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Why Students Cheat on Homework and How to Prevent It

One of the most frustrating aspects of teaching in today’s world is the cheating epidemic. There’s nothing more irritating than getting halfway through grading a large stack of papers only to realize some students cheated on the assignment. There’s really not much point in teachers grading work that has a high likelihood of having been copied or otherwise unethically completed. So. What is a teacher to do? We need to be able to assess students. Why do students cheat on homework, and how can we address it?

Like most new teachers, I learned the hard way over the course of many years of teaching that it is possible to reduce cheating on homework, if not completely prevent it. Here are six suggestions to keep your students honest and to keep yourself sane.

ASSIGN LESS HOMEWORK

One of the reasons students cheat on homework is because they are overwhelmed. I remember vividly what it felt like to be a high school student in honors classes with multiple extracurricular activities on my plate. Other teens have after school jobs to help support their families, and some don’t have a home environment that is conducive to studying.

While cheating is never excusable under any circumstances, it does help to walk a mile in our students’ shoes. If they are consistently making the decision to cheat, it might be time to reduce the amount of homework we are assigning.

I used to give homework every night – especially to my advanced students. I wanted to push them. Instead, I stressed them out. They wanted so badly to be in the Top 10 at graduation that they would do whatever they needed to do in order to complete their assignments on time – even if that meant cheating.

When assigning homework, consider the at-home support, maturity, and outside-of-school commitments involved. Think about the kind of school and home balance you would want for your own children. Go with that.

PROVIDE CLASS TIME

Allowing students time in class to get started on their assignments seems to curb cheating to some extent. When students have class time, they are able to knock out part of the assignment, which leaves less to fret over later. Additionally, it gives them an opportunity to ask questions.

When students are confused while completing assignments at home, they often seek “help” from a friend instead of going in early the next morning to request guidance from the teacher. Often, completing a portion of a homework assignment in class gives students the confidence that they can do it successfully on their own. Plus, it provides the social aspect of learning that many students crave. Instead of fighting cheating outside of class , we can allow students to work in pairs or small groups in class to learn from each other.

Plus, to prevent students from wanting to cheat on homework, we can extend the time we allow them to complete it. Maybe students would work better if they have multiple nights to choose among options on a choice board. Home schedules can be busy, so building in some flexibility to the timeline can help reduce pressure to finish work in a hurry.

GIVE MEANINGFUL WORK

If you find students cheat on homework, they probably lack the vision for how the work is beneficial. It’s important to consider the meaningfulness and valuable of the assignment from students’ perspectives. They need to see how it is relevant to them.

In my class, I’ve learned to assign work that cannot be copied. I’ve never had luck assigning worksheets as homework because even though worksheets have value, it’s generally not obvious to teenagers. It’s nearly impossible to catch cheating on worksheets that have “right or wrong” answers. That’s not to say I don’t use worksheets. I do! But. I use them as in-class station, competition, and practice activities, not homework.

So what are examples of more effective and meaningful types of homework to assign?

Ask students to complete a reading assignment and respond in writing .
Have students watch a video clip and answer an oral entrance question.
Require that students contribute to an online discussion post.
Assign them a reflection on the day’s lesson in the form of a short project, like a one-pager or a mind map.

As you can see, these options require unique, valuable responses, thereby reducing the opportunity for students to cheat on them. The more open-ended an assignment is, the more invested students need to be to complete it well.

DIFFERENTIATE

Part of giving meaningful work involves accounting for readiness levels. Whenever we can tier assignments or build in choice, the better. A huge cause of cheating is when work is either too easy (and students are bored) or too hard (and they are frustrated). Getting to know our students as learners can help us to provide meaningful differentiation options. Plus, we can ask them!

This is what you need to be able to demonstrate the ability to do. How would you like to show me you can do it?

Wondering why students cheat on homework and how to prevent it? This post is full of tips that can help. #MiddleSchoolTeacher #HighSchoolTeacher #ClassroomManagement

REDUCE THE POINT VALUE

If you’re sincerely concerned about students cheating on assignments, consider reducing the point value. Reflect on your grading system.

Are homework grades carrying so much weight that students feel the need to cheat in order to maintain an A? In a standards-based system, will the assignment be a key determining factor in whether or not students are proficient with a skill?

Each teacher has to do what works for him or her. In my classroom, homework is worth the least amount out of any category. If I assign something for which I plan on giving completion credit, the point value is even less than it typically would be. Projects, essays, and formal assessments count for much more.

CREATE AN ETHICAL CULTURE

To some extent, this part is out of educators’ hands. Much of the ethical and moral training a student receives comes from home. Still, we can do our best to create a classroom culture in which we continually talk about integrity, responsibility, honor, and the benefits of working hard. What are some specific ways can we do this?

Building Community and Honestly

Talk to students about what it means to cheat on homework. Explain to them that there are different kinds. Many students are unaware, for instance, that the “divide and conquer (you do the first half, I’ll do the second half, and then we will trade answers)” is cheating.
As a class, develop expectations and consequences for students who decide to take short cuts.
Decorate your room with motivational quotes that relate to honesty and doing the right thing.
Discuss how making a poor decision doesn’t make you a bad person. It is an opportunity to grow.
Share with students that you care about them and their futures. The assignments you give them are intended to prepare them for success.
Offer them many different ways to seek help from you if and when they are confused.
Provide revision opportunities for homework assignments.
Explain that you partner with their parents and that guardians will be notified if cheating occurs.
Explore hypothetical situations. What if you have a late night? Let’s pretend you don’t get home until after orchestra and Lego practices. You have three hours of homework to do. You know you can call your friend, Bob, who always has his homework done. How do you handle this situation?

EDUCATE ABOUT PLAGIARISM

Many students don’t realize that plagiarism applies to more than just essays. At the beginning of the school year, teachers have an energized group of students, fresh off of summer break. I’ve always found it’s easiest to motivate my students at this time. I capitalize on this opportunity by beginning with a plagiarism mini unit .

While much of the information we discuss is about writing, I always make sure my students know that homework can be plagiarized. Speeches can be plagiarized. Videos can be plagiarized. Anything can be plagiarized, and the repercussions for stealing someone else’s ideas (even in the form of a simple worksheet) are never worth the time saved by doing so.

In an ideal world, no one would cheat. However, teaching and learning in the 21st century is much different than it was fifty years ago. Cheating? It’s increased. Maybe because of the digital age… the differences in morals and values of our culture… people are busier. Maybe because students don’t see how the school work they are completing relates to their lives.

No matter what the root cause, teachers need to be proactive. We need to know why students feel compelled to cheat on homework and what we can do to help them make learning for beneficial. Personally, I don’t advocate for completely eliminating homework with older students. To me, it has the potential to teach students many lessons both related to school and life. Still, the “right” answer to this issue will be different for each teacher, depending on her community, students, and culture.

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The launch of ChatGPT and other artificial intelligence (AI) chatbots has triggered an alarm for many educators, who worry about students using the technology to cheat by passing its writing off as their own. But two Stanford researchers say that concern is misdirected, based on their ongoing research into cheating among U.S. high school students before and after the release of ChatGPT.

“There’s been a ton of media coverage about AI making it easier and more likely for students to cheat,” said Denise Pope , a senior lecturer at Stanford Graduate School of Education (GSE). “But we haven’t seen that bear out in our data so far. And we know from our research that when students do cheat, it’s typically for reasons that have very little to do with their access to technology.”

Pope is a co-founder of Challenge Success , a school reform nonprofit affiliated with the GSE, which conducts research into the student experience, including students’ well-being and sense of belonging, academic integrity, and their engagement with learning. She is the author of Doing School: How We Are Creating a Generation of Stressed-Out, Materialistic, and Miseducated Students , and coauthor of Overloaded and Underprepared: Strategies for Stronger Schools and Healthy, Successful Kids.

Victor Lee is an associate professor at the GSE whose focus includes researching and designing learning experiences for K-12 data science education and AI literacy. He is the faculty lead for the AI + Education initiative at the Stanford Accelerator for Learning and director of CRAFT (Classroom-Ready Resources about AI for Teaching), a program that provides free resources to help teach AI literacy to high school students.

Here, Lee and Pope discuss the state of cheating in U.S. schools, what research shows about why students cheat, and their recommendations for educators working to address the problem.

Denise Pope

What do we know about how much students cheat?

Pope: We know that cheating rates have been high for a long time. At Challenge Success we’ve been running surveys and focus groups at schools for over 15 years, asking students about different aspects of their lives — the amount of sleep they get, homework pressure, extracurricular activities, family expectations, things like that — and also several questions about different forms of cheating.

For years, long before ChatGPT hit the scene, some 60 to 70 percent of students have reported engaging in at least one “cheating” behavior during the previous month. That percentage has stayed about the same or even decreased slightly in our 2023 surveys, when we added questions specific to new AI technologies, like ChatGPT, and how students are using it for school assignments.

Isn’t it possible that they’re lying about cheating?

Pope: Because these surveys are anonymous, students are surprisingly honest — especially when they know we’re doing these surveys to help improve their school experience. We often follow up our surveys with focus groups where the students tell us that those numbers seem accurate. If anything, they’re underreporting the frequency of these behaviors.

Lee: The surveys are also carefully written so they don’t ask, point-blank, “Do you cheat?” They ask about specific actions that are classified as cheating, like whether they have copied material word for word for an assignment in the past month or knowingly looked at someone else’s answer during a test. With AI, most of the fear is that the chatbot will write the paper for the student. But there isn’t evidence of an increase in that.

So AI isn’t changing how often students cheat — just the tools that they’re using?

Lee: The most prudent thing to say right now is that the data suggest, perhaps to the surprise of many people, that AI is not increasing the frequency of cheating. This may change as students become increasingly familiar with the technology, and we’ll continue to study it and see if and how this changes.

But I think it’s important to point out that, in Challenge Success’ most recent survey, students were also asked if and how they felt an AI chatbot like ChatGPT should be allowed for school-related tasks. Many said they thought it should be acceptable for “starter” purposes, like explaining a new concept or generating ideas for a paper. But the vast majority said that using a chatbot to write an entire paper should never be allowed. So this idea that students who’ve never cheated before are going to suddenly run amok and have AI write all of their papers appears unfounded.

But clearly a lot of students are cheating in the first place. Isn’t that a problem?

Pope: There are so many reasons why students cheat. They might be struggling with the material and unable to get the help they need. Maybe they have too much homework and not enough time to do it. Or maybe assignments feel like pointless busywork. Many students tell us they’re overwhelmed by the pressure to achieve — they know cheating is wrong, but they don’t want to let their family down by bringing home a low grade.

We know from our research that cheating is generally a symptom of a deeper, systemic problem. When students feel respected and valued, they’re more likely to engage in learning and act with integrity. They’re less likely to cheat when they feel a sense of belonging and connection at school, and when they find purpose and meaning in their classes. Strategies to help students feel more engaged and valued are likely to be more effective than taking a hard line on AI, especially since we know AI is here to stay and can actually be a great tool to promote deeper engagement with learning.

What would you suggest to school leaders who are concerned about students using AI chatbots?

Pope: Even before ChatGPT, we could never be sure whether kids were getting help from a parent or tutor or another source on their assignments, and this was not considered cheating. Kids in our focus groups are wondering why they can't use ChatGPT as another resource to help them write their papers — not to write the whole thing word for word, but to get the kind of help a parent or tutor would offer. We need to help students and educators find ways to discuss the ethics of using this technology and when it is and isn't useful for student learning.

Lee: There’s a lot of fear about students using this technology. Schools have considered putting significant amounts of money in AI-detection software, which studies show can be highly unreliable. Some districts have tried blocking AI chatbots from school wifi and devices, then repealed those bans because they were ineffective.

AI is not going away. Along with addressing the deeper reasons why students cheat, we need to teach students how to understand and think critically about this technology. For starters, at Stanford we’ve begun developing free resources to help teachers bring these topics into the classroom as it relates to different subject areas. We know that teachers don’t have time to introduce a whole new class, but we have been working with teachers to make sure these are activities and lessons that can fit with what they’re already covering in the time they have available.

I think of AI literacy as being akin to driver’s ed: We’ve got a powerful tool that can be a great asset, but it can also be dangerous. We want students to learn how to use it responsibly.

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The Real Roots of Student Cheating

Let's address the mixed messages we are sending to young people..

Updated September 28, 2023 | Reviewed by Ray Parker

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Cheating is rampant, yet young people consistently affirm honesty and the belief that cheating is wrong.
This discrepancy arises, in part, from the tension students perceive between honesty and the terms of success.
In an integrated environment, achievement and the real world are not seen as at odds with honesty.

The release of ChatGPT has high school and college teachers wringing their hands. A Columbia University undergraduate rubbed it in our face last May with an opinion piece in the Chronicle of Higher Education titled I’m a Student. You Have No Idea How Much We’re Using ChatGPT.

He goes on to detail how students use the program to “do the lion’s share of the thinking,” while passing off the work as their own. Catching the deception , he insists, is impossible.

As if students needed more ways to cheat. Every survey of students, whether high school or college, has found that cheating is “rampant,” “epidemic,” “commonplace, and practically expected,” to use a few of the terms with which researchers have described the scope of academic dishonesty.

In a 2010 study by the Josephson Institute, for example, 59 percent of the 43,000 high school students admitted to cheating on a test in the past year. According to a 2012 white paper, Cheat or Be Cheated? prepared by Challenge Success, 80 percent admitted to copying another student’s homework. The other studies summarized in the paper found self-reports of past-year cheating by high school students in the 70 percent to 80 percent range and higher.

At colleges, the situation is only marginally better. Studies consistently put the level of self-reported cheating among undergraduates between 50 percent and 70 percent depending in part on what behaviors are included. 1

The sad fact is that cheating is widespread.

Commitment to Honesty

Yet, when asked, most young people affirm the moral value of honesty and the belief that cheating is wrong. For example, in a survey of more than 3,000 teens conducted by my colleagues at the University of Virginia, the great majority (83 percent) indicated that to become “honest—someone who doesn’t lie or cheat,” was very important, if not essential to them.

On a long list of traits and qualities, they ranked honesty just below “hard-working” and “reliable and dependent,” and far ahead of traits like being “ambitious,” “a leader ,” and “popular.” When asked directly about cheating, only 6 percent thought it was rarely or never wrong.

Other studies find similar commitments, as do experimental studies by psychologists. In experiments, researchers manipulate the salience of moral beliefs concerning cheating by, for example, inserting moral reminders into the test situation to gauge their effect. Although students often regard some forms of cheating, such as doing homework together when they are expected to do it alone, as trivial, the studies find that young people view cheating in general, along with specific forms of dishonesty, such as copying off another person’s test, as wrong.

They find that young people strongly care to think of themselves as honest and temper their cheating behavior accordingly. 2

The Discrepancy Between Belief and Behavior

Bottom line: Kids whose ideal is to be honest and who know cheating is wrong also routinely cheat in school.

What accounts for this discrepancy? In the psychological and educational literature, researchers typically focus on personal and situational factors that work to override students’ commitment to do the right thing.

These factors include the force of different motives to cheat, such as the desire to avoid failure, and the self-serving rationalizations that students use to excuse their behavior, like minimizing responsibility—“everyone is doing it”—or dismissing their actions because “no one is hurt.”

While these explanations have obvious merit—we all know the gap between our ideals and our actions—I want to suggest another possibility: Perhaps the inconsistency also reflects the mixed messages to which young people (all of us, in fact) are constantly subjected.

Mixed Messages

Consider the story that young people hear about success. What student hasn’t been told doing well includes such things as getting good grades, going to a good college, living up to their potential, aiming high, and letting go of “limiting beliefs” that stand in their way? Schools, not to mention parents, media, and employers, all, in various ways, communicate these expectations and portray them as integral to the good in life.

They tell young people that these are the standards they should meet, the yardsticks by which they should measure themselves.

In my interviews and discussions with young people, it is clear they have absorbed these powerful messages and feel held to answer, to themselves and others, for how they are measuring up. Falling short, as they understand and feel it, is highly distressful.

At the same time, they are regularly exposed to the idea that success involves a trade-off with honesty and that cheating behavior, though regrettable, is “real life.” These words are from a student on a survey administered at an elite high school. “People,” he continued, “who are rich and successful lie and cheat every day.”

In this thinking, he is far from alone. In a 2012 Josephson Institute survey of 23,000 high school students, 57 percent agreed that “in the real world, successful people do what they have to do to win, even if others consider it cheating.” 3

Putting these together, another high school student told a researcher: “Grades are everything. You have to realize it’s the only possible way to get into a good college and you resort to any means necessary.”

In a 2021 survey of college students by College Pulse, the single biggest reason given for cheating, endorsed by 72 percent of the respondents, was “pressure to do well.”

What we see here are two goods—educational success and honesty—pitted against each other. When the two collide, the call to be successful is likely to be the far more immediate and tangible imperative.

A young person’s very future appears to hang in the balance. And, when asked in surveys , youths often perceive both their parents’ and teachers’ priorities to be more focused on getting “good grades in my classes,” than on character qualities, such as being a “caring community member.”

In noting the mixed messages, my point is not to offer another excuse for bad behavior. But some of the messages just don’t mix, placing young people in a difficult bind. Answering the expectations placed on them can be at odds with being an honest person. In the trade-off, cheating takes on a certain logic.

The proposed remedies to academic dishonesty typically focus on parents and schools. One commonly recommended strategy is to do more to promote student integrity. That seems obvious. Yet, as we saw, students already believe in honesty and the wrongness of (most) cheating. It’s not clear how more teaching on that point would make much of a difference.

Integrity, though, has another meaning, in addition to the personal qualities of being honest and of strong moral principles. Integrity is also the “quality or state of being whole or undivided.” In this second sense, we can speak of social life itself as having integrity.

It is “whole or undivided” when the different contexts of everyday life are integrated in such a way that norms, values, and expectations are fairly consistent and tend to reinforce each other—and when messages about what it means to be a good, accomplished person are not mixed but harmonious.

While social integrity rooted in ethical principles does not guarantee personal integrity, it is not hard to see how that foundation would make a major difference. Rather than confronting students with trade-offs that incentivize “any means necessary,” they would receive positive, consistent reinforcement to speak and act truthfully.

Talk of personal integrity is all for the good. But as pervasive cheating suggests, more is needed. We must also work to shape an integrated environment in which achievement and the “real world” are not set in opposition to honesty.

1. Liora Pedhazur Schmelkin, et al. “A Multidimensional Scaling of College Students’ Perceptions of Academic Dishonesty.” The Journal of Higher Education 79 (2008): 587–607.

2. See, for example, the studies in Christian B. Miller, Character and Moral Psychology. New York: Oxford University Press, 2014, Ch. 3.

3. Josephson Institute. The 2012 Report Card on the Ethics of American Youth (Installment 1: Honesty and Integrity). Josephson Institute of Ethics, 2012.

Joseph E. Davis is Research Professor of Sociology and Director of the Picturing the Human Colloquy of the Institute for Advanced Studies in Culture at the University of Virginia.

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Impact and Prevention of Technology Concerning Student Cheating

BY ANNABEL MONAGHAN

The vast majority of Americans – 95 percent – today own a mobile phone. In 2015, 64 percent of American adults owned a smartphone and that percentage has grown to almost 77 percent in recent years. For adults aged 18 to 29, a whopping 94 percent own smartphones, according to Pew Research Center.

While the growing popularity of smartphones is often seen as “progress”, it is also having a monumentally negative impact on the tertiary education sector. The increased use of technology has contributed to the simplification and ease of copying homework assignments – and cheating in general – across schools and tertiary institutions around the world. Despite the fact that repercussions for cheating are severe, involving possible suspension or expulsion, 62% of U.S. students have reported seeing or hearing of another student using a connected device to cheat on an exam, quiz or project. In the U.K., there has been a 42% rise in cheating cases involving gadgets such as mobile phones and hidden earpieces since 2012, and in Australia cheating via technology is also on the rise at universities, with engineering and international students the most likely offenders. In one study across eight national universities and four colleges in Australia, it was found that a “widespread tolerance for cheating” existed among students and staff, with 68 percent of university staff admitting they had found “suspected contract cheaters” among their students in the past.

“Contract cheating” is perhaps the most serious form of academic dishonesty, involving students putting out a tender for others to complete their homework, coursework and assessments. But most students are cheating in a far simpler way: by switching on their mobile devices and snapping a photo of a classmate’s work, enabling them to copy that homework almost word for word in order to avoid doing it themselves. Students are also using mobile phones or earpieces during exams, by activating their device’s infrared, Bluetooth, or texting applications to share exam information with other test takers.

With the rise of technology, academic cheating is becoming more and more prolific, with hundreds of thousands of websites now offering custom-written papers, selling cheat aids and publishing how-to-cheat videos, teaching students anything from how to load programmable calculators with exam responses to how to replace a water bottle’s nutrition information with mathematics notes. Students are cheating in extremely advanced ways – with some even resorting to the use of a virtual private network to protect their activities.

But teachers are catching up, quickly.

The learning center Happy Numbers notes, “using new technologies, including text-matching software and plagiarism websites, webcams, biometric equipment, as well as drawing on strategies such as virtual students and cheat-proof tests, it is ever so slowly becoming harder to plagiarize other students work”. Surprisingly, teachers often find they have the most success in identifying plagiarism by simply Googling phrases they find in students’ papers. But more tech-savvy professors and teachers set up web “honey pots” – phony Web pages that answer specific questions allocated by them for homework with blatantly out-of-date or inaccurate information. Innovative technologies like Computerized Adaptive Testing (CAT) provide a way of improving the accuracy of assessment by addressing cheating concerns, by using an algorithm to choose test items based on students’ strengths and weaknesses. Using this method, every student takes a different test. As a result of new “anti-cheat” innovations like these, the U.S. has seen the percentage of students who admit to cheating – which rose from 20 percent in the mid-1900s to over 50 percent in 2002 – drop down to around 10 percent in recent years.

But the reality is, advances in technology will continue allowing for easy, accessible sharing unless significant steps are taken to address the problem.

Some attribute the rise in student cheating to an ever-increasing workload, others see it as a changing work ethic seen in the Millenial and Gen Z groups. Some see a direct correlation between the rise of standardized testing and cheating. Others hold accountability policies responsible: they have pressured educators to raise test scores. Whatever the cause, it’s evident the education sector needs to address the phenomenon soon before cheating becomes the status quo, as opposed to a rare lapse in judgment.

To ensure you don’t find yourself falling for the same traps other students have and “accidentally” plagiarizing your next assessment, try to implement the following measures. Develop a more efficient weekly schedule so that you can spend more time on each subject – and assessment – so that when deadlines approach you aren’t tempted to find a “quick solution” to completing your work. If in doubt, don’t copy and paste a piece of work found online but if you must, ensure it is correctly referenced. Don’t give in to peer pressure and share your work with others, because developing a habit of cheating – either for yourself or for others – creates a poor work ethic that can damage your future. And lastly, always remember your ethics. They will get a lot further than an A+ will.

Annabel Monaghan is a writer with a passion for education and edtech. She writes education and career articles for The College Puzzle with the aim of providing useful information for students and young professionals. If you have any questions, please feel free to email her at [email protected].

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Reports Of Cheating At Colleges Soar During The Pandemic

Illustration of college students cheating.

Mariam Aly, an assistant professor at Columbia University, has tried everything to keep her students from cheating. In her cognitive neuroscience class, she gives her students a week to complete an open-book exam. And, as part of that exam, the nearly 180 students in the class have to sign an honor code.

But they're still cheating. And dealing with student misconduct, she says, is the worst part of her job. "It's just awkward and painful for everybody involved," Aly says. "And it's really hard to blame them for it. You do feel disappointed and frustrated."

Her students are facing unprecedented levels of stress and uncertainty, she says, and she gets that. "I didn't go to school during a pandemic."

As college moved online in the COVID-19 crisis, many universities are reporting increases, sometimes dramatic ones, in academic misconduct. At Virginia Commonwealth University, reports of academic misconduct soared during the 2020-21 school year, to 1,077 — more than three times the previous year's number. At the University of Georgia, cases more than doubled; from 228 in the fall of 2019 to more than 600 last fall. And, at The Ohio State University, reported incidents of cheating were up more than 50% over the year before.

But while students may have had new and different opportunities for cutting corners in the online learning environment, it's unclear how much cheating actually increased. Some educators note that there are other factors at play, such as an increased ability to identify misconduct.

"There was probably increased cheating because there were more temptations and opportunities and stress and pressure. And, faculty were probably detecting it more," says Tricia Bertram Gallant, who researches academic integrity at the University of California, San Diego. "It's easier to catch in the virtual world, in many ways, than it is in the in-person world."

When collaboration morphs into cheating

When colleges shut down or restricted in-person access, students were taking exams in their bedrooms, with unfettered access to cellphones and other technology. This, educators say, spurred cheating to take on new and different forms.

One student at Middle Tennessee State University used his smart speaker to find answers during an exam, according to Michael Baily, the school's director of academic integrity. California State University, Los Angeles, had a large-scale cheating scandal early on in the pandemic, after one student alleged that her peers were sharing exam answers through a GroupMe chat.

Unauthorized collaboration was a big factor in reports of misconduct at Virginia Commonwealth, says Karen Belanger, the university's director of student conduct and academic integrity. "They were so desperate to connect that they were using — or in some courses being encouraged to create — group chats," she says. "Those chats then became a place where they may talk about homework or talk about exam questions."

Students were confused about what was permitted and what wasn't during an exam, Belanger adds. "Sometimes, people just lost track of where the guardrails were in the virtual environment."'

Faculty at the University of Georgia gave more open-book exams during the pandemic. Some students then turned to third-party study sites to complete those exams, which is considered a misconduct violation, explains Phillip Griffeth, the school's director of academic honesty.

"There was a miscommunication. Some students might have saw 'open-book, open-note' as 'open-Internet, open-resources,' " Griffeth explains.

Ohio State also saw a large increase in cases where students shared information during the exam or used unauthorized materials, according to an annual report from the school's committee on academic misconduct.

Schools, including the University of Georgia and Ohio State, are now trying to educate students on what constitutes an academic misconduct violation.

"The university is taking several steps to enhance the resources available related to academic integrity so that students continue to be fully aware of expectations and to support instructors in dealing with this issue," an Ohio State spokesman wrote to NPR.

When cheating feels like the only option

Annie Stearns will be a sophomore this fall at St. Mary's College of California, where misconduct reports doubled last fall over the previous year. During the pandemic, the challenges of learning online were entwined with social isolation and additional family responsibilities, she says.

On top of that, tutoring services and academic resources scaled back or moved online. Some students, facing Zoom burnout, stopped asking for help altogether.

"If you're in class, and then you have to go to office hours, that's another Zoom meeting. And if you have to go to the writing center, that's another Zoom meeting," Stearns explains. "People would get too overwhelmed with being on video calls and just opt out."

Stearns, who logged onto classes from her family's home last year, faced the pressures of online classes herself, but she sits on her school's academic honor council. For other students, she says, cheating can feel like the only option.

"We're going through such an unprecedented time that (cheating is) bound to happen," Stearns says. "They prefer to take the shortcut and risk getting caught, than have an email conversation with their professor because they're too ashamed to be like, 'I need assistance.' "

More cheating? Or just better tracking?

Many factors are at play in the rise in reports of cheating and misconduct, and, in interviews with NPR, experts across the higher education spectrum say they aren't at all certain whether, or how much, cheating actually increased.

"Just because there's an increase in reports of academic misconduct doesn't mean that there's more cheating occurring," says James Orr, a board member of the International Center for Academic Integrity. "In the online environment, I think that faculty across the country are more vigilant in looking for academic misconduct."

Data from before the pandemic showed similar rates of cheating when comparing online and face-to-face learning environments.

And at least one school, the University of Texas at Austin, found that reports of academic misconduct cases actually declined during the pandemic. Katie McGee, the executive director for student conduct and academic integrity there, explains that before the pandemic, UT-Austin had toughened its ability, through software, to detect cheating.

With online learning, educators are using third-party tools, which can make cheating easier to detect. Middle Tennessee State, for example, rolled out an online proctoring tool, Examity, at the start of the pandemic. The tool records testing sessions on students' webcams and uses software to flag possible cheating. The university has seen reports of cheating jump by more than 79% from fall of 2019 to spring of 2021.

"I don't believe that more students started cheating during the pandemic," said Baily. "What I believe is that we then put in place these proctoring systems that enabled us to find these students who were cheating."

And Baily says Examity is here to stay at Middle Tennessee State. Orr calls remote, third-party proctoring tools a "new industry standard."

That could be a problem for some students and faculty who have raised privacy and equity concerns around such services. At the start of the pandemic, students at Florida State University petitioned the school to stop using Honorlock. The petition says using Honorlock "blatantly violates privacy rights."

And at Miami University, in Ohio, petitioners argue that yet another service, Proctorio, discriminates against some students, "as it tracks a student's gaze, and flags students who look away from the screen as 'suspicious' too, which negatively impacts people who have ADHD-like symptoms." The petition also goes on to note, "students with black or brown skin have been asked to shine more light on their faces, as the software had difficulty recognizing them or tracking their movements."

At the University of Minnesota, students are also petitioning against the use of Proctorio, calling the service a "huge invasion of privacy."

Mike Olsen, the head of Proctorio, wrote in a statement to NPR that humans make all final determinations regarding exam integrity. He added that the company has partnered with third-party data security auditors, and an analysis of Proctorio's latest face-detection models found no measurable bias.

Honorlock declined NPR's request for comment.

Ken Leopold, a chemistry professor at the University of Minnesota, says he and other faculty must balance privacy concerns with the need to guard against cheating. He says he has avoided using Proctorio in his classes, saying the software "didn't sit right" with him. But then came the pandemic.

The school is having conversations with students about remote proctoring. But, he says, "I can't see Proctorio or some equivalent entirely vanishing from the university at this point."

"We're sensitive to the students' concerns, but at the same time, we have to uphold academic integrity,'' says Leopold, who advises the university on remote proctoring and academic misconduct. "If you're going to give an exam remotely, you have very little choice."

Correction Aug. 27, 2021

A previous version of this story incorrectly said Tricia Bertram Gallant was affiliated with the University of California, Santa Barbara. In fact, she researches academic integrity at the University of California, San Diego.

Our Mission

Why Students Cheat—and What to Do About It

A teacher seeks answers from researchers and psychologists.

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

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

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

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

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

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

Rationalizing It

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

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

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

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

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

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

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

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

A Developmental Stage

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

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

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

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

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

A student cheats using answers on his hand.

Technology Facilitates and Normalizes It

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

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

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

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

Strategies for Reducing Cheating

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

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

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

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

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

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

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

clock This article was published more than 3 years ago

Another problem with shifting education online: A rise in cheating

When universities went online in response to the coronavirus pandemic, so did the tests their students took. But one of the people who logged on to take an exam in a pre-med chemistry class at a well-known Mid-Atlantic university turned out not to be a student at all.

He was a plant. An impostor. A paid ringer.

Proctors — remote monitors some schools have hired to watch test-takers through their webcams — discovered by reviewing video recordings that this same person had taken tests for at least a dozen students enrolled at seven universities across the country.

But he was in Qatar, beyond the reach of any attempts to hold him accountable, according to proctors familiar with the situation. They could not say what happened to the students who allegedly hired him.

It was a dramatic case but far from unique. Universal online testing has created a documented increase in cheating, often because universities, colleges and testing companies were unprepared for the scale of the transformation or unable or unwilling to pay for safeguards, according to faculty members and testing experts.

Even with trained proctors watching test-takers and checking their IDs, cheating is up. Before the coronavirus forced millions of students online, one of the companies that provides that service, ProctorU, caught people cheating on fewer than 1 percent of the 340,000 exams it administered from January through March. During the height of remote testing, the company says, the number of exams it supervised jumped to 1.3 million from April through June, and the cheating rate rose above 8 percent.

“We can only imagine what the rate of inappropriate testing activity is when no one is watching,” said Scott McFarland, chief executive of ProctorU.

And for most online test-takers, no one has been watching. One reason is that, as demand for online testing spiked, proctoring capacity was overwhelmed. One company, Examity, suspended its live proctoring services during the demand surge when its 1,000 proctors in India were locked down to curb the spread of the coronavirus there. Ninety-three percent of instructors think students are more likely to cheat online than in person, according to a survey conducted in May by the publishing and digital education company Wiley. Only a third said they were using some type of proctoring to prevent it. Many colleges and universities moved ahead with online testing without supervision to save money. Others opted instead for less expensive, scaled-down kinds of test security, such as software that can lock a web browser while a student takes a test.

While locking a browser during an exam may help — and about 15 percent of instructors take that step, the Wiley survey found — it can’t stop other forms of cheating.

“You cannot give an exam if it is not proctored,” said Charles M. Krousgrill, a professor of engineering at Purdue University, where faculty have been more willing to publicly discuss cheating than their counterparts at many other schools.

When, after the coronavirus shutdowns, Purdue gave students extra time to take their tests online, said Krousgrill, “there was rampant dishonesty.” He described some students in his department organizing videoconferences and sharing answers. “Once we went to online instruction, we could not watch. [The students] knew it and knew the game was up for grabs.”

Online tests have also meant a booming business for companies that sell homework and test answers, including Chegg and Course Hero. Students pay subscription fees to get answers to questions on tests or copies of entire tests with answers already provided. The tests are uploaded by other students who have already taken them, in exchange for credits, or answers are quickly provided by “tutors” who work for the sites.

Though these sites have been around since before the pandemic, their use appears to have exploded as more tests are given online. Students used Chegg to allegedly cheat on online exams and tests in the spring at schools including Georgia Tech, Boston University, North Carolina State and Purdue, according to faculty at those institutions and news reports.

At North Carolina State, more than 200 of the 800 students in a single Statistics 311 class were referred for disciplinary action for using “tutor-provided solutions” to exam questions from Chegg, said Tyler Johnson, the course coordinator.

After the exam, Johnson said, he asked his university to get Chegg to remove the questions, citing copyright law. Chegg did, and it furnished a report of users who had either posted or accessed the exam materials.

“I was initially really naive to the extent to which these services are utilized by students,” he said.

The North Carolina State students have protested in a petition that they didn’t know using Chegg would be considered cheating and that Johnson showed “no regard to the personal stresses we are enduring and have endured throughout the semester.”

Krousgrill and his colleagues at Purdue found “a massive number” of students who had used Chegg to get test answers, he said. In one class, Krousgrill said, as many as 60 students out of 250 had done so, and 100 students in a colleague’s class were identified as having used Chegg in a similar fashion.

The number of students who are cheating is almost certainly higher than the number being caught or reported. Research has shown that instructors believe cheating happens much less often than students do, which means they may not be looking for it. When they do find it, many choose to simply give cheaters an F, without reporting the incidents further.

“I had a conversation with a group of students several months ago,” said James Pitarresi, vice provost at Binghamton University. “And one of the students said, ‘Look, you know, probably 80 percent of the class is looking at Chegg. What are you going to do, expel all of us?’ ”

Chegg, which offers online tutoring services, declined to comment at length. A spokesman said the company supports academic integrity and hasn’t seen “any relative increase in honor code issues since the covid-19 crisis began.” In an interview with the New York Times, Chegg chief executive Dan Rosensweig, when asked whether his company’s services were being used for cheating, said: “Let’s face it: Students have always found a way, whether it’s in fraternities, or whether they go to Google. But Chegg is not built for that.”

The firm reported $153 million in revenue for the second quarter, when the pandemic shutdowns were at their peak — a 63 percent year-over-year increase.

Colleges were not the only institutions to rush examinations online. Advanced placement and other tests also went virtual in the spring. So did law school entrance and placement exams, professional certification tests for financial managers and food handlers and many others.

The College Board, which administers the AP tests, reconfigured these exams to be “open book” when they were moved online, but without proctoring. Students reportedly used private messaging apps to collaborate on answers. Even before the exams began, College Board officials tweeted about “a ring of students who were developing plans to cheat” and canceled their registrations.

The College Board won’t disclose whether any cheating actually happened. A spokesman would say only that “at-home testing presents some different security challenges” and that the organization took steps to prevent it.

“One student with a pattern of cheating is an ethical problem for that student. Multiple students with a pattern of cheating devalues any grade or degree they might be receiving,” said Steve Saladin, a co-author of a study published in the spring by the Journal of the National College Testing Association. “And when cheating spreads to many students in many programs and schools, degrees and grades cease to provide a measure of an individual’s preparedness for a profession or position. And perhaps even more importantly, it suggests a society that blindly accepts any means to an end as a given.”

This story about online testing was produced by the Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education.

An earlier version of this article stated incorrectly that the SAT went virtual in the spring.

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Cheating Fears Over Chatbots Were Overblown, New Research Suggests

A.I. tools like ChatGPT did not boost the frequency of cheating in high schools, Stanford researchers say.

A casually dressed man and a woman pose for a photo near a stairwell.

By Natasha Singer

Natasha Singer writes about education technology.

Last December, as high school and college students began trying out a new A.I. chatbot called ChatGPT to manufacture writing assignments, fears of mass cheating spread across the United States.

To hinder bot-enabled plagiarism, some large public schools districts — including those in Los Angeles , Seattle and New York City — quickly blocked ChatGPT on school-issued laptops and school Wi-Fi.

But the alarm may have been overblown — at least in high schools.

According to new research from Stanford University, the popularization of A.I. chatbots has not boosted overall cheating rates in schools. In surveys this year of more than 40 U.S. high schools, some 60 to 70 percent of students said they had recently engaged in cheating — about the same percent as in previous years, Stanford education researchers said .

“There was a panic that these A.I. models will allow a whole new way of doing something that could be construed as cheating,” said Denise Pope , a senior lecturer at Stanford Graduate School of Education who has surveyed high school students for more than a decade through an education nonprofit she co-founded. But “we’re just not seeing the change in the data.”

ChatGPT, developed by OpenAI in San Francisco, began to capture the public imagination late last year with its ability to fabricate human-sounding essays and emails. Almost immediately, classroom technology boosters started promising that A.I. tools like ChatGPT would revolutionize education. And critics began warning that such tools — which liberally make stuff up — would enable widespread cheating, and amplify misinformation, in schools.

Now the Stanford research , along with a recent report from the Pew Research Center, are challenging the notion that A.I. chatbots are upending public schools.

Many teens know little about ChatGPT, Pew found. And most say they have never used it for schoolwork.

Those trends could change, of course, as more high school students become familiar with A.I. tools.

Many Teens Have Never Heard of ChatGPT

How much, if anything, have you heard about ChatGPT, an artificial intelligence (A.I.) program used to create text?

This fall, Pew Research Center surveyed more than 1,400 U.S. teenagers, aged 13 to 17, about their knowledge, use and views of ChatGPT. The results may seem counterintuitive, given the plethora of panicked headlines last spring.

Nearly one-third of teens said they had heard “nothing at all” about the chatbot, according to the Pew survey , conducted from Sept. 26 to Oct. 23, 2023. Another 44 percent said they had heard “a little” about it.

Only 23 percent said they had heard a lot about ChatGPT. (The Pew survey did not ask the teens about other A.I. chatbots like Google’s Bard or OpenAI’s GPT-4.)

Responses varied by race and household income. About 72 percent of white teens said they had heard about the chatbot compared with about 56 percent of Black teens, Pew said.

About 75 percent of teens in households with annual incomes of $75,000 or more said they had heard about ChatGPT, Pew found, compared to just 41 percent of teens in households with annual incomes of less than $30,000.

Pew also asked teens whether they had ever used ChatGPT to help with their schoolwork. Only a small minority — 13 percent — said they had.

The Pew survey results suggest that ChatGPT, at least for now, has not become the disruptive phenomenon in schools that proponents and critics forecast. Among the subset of teens who said they had heard about the chatbot, the vast majority — 81 percent — said they had not used it to help with their schoolwork.

“Most teens do have some level of awareness of ChatGPT,” said Jeffrey Gottfried, an associate director of research at Pew. “But this is not a majority of teens who are incorporating it into their schoolwork quite yet.”

Cheating Rates Haven’t Changed Much

Cheating has long been rampant in schools. In surveys of more than 70,000 high school students between 2002 and 2015 , 64 percent said they had cheated on a test. And 58 percent said they had plagiarized.

Since the introduction of ChatGPT in 2022, the overall frequency of high school students reporting they recently engaged in cheating has not increased, according to the Stanford researchers.

The new research does not shed light on how frequently college students may employ chatbots as cheating bots. The Stanford and Pew researchers did not survey college students about their use of A.I. tools.

This year, the Stanford researchers added survey questions that specifically asked high school students about their use of A.I. chatbots. This fall, 12 to 28 percent of students at four East Coast and West Coast high schools said they had used an A.I. tool or digital device — such as ChatGPT or a smartphone — within the last month as an unauthorized aid during a school test, assignment or homework.

Among the high school students who said they had used an A.I. chatbot, about 55 to 77 percent said they had used it to generate an idea for a paper, project or assignment; about 19 to 49 percent said they had used it to edit or complete a portion of a paper; and about 9 to 16 percent said they had used it to write all of a paper or other assignment, the Stanford researchers found.

The findings could help shift discussions about chatbots in schools to focus less on cheating fears and more on helping students learn to understand, use and think critically about new A.I. tools, the researchers said.

“ There are other ways to think about A.I. — not simply as this uncontrollable temptation that undermines everything,” said Victor R. Lee , an associate professor at Stanford Graduate School of Education who researches A.I. learning experiences and led the recent research on cheating with Dr. Pope. “There’s so much more that could and should be talked about in schools.”

‘Not Acceptable’ for Essay Writing

While schools are still developing acceptable usage rules for the A.I. tools, students are developing nuanced views on using ChatGPT for schoolwork.

Only 20 percent of teens aged 13 to 17 said they thought it was acceptable for students to use ChatGPT to write essays, Pew found. But nearly 70 percent said it was acceptable for students to use the A.I. chatbot to research new topics.

Do you think it’s acceptable for students to use ChatGPT for … ?

This does not mean that students are not trying to pass off chatbot-generated texts as their own schoolwork.

Christine Meade, an Advanced Placement history teacher at a high school in Vallejo, Calif., said chatbot cheating was widespread among 12th graders last spring. She even caught a few using the A.I. chatbots on their smartwatches during school tests.

But this year, after she told her students they could use ChatGPT and Bard for certain research projects, the situation “completely changed,” she said.

“I had a bunch of students in my A.P. history class use chatbots to generate a list of events that happened right after the Civil War, in the 1880s,” Ms. Meade said. “It was pretty accurate — except for the 1980s event during the Reagan administration.”

Natasha Singer writes about technology, business and society. She is currently reporting on the far-reaching ways that tech companies and their tools are reshaping public schools, higher education and job opportunities. More about Natasha Singer

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Science News

How chatgpt and similar ai will disrupt education.

Teachers are concerned about cheating and inaccurate information

Students are turning to ChatGPT for homework help. Educators have mixed feeling about the tool and other generative AI.

Glenn Harvey

Who said what?

When prompted, ChatGPT can craft answers that sound surprisingly like those from a student. We asked middle school and high school students from across the country, all participants in our Science News Learning education program , to answer some basic science questions in two sentences or less. The examples throughout the story compare how students responded with how ChatGPT responded when asked to answer the question at the same grade level.

What effect do greenhouse gases have on the Earth?

Agnes b. | grade 11, harbor city international school, minn..

Greenhouse gases effectively trap heat from dissipating out of the atmosphere, increasing the amount of heat that remains near Earth in the troposphere.

Greenhouse gases trap heat in the Earth’s atmosphere, causing the planet to warm up and leading to climate change and its associated impacts like sea level rise, more frequent extreme weather events and shifts in ecosystems.

The good, bad and weird of ChatGPT

ChatGPT has wowed its users. “It’s so much more realistic than I thought a robot could be,” says Avani Rao, a sophomore in high school in California. She hasn’t used the bot to do homework. But for fun, she’s prompted it to say creative or silly things. She asked it to explain addition, for instance, in the voice of an evil villain.

Given how well it performs, there are plenty of ways that ChatGPT could level the playing field for students and others working in a second language or struggling with composing sentences. Since ChatGPT generates new, original material, its text is not technically plagiarism.

Students could use ChatGPT like a coach to help improve their writing and grammar, or even to explain subjects they find challenging. “It really will tutor you,” says Vogelsinger, who had one student come to him excited that ChatGPT had clearly outlined a concept from science class.

Educators could use ChatGPT to help generate lesson plans, activities or assessments — perhaps even personalized to address the needs or goals of specific students.

Xiaoming Zhai, an expert in science education at the University of Georgia in Athens, tested ChatGPT to see if it could write an academic paper . He was impressed with how easy it was to summarize knowledge and generate good writing using the tool. “It’s really amazing,” he says.

All of this sounds wonderful, but really big problems exist. Most worrying, ChatGPT and other similar tools can often get things very wrong. They don’t pull facts from databases. Rather, they are trained to generate new text that sounds natural. They remix language without understanding it, which can lead to glaring mistakes.

The news website CNET came under fire earlier this year for using AI to churn out dozens of articles, many of them packed with errors. In an early advertisement for the Bard chatbot, it made a factual error about the James Webb Space Telescope, incorrectly claiming that it had taken the very first picture of an exoplanet. And ChatGPT said in a conversation posted on Twitter that the fastest marine mammal was the peregrine falcon. A falcon, of course, is a bird and doesn’t live in the ocean.

ChatGPT is “confidently wrong,” says Casey Fiesler, an expert in the ethics of technology at the University of Colorado Boulder. “There are mistakes and bad information.” She has made multiple TikTok videos about the pitfalls of ChatGPT .

Most of ChatGPT’s training data come from before September 2021, and it does not provide sources for its information. If asked for sources, it makes them up, Fiesler revealed in one video . Zhai, who sees the tool as an assistant, discovered the exact same thing. When he asked ChatGPT for citations, it gave him sources that looked correct. But they didn’t actually exist.

Define the term biodiversity.

Dante a. | grade 10, clark magnet high school, calif..

Biodiversity refers to the variety of living species and ecosystems that exist in a particular region or on the planet as a whole. It encompasses the different genes, species and ecosystems that make up the natural world and the relationships between them.

Biodiversity refers to the variety of living organisms that inhabit the Earth and the ecosystems they form. It includes the diversity of species, genes and ecosystems, and is important for maintaining the balance of nature and sustaining life on our planet.

How ChatGPT works

ChatGPT’s mistakes make sense if you know how it works. “It doesn’t reason. It doesn’t have ideas. It doesn’t have thoughts,” explains Emily M. Bender, a computational linguist at the University of Washington in Seattle.

ChatGPT was developed using at least two types of machine learning. The primary type is a large language model based on an artificial neural network. Loosely inspired by how neurons in the brain interact, this computing architecture finds statistical patterns in vast amounts of data.

A language model learns to predict what words will come next in a sentence or phrase by churning through vast amounts of text. It places words and phrases into a multidimensional map that represents their relationships to one another. Words that tend to come together, like peanut butter and jelly, end up closer together in this map.

The size of an artificial neural network is measured in parameters. These internal values get tweaked as the model learns. In 2020, OpenAI released GPT-3. At the time, it was the biggest language model ever, containing 175 billion parameters. It had trained on text from the internet as well as digitized books and academic journals. Training text also included transcripts of dialog, essays, exams and more, says Sasha Luccioni, a Montreal-based researcher at Hugging Face, a company that builds AI tools.

OpenAI improved upon GPT-3 to create GPT-3.5. In early 2022, the company released a fine-tuned version of GPT-3.5 called InstructGPT. This time, OpenAI added a new type of machine learning. Called reinforcement learning with human feedback, it puts people into the training process. These workers check the AI’s output. Responses that people like get rewarded. Human feedback can also help reduce hurtful, biased or inappropriate responses. This fine-tuned language model powers freely available ChatGPT. As of March, paying users receive answers powered by GPT-4, a bigger language model.

During ChatGPT’s development, OpenAI added extra safety rules to the model. It will refuse to answer certain sensitive prompts or provide harmful information. But this step raises another issue: Whose values are programmed into the bot, including what it is — or is not — allowed to talk about?

OpenAI is not offering exact details about how it developed and trained ChatGPT. The company has not released its code or training data. This disappoints Luccioni because it means the tool can’t benefit from the perspectives of the larger AI community. “I’d like to know how it works so I can understand how to make it better,” she says.

When asked to comment on this story, OpenAI provided a statement from an unnamed spokesperson. “We made ChatGPT available as a research preview to learn from real-world use, which we believe is a critical part of developing and deploying capable, safe AI systems,” the statement said. “We are constantly incorporating feedback and lessons learned.” Indeed, some experimenters have gotten the bot to say biased or inappropriate things despite the safety rules. OpenAI has been patching the tool as these problems come up.

ChatGPT is not a finished product. OpenAI needs data from the real world. The people who are using it are the guinea pigs. Notes Bender: “You are working for OpenAI for free.”

What are black holes and where are they found?

Althea c. | grade 11, waimea high school, hawaii.

A black hole is a place in space where gravity is so strong that nothing, not even light, may come out.

Black holes are extremely dense regions in space where the gravity is so strong that not even light can escape, and they are found throughout the universe.

ChatGPT’s academic performance

How good is ChatGPT in an academic setting? Catherine Gao, a doctor and medical researcher at Northwestern University’s Feinberg School of Medicine in Chicago, is part of one team of researchers that is putting the tool to the test.

Gao and her colleagues gathered 50 real abstracts from research papers in medical journals and then, after providing the titles of the papers and the journal names, asked ChatGPT to generate 50 fake abstracts. The team asked people familiar with reading and writing these types of research papers to identify which were which .

“I was surprised by how realistic and convincing the generated abstracts were,” Gao says. The reviewers mistook roughly one-third of the AI-generated abstracts as human-generated.

In another study, Will Yeadon and colleagues tested whether AI tools could pass a college exam . Yeadon, a physics instructor at Durham University in England, picked an exam from a course that he teaches. The test asks students to write five short essays about physics and its history. Students have an average score of 71 percent, which he says is equivalent to an A in the United States.

Yeadon used the tool davinci-003, a close cousin of ChatGPT. It generated 10 sets of exam answers. Then Yeadon and four other teachers graded the answers using their typical standards. The AI also scored an average of 71 percent. Unlike the human students, though, it had no very low or very high marks. It consistently wrote well, but not excellently. For students who regularly get bad grades in writing, Yeadon says, it “will write a better essay than you.”

These graders knew they were looking at AI work. In a follow-up study, Yeadon plans to use work from the AI and students and not tell the graders whose is whose.

What is heat?

Precious a. | grade 6, canyon day junior high school, ariz..

Heat is the transfer of kinetic energy from one medium or object to another, or from an energy source to a medium or object through radiation, conduction and convection.

Heat is a type of energy that makes things warmer. It can be produced by burning something or through electricity.

Tools to check for cheating

When it’s unclear whether ChatGPT wrote something or not, other AI tools may help. These tools typically train on AI-generated text and sometimes human-generated text as well. They can tell you how likely it is that text was composed by an AI. Many of the existing tools were trained on older language models, but developers are working quickly to put out new, improved tools.

A company called Originality.ai sells access to a tool that trained on GPT-3. Founder Jon Gillham says that in a test of 10,000 samples of texts composed by models based on GPT-3, the tool tagged 94 percent of them correctly as AI-generated. When ChatGPT came out, his team tested a smaller set of 20 samples. Each only 500 words in length, these had been created by ChatGPT and other models based on GPT-3 and GPT-3.5. Here, Gillham says, the tool “tagged all of them as AI-generated. And it was 99 percent confident, on average.”

In late January 2023, OpenAI released its own free tool for spotting AI writing, cautioning that the tool was “not fully reliable.” The company is working to add watermarks to its AI text, which would tag the output as machine-generated, but doesn’t give details on how. Gillham describes one possible approach: Whenever it generates text, the AI ranks many different possible words for each position. If its developers told it to always choose the word ranked in third place rather than first place at specific points in its output, those words could act as a fingerprint, he says.

As AI writing tools improve, the tools to sniff them out will need to improve as well. Eventually, some sort of watermark might be the only way to sort out true authorship.

What is DNA and how is it organized?

Luke m. | grade 8, eastern york middle school, pa..

DNA, or deoxyribonucleic acid, is kept inside the cells of living things, where it holds instructions for the genetics of the organism it is inhabiting.

DNA is like a set of instructions that tells our cells what to do. It’s organized into structures called chromosomes, which contain all of the DNA in a cell.

ChatGPT and the future of writing

There’s no doubt we will soon have to adjust to a world in which computers can write for us. But educators have made these sorts of adjustments before. As high school student Rao points out, Google was once seen as a threat to education because it made it possible to look up facts instantly. Teachers adapted by coming up with teaching and testing materials that don’t depend as heavily on memorization.

Now that AI can generate essays and stories, teachers may once again have to rethink how they teach and test. Rao says: “We might have to shift our point of view about what’s cheating and what isn’t.”

Some teachers will prevent students from using AI by limiting access to technology. Right now, Vogelsinger says, teachers regularly ask students to write out answers or essays at home. “I think those assignments will have to change,” he says. But he hopes that doesn’t mean kids do less writing.

Teaching students to write without AI’s help will remain essential, agrees Zhai. That’s because “we really care about a student’s thinking,” he stresses. And writing is a great way to demonstrate thinking. Though ChatGPT can help a student organize their thoughts, it can’t think for them, he says.

Kids still learn to do basic math even though they have calculators (which are often on the phones they never leave home without), Zhai acknowledges. Once students have learned basic math, they can lean on a calculator for help with more complex problems.

In the same way, once students have learned to compose their thoughts, they could turn to a tool like ChatGPT for assistance with crafting an essay or story. Vogelsinger doesn’t expect writing classes to become editing classes, where students brush up AI content. He instead imagines students doing prewriting or brainstorming, then using AI to generate parts of a draft, and working back and forth to revise and refine from there.

Though he’s overwhelmed about the prospect of having to adapt his teaching to another new technology, he says he is “having fun” figuring out how to navigate the new tech with his students.

Rao doesn’t see AI ever replacing stories and other texts generated by humans. Why? “The reason those things exist is not only because we want to read it but because we want to write it,” she says. People will always want to make their voices heard.

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Adjusting to an Online Cheating Environment

By shoellis

By: Sierra President, Ethics and Policy Intern

Today, cheating is easier than ever. Regardless of its ease, cheating is still frowned upon in most traditional academic settings and will lead to negative consequences if caught. And yet, people continue to cheat. The recent advancement of artificial intelligence (AI), an overload of online resources, and a lack of student understanding regarding academic policies make it more likely that students will cheat and get away with it. Since we are in a digital age, where notebooks are replaced with screens and pencils are traded for keyboards, academics must find ways to regulate the use of these new technologies. If they don’t, learning and integrity may be put on the back burner while students still reap the benefit of their ill-gotten degrees.

What is cheating?

According to the Merriam-Webster Dictionary, cheating is defined as “to deprive of something valuable by the use of deceit or fraud.” [1] However, this blog is focused on cheating in an academic environment. Many universities have their definitions for cheating and typically consider it academic dishonesty.

For instance, the Office of Student Conduct website says, “Generally, academic misconduct can be thought of as any behavior that involves the giving, taking, or presenting of information by a student that unethically or fraudulently aids the student or another on any work which is to be considered in the determination of a grade or the completion of academic requirements or the enhancement of that student’s record or academic career.” [2]

The website also describes the most common forms of cheating, which include:

Copying from another assignment or test,
Collaborating with others on an assignment with the professor has required independent work,
Using outside resources when completing an assignment or test,
Falsifying test answers or grades. [3]

Under its Code of Student Conduct, NC State also expands its definition of cheating to account for technological advances. Specifically, the code says, “Using materials, equipment, or assistance in connection with an assignment, examination, or other academic exercise which have not been authorized by the faculty member, including but not limited to notes, calculator, or other technology.” [4]

Many universities nationwide have policies like NC State’s. Students should acknowledge these definitions, but educators must also recognize the benefits of using online resources.

Why are students cheating?

According to the International Center for Academic Integrity, 68 percent of undergraduate students say they have cheated on their assignments. [5] It might seem obvious why students cheat, but the University of Buffalo’s Office of Academic Integrity released a list that describes multiple reasons why students cheat, including some that may not immediately come to mind. [6] This list includes:

Poor time management,
Wanting to help friends,
Fear of failure,
Because everyone else is doing it,
Unmonitored environment or weak assignment design, and
Lack of academic policy understanding.

In an article published in The Chronicle of Higher Education , Owen Kichizo Terry expanded on the reasoning as to why students cheat by saying that the emergence of AI, like ChatGPT, makes it harder to get caught. [7] In the article, he provided a blueprint for how ChatGPT can be used to write an essay without detection. Terry argued, “In reality, it’s very easy to use AI to do the lion’s share of the thinking while still submitting work that looks like your own.” He said that ChatGPT can give students multiple ideas for a singular prompt. So, if a student uses one of the chatbot’s options and changes the words, then a professor may not think twice about who wrote it.

Kathryn Hulick wrote a ScienceNews article arguing that since ChatGPT and similar programs create new material, it is hard to consider plagiarism because plagiarism is when someone else’s existing work is copied without credit. Hulick also argued that, while there are many illegitimate uses for the technology, AI can also help with writing, like how calculators help with math, and Google helps find facts. Hulick also said that ChatGPT, for example, can help students struggling with sentence structure and grammar. [8] It is likely that when universities do not have policies about tools like chatbots that use AI, students may not see it as an issue to use them for assignments. While most universities are actively developing their AI policies, professors have recommended that students unsure about when and how to use AI should come to them for a conversation. This is particularly important since students may not realize the potential negative impacts of using AI.

What are the punishments for cheating?

Punishments for cheating can vary based on the assignment, professor, and academic institution. Ironically, I asked ChatGPT what can happen if someone cheats on an assignment. ChatGPT outlined several penalties that universities could require for cheating, which include:

Receiving a failing grade
Academic probation
Loss of privileges (access to campus facilities or activities)
A note on the student’s permanent record
Required completion of an academic integrity course
Suspension or expulsion
Legal action

It is important to note that ChatGPT only provided an overview of the possible penalties, meaning that it is possible for a student not to receive any punishment or to receive something that is not on this list. Each professor, department, and university has a different way of handling cheating, some of which may include a warning system.

In 2020, Georgia Tech had a cheating scandal when it was discovered that multiple students in an online physics class were using Chegg to get complete answers to their final exam. [9] Chegg is a company that provides digital homework help. Since users can freely post on the website, the answers to some assignments are posted in their entirety, giving students another way to cheat. The physics class received an email stating that if they admitted to using Chegg, they would be offered a second chance to take the exam. If a student did not admit to cheating but was found to have been using Chegg during the exam, they were reported to the Dean’s Office for Academic Misconduct and recommended to fail the course. Similar Chegg investigations were also underway at Texas A&M and Boston University. [10] Chegg states in their honor code that they do not condone the use of their website for cheating and will act against anyone who violates this, which should deter students from these actions. [11]

Jarrod Morgan, the founder of online test proctoring site ProctorU, said finances are a huge stressor for college students. [12] The possibility of having to repeat a course and pay for it again can add to their stress.

How can professors and administrators limit cheating?

The easy answer is to bring back in-person paper and pencil tests. However, the ease of using technology in classrooms makes this an unlikely option. As of 2023, 87 percent of classrooms globally use digital teaching practices. [13] There is now an “arms race” between technological advances that make cheating easier for students and technologies meant to detect or prevent cheating. Below are some tools and initiatives that can help educators monitor online cheating.

Vicky Harmon, the instructional design and manager of professional development at Arizona State University-Tempe, said, “If a student is going to do it, they’re going to do it, but we try to make it as difficult as possible.” [14] As a result of professors trying to manage cheating concerns, below are some helpful tools:

Online Test Proctoring which monitors and records a student’s test taking to ensure outside materials aren’t used.
Plagiarism Software which helps professors cross reference written assignments with possibly plagiarized information.
AI Detection Software is discussed more in-depth in Ethics of College Students Using ChatGPT
Lockdown browsers require students to download software on their computers, which limits the number of browsers that the student can open while they are taking exams.

AI Advancement Initiatives, Guidelines and Policies

Aside from using software to detect and prevent cheating, many universities are making students and faculty aware of changes in AI.

In Fall of 2023, the University of North Carolina at Chapel Hill created the UNC-Chapel Hill Generative AI Committee to help students and staff adapt to AI. This committee included a broad range of faculty and staff members and provided guidance for employees and students about how to use AI in classroom, research, and administrative work. This guidance outlines the following main points about the use of AI in teaching and class assignments:

Students should only use AI to help them think, not to complete assignments,
AI should be used responsibly and ethically,
Students are fully responsible for their submitted work and cannot blame AI for anything wrong or false,
Students should document any time they use AI,
Professors reserve the right to change specific AI guidelines depending on the assignment/exam, and
Confidential or personal information should not be put into AI tools.

UNC-Chapel Hill also has a “Carolina AI Literacy” initiative, which currently provides three instructional videos for students on:

AI prompting and thinking,
AI misinformation and biases, and
AI plagiarism and citation. [15]

UNC-Chapel Hill also has Generative AI Training Modules for faculty members. These modules are split into these categories:

Module 1 – Introduction to Generative AI
Module 2 – The Art & Science of Prompting AI
Module 3 – Teaching with AI
Module 4 – Ensuring Academic Integrity with AI
Module 5 – Launching Your AI Trajectory [16]

The UNC-Chapel Hill Writing Center provides tips that explain what generative AI is, how it can be used in education, and what the downsides of it can be. [17]

What is the takeaway?

In summary, there is no way around it: technology-based school learning is here to stay. Instead of trying to avoid it, professors need to be upfront with students as early as possible about what is and what is not accepted.

Professors should also take advantage of the online tools that are available to help them in their professional duties, including monitoring cheating.

With the quick emergence of AI, students may find out about new platforms before a professor can give the okay on its usage. To combat this, universities need to create and continuously update initiatives regarding AI. As a result of the fast-paced evolution of AI, UNC-Chapel Hill uses recommendations and best practices about AI usage, but in the future, this may shift towards requiring certain behavior through policy. It is also important for students and faculty alike to cooperate and communicate during this process since this new way of learning is new for everyone.

[1] Cheat Definition & Meaning – Merriam-Webster

[2] Academic Integrity: Overview | Office of Student Conduct (ncsu.edu)

[3] Academic Misconduct | Office of Student Conduct (ncsu.edu)

[4] POL 11.35.01 – Code of Student Conduct – Policies, Regulations & Rules (ncsu.edu)

[5] Think Twice Before Cheating in Online Courses (usnews.com)

[6] Common Reasons Students Cheat – Office of Academic Integrity – University at Buffalo

[7] I’m a Student. You Have No Idea How Much We’re Using ChatGPT. (chronicle.com)

[8] How ChatGPT and similar AI will disrupt education (sciencenews.org)

[9] Georgia Tech warns physics students who cheated: Confess or fail (ajc.com)

[10] Texas A&M investigating ‘large scale’ cheating case as universities see more academic misconduct in era of online classes – ABC13 Houston

[11] Honor Code | Chegg

[12] How Cheating in College Hurts Students (usnews.com)

[13] What Percentage of Schools Use Technology in the Classroom? (techyinspire.com)

[14] Think Twice Before Cheating in Online Courses (usnews.com)

[15] Videos | Carolina AI Literacy (unc.edu)

[16] Generative AI Training Modules (tarheels.live)

[17] Generative AI in Academic Writing – The Writing Center • University of North Carolina at Chapel Hill (unc.edu)

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How Teens Use Technology to Cheat in School

Why teens cheat, text messaging during tests, storing notes, copying and pasting, social media, homework apps and websites, talk to your teen.

Expectations and Consequences

When you were in school, teens who were cheating were likely looking at a neighbor’s paper or copying a friend’s homework. The most high-tech attempts to cheat may have involved a student who wrote the answers to a test on the cover of their notebook.

Cheating in today’s world has evolved, and unfortunately, become pervasive. Technology makes cheating all too tempting, common, and easy to pull off. Not only can kids use their phones to covertly communicate with each other, but they can also easily look up answers or get their work done on the Internet.

In one study, a whopping 35% of teens admit to using their smartphones to cheat on homework or tests. 65% of the same surveyed students also stated they have seen others use their phones to cheat in school. Other research has also pointed to widespread academic indiscretions among teens.

Sadly, academic dishonesty often is easily normalized among teens. Many of them may not even recognize that sharing answers, looking up facts online, consulting a friend, or using a homework app could constitute cheating. It may be a slippery slope as well, with kids fudging the honesty line a tiny bit here or there before beginning full-fledged cheating.

For those who are well aware that their behavior constitutes cheating, the academic pressure to succeed may outweigh the risk of getting caught. They may want to get into top colleges or earn scholarships for their grades. Some teens may feel that the best way to gain a competitive edge is by cheating.

Other students may just be looking for shortcuts. It may seem easier to cheat rather than look up the answers, figure things out in their heads, or study for a test. Plus, it can be rationalized that they are "studying" on their phone rather than actually cheating.

Teens with busy schedules may be especially tempted to cheat. The demands of sports, a part-time job , family commitments, or other after-school responsibilities can make academic dishonesty seem like a time-saving option.

Sometimes, there’s also a fairly low risk of getting caught. Some teachers rely on an honor system, and in some cases, technology has evolved faster than school policies. Many teachers lack the resources to detect academic dishonesty in the classroom. However, increasingly, there are programs and methods that let teachers scan student work for plagiarism.

Finally, some teens get confused about their family's values and may forget that learning is the goal of schooling rather than just the grades they get. They may assume that their parent would rather they cheat than get a bad grade—or they fear disappointing them. Plus, they see so many other kids cheating that it may start to feel expected.

It’s important to educate yourself about the various ways that today’s teens are cheating so you can be aware of the temptations your teen may face. Let's look at how teens are using phones and technology to cheat.

Texting is one of the fastest ways for students to get answers to test questions from other students in the room—it's become the modern equivalent of note passing. Teens hide their smartphones on their seats and text one another, looking down to view responses while the teacher isn't paying attention.

Teens often admit the practice is easy to get away with even when phones aren't allowed (provided the teacher isn't walking around the room to check for cellphones).

Some teens store notes for test time on their cell phones and access these notes during class. As with texting, this is done on the sly, hiding the phone from view. The internet offers other unusual tips for cheating with notes, too.

For example, several sites guide teens to print their notes out in the nutrition information portion of a water bottle label, providing a downloadable template to do so. Teens replace the water or beverage bottle labels with their own for a nearly undetectable setup, especially in a large class. This, of course, only works if the teacher allows beverages during class.

Rather than conduct research to find sources, some students are copying and pasting material. They may plagiarize a report by trying to pass off a Wikipedia article as their own paper, for example.

Teachers may get wise to this type of plagiarism by doing a simple internet search of their own. Pasting a few sentences of a paper into a search engine can help teachers identify if the content was taken from a website.

A few websites offer complete research papers for free based on popular subjects or common books. Others allow students to purchase a paper. Then, a professional writer, or perhaps even another student, will complete the report for them.

Teachers may be able to detect this type of cheating when a student’s paper seems to be written in a different voice. A perfectly polished paper may indicate a ninth-grade student’s work isn’t their own. Teachers may also just be able to tell that the paper just doesn't sound like the student who turned it in.

Crowdsourced sites such as Homework Helper also provide their share of homework answers. Students simply ask a question and others chime in to give them the answers.

Teenagers use social media to help one another on tests, too. It only takes a second to capture a picture of an exam when the teacher isn’t looking.

That picture may then be shared with friends who want a sneak peek of the test before they take it. The photo may be uploaded to a special Facebook group or simply shared via text message. Then, other teens can look up the answers to the exam once they know the questions ahead of time.

While many tech-savvy cheating methods aren’t all that surprising, some methods require very little effort on the student’s part. Numerous free math apps such as Photomath allow a student to take a picture of the math problem. The app scans the problem and spits out the answers, even for complex algebra problems. That means students can quickly complete the homework without actually understanding the material.

Other apps, such as HWPic , send a picture of the problem to an actual tutor, who offers a step-by-step solution to the problem. While some students may use this to better understand their homework, others just copy down the answers, complete with the steps that justify the answer.

Websites such as Cymayth and Wolfram Alpha solve math problems on the fly—Wolfram can even handle college-level math problems. While the sites and apps state they are designed to help students figure out how to do the math, they are also used by students who would rather have the answers without the effort required to think them through on their own.

Other apps quickly translate foreign languages. Rather than have to decipher what a recording says or translate written words, apps can easily translate the information for the student.

The American Academy of Pediatrics encourages parents to talk to teens about cheating and their expectations for honesty, school, and communication. Many parents may have never had a serious talk with their child about cheating. It may not even come up unless their child gets caught cheating. Some parents may not think it’s necessary to discuss because they assume their child would never cheat.

However, clearly, the statistics show that many kids do engage in academic discretions. So, don’t assume your child wouldn’t cheat. Often, "good kids" and "honest kids" make bad decisions. Make it clear to your teen that you value hard work and honesty.

Talk to your teen regularly about the dangers of cheating. Make it clear that cheaters tend not to get ahead in life.

Discuss the academic and social consequences of cheating, too. For example, your teen might get a zero or get kicked out of a class for cheating. Even worse, other people may not believe them when they tell the truth if they become known as dishonest or a cheater. It could also go on their transcripts, which could impair their academic future.

It’s important for your teen to understand that cheating—and heavy cell phone use—can take a toll on their mental health , as well. Additionally, studies make clear that poor mental health, particularly relating to self-image, stress levels, and academic engagement, makes kids more likely to indulge in academic dishonestly. So, be sure to consider the whole picture of why your child may be cheating or feel tempted to cheat.

A 2016 study found that cheaters actually cheat themselves out of happiness. Although they may think the advantage they gain by cheating will make them happier, research shows cheating causes people to feel worse.

Establish Clear Expectations and Consequences

Deciphering what constitutes cheating in today's world can be a little tricky. If your teen uses a homework app to get help, is that cheating? What if they use a website that translates Spanish into English? Also, note that different teachers have different expectations and will allow different levels of outside academic support.

Expectations

So, you may need to take it on a case-by-case basis to determine whether your teen's use of technology enhances or hinders their learning and/or is approved by their teacher. When in doubt, you can always ask the teacher directly if using technology for homework or other projects is acceptable.

To help prevent cheating, take a firm, clear stance so that your child understands your values and expectations. Also, make sure they have any needed supports in place so that they aren't tempted to cheat due to academic frustrations or challenges.

Tell your teen, ideally before an incident of academic dishonesty occurs, that you don’t condone cheating of any kind and you’d prefer a bad grade over dishonesty.

Stay involved in your teen’s education. Know what type of homework your teen is doing and be aware of the various ways your teen may be tempted to use their laptop or smartphone to cheat.

To encourage honesty in your child, help them develop a healthy moral compass by being an honest role model. If you cheat on your taxes or lie about your teen’s age to get into the movies for a cheaper price, you may send them the message that cheating is acceptable.

Consequences

If you do catch your teen cheating, take action . Just because your teen insists, “Everyone uses an app to get homework done,” don’t blindly believe it or let that give them a free pass. Instead, reiterate your expectations and provide substantive consequences. These may include removing phone privileges for a specified period of time. Sometimes the loss of privileges —such as your teen’s electronics—for 24 hours is enough to send a clear message.

Allow your teen to face consequences at school as well. If they get a zero on a test for cheating, don’t argue with the teacher. Instead, let your teen know that cheating has serious ramifications—and that they will not get away with this behavior.

However, do find out why your teen is cheating. Consider if they're over-scheduled or afraid they can’t keep up with their peers. Are they struggling to understand the material? Do they feel unhealthy pressure to excel? Ask questions to gain an understanding so you can help prevent cheating in the future and ensure they can succeed on their own.

It’s better for your teen to learn lessons about cheating now, rather than later in life. Dishonesty can have serious consequences. Cheating in college could get your teen expelled and cheating at a future job could get them fired or it could even lead to legal action. Cheating on a future partner could lead to the end of the relationship.

A Word From Verywell

Make sure your teen knows that honesty and focusing on learning rather than only on getting "good grades," at all costs, really is the best policy. Talk about honesty often and validate your teen’s feelings when they're frustrated with schoolwork—and the fact that some students who cheat seem to get ahead without getting caught. Assure them that ultimately, people who cheat truly are cheating themselves.

Common Sense Media. It's ridiculously easy for kids to cheat now .

Common Sense Media. 35% of kids admit to using cell phones to cheat .

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Marksteiner T, Nishen AK, Dickhäuser O. Students' perception of teachers' reference norm orientation and cheating in the classroom . Front Psychol . 2021;12:614199. doi:10.3389/fpsyg.2021.614199

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Farnese ML, Tramontano C, Fida R, Paciello M. Cheating behaviors in academic context: does academic moral disengagement matter? Procedia - Social and Behavioral Sciences . 2011;29:356-365. doi:10.1016/j.sbspro.2011.11.250

Pew Research Center. How parents and schools regulate teens' mobile phones .

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By Amy Morin, LCSW Amy Morin, LCSW, is the Editor-in-Chief of Verywell Mind. She's also a psychotherapist, an international bestselling author of books on mental strength and host of The Verywell Mind Podcast. She delivered one of the most popular TEDx talks of all time.

Why Do Students Cheat?

Posted July 19, 2016
By Zachary Goldman

In March, Usable Knowledge published an article on ethical collaboration , which explored researchers’ ideas about how to develop classrooms and schools where collaboration is nurtured but cheating is avoided. The piece offers several explanations for why students cheat and provides powerful ideas about how to create ethical communities. The article left me wondering how students themselves might respond to these ideas, and whether their experiences with cheating reflected the researchers’ understanding. In other words, how are young people “reading the world,” to quote Paulo Freire , when it comes to questions of cheating, and what might we learn from their perspectives?

I worked with Gretchen Brion-Meisels to investigate these questions by talking to two classrooms of students from Massachusetts and Texas about their experiences with cheating. We asked these youth informants to connect their own insights and ideas about cheating with the ideas described in " Ethical Collaboration ." They wrote from a range of perspectives, grappling with what constitutes cheating, why people cheat, how people cheat, and when cheating might be ethically acceptable. In doing so, they provide us with additional insights into why students cheat and how schools might better foster ethical collaboration.

Why Students Cheat

Students critiqued both the individual decision-making of peers and the school-based structures that encourage cheating. For example, Julio (Massachusetts) wrote, “Teachers care about cheating because its not fair [that] students get good grades [but] didn't follow the teacher's rules.” His perspective represents one set of ideas that we heard, which suggests that cheating is an unethical decision caused by personal misjudgment. Umna (Massachusetts) echoed this idea, noting that “cheating is … not using the evidence in your head and only using the evidence that’s from someone else’s head.”

Other students focused on external factors that might make their peers feel pressured to cheat. For example, Michima (Massachusetts) wrote, “Peer pressure makes students cheat. Sometimes they have a reason to cheat like feeling [like] they need to be the smartest kid in class.” Kayla (Massachusetts) agreed, noting, “Some people cheat because they want to seem cooler than their friends or try to impress their friends. Students cheat because they think if they cheat all the time they’re going to get smarter.” In addition to pressure from peers, students spoke about pressure from adults, pressure related to standardized testing, and the demands of competing responsibilities.

When Cheating is Acceptable

Students noted a few types of extenuating circumstances, including high stakes moments. For example, Alejandra (Texas) wrote, “The times I had cheated [were] when I was failing a class, and if I failed the final I would repeat the class. And I hated that class and I didn’t want to retake it again.” Here, she identifies allegiance to a parallel ethical value: Graduating from high school. In this case, while cheating might be wrong, it is an acceptable means to a higher-level goal.

Encouraging an Ethical School Community

Several of the older students with whom we spoke were able to offer us ideas about how schools might create more ethical communities. Sam (Texas) wrote, “A school where cheating isn't necessary would be centered around individualization and learning. Students would learn information and be tested on the information. From there the teachers would assess students' progress with this information, new material would be created to help individual students with what they don't understand. This way of teaching wouldn't be based on time crunching every lesson, but more about helping a student understand a concept.”

Sam provides a vision for the type of school climate in which collaboration, not cheating, would be most encouraged. Kaith (Texas), added to this vision, writing, “In my own opinion students wouldn’t find the need to cheat if they knew that they had the right undivided attention towards them from their teachers and actually showed them that they care about their learning. So a school where cheating wasn’t necessary would be amazing for both teachers and students because teachers would be actually getting new things into our brains and us as students would be not only attentive of our teachers but also in fact learning.”

Both of these visions echo a big idea from “ Ethical Collaboration ”: The importance of reducing the pressure to achieve. Across students’ comments, we heard about how self-imposed pressure, peer pressure, and pressure from adults can encourage cheating.

Where Student Opinions Diverge from Research

The ways in which students spoke about support differed from the descriptions in “ Ethical Collaboration .” The researchers explain that, to reduce cheating, students need “vertical support,” or standards, guidelines, and models of ethical behavior. This implies that students need support understanding what is ethical. However, our youth informants describe a type of vertical support that centers on listening and responding to students’ needs. They want teachers to enable ethical behavior through holistic support of individual learning styles and goals. Similarly, researchers describe “horizontal support” as creating “a school environment where students know, and can persuade their peers, that no one benefits from cheating,” again implying that students need help understanding the ethics of cheating. Our youth informants led us to believe instead that the type of horizontal support needed may be one where collective success is seen as more important than individual competition.

Why Youth Voices Matter, and How to Help Them Be Heard

Our purpose in reaching out to youth respondents was to better understand whether the research perspectives on cheating offered in “ Ethical Collaboration ” mirrored the lived experiences of young people. This blog post is only a small step in that direction; young peoples’ perspectives vary widely across geographic, demographic, developmental, and contextual dimensions, and we do not mean to imply that these youth informants speak for all youth. However, our brief conversations suggest that asking youth about their lived experiences can benefit the way that educators understand school structures.

Too often, though, students are cut out of conversations about school policies and culture. They rarely even have access to information on current educational research, partially because they are not the intended audience of such work. To expand opportunities for student voice, we need to create spaces — either online or in schools — where students can research a current topic that interests them. Then they can collect information, craft arguments they want to make, and deliver their messages. Educators can create the spaces for this youth-driven work in schools, communities, and even policy settings — helping to support young people as both knowledge creators and knowledge consumers.

Additional Resources

Read “ Student Voice in Educational Research and Reform ” [PDF] by Alison Cook-Sather.
Read “ The Significance of Students ” [PDF] by Dana L. Mitra.
Read “ Beyond School Spirit ” by Emily J. Ozer and Dana Wright.

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Cheating in the classroom increases in the digital age

In the end, students who cheat are cheating themselves

Photo via Flikr under the Creative Commons License

A student cheating on a multiple choice test.

Jasmyn Sanchez , Staff Writer March 18, 2019

You forgot to study for the big test that lays on your desk glaring back at you. You can feel your leg shake, as sweat beads up on your forehead. You sneak a peek to your left and catch a glimpse of the student who always studies. Then, you tilt your head just a tad and shift your eyes just far enough to spot the answer to question number 7. You quickly copy down the answer. Guilt building up in your chest as you take that lonely march to the front of the classroom to hand in your test.

Cheating. It is basically plagiarism, the act of taking someone’s work or ideas and passing it off as your own. It has, and always will be, in the classrooms of schools at all levels. Practically everybody has either cheated or at least thought about it once in his or her life.

It is a seemingly easy way to get a good grade. For a variety of reasons, there are more opportunities to cheat and beef up one’s GPA. So, is this kind of behavior happening more often than ever?

The answer is simple: Yes.

Cheating has shown to be getting worse everywhere. A study conducted by Josephson Institute Center for Youth Ethics found interesting statistics on cheating. Fifty-nine percent of high school students admitted to cheating on a test during the last year and 34 percent reported doing it more than twice. Years later a survey of 24,000 students showed that 95 percent admitted to some form of cheating.

There are a variety of reasons why students turn to cheating.

“I think students feel the need to cheat for a lot of different reasons like being under stress can make you desperate,” said junior Rhode Theodore. “Cheating is getting worse because our generation is under a lot more stress and pressure than before.”

Clearly, cheating is not going away any time soon. Students who choose not to take this route tend to get frustrated with those who do.

“I think it’s unfair that some people put in their time and effort into trying to get a good grade while other people slack off and use the easy way to get good grades,” said sophomore Thomas Mathiesen.

Polls conducted at Fordham University, have shown that cheaters have a 3.41 Grade Point Average (GPA), whereas the average of non0-cheaters is only 2.85.

This statistic is staggering. Obviously, the students who play fair have a right to be upset. They study for hours and try their very best in their classes, only to score lower than students who didn’t put the same work and effort.

“I think students feel the need to cheat because they either have no time to study due to extracurriculars or personal issues, or they would rather spend their time watching Netflix or scrolling through Instagram,” said sophomore Isabella Contino. “At this point, cheating is the only answer in their eyes.”

Yet cheating doesn’t come without serious consequences — if a student is caught.

Schools have implemented rules and consequences for students who are found cheating. Once caught, these students are sometimes frowned upon by their peers, as well as their teachers.

Obviously, instant access to online resources can make it easier for students to cheat. Not only are they cheating on the test, but they are cheating themselves out of an essential skill in life: critical thinking. What’s even worse is that studies show that students who cheat in school will likely cheat in the workplace.

Perhaps the most effective change made at SHS to help curb cheating is the new cell phone policy. Students are required to turn their phones in at the beginning of every class. This prevents them from craftily looking up information during test-taking. Thus, students must rely on old school cheating.

“We don’t have the ability to keep our phones any more during classes but students still cheat by looking at their classmate’s exam who are sitting by or near them.” said sophomore Mehrin Hossain.

Overall, cheating has gotten worse and will always be an easy way for some students to earn good grades. Though they may not admit it now, they will find out that, in the long run, they are really cheating themselves.

“The world is filled with people who want to succeed through their own work and people who want to succeed but without putting any effort into the success they desire,” says senior Kendall White. “There will always be cheaters, it’s sad to say but it’s true. A lot of people seek the easy way to success but later on it will catch up with them and sooner or later they’re going to fail.”

It would be better for everybody if they simply put the work in themselves and earned the grades the old fashioned way: through hard work.

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Justin Meserole • Mar 20, 2019 at 9:56 AM

The biggest difference between cheating and plagiarism is that plagiarism the theft of copyrighted works without credit. Tests are standardized to have all the same answers and information even if you were to cheat off of someones test you’d still have a likely chance of getting answers correctly especially on scantron sheets which are highly popular for testing.

Dan Malec • Mar 19, 2019 at 1:12 PM

I agree with the fact about kids being under more pressure than before.

Brandyn wilson • Mar 19, 2024 at 10:56 AM

This is mostly true

Michael guzman • Mar 19, 2019 at 1:02 PM

While the phone boxes are annoying and inconvenient there has been a big decrease from cheating because students lack phones. From my experience in the classroom students now are paying more attention to the teacher instead of their pockets so whether we like it or not phone boxes work.

Lukas cardoni • Mar 19, 2019 at 9:10 AM

The rise in cheating is not because of students lacking morals but because of the school system itself.

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

Open access
Published: 23 July 2022
Volume 28 , pages 1251–1271, ( 2023 )

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Juliette C. Désiron ORCID: orcid.org/0000-0002-3074-9018 1 &
Dominik Petko ORCID: orcid.org/0000-0003-1569-1302 1

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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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Controversial AI ChatGPT didn't increase cheating in high schools, Stanford study finds

When ChatGPT launched late last year, some high schools quickly developed strict policies to prohibit students from using the powerful AI chatbot tool over fears of cheating on assignments.

But now a new study from researchers at Stanford reveals the percentage of high school students who cheat remains statistically unchanged compared to previous years without ChatGPT.

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The university, which conducted an anonymous survey among students at 40 US high schools, found about 60% to 70% of students have engaged in cheating behavior in the last month, a number that is the same or even decreased slightly since the debut of ChatGPT, according to the researchers.

In November 2022, ChatGPT -- developed by OpenAI -- went viral for generating convincing responses and essays in response to user prompts in seconds. While ChatGPT and similar AI tools have gained traction, the technology has raised some concerns over inaccuracies and its potential to perpetuate biases , spread misinformation and enable plagiarism.

ALSO SEE: What's included in the EU's new rules on AI and what it means for future regulation

"While there are individual alarming cases in the news about AI being used for cheating, we are seeing little evidence that the needle has moved for high schoolers overall," Victor Lee, Stanford's faculty lead for AI and education who helped oversee the survey, told CNN.

The findings come as research center Pew recently reported only 19% of teens ages 13 to 17 have used the platform for schoolwork. (And only two-thirds of teens have heard of ChatGPT).

Lee said the number of students accessing ChatGPT could change in the future as they learn more about the technology.

The survey also revealed students believe the tool should be allowed for "starter" purposes with assignments, such as asking it to generate new concepts or ideas for an assignment. Most of the respondents, however, agreed it should not be used to write a paper.

"It shows that a majority of students truly want to learn and see AI as a way to help them - as opposed to seeing it only as a tool to 'do school' and cut corners or save time as they complete assignments," said Denise Pope, a senior lecturer at Stanford's Graduate School of Education who also helped oversee the survey.

Some of the main cited reasons why students cheat include struggling to grasp subject material, not having enough time to do homework and feeling pressured to perform well, according to the researchers.

"We are only a little over a year into ChatGPT capturing public attention, so we all should expect some shifts over time with schools, work, and daily life," Lee said. "A lot depends on how schools choose to approach AI as a topic and a tool, which could move things in either direction."

Pope said educators should consider inviting student voices into these conversations, calling them "insightful and thoughtful" on the topic of AI and cheating. In a recent panel discussion, the researchers said students talked through the purpose of learning to write and debated what else they should be learning in school as AI continues to emerge. "That allowed all of us in the discussion to talk about the role of schools moving forward in a world where AI is ubiquitous," she said.

School responses

In the first few months after the release of ChatGPT, fears over cheating escalated. Public schools in New York City and Seattle were among the first institutions to ban students and teachers from using ChatGPT on the district's networks and devices

Some college-level instructors told CNN at the time they shifted back to in-classroom essays for the first time in years, and others required more personalized essays. Others said students were also required to film short videos that elaborate on their thought process.

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Nowadays, however, more schools are encouraging and even teaching students how to best use these tools. Vanderbilt University, for example, is an early leader taking a strong stance in support of generative AI by offering university-wide training and workshops to faculty and students. A three-week 18-hour online course offered this summer was taken by over 90,000 students.

With more experts expecting the continued application of artificial intelligence, professors fear ignoring or discouraging the use of it will be a disservice to students and leave many behind when entering the workforce.

"It cannot be ignored," Jules White, an associate professor of computer science at Vanderbilt University, previously told CNN. "I think it's incredibly important for students, faculty and alumni to become experts in AI because it will be so transformative across every industry in demand so we provide the right training."

Although concerns around cheating still exist, White said he believed students who want to plagiarize can still seek out other methods such as Wikipedia or Google searches. Instead, he said students should be taught that "if they use it in other ways, they will be far more successful."

Stanford also offers an online hub with free resources to help teachers explain to high school students the dos and don'ts of using AI.

In the meantime, the researchers said they will continue to collect data throughout the school year to see if they find evidence that more students are using ChatGPT for cheating purposes.

"The jury is still out, but our current data shows that students don't necessarily want to use it to short-cut learning as much as they want to use it to enhance their learning," Pope said.

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Behavioral correlates of cheating: Environmental specificity and reward expectation

Michael isakov.

1 Lincoln-Sudbury Regional High School, Sudbury, Massachusetts, United States of America

Arnav Tripathy

2 Department of Mathematics, Stanford University, Stanford, California, United States of America

Associated Data

All files are available from the following repository: https://sourceforge.net/projects/behavioral-correlates-cheating/ .

Academic dishonesty has been and continues to be a major problem in America’s schools and universities. Such dishonesty is especially important in high schools, where grades earned directly impact the academic careers of students for many years to come. The rising pressure to get the best grades in school, get into the best college, and land the best paying job is a cycle that has made academic dishonesty increase exponentially. Thus, finding the widespread roots of cheating is more important now than ever. In this study, we focus on how societal norms and interactions with peers influence lying about scores in order to obtain a benefit in a high school population. We show that (1) the societal norms that go hand in hand with test-taking in school, as administered by a teacher, significantly dampen small-scale dishonesty, perhaps suggesting that context-dependent rewards offset cheating; (2) providing reminders of societal norms via pre-reported average scores leads to more truthful self-reporting of honesty; (3) the matrix search task was shown to not depend on class difficulty, confirming its effectiveness as an appropriate method for this study; (4) males seem to cheat more than females; and (5) teenagers are more dishonest earlier in the day. We suggest that students understand that cheating is wrong, an idea backed up by the literature, and that an environment which clearly does not condone dishonesty helps dampen widespread cheating in certain instances. This dampening effect seems to be dependent on the reward that students thought they would get for exaggerating their performance.

Introduction

Cheating is a complex and often contradictory phenomenon. It is well-established that humans choose cooperative options in many realistic scenarios, with cooperation or “playing fair” often shaped by social heuristics [ 1 – 3 ]. However, cheating in specific situations is still seen to be highly prevalent [ 4 ]. One particularly intriguing phenomenon is academic dishonesty. This is perhaps most evident in high schools, where grades earned are thought to pave the path to students’ futures. The rapidly rising expectations of high schoolers has brought levels of cheating to dizzying heights; as many as 90 percent of students reported cheating in high school or in college [ 5 ]. This is up from just under 25 percent in the 1940s. Maturity is often thought to be one of the main constraining factors for cheating. This is true in that younger students (freshman and sophomores in high school), cheat more than older kids on tests, homework, and essays [ 6 , 7 ]. However, this trend is ‘reset’ upon entering a new environment, that is, younger students in college are more likely to cheat than older students in high schools, with overall cheating being similar in different environments. Thus, it appears that there are other things impacting dishonesty apart from physiology, knowledge, and general maturity.

Although cheating has important applications for school related activities, individuals who engage in academic dishonesty are also more likely to engage in unethical behavior outside of school [ 8 , 9 ]. This is because individuals who succumb to the temptation to cheat have been shown to have less self-control than those who do not, a key point with many societal ramifications [ 5 ]. Considering that dishonesty is so common in academic and professional environments, we expect to find widespread dishonesty and corruption in other areas. With that in mind, it must be noted that young children do not have nearly the same ability or willingness to be dishonest, suggesting that it is not an innate property of humans.

Unethical practices by corporations costs the US tens of billions of dollars each year. However, things that ordinary people would not consider problematic can prove to be when occurring on a large scale in a population. For example, insurance fraud and small-scale tax evasion by millions of people costs the US government more than $320 billion dollars in revenue each year [ 10 ]. Such statistics beg the question of what so many different people could possibly have in common if dishonesty is indeed not innate. That is, if humans understand fairness on an intuitive level driven by both societal mechanisms and by social heuristics, what enables this high level cheating in specific situations?

There are many root causes of academic dishonesty, perhaps one of the most important of which is the idea of social conformity and societal pressure to succeed [ 11 , 12 ]. Such societal factors have the ability to affect large masses of people, making them suitable candidates for explaining the widespread phenomenon of cheating. Many studies have shown that the people around us affect our behavior in subtle ways [ 13 ]. Part of the reason that cheating in high schools has reached such astronomical heights is that a self-perpetuating system of pressure and stress is running in America’s high schools. In an age of online statistics concerning just about everything, rising pressure is on students to succeed [ 14 ]. This increases stress, decreases actual performance, and increases cheating, part of a horrible cycle that has led some researchers to refer to cheating in high schools as an “epidemic “[ 5 ]. This issue is exacerbated by the fact that many teachers are not fully aware of the stress they may be causing their students [ 15 ]. The idea of necessary, objective success in school is a huge problem in our society, and has other implications such as depression, brought on by the dichotomous thinking promoted by many ill-advised parents. However, this is not the only thing that makes cheating as prevalent in American schools.

Conformity has been shown to have an incredibly powerful effect on people’s opinions and people's’ actions, sometimes even causing individuals to give an obviously incorrect answer just to fit in with a group that is blatantly wrong about something [ 16 ]. Despite this being a prime candidate for why immoral academic behavior is so prevalent in our schools, surprisingly little research has been done on the topic. Many students seem to (correctly) believe that many of their peers are cheating and use this to justify their actions [ 17 , 18 ]. However, another study came up with a seemingly contradictory finding–cheating decreased significantly in classes that reported high student cohesiveness in their classroom [ 19 ]. Furthermore, that study also found that cheaters operated on less mature stages of moral development, thus suggesting that cheating was an individual choice and not a result of true vicarious learning. Since many of the few field studies done on the topic have been self-reported surveys, more research, particularly more direct observational research, needs to be done in order to find what the true correlation between various social interactions and cheating is. It is important to note that different types of social interactions (such as the ones between friends, family, or strangers) could lead to different results in terms of promoting or inhibiting dishonest behavior.

An important influence of cheating, and one that often goes unmentioned, is the effect of the environment on the rate of dishonest behavior. This is a difficult factor to study because most test-taking situations where cheating is directly observed by researchers are outside of the usual learning environment, such as a classroom. Also, surveys, the most common way to study dishonest behavior, cannot realistically expect the participant to recall an accurate answer about places where they cheated. Much of the research in this area has focused on asking students about their perceptions of the classroom and then surveying the participant about dishonesty there [ 19 , 20 ]. The results of two different surveys conclusively found that different classroom settings have significantly different levels of cheating, with similar qualities describing classrooms with reduced levels of dishonesty in both the US and South Korea. This is important in and of itself because it shows that research about how social interaction and perception of the environment affects academic dishonesty in high school is probably generalizable to other societies. However, nearly all of the aforementioned studies fail to recognize the importance of the actual classroom in the dishonest experience. This oversight leads us to believe that some conclusions may not representative of academic cheating as it naturally occurs.

Previous studies have found that priming can make a significant difference on how much people falsify their scores; for example, thinking about the Ten Commandments reportedly eliminates statistically significant cheating. Some of those studies also found that creativity was an important factor in academic dishonesty, that is, more creative people cheated more. Interestingly, intelligence was not correlated with cheating in those studies[ 10 , 21 ].

Different studies of cheating often come up with vastly different conclusions, probably due to the sheer number of variables that can impact dishonesty. For example, increasing the expected magnitude of reward for dishonesty was not found to significantly increase cheating. However, other studies have studied something similar and have come up with opposite or inconclusive results. One of the many variables that must be considered in such experiments is perceived punishment for dishonesty. The effect of punishment on cheaters was found to be dependent on the population, various environmental factors, and perceived benefit from dishonesty [ 22 – 24 ]. Gender is also an interesting factor to consider when studying academic dishonesty; many studies found that males cheat slightly more than females without a statistically significant result. For instance, a study of more than 270 students in Italy found no statistically significant difference between cheating in males and females, but proposed that a larger sample size or a different experiment might show one [ 25 ].

For this study, we collected and analyzed data from tests administered by teachers during class time in order to simulate the effect of the school environment on cheating. We delve into how various factors related to social behaviors relate to dishonesty, both individually, and when working in pairs.

Materials and methods

All anonymized data is available online at https://sourceforge.net/projects/behavioral-correlates-cheating . The project was approved by the Massachusetts State Science and Engineering Fair SRC and the Lincoln-Sudbury Regional High School IRB. The project was reviewed and a form was signed (written consent) by three members of the school IRB. All participants gave written consent to the experiment, and consent on behalf of minors was given by participants’ parents. The IRB reviewed the method of consent used for minor participants in this study. Although participants were blinded to the goals during testing, teachers were instructed to debrief their students after all tests were administered.

In this study, we gave a matrix search task test to N = 243 students (N individual = 161 split among 4 individual experimental conditions, and N pairs = 82 split among 2 pair conditions) from different classes and grade levels at Lincoln-Sudbury Regional High School, a US high school located in Sudbury, MA. Participants were recruited through their teachers, who told students in their classes that this experiment would be taking place during class time. No exclusion criteria were applied: all students were allowed to participate, and participation was voluntary (see S1 Table for a table of descriptive statistics on participants).

The individual conditions consisted of a control and three experimental versions, which involved self-reported scores by the students and the recycling of other testing materials to eliminate any anxiety over repercussions. In particular:

Control Condition: Students were told that their entire testing packet would be collected. At the end, the packets were collected and hand-graded (N = 42),
Experimental Regular: before beginning the task, students were told that they would not be submitting the testing materials, and that test materials would be destroyed at the end of the session. We collected only a sheet with self-reported scores (N = 30).
Experimental Friend (Priming): same as Experimental Regular, except that prior to the beginning of the task, participants were asked to list three qualities that described their best friend. (N = 60).
Experimental Average (Priming): Same as Experimental Regular, except that prior to the beginning of the matrix search task, participants were told that an average number of matrices solved was 11 (this number was meant to be significantly higher than the expected average in the control). (N = 29).

The pair versions were divided into a control (N = 21 pairs) and experimental (N = 20 pairs) section, with double the questions. For the pair experimental there was no priming, resulting in a test analogous to the plain self-reported version from the individual conditions. Pairs were assigned by a random number generator. We could see if people were dishonest by comparing the averages of the classes for the control and experimental groups–a large discrepancy would indicate cheating on the part of the experimental group. The test consisted of 20 or 40 (individual test and pair test, respectively) 4x3 matrices where the participant had to find the two numbers that sum up to 10 in as many matrices as they could in four minutes (see Fig 1 for schematic of task). In the instructions, students were told that four randomly chosen students from each class would receive a Jolly Rancher for every matrix they correctly solved.

An external file that holds a picture, illustration, etc.
Object name is pone.0186054.g001.jpg

The bottom of the figure shows a larger view of one of the matrices, with the correct answer filled in blue. The real task had 20 matrices (individual condition) and two independent sets of 20 matrices (for a total of 40) for the pair condition.

After the test, participants were asked a series of post experimentation questions about how they perceived their honesty, intelligence, and popularity, as well as the class and the ‘block’ in which they were taking the test. We ranked the classes on a scale of 1–3, with 1 being the most difficult, to see if class difficulty correlated with score or the self-reported characteristics. The ‘block’ is a system of time used by the high school where we conducted this experiment, and was converted into a number 1–6 which represented when the class occurred during the day, with 1 being the earliest (at 7:50 A.M.). This data would be used to test if anything related to time, such as alertness, was correlated with academic dishonesty. We used peoples’ names to identify their gender. Outliers such as those with scores greater than the number of matrices given were removed from our analyses (N = 2). For this study, we mainly considered the individual conditions, although we also discuss some observations about the pair conditions as well.

Looking at the distribution of scores, the individual Control Condition is a positively-skewed unimodal distribution (median = 6, skewness = 0.67), while the Experimental Average group more closely resembles a normal distribution with an outlier (median = 6, skewness = 0.17 with the outlier removed). The large standard deviation of the scores of the control classes (SD = 3.93) is almost double that reported in prior literature using the same experimental task [ 10 ]. The Experimental Friend group is highly asymmetrical despite having the same median (median = 6), and is less spread out (SD = 3.27) than the Experimental Regular group (see Fig 2 ). Focusing on individual groups, we found no statistically significant difference between the means of the different designs (see Fig 3 ). A formal comparison of distributions with the Kolmogorov-Smirnov test was also not significant (p = 0.886), likely due to the sample size. However, the differing significance in regression models (such as dependence on gender in the experimental conditions but not in the control, which has been shown to be associated with cheating in the literature) leads us to believe that some cheating did occur. The lack of pronounced cheating may have been influenced by either the nature or the magnitude of the rewards. While the latter is in line with previous studies, the former may have had a significant effect due to the fact that the experiment took place in a classroom setting (see Discussion ).

An external file that holds a picture, illustration, etc.
Object name is pone.0186054.g002.jpg

Blue line represents mean.

An external file that holds a picture, illustration, etc.
Object name is pone.0186054.g003.jpg

Error bars are 95% confidence intervals. While the distributions are visibly different between conditions (compare Fig 2 ), there is no significant difference in means between individual conditions.

First, we examined how demographics (age, gender, number of siblings), self-perception (honesty, popularity, intelligence), and environmental factors (class level, block) influenced individual score across univariate models. Scores were not dependent on class level in either the control (p = 0.054) or an aggregate of the experimental conditions (p = 0.189), in accordance with literature that claimed that this task was not correlated with success in school (see S2 Table ). Our study also found a difference between cheating in boys and girls. It was statistically significant for the Experimental Average condition (p = 0.032) with a large effect size of 3.4 extra matrices found among males, while the other experimental conditions were suggestive of a gender gap in performance, with boys performing better in all three. In the Control Condition, no such difference was present (p = 0.107), leading us to believe that boys cheated more than girls overall. Indeed, when we pooled all the experimental conditions together, the gender gap turned out to be statistically significant, with boys cheating more by about 1.8 matrices (p = 0.013; see S2 Table ). We also found time of day to be negatively correlated with cheating: for each block later in the day, students in the experimental conditions ‘performed’ 0.5 matrices worse (p = 0.008). There was no such difference in the control (p = 0.545; see S2 Table ), suggesting dishonesty in the self-reported scores. The additional variables were not significant predictors of score in univariate models (p > 0.05).

We also found interesting results concerning self-perception. In the Experimental Average condition, score and honesty were negatively correlated–a one point decrease in honesty corresponded to a score of an additional 1.2 matrices (p < 0.001; see S3 Table ). Other demographic, self-perception, and environmental variables were ultimately not predictive of score. All of the aforementioned statistically significant results survived appropriate controls.

Interestingly, the absolute values of participants’ scores in our study were quite different from the literature. The mean score in our control group was 6.8 matrices answered correctly, more than 50% higher than were reported by similar studies [ 10 ]. Our standard deviation was also significantly larger than that shown in previous studies.

Potentially due to the sample size and to testing irregularities that emerged after the conclusion of the experiment in post-experiment interviews with teachers, none of the variables we tested for in the pair experiments were significant predictors of score. So, we will focus our analysis on the individual versions of the test. However, we note the interesting finding that tests done in pairs ‘underperformed’. That is, even in the control group, the mean did not even come near to having a mean double that of the individual tests (the pair average was just under 65 percent higher than the individual average).

This study strongly suggests that setting has a large impact on cheating behaviors. Some studies found in the literature were done in universities, but it appears as though they were not done in the classroom during regular class hours, all but negating the effect of the school environment on the study. While this is useful for certain things, since it eases restrictions on generalizing results, it does not accurately factor in the effects of societal norms on cheating. As we noted in the results, the distribution of scores in the control was very different from the experimental conditions, which leads us to believe that some people did in fact cheat, just not enough to make a noticeable difference in our relatively small sample size. Additionally, it is important to note that since participants were told in advance how they would be scored (self-reported or not), it is possible that those who knew they would be graded by an authority put in more effort than those who knew they could cheat. This might also contribute to the apparent lack of dishonesty in the experimental conditions. That is, lying may have at least partially compensated for the lack of effort.

This study further suggests that the type of reward is important in whether or not dishonesty will be widespread. The dampening of a cheating effect might mean that the classroom setting is prone only to one type of dishonesty, that is, cheating that concerns grades. If someone expects a very specific benefit from their actions, they may be less likely to cheat for a different reward of the same magnitude. This would make our rewards for success seem unimportant, and thus not result in the widespread cheating that is reported by surveys in high schools around the country. This idea makes sense because morality is enforced in schools outside of graded assignments, and seems to actually change the behavior of students for the better when things like grades are not concerned [ 26 ].

When all the conditions are pooled together, class level was found to correlate with score. This finding supports the notion that environment influences motivation as well–the data may suggest that students in more difficult classes were more motivated to do well even on something as unrelated to their studies as this matrix search task. This study confirms earlier findings that cheating is not correlated with intelligence, since different level classes had a similar difference between control and experimental conditions.

Self-reported honesty was found to be correlated with score in the Experimental Average condition, and although this result only appeared in one condition, we consider it important for several reasons. Firstly, it seems to support the idea that some cheating occurred, just not enough to be picked up by the Kolmogorov-Smirnov test. This is because the negative coefficient of the regression is in line with logic–higher scores, presumably achieved by cheating, result in lower self-reported honesty. Furthermore, this finding seems to stress the importance of the surroundings on participants–the presence of the average was the only difference between this and the Experimental Regular group, which leads us to believe that the very idea of norms brought on by the mention of an average made people self-report more truthfully than in other experimental groups.

Self-reported intelligence was correlated with score in the control, but not in the experimental conditions, leading us to believe that cheaters understand that their new score is not representative of their ability. The larger standard deviation in the experimental conditions, probably caused by sporadic dishonesty, made the correlation not statistically significant. We found that self-reported popularity was not significant in any case, possibly because of the open-ended nature of popularity. The negative correlation between time of day and dishonest behavior is interesting in that it suggests a possible link between alertness and cheating, and also because it could have important policy implications for testing. The small age range in the high school made correlation between it and score unlikely, and we accordingly found none.

We showed a statistically significant correlation between the score of males and the score of females, especially in the experimental conditions. An ANOVA on score that controlled for experimental condition and gender returned a statistically significant result (p = 0.005). Since there was no significant gender gap in the control, we believe that males cheated more when given the opportunity to do so. Furthermore, an overall model of all the individual versions also saw males performing better, likely due to dishonesty. Although for our study, age did not seem to be linked with this effect, the difference between this and an earlier study which found no gender gap in young children implies that genders begin to differentiate in morality sometime between 12 and 15. This makes sense in biological terms–more white matter in the brain develops the ability to cheat and lie. Also, adolescent boys are known for being significantly more impulsive than their female counterparts, which might cause them to cheat once and get trapped in the endless cycle of cheating and stress. This result is especially intriguing because it shows that maturity, which generally increases with age, does not consistently offset the biological and environmental factors that make cheating more likely.

As mentioned earlier, pairs significantly underperformed when compared to individuals taking the test. This is probably due to two factors: any cheating that occurred in the individual versions was negated because of limited time to cooperate, and time constraints did not allow for proper divvying up of work and focus on the completion of the task. Thus, teachers might use group work on certain tasks to reduce widespread cheating. However, they would have to remember that two people in a group work at a different pace than as individuals, a fact that has been often overlooked in the literature.

We generated a matrix search task test which we distributed to 16 high school classes (N = 243) in the form of six different experimental conditions. The participants were then asked the time they were taking the test, their age, their perceived intelligence, popularity, and honesty. We ranked the classes they were taking the test in by level of difficulty. The most important findings were: (1) the societal norms that go hand in hand with test-taking in school as administered by a teacher significantly dampen small-scale cheating–perhaps suggesting a trend of environment-specific rewards setting off cheating; (2) reminding participants about societal norms by giving them an average score made people report honesty more truthfully; (3) a matrix search task is appropriate for these kind of studies because results do not correlate with scholastic achievement; (4) males seem to cheat more than females; and (5) later time of day dampens cheating in high school students. Dishonesty in school has important implications in the lives of students after high school or college, and the various factors that influence and maintain the prevalence of cheating in America’s public school systems are critical to curbing the massive damage caused by seemingly minor dishonesty on the parts of millions of people in things like tax returns and insurance claims. Furthermore, the idea that situational rewards seem to affect cheating rates is interesting and could be important in curbing academic dishonesty in the future.

For future work, it would be interesting to examine the idea of environment-dependent rewards, which have been suggested by a few studies in the literature, much further. This would involve looking at different settings, which would likely give vastly different results. For instance, a child might be willing to act in a dishonest fashion to obtain a balloon at a party, but be less inclined to cheat on a similar task when alone.

It would be interesting to look at the responses to the priming question to see how certain words correlate with score. For instance, are people who answer “honesty” less likely to cheat? This might require a larger sample size and additional data collection. Further research might also concern the gender gap between dishonesty, and what factors influence how wide it is. We could also examine different types of cheating, such as copying or plagiarism, and how the results differ from the ones presented here. This research also raises the question of how participants would fare on untimed or longer tests, especially in the pair groups. Further investigation into cheating in different types of classes might yield interesting results: for example, might people in English classes cheat more than those in math classes?

Examining different age ranges for this type of behavior might help solidify a link between adolescence and cheating, and perhaps showing the ‘tipping point’ (if it exists) where maturity starts to override impulse in cases of academic dishonesty. A larger sample size could allow for further analysis of how tiredness and alertness affect dishonesty. Studies could also be done to examine if a person cheats more if a situation is perceived to be unfair or a task is seemingly undoable, which could involve putting unreasonable time constraints on a task or giving another (fake) participant an obvious advantage. Groups of more than two could also be examined, as could the effect of doing a group activity first and then taking the test individually. Dishonest behavior in various forms pervades everyday life, and we expect that studying not only the behavior but also the context in which it occurs will lead to a better understanding of how to mitigate it.

Ethics statement

IRB permission was obtained prior to conducting experiments. Participants all signed informed consent forms,and consent on behalf of minors was given by participants’ parents. The IRB reviewed the method of consent used for minor participants in this study. Data was anonymized to preserve confidentiality.

Supporting information

1 Gender reported as a percentage.

Univariate regressions with tobit model of Score on Class Level, Gender, and Block for the control condition (left) and all experimental conditions (right).

Regression with tobit model of Score on self-reported Honesty for the control condition (left) and the experimental condition with the average given (right).

Multivariate regression with tobit model of Score on Demographics, Self-Perception, and Environmental Factors for the control condition (left) and all experimental conditions (right).

Regression with tobit model of score on treatment dummies.

Acknowledgments

We thank Lincoln-Sudbury High School teachers Erica Wilsen, Lori Hodin, Benjamin Coleman, Helen Sotiriou, and Seth Weiss for administering tests to their classes. We thank Leah, Gregory, Kimberly, and Alexander Isakov for helpful discussions.

Funding Statement

The authors received no specific funding for this work.

Data Availability

IMAGES

Why Students Cheat on Homework and How to Prevent It
How to Cheat on Homework: Traditional and Technological Approaches
6 Ways to Prevent Cheating on Homework
How to Cheat on Homework Using 5 Ways { 2nd is my Favorite }
Cheat on Homework
Homework Cheating

COMMENTS

Why Students Cheat on Homework and How to Prevent It
If you find students cheat on homework, they probably lack the vision for how the work is beneficial. It's important to consider the meaningfulness and valuable of the assignment from students' perspectives. They need to see how it is relevant to them. In my class, I've learned to assign work that cannot be copied.
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What do we know about how much students cheat? Pope: We know that cheating rates have been high for a long time.At Challenge Success we've been running surveys and focus groups at schools for over 15 years, asking students about different aspects of their lives — the amount of sleep they get, homework pressure, extracurricular activities, family expectations, things like that — and also ...
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According to a 2012 white paper, Cheat or Be Cheated? prepared by Challenge Success, 80 percent admitted to copying another student's homework. The other studies summarized in the paper found ...
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Earlier this month, 22-year-old Princeton student Edward Tian created an app to detect if something had been written by a machine. Named GPTZero, it was so popular that when he launched it, the ...
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The increased use of technology has contributed to the simplification and ease of copying homework assignments - and cheating in general - across schools and tertiary institutions around the world. Despite the fact that repercussions for cheating are severe, involving possible suspension or expulsion, 62% of U.S. students have reported ...
Reports Of Cheating At Colleges Soar During COVID-19 : NPR
The university has seen reports of cheating jump by more than 79% from fall of 2019 to spring of 2021. "I don't believe that more students started cheating during the pandemic," said Baily. "What ...
Technology Makes it Easier, But What Do We Really Know About Why
A new survey by McAfee, an online security software maker, found that one-third of high school students admit to using cell phones or other devices to cheat in school. Six in ten reported that they have seen or know another colleague who has cheated on an exam or quiz. The results weren't markedly different from a 2009 survey by Common Sense ...
Why Students Cheat—and What to Do About It
But students also rationalize cheating on assignments they see as having value. High-achieving students who feel pressured to attain perfection (and Ivy League acceptances) may turn to cheating as a way to find an edge on the competition or to keep a single bad test score from sabotaging months of hard work. At Stuyvesant, for example, students ...
Cheating rises with online education
August 7, 2020 at 12:57 p.m. EDT. When universities went online in response to the coronavirus pandemic, so did the tests their students took. But one of the people who logged on to take an exam ...
Cheating Fears Over Chatbots Were Overblown, New Research Suggests
Cheating Rates Haven't Changed Much. Cheating has long been rampant in schools. In surveys of more than 70,000 high school students between 2002 and 2015, 64 percent said they had cheated on a ...
How ChatGPT and similar AI will disrupt education
But students can also use it to cheat. ChatGPT marks the beginning of a new wave of AI, a wave that's poised to disrupt education. When Stanford University's student-run newspaper polled ...
Adjusting to an Online Cheating Environment
Chegg is a company that provides digital homework help. Since users can freely post on the website, the answers to some assignments are posted in their entirety, giving students another way to cheat. The physics class received an email stating that if they admitted to using Chegg, they would be offered a second chance to take the exam.
Homework Pros and Cons
One study concluded that homework increases social inequality because it "potentially serves as a mechanism to further advantage those students who already experience some privilege in the school system while further disadvantaging those who may ... "Cheating Is a Personal Foul: Academic Cheating Background," glass-castle.com (accessed ...
How Teens Use Technology to Cheat in School
Cheating in today's world has evolved, and unfortunately, become pervasive. Technology makes cheating all too tempting, common, and easy to pull off. Not only can kids use their phones to covertly communicate with each other, but they can also easily look up answers or get their work done on the Internet. In one study, a whopping 35% of teens ...
ChatGPT did not increase cheating in high schools, Stanford researchers
The university, which conducted an anonymous survey among students at 40 US high schools, found about 60% to 70% of students have engaged in cheating behavior in the last month, a number that is ...
Why Do Students Cheat?
Sometimes they have a reason to cheat like feeling [like] they need to be the smartest kid in class.". Kayla (Massachusetts) agreed, noting, "Some people cheat because they want to seem cooler than their friends or try to impress their friends. Students cheat because they think if they cheat all the time they're going to get smarter.".
Cheating in the classroom increases in the digital age
Cheating in the classroom increases in the digital age. In the end, students who cheat are cheating themselves. A student cheating on a multiple choice test. Jasmyn Sanchez, Staff WriterMarch 18, 2019. You forgot to study for the big test that lays on your desk glaring back at you. You can feel your leg shake, as sweat beads up on your forehead.
The Relationships between Personal Values, Justifications, and Academic
We additionally examine how cheating behaviors have changed as advances in technology and society have made cheating easier. In particular, the increased availability of resources on the Internet, ... Received homework answers from students who have already done the homework: 2.58* 1.11: 2.70: 2.41-.24.76-.22-.27: 5. Given other students exam ...
When Opportunity Knocks: College Students' Cheating Amid the COVID-19
Regarding the latter, it is unclear whether an increase in cheating is due to greater opportunities for cheating (e.g., ... 2012 included cheating on homework) and some have started to examine cheating in online classes (Harbin & Humphrey, 2013). Thus, the nuances of cheating in today's virtual college classroom (especially post-pandemic ...
Academic dishonesty when doing homework: How digital ...
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 , namely cheating and ...
AI cheating is hopelessly, irreparably corrupting US higher education
AI cheating is hopelessly, irreparably corrupting US higher education. by Mark Massaro, Opinion Contributor - 08/23/23 7:30 AM ET. I teach composition and literature courses at a state college in ...
Controversial AI ChatGPT didn't increase cheating in high schools
The university, which conducted an anonymous survey among students at 40 US high schools, found about 60% to 70% of students have engaged in cheating behavior in the last month, a number that is ...
Behavioral correlates of cheating: Environmental specificity and reward
The rapidly rising expectations of high schoolers has brought levels of cheating to dizzying heights; as many as 90 percent of students reported cheating in high school or in college [ 5 ]. This is up from just under 25 percent in the 1940s. Maturity is often thought to be one of the main constraining factors for cheating.