homework makes students cheat

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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Common Reasons Students Cheat

Poor Time Management

The most common reason students cite for committing academic dishonesty is that they ran out of time. The good news is that this is almost always avoidable. Good time management skills are a must for success in college (as well as in life). Visit the Undergraduate Academic Advisement website  for tips on how to manage your time in college.

Stress/Overload

Another common reason students engage in dishonest behavior has to do with overload: too many homework assignments, work issues, relationship problems, COVID-19. Before you resort to behaving in an academically dishonest way, we encourage you to reach out to your professor, your TA, your academic advisor or even  UB’s counseling services .

Wanting to Help Friends

While this sounds like a good reason to do something, it in no way helps a person to be assisted in academic dishonesty. Your friends are responsible for learning what is expected of them and providing evidence of that learning to their instructor. Your unauthorized assistance falls under the “ aiding in academic dishonesty ” violation and makes both you and your friend guilty.

Fear of Failure

Students report that they resort to academic dishonesty when they feel that they won’t be able to successfully perform the task (e.g., write the computer code, compose the paper, do well on the test). Fear of failure prompts students to get unauthorized help, but the repercussions of cheating far outweigh the repercussions of failing. First, when you are caught cheating, you may fail anyway. Second, you tarnish your reputation as a trustworthy student. And third, you are establishing habits that will hurt you in the long run. When your employer or graduate program expects you to have certain knowledge based on your coursework and you don’t have that knowledge, you diminish the value of a UB education for you and your fellow alumni.

"Everyone Does it" Phenomenon

Sometimes it can feel like everyone around us is dishonest or taking shortcuts. We hear about integrity scandals on the news and in our social media feeds. Plus, sometimes we witness students cheating and seeming to get away with it. This feeling that “everyone does it” is often reported by students as a reason that they decided to be academically dishonest. The important thing to remember is that you have one reputation and you need to protect it. Once identified as someone who lacks integrity, you are no longer given the benefit of the doubt in any situation. Additionally, research shows that once you cheat, it’s easier to do it the next time and the next, paving the path for you to become genuinely dishonest in your academic pursuits.

Temptation Due to Unmonitored Environments or Weak Assignment Design

When students take assessments without anyone monitoring them, they may be tempted to access unauthorized resources because they feel like no one will know. Especially during the COVID-19 pandemic, students have been tempted to peek at online answer sites, Google a test question, or even converse with friends during a test. Because our environments may have changed does not mean that our expectations have. If you wouldn’t cheat in a classroom, don’t be tempted to cheat at home. Your personal integrity is also at stake.

Different Understanding of Academic Integrity Policies

Standards and norms for academically acceptable behavior can vary. No matter where you’re from, whether the West Coast or the far East, the standards for academic integrity at UB must be followed to further the goals of a premier research institution. Become familiar with our policies that govern academically honest behavior.

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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Insights into How & Why Students Cheat at High Performing Schools

“ A LOT of people cheat and I feel like it would ruin my character and personal standards if I also took part in cheating, but everyone tells me there’s no way I can finish the school year with straight As without cheating. It really makes me upset but I’m honestly contemplating it because colleges can’t see who does and doesn’t cheat. ” – High school student

“Academic dishonesty is any deceitful or unfair act intended to produce a more desirable outcome on an exam, paper, homework assignment, or other assessment of learning.” (Miller, Murdock & Grotwiel, 2017).

Cheating has been a hot topic in the news lately with the unfolding of the college admissions scandal involving affluent parents allegedly using bribery and forgery to help their kids get into selective colleges. Unfortunately, we also see that cheating is common among students in middle schools through graduate schools (Miller, Murdock & Grotwiel, 2017), including the high-performing middle and high schools that Challenge Success has surveyed. To better understand who is cheating in these high schools, how they are cheating, and what is driving this behavior, we looked at recent data from the Challenge Success Student Survey completed in Fall 2018—including 16,054 students from 15 high-performing U.S. high schools (73% public, 27% private). We asked students to self-report their engagement in 12 cheating behaviors during the past month. On each of the items, adapted from a scale developed by McCabe (1999), students could select one of four options: never; once; two to three times; four or more times. We found that 79% of students cheated in some way in the past month.

