines or electricity). Thereafter, tell them to present their findings on a timeline or create a short play or skit showing the scientists involved and their challenges.

Also Read: Class 3 Holiday Homework- Session 2024-25

Creative Holiday Homework for Class 8 Science: Exercises

Thereafter, this section introduces different types of exercises for creative holiday homework for Class 8 Science. 

CBSE Class 8 Short Answer Questions

Cbse class 8 mcqs, cbse class 8 long answer questions.

Also Read: Exciting Holiday Homework Ideas for Class 2

Creative Holiday Homework for Class 8 Science: Projects

Finally, let us have a look at projects for creative holiday homework for class 8 science. 

Ans: Make holiday homework creative by incorporating art, multimedia, or interactive elements. Use storytelling, presentations, or hands-on projects. Collaborate with classmates or explore real-world applications for a unique touch.

Ans: During summer vacation, set aside specific times for homework to maintain consistency. Break tasks into manageable chunks, utilize effective study techniques and create a conducive environment. Reward yourself for completing tasks to stay motivated and ensure a balanced approach to learning and leisure.

Ans: Here are some interesting ideas: – Ask students to choose a scientific concept they learned in class (like acids and bases, and chemical reactions) and design a fun and safe experiment around it.  – Suggest students write a short story about a future technology based on scientific concepts they have learned recently. Tell them to explain how the technology works and its potential benefits or drawbacks in their respective stories.

Follow the school education page of Leverage Edu to discover other holiday homework and project ideas for school students. 

Ankita Singh

Ankita is a history enthusiast with a few years of experience in academic writing. Her love for literature and history helps her curate engaging and informative content for education blog. When not writing, she finds peace in analysing historical and political anectodes.

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Clarkson University celebrates $6.1B federal investment into Micron

POTSDAM, N.Y. (WWTI) — A win for Micron Technology and Northern New York STEM education.

In mid-April, Micron was awarded $6.1 in federal funding to support the construction of its $100 billion megafab in Central New York.

U.S. President Joe Biden visited Syracuse to celebrate the major federal investment on April 25.

Micron’s campus in Clay, New York will be built over the next 20 years. According to the company’s plans the semiconductor factory, will cover about 2.4 million square feet, which is the size of almost 40 football fields.

The new federal investment has excited local higher education institutions, like Clarkson University.

“The bottom line is that you’re bringing bringing a company like Micron into the New York sort of chip manufacturing fold is really, really good,” Devon Shipp, the director of Clarkson’s Center for Advanced Materials Processing said.

The Center for Advanced Materials Processing, otherwise known as CAMP, has been at the forefront of worldwide semiconductor research since the 1980s.

With this reputation, they are now leading projects with Micron. CAMP’s main projects include Chemical Mechanical Planarization and environmental sustainbility of chip manufacturing.

“One of the key components of a chip manufacturing process is to deposit layer upon layer of materials at a really, really small level, like atomically flat surfaces. To be able to make sure that those materials are completely flat, there’s a technology called Chemical mechanical planarization or CMP,” Shipp explained. “Sort of really understanding and pushing that technology to its limits or that can be faster or smaller and so on.”

Shipp is also a professor of  chemistry and biomolecular science at Clarkson.

He added that the entire University has worked to train its students and create the next generation of Micron workers.

“Students really get to know not just the technology, but they get sort of ingrained in the fabric of the research projects and then they getting engaged with people who work in industry,” Shipp said.

So Shipp, his students, fellow faculty and Clarkson University as a whole, are excited for Micron’s move to Central New York.

“While I have to add other fabs, I think there’s something even more exciting about this being, you know, literally just down the road,” Shipp expressed. “Clarkson has carved out it’s sort of a niche area where it can be is successful and we can collaborate with the other universities, other entities around around New York State and make sure that we’re sort of fully successful.”

For the latest news, weather, sports, and streaming video, head to WETM - MyTwinTiers.com.

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Breaking gender barriers through education

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Roseline Adewuyi  is a fervent advocate for gender equality in Nigeria, driven by a passion for dismantling entrenched gender stereotypes. She spoke to Africa Renewal’s  Kingsley Ighobor on the need to empower girls through education. This is in line with the African Union’s theme for 2024: Educating and skilling Africa for the 21 st   Century.

Roseline Adewuyi believes that fighting gender inequality requires raising awareness and empowering young women and girls through education.

“My goal is to help break those barriers that limit our potential,” she told  African Renewal  in an interview. “I am talking about issues related to land rights, access to education, economic empowerment, leadership, and trust me, gender discrimination.”

Gender discrimination, she explains, is heightened during times of severe economic constraints such as now, when the tendency is often to invest in boys over girls. “That’s when parents often choose to send their sons to school or provide them start-up funding for business ventures, while daughters are expected to focus on house chores and wait for marriage. It’s absolutely absurd.” she insists. 

Roseline has her work cut out for her. “We are constantly finding ways to help women and girls break free from these constraints.” 

She founded the Ending Gender Stereotypes in Schools (ENGENDERS) project, which is dedicated to unlearning gender stereotypes in educational institutions.

“We reach the students, boys and girls in high schools and universities, and we do community engagement, speaking to parents and other influential community inhabitants,” she explains.

Already, she claims to have reached tens of communities and over 6,000 young girls through seminars and webinars, while her  blog , featuring over 300 articles on gender equity, has garnered a wide audience.

Currently pursuing a Ph.D. in French Literature with a focus on women, gender, and sexuality studies at Purdue University in Indiana, US, Roseline now aims to merge academic rigour with passionate advocacy.

“It’s an interesting intersection,” she says, adding that “The body of knowledge that we pass on to future generations is full of gender stereotypes. Our books need to be gender conscious.

“In most African literature, characters often depict women or girls as housemaids and men as pilots or engineers. It reinforces stereotypes; we need to root it out,” she stresses.

Roseline's journey into gender advocacy began in her childhood, fueled by a belief in the transformative power of education. She recognized the systemic challenges faced by African women and girls, including limited access to education and entrenched cultural biases.

“When I served as a prefect in secondary school, the belief among boys and even some girls was that I did not merit the position, that leadership was reserved for the boys. That experience sparked my curiosity as to why girls weren’t perceived as equally competent as boys.”

In 2019, she worked as a translator and interpreter for the African Union (AU), having been selected as one of 120 young people from various African countries to participate in the AU Youth Volunteer Corps. 

Her exposure to continental leaders' efforts to address gender-related challenges reinforced her conviction that gender equality is essential for achieving sustainable peace and security.

“At the AU, I also realized the connection between gender and peace and security. When there is a crisis, it is women who suffer the most. Therefore, women must be at the centre of efforts to achieve peace in our societies,” she adds.

Her international exposure includes being a participant in the Young African Leaders Initiative in 2016 (YALI – Regional Leadership Center West Africa), as well as being a Dalai Lama fellow in 2018. She says these experiences exposed her to gender best practices and strengthened her resolve to advocate for change in her home country.

Although some advances have been made in gender equality in Nigeria, Roseline highlights that the remaining hurdles include challenges in female land ownership, financial inclusion, and access to education.

“For example, we have laws [in Nigeria] that provide for women’s rights to land, but many communities still prevent them from owning a piece of land. We also have situations in which widows are not allowed to inherit the properties of their husbands. 

She says: “So, we have a lot more work to do. We need effective community engagement in raising awareness among women about their rights.

“Importantly, we need to provide women with access to education to equip them with the knowledge and skills to assert their rights effectively.”

In her ongoing advocacy work, she acknowledges facing cyberbullying, which she attributes to resistance from elements of a patriarchal society reluctant to embrace progress.

Roseline's final message to young African women and girls is for them to drive positive change, stand up for their rights, and challenge gender norms.

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30 Best universities for Mechanical Engineering in Moscow, Russia

Updated: February 29, 2024

• Art & Design
• Computer Science
• Engineering
• Environmental Science
• Liberal Arts & Social Sciences
• Mathematics

Below is a list of best universities in Moscow ranked based on their research performance in Mechanical Engineering. A graph of 269K citations received by 45.8K academic papers made by 30 universities in Moscow was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. Moscow State University

For Mechanical Engineering

2. Bauman Moscow State Technical University

3. National Research University Higher School of Economics

4. Moscow Aviation Institute

5. N.R.U. Moscow Power Engineering Institute

6. National Research Nuclear University MEPI

7. National University of Science and Technology "MISIS"

8. Moscow Institute of Physics and Technology

9. Moscow State Technological University "Stankin"

10. RUDN University

11. Moscow Polytech

12. Moscow State University of Railway Engineering

13. Finance Academy under the Government of the Russian Federation

14. Moscow Medical Academy

15. Russian State University of Oil and Gas

16. mendeleev university of chemical technology of russia.

17. Russian National Research Medical University

18. Plekhanov Russian University of Economics

19. National Research University of Electronic Technology

20. Moscow State Pedagogical University

21. Russian Presidential Academy of National Economy and Public Administration

22. State University of Management

23. Moscow State Institute of International Relations

24. Russian State Geological Prospecting University

25. russian state agricultural university.

26. New Economic School

27. Moscow State Technical University of Civil Aviation

28. Russian State University for the Humanities

29. Russian State Social University

30. Moscow State Linguistic University

Universities for Mechanical Engineering near Moscow

Engineering subfields in moscow.

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