How Students Cheat & Who Does It

There are two types of cheating that the students we surveyed engage in: (1) cheating collectively and (2) cheating independently. Overall rates of cheating collectively were higher than rates of cheating individually. Examples of cheating collectively include, working on an assignment with others when the instructor asked for individual work, helping someone else cheat on an assessment, and copying from another student during an assessment with that person’s knowledge. Examples of independent cheating include using unpermitted cheat sheets during an assessment, copying from another student during an assessment without their knowledge, or copying material word for word without citing it and turning it in as your own work.

When we looked more closely at who is cheating according to our survey data, we found that 9 th graders were less likely than 10 th , 11 th , and 12 th graders to cheat individually and collectively. This is consistent with other research in the field that shows that cheating tends to increase with grade level (Murdock, Stephens, & Grotewiel, 2016). We also found that male students were more likely to cheat individually than female students. Broader research from the field about cheating by gender has yielded mixed results. Some find that rates for boys are higher than for girls, while others find no difference (McCabe, Treviño & Butterfield, 2001; Murdock, Hale & Weber, 2001; Anderman & Midgley, 2004).

Why Students Cheat

“I think what causes us stress during the school year is the amount of cheating going on around school…Some of my friends and classmates who have siblings or friends that took the classes before in a way have a copy of what the tests will look like. It makes them have a competitive advantage over other people who have no siblings or known friends that took the class before. To have people who have access to these past tests, it creates more stress on students because we have to study more and push ourselves harder.” – High School Student

Why are students cheating at such high rates? Previous research on cheating suggests students may be inclined to cheat and rationalize their behaviors because of various factors including:

• Performance over Mastery: Students may cheat because of the risk of low grades due to worry, pressure on academic performance, or a fixed mindset ( Miller, Murdock & Grotewiel, 2017). School environments perceived by students to be focused on performance goals like grades and test scores over mastery have been associated with behaviors such as cheating (Anderman & Midgley, 2004).
• Peer Relationships/Social Comparison: The increase of social comparisons and competition that many children and adolescents experience in high performing schools or classrooms or the desire to help a friend ( Miller, Murdock & Grotewiel, 2017) may be another factor of choosing to cheat. Students in high-achieving cultures, furthermore, tend to cheat more when they see or perceive their peers cheating (Galloway, 2012).
• Overloaded : Another factor in students cheating is the pressure in high-performing schools to “do it all” which can be influenced by heavy workloads and/or multiple tests on the same day ( Miller, Murdock & Grotewiel, 2017)
• “Cheat or be cheated” rationale: Students may rationalize cheating by blaming the teachers or situation. This often occurs when students see the teacher as uncaring or focused on performance over mastery ( Miller, Murdock & Grotewiel, 2017). Students may rationalize and normalize cheating as the way to succeed in a challenging environment where achievement is paramount (Galloway, 2012).
• Pressure: Students may also cheat because they feel pressure to maintain their status in a success focused community where they see the situation as “cheat or be cheated” ( Miller, Murdock & Grotewiel, 2017).

We see many of these factors reflected in our survey data. Students listed their major sources of stress as grades, tests, finals, or assessments (80% of students) and overall workload and homework (71% of students). We also found that 59% of students feel they have “too much homework,” 75% of students feel “often” or “always” stressed by their schoolwork , 31% of students feel that “many” or “all” of their classes assign homework that helps them learn the material, and 74% worry “quite a bit” or “a lot” about taking assessments while 70% worry the same amount about school assignments.

Reflecting high pressure from within their community, only 51% of students feel they can meet their parents expectations “often” or “always,” 52% of students worry at least a little that if they do not do well in school their friends will not accept them, and 80% of students feel “quite a bit” or “a lot” of pressure to do well in school. Meanwhile, only 33% of students feel “quite” or “very” confident in their ability to cope with stress . Open-ended responses reported by students on our survey reinforce the quantitative data:    

“It is hard to do well in classes and become well rounded for applying to college without something giving way… in some cases students cheat. ”

“ I don’t think anyone is having a great time here, when all they’re focusing on is cheating and getting the grade that they want in order to ‘succeed’ in life after high school by going to a great college or university.”

“ Teachers often give very challenging tests that require very large curves to present even reasonable grades and this creates a very stressful atmosphere. Students are often caught cheating because that is often times the only route to getting a decent grade. ”

Quotes like these suggest that there may be a relationship between heavy amounts of homework on top of busy extracurriculars and students feeling that cheating is the only way to get everything done.

What Can Schools Do About It  

Schools may find the prevalence of the cheating culture overwhelming—potentially daunted by counteracting the normalization and prevalence of achievement at-all-costs and cheating behaviors. Students themselves, in our survey and in previous research, call for a learning environment where cheating is not an expectation or everyday behavior for getting ahead, and students are held responsible for their behavior (McCabe, 2001).

“ The administration needs to punish students who cheat. The school does not crack down on these kids, and it makes it harder for others to succeed. ”

“ Since I was in 9th grade it feels like our counselors only really care about our class rank and GPA. I am a hard worker but I don’t have the best GPA. Our school focuses too much on grades. This creates pressure on students to cheat just to get a good grade to boost their GPA. Learning has been compromised by a desire for a number that we have been told defines us as people. ”

Schools can work with students to change the prevailing culture of cheating through listening to students about their experiences and perceptions, acknowledging the issue and predominant culture, and collaborating with students to clarify and redefine how and why students learn. Some areas we (and other researchers) recommend that schools can address underlying causes of cheating include:

• Strive for school-wide buy-in for honest academic practices including defining what constitutes cheating and academic dishonesty for students and providing clear consequences for cheating (Galloway, 2012). Further providing open dialogue and discussions with students, parents, and teachers may help students feel that teachers are treating then with respect and fairness (Murdock et al., 2004).
• Educate students on what cheating means in their school community so that cheating is viewed as unacceptable ( Miller, Murdock & Grotewiel, 2017)
• Establish a climate of care and a classroom where it is evident that the teacher cares about student progress, learning, and understanding.
• Emphasize mastery and learning over performance . One strategy is through using formative assessments such as practice exams that can be reviewed in class and homework that can be corrected until students achieve mastery on the concepts ( Miller, Murdock & Grotewiel, 2017).
• Revise assessments and grading policies to allow for redemption and revision.
• Ensure that students are met with “reasonable demands” such as spacing assignments and assessments across days and reduce workload without reducing rigor ( Miller, Murdock & Grotewiel, 2017)
• Teach students time management strategies (e.g. using a planner, breaking tasks into manageable pieces, and how to use resources or ask for help). Schools may even teach parents how to help students organize and manage their work rather than providing them with answers. ( Miller, Murdock & Grotewiel, 2017)

Overall, schools should aim to change student attitudes around integrity through “clear, fair, and consistent” assessments, valuing learning over mastery, reducing comparisons and competition between students, teaching students management and organization skills, and demonstrating care and empathy for students and the pressures that face ( Miller, Murdock & Grotewiel, 2017) .

Anderman, E.M. & Midgley, C. (2004). Changes in self-reported academic cheating across the transition from middle school to high school. Contemporary Educational Psychology , 29(4), 499-517.

Galloway, M. K. (2012). Cheating in advantaged high schools: Prevalence, justifications, and possibilities for change. Ethics & Behavior, 22(5), 378-399.

McCabe, D. (1999). Academic dishonesty among high school students. Adolescence, 34 (136), 681- 687.

McCabe, D. (2001) Cheating: Why students do it and how we can help them stop. American Educator , Winter, 38-43.

McCabe, D. L., Treviño, L. K., & Butterfield, K. D. (2001). Cheating in academic institutions: A decade of research. Ethics & Behavior , 11, 219-232.

Miller, A. D., Murdock, T. B., & Grotewiel, M. M. (2017). Addressing Academic Dishonesty Among the Highest Achievers. Theory Into Practice , 56 (2), 121-128.

Murdock, T., Hale, N., & Weber, M. (2001). Predictors of cheating among early adolescents: Academic and social motivations. Contemporary Educational Psychology , 26, 96-115.

Murdock, T. B., Miller, A., & Kohlhardt, J. (2004). Effects of Classroom Context Variables on High School Students’ Judgments of the Acceptability and Likelihood of Cheating. Journal of Educational Psychology , 96 (4), 765-777.

Murdock, T., Stephens, J., & Grotewiel, M. (2016). Student dishonesty in the face of assessment. In G. Brown and L. Harris (Eds.), Handbook of Human and Social Conditions in Assessment (pp. 186-203). London, England: Routledge.

Wangaard, D. B. & J. M. Stephens (2011). Academic integrity: A critical challenge for schools. Excellence & Ethics , Winter 2011.

Interested in learning more about your students’ perceptions of their school experiences? Learn more about the Challenge Success Student Survey here .

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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?

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.

STRATEGIES FOR ADDRESSING CHALLENGING BEHAVIORS IN SECONDARY

You are so right about communicating the purpose of the assignment and giving students time in class to do homework. I also use an article of the week on plagiarism. I give students points for the learning – not the doing. It makes all the difference. I tell my students why they need to learn how to do “—” for high school or college or even in life experiences. Since, they get an A or F for the effort, my students are more motivated to give it a try. No effort and they sit in my class to work with me on the assignment. Showing me the effort to learn it — asking me questions about the assignment, getting help from a peer or me, helping a peer are all ways to get full credit for the homework- even if it’s not complete. I also choose one thing from each assignment for the test which is a motivator for learning the material – not just “doing it.” Also, no one is permitted to earn a D or F on a test. Any student earning an F or D on a test is then required to do a project over the weekend or at lunch or after school with me. All of this reinforces the idea – learning is what is the goal. Giving students options to show their learning is also important. Cheating is greatly reduced when the goal is to learn and not simply earn the grade.

Thanks for sharing your unique approaches, Sandra! Learning is definitely the goal, and getting students to own their learning is key.

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

Students cheat on assignments and exams..

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

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

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

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

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

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

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

Students might perceive the possibility to cheat without getting caught.

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

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

This site supplements our 1-on-1 teaching consultations. CONTACT US to talk with an Eberly colleague in person!

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What is the real reason students turn to cheating?

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Issues of student cheating have been increasing over the years as more and more ‘help with homework’ sites have been accessible to students across the UK. A 2018 study by Swansea University found that as many as one in seven graduates had used contract cheating services to complete assignments . The switch to remote learning brought about by the COVID-19 pandemic only exacerbated these issues, and in 2020 the number of students outsourcing their coursework rose rapidly with usage figures for one of the most popular ‘help with homework’ websites increasing by 196%. In early 2021 there were contract cheating websites operating in the UK. 

In October 2021 The Department for Education announced that it would introduce an amendment to the Skills and Post-16 Education Bill, that would make it a criminal offence to provide, arrange or advertise contract cheating services or ‘essay mills’. Australia, New Zealand, Ireland and some US states have taken similar steps. However, a recent study from the journal Assessment and Evaluation in Higher Education revealed that students will still engage with third party homework services even when they believe they are breaking the law. These findings bring into question how effective legislation will be against contract cheating, and what can be done to prevent students seeking out alternative opportunities to outsource their work.

Why do students turn to contract cheating services? Students’ skills in academic writing, such as reports, essays and other written formal documents are becoming an increasing source of anxiety for them. In a Pearson HE learner survey from June 2020, 77% said they had struggled with their first assignments , partly owing to a lack of confidence in their academic skills as they step up to a university standard of working.  

Therefore, instead of viewing students who outsource their coursework as cheats who are undermining the value of academic performance, should we instead question why they are lacking confidence and turn to cheating in the first place – and what role do institutions play in this? 

Download Pearson’s latest report to take an in-depth look at the issue of academic writing, understand why students turn to ‘contract cheating’, and see how universities can take action to nurture their writing abilities with legitimate support and feedback, so they learn, gain confidence, and improve their own work.

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What do ai chatbots really mean for students and cheating.

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

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

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

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1 Introduction

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

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

1.1 Prevalence and factors of digital academic dishonesty in schools

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

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

1.2 Effects of homework engagement and digital dishonesty on school performance

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

1.3 Present study and hypotheses

The present study serves three combined purposes.

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

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

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

2.1 Participants

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

2.2 Measures

2.2.1 digital dishonesty in homework scale.

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

2.2.2 Homework engagement scale

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

2.2.3 Demographics

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

2.2.4 Study program

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

2.2.5 Technologies and schools

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

2.2.6 Test scores

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

2.3 Data analyses

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

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

3.1 Additional scales for Switzerland

3.1.1 digital dishonesty in homework practices.

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

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

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

3.1.2 Homework effort

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

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

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

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

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

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

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

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

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

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

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

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

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

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

4 Discussion

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

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

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

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

4.1 Conclusions and recommendations

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

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

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

4.2 Limitations and directions

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

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

Data availability

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

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List of abbreviations related to PISA datasets

students’ perceived autonomy related to ICT use

students’ perceived ICT competence

frequency of computer use at home for entertainment purposes

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

parents’ highest occupational status

home possessions

frequency of computer use for school-related purposes at home

digital cheating for homework items for Switzerland

homework engagement items for Switzerland

positive attitude towards ICT as a learning tool

student’s ICT interest

parents’ highest level of education

students’ ICT as a topic in social interaction

frequency of computer use at school

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

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Motivation is a key factor in whether students cheat

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Carlton J. Fong, Assistant Professor of Education at Texas State University & Megan Krou, Research Analyst, Teachers College, Columbia University | March 4, 2021

Ever since the COVID-19 pandemic caused many U.S. colleges to shift to remote learning in the spring of 2020, student cheating has been a concern for instructors and students alike.

To detect student cheating, considerable resources have been devoted to using technology to monitor students online . This online surveillance has increased students’ anxiety and distress . For instance, some students have indicated the monitoring technology required them to stay at their desks or risk being labeled as cheaters.

Although relying on electronic eyes may partially curb cheating, there’s another factor in the reasons students cheat that often gets overlooked – student motivation.

As a team of researchers in educational psychology and higher education , we became interested in how students’ motivation to learn, or what drives them to want to succeed in class, affects how much they cheated in their schoolwork.

To shine light on why students cheat, we conducted an analysis of 79 research studies and published our findings in the journal Educational Psychology Review. We determined that a variety of motivational factors, ranging from a desire for good grades to a student’s academic confidence, come into play when explaining why students cheat. With these factors in mind, we see a number of things that both students and instructors can do to harness the power of motivation as a way to combat cheating, whether in virtual or in-person classrooms. Here are five takeaways:

1. Avoid emphasizing grades

Although obtaining straight A’s is quite appealing, the more students are focused solely on earning high grades, the more likely they are to cheat. When the grade itself becomes the goal, cheating can serve as a way to achieve this goal.

Students’ desire to learn can diminish when instructors overly emphasize high test scores, beating the curve, and student rankings. Graded assessments have a role to play, but so does acquisition of skills and actually learning the content, not only doing what it takes to get good grades.

2. Focus on expertise and mastery

Striving to increase one’s knowledge and improve skills in a course was associated with less cheating. This suggests that the more students are motivated to gain expertise, the less likely they are to cheat. Instructors can teach with a focus on mastery, such as providing additional opportunities for students to redo assignments or exams. This reinforces the goal of personal growth and improvement.

3. Combat boredom with relevance

Compared with students motivated by either gaining rewards or expertise, there might be a group of students who are simply not motivated at all, or experiencing what researchers call amotivation. Nothing in their environment or within themselves motivates them to learn. For these students, cheating is quite common and seen as a viable pathway to complete coursework successfully rather than putting forth their own effort. However, when students find relevance in what they’re learning, they are less likely to cheat.

When students see connections between their coursework and other courses, fields of study or their future careers, it can stimulate them to see how valuable the subject might be. Instructors can be intentional in providing rationales for why learning a particular topic might be useful and connecting students’ interest to the course content.

4. Encourage ownership of learning

When students struggle, they sometimes blame circumstances beyond their control, such as believing their instructor to have unrealistic standards. Our findings show that when students believe they are responsible for their own learning, they are less likely to cheat.

Encouraging students to take ownership over their learning and put in the required effort can decrease academic dishonesty. Also, providing meaningful choices can help students feel they are in charge of their own learning journey, rather than being told what to do.

5. Build confidence

Our study found that when students believed they could succeed in their coursework, cheating decreased. When students do not believe they will be successful, a teaching approach called scaffolding is key. Essentially, the scaffolding approach involves assigning tasks that match the students’ ability level and gradually increase in difficulty. This progression slowly builds students’ confidence to take on new challenges. And when students feel confident to learn, they are willing to put in more effort in school.

An inexpensive solution

With these tips in mind, we expect cheating might pose less of a threat during the pandemic and beyond. Focusing on student motivation is a much less controversial and inexpensive solution to curtail any tendencies students may have to cheat their way through school.

Are these motivational strategies the cure-all to cheating? Not necessarily. But they are worth considering – along with other strategies – to fight against academic dishonesty.

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A.I. Is Making It Easier Than Ever for Students to Cheat

Look out, educators. You’re about to confront a pernicious new challenge that is spreading, kudzu-like , into your student writing assignments: papers augmented with artificial intelligence.

The first online article generator debuted in 2005. Now, A.I.-generated text can now be found in novels , fake news articles and real news articles , marketing campaigns, and dozens of other written products. The tech is either free or cheap to use, which places it in the hands of anyone. And it’s probably already burrowing into America’s classrooms right now.

Using an A.I. program is not “plagiarism” in the traditional sense—there’s no previous work for the student to copy, and thus no original for teachers’ plagiarism detectors to catch. Instead, a student first feeds text from either a single or multiple sources into the program to begin the process. The program then generates content by using a set of parameters on a topic, which then can be personalized to the writer’s specifications. With a little bit of practice, a student can use AI to write his or her paper in a fraction of the time that it would normally take to write an essay.

I wanted to see what would happen if I fed an A.I. text generator like Sudowrite some sample texts for assignments. (Sudowrite is just one such program; I could name more, but I’d rather not make it even easier for students to cheat.) The results showed that teachers must be made aware of what is coming to their classrooms.

Say a student wanted to write an essay about U.S.-China policy and decided to use an A.I. program to speed along the process. I fed it the first few lines from a recent Pentagon report : “The PRC is increasingly clear in its ambitions and intentions. Beijing seeks to reshape the international order to better align with its authoritarian system and national interests, as a vital component of its strategy to achieve the ‘great rejuvenation of the Chinese nation.’ ” The A.I. text generator provided these following sentences:

It is increasingly willing to disregard—or to actively undermine—existing international rules and norms when it feels its vital interests are at stake. The U.S. and its allies face a rapidly modernizing military, whose capabilities are growing rapidly, especially in the air and at sea. China has also made great strides in its development of cyber capabilities, and it is focused on the ability to degrade or disrupt critical U.S. military technology, as well as on targeting civilian infrastructure. In addition to being a challenge to the U.S. military and its allies, China’s activities in cyberspace have the potential to degrade U.S. political and economic institutions, and the global information infrastructure is at risk. 

If a high school student turned that in verbatim, their teacher would probably suspect that there was something amiss. But if this were turned in at the undergraduate or graduate level, and especially if the student were to edit the text, it would be much harder to detect.

Or let’s say they need to write a paper about climate change. Here’s what came up when I fed Sudowrite the first few lines from an article on climate change impacts from the National Oceanic and Atmospheric Administration website:

Though we often think about human-induced climate change as something that will happen in the future, it is an ongoing process. Ecosystems and communities in the United States and around the world are being impacted today. 

It’s not particularly insightful, but it provides the A.I. program some basic building blocks. The artificial intelligence continued along this slightly edited line of reasoning:

The consensus view emerging from the Intergovernmental Panel on Climate Change (IPCC) and other respected assessments is that the planet is warming because of the accumulation of heat-trapping gases in the atmosphere caused by human activity. The level of scientific consensus that human activities are primarily responsible for climate change is like the consensus finding on smoking causing lung cancer.

The program had likely already been trained to know the term “climate change” was connected to the IPCC; by making certain inferences it could generate text which seemed like a reasonable extension of the idea.

What about ninth-grade English? Channeling my 14-year-old self, I wrote these lines:

“Romeo and Juliet” is a play that explores many different topics such as romance, betrayal, and tragedy. It has interesting characters that make it such a good story, even 400 years later. 

The computer spat back this take (which I’ve edited slightly):

Romeo, the main character, is a very passionate and immature young man who is torn between his love for Rosaline and his love for Juliet. He is also very rash and desperate to get Juliet and will do almost anything to win her. His desperation for Juliet is an interesting trait and is one that the younger kids can relate to, as well as older adults with first crushes. Romeo is an interesting character and is very different from how kids would imagine him to be. But he is also a great inspiration, showing that love is worth fighting for.

Again, the A.I. program had been previously trained to know that Romeo and Juliet contained certain characters, themes, and plot elements. But what stood out to me was that the text was crafted at an appropriate writing level for a high schooler, who would be reading about these star-crossed lovers for the first time. The awkward phrasing and the syntax errors baked into the program make it seem convincing.

I’ve struggled to find the right analogy to describe this phenomenon. Is using A.I. to write graded papers like athletes taking performance-enhancing drugs? As a society and as a sporting culture, we’ve decided certain drugs are forbidden, as they provide the user unfair advantages. Further, the cocktail of drugs flowing through these competitors and malicious sports programs could cause real physical and psychological harm to the athletes themselves. Would individuals using AI in writing be likewise considered in the same boat—a cheat to the system providing undue advantages, which also creates harm in the long run by impeding writing skills?

Or might using A.I. be more like using performance-enhancing gear in sports, which is both acceptable and encouraged? To use another sports analogy, even beginner tennis players today use high-performance carbon composite rackets instead of 1960s-era wooden racket technology. Swimmers wear nylon and elastane suits and caps to reduce drag. Bikers have stronger, lighter bicycles than their counterparts used a generation ago. Baseball bats evolved from wood to aluminum and developed better grips; baseball mitts have become more specialized over the decades.

Numerous educators assert that A.I. is more like the former. They consider using these programs violate academic integrity. Georgetown University professor Lise Howard told me, “I do think it’s unethical and an academic violation to use AI to write paragraphs, because academic work is all about original writing.” Written assignments have two purposes, argues Ani Ross Grubb, part-time faculty member in the Carroll School of Management at Boston College: “First is to test the learning, understanding, and critical thinking skills of students. Second is to provide scaffolding to develop those skills. Having AI write your assignments would go against those goals.”

Certainly, one can argue that this topic has already been covered in university academic integrity codes. Using A.I. might open students to serious charges. For instance, American University indicates, “All papers and materials submitted for a course must be the student’s original work unless the sources are cited” while the University of Maryland similarly notes that it is prohibited to use dishonesty to “gain an unfair advantage, and/or using or attempting to use unauthorized materials, information, or study aids in any academic course or exercise.”

But some study aids are generally considered acceptable. When writing papers, it is perfectly fine to use grammar- and syntax-checking products standard on Microsoft Word and other document creating programs. Other A.I. programs like Grammarly help write better sentences and fix errors. Google Docs finishes sentences in drafts and emails.

So the border between using those kinds of assistive computer programs and full-on cheating remains fuzzy. Indeed, as Jade Wexler, associate professor of special education at the University of Maryland, noted, A.I. could be a valuable tool to help level the playing field for some students. “It goes back to teachers’ objectives and students’ needs,” she said. “There’s a fine balance making sure both of those are met.”

Thus there are two intertwined questions at work. First: Should institutions permit A.I.-enhanced writing? If the answer is no, then the second question is: How can professors detect it? After all, it’s unclear whether there’s a technical solution to keeping A.I. from worming into student papers. An educator’s up-to-date knowledge on relevant sources will be of limited utility since the verbiage has not been swiped from pre-existing texts.

Still, there may be ways to minimize these artificial enhancements. One is to codify at the institutional level what is acceptable and what is not; in July the Council of Europe took a few small steps, publishing new guidelines which begin to grapple with these new technologies creating fraud in education. Another would be to keep classes small and give individual attention to students. As Jessica Chiccehitto Hindman, associate professor of English at Northern Kentucky University, noted, “When a writing instructor is in a classroom situation where they are unable to provide individualized attention, the chance for students to phone it in—whether this is plagiarism, A.I., or just writing in a boring, uninvested way—goes up.” More in-class writing assignments—no screens allowed—could also help. Virginia Lee Strain, associate professor of English and director of the honors program at Loyola University Chicago, further argued, “AI is not a problem in the classroom when a student sits down with paper and pencil.”

But in many settings, more one-on-one time simply isn’t a realistic solution, especially at high schools or colleges with large classes. Educators juggle multiple classes and courses, and for them to get to know every student every semester isn’t going to happen.

A more aggressive stance would be for high schools and universities to explicitly declare using A.I. will be considered an academic violation—or at least update their honor codes to reflect what they believe is the right side of the line concerning academic integrity. That said, absent a mechanism to police students, it might paradoxically introduce students to a new way to generate papers faster.

Educators realize some large percentage of students will cheat or try to game the system to their advantage. But perhaps, as Hindman says, “if a professor is concerned that students are using plagiarism or AI to complete assignments, the assignments themselves are the problem, not the students or the AI.” If an educator is convinced that students are using these forbidden tools, he or she might consider using alternate means to generate grades such as assigning oral exams, group projects, and class presentations. Of course, as Hindman notes, “these types of high-impact learning practices are only feasible if you have a manageable number of students.”

AI is here to stay whether we like it or not. Provide unscrupulous students the ability to use these shortcuts without much capacity for the educator to detect them, combined with other crutches like outright plagiarism, and companies that sell papers, homework, and test answers, and it’s a recipe for—well, not disaster, but the further degradation of a type of assignment that has been around for centuries.

Future Tense is a partnership of Slate , New America , and Arizona State University that examines emerging technologies, public policy, and society.

Teens Will Use AI for Schoolwork, But Most Think It’s Cheating, Survey Says

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More than 4 in 10 teens are likely to use artificial intelligence to do their schoolwork instead of doing it themselves this coming school year, according to a new survey.

But 60 percent of teens consider using AI for schoolwork as cheating, according to the nationally representative survey of 1,006 13- to 17-year-olds conducted by research firm Big Village in July for the nonprofit Junior Achievement .

The survey findings come as the emergence of ChatGPT —an AI-powered chatbot that can respond instantly to seemingly any prompt—has put discussions about how teachers and students should use it front and center in schools across the country.

Nearly half of educators who responded to an EdWeek Research Center survey conducted this spring said AI would have a negative or very negative impact on teaching and learning in the next five years. Twenty-seven percent said AI’s impact would be positive or very positive.

And in ChatGPT’s early days, some districts—including New York City schools —took a hardline approach and banned the technology in classrooms, because of concerns about cheating and data privacy. (The New York City district has since removed the ban on ChatGPT and is now encouraging students and teachers to learn how to use it effectively.)

When asked why they would use AI to do their schoolwork for them, the top response in the Junior Achievement survey was that AI is just another tool (62 percent). Others said they didn’t like school or schoolwork (24 percent), that they wouldn’t need to know the information because of AI (22 percent), that everybody else is doing it (22 percent), that they would do poorly otherwise (17 percent), and that it’s not important to know the subjects for which they use AI (8 percent).

The survey had a margin of error of plus or minus 3.1 percent.

“The misuse of AI to do all schoolwork not only raises ethical concerns, but this behavior could also shortchange many students’ educations since they may not be learning the subjects they are using AI for,” Jack E. Kosakowski, the president and CEO of Junior Achievement USA, said in a written statement. “Given the growing demand for marketable skills, this could become very problematic.”

Experts say educators should teach students how to use it as a tool and an assistant in their learning, instead of using it as a replacement for learning.

But given that 44 percent of teens say they’re likely to use AI to do their schoolwork for them, and 48 percent said they know friends and classmates who have used AI this way, schools have a lot of work cut out for them.

So how can educators incorporate AI use into their lessons, guard against cheating, and teach students to use it as a helper? Here are some examples that experts have shared with Education Week :

• Create assignments that are impossible to complete with these tools, such as assignments about very recent news events or about the local community.
• Allow students to complete assignments in class.
• Ask students to give an oral presentation.
• Create project-based learning assignments.
• Allow the use of ChatGPT and other AI tools but require students to acknowledge and document how they used them. For example, students could use ChatGPT to get feedback on their essay drafts and explain which of the tool’s suggestions they agreed with and which ones they didn’t. This approach allows students to learn how to use the tool as a partner, instead of having it do all the work for them.

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Why do students cheat? Listen to this dean’s words

Associate Dean, Director Student Conduct and Conflict Resolution, University of Florida

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Editor’s note: Since the publication of this article, the University of Florida terminated Chris Loschiavo’s employment when it learned he used his UF work computer account to purchase pornography.

Cheating in college has been with us since the inception of higher education. In recent months, cases of cheating, including large-scale cheating at elite colleges , have led to considerable turmoil.

Many of these behaviors could well start to take shape right at the level of high school. A survey conducted by renowned academic integrity researcher Don McCabe shows how widespread the problem is in high schools.

Large-scale cheating

In a survey of 24,000 students at 70 high schools, McCabe found “64% of students admitted to cheating on a test, 58% admitted to plagiarism and 95% said they participated in some form of cheating, whether it was on a test, plagiarism or copying homework.”

Statistics for cheating for college students are much the same. Surveys indicate as high as 70% of students report some kind of cheating in college. These survey results, which have remained consistent over time, represent a variety of behaviors.

So, what could possibly lead to such behaviors?

As Director of Student Conduct, I have been responsible for addressing these behaviors for the last 16 years. I have also served as president of the Association for Student Conduct Administration (ASCA) , an organization of over 3,300 professionals doing student conduct work at over 1,800 institutions across the US and Canada. All these positions have given me unique insights into the issue of cheating beyond my institution. And I can say these results are not at all surprising to me.

Students cheat for a variety of reasons:

It can be an intentional, calculated decision in order to get ahead. Often, it is motivated by the path to success that they see around them – people cheating without incurring any real consequences.

From politicians cheating, to corporate scandals such as Enron , to the steroid scandal in Major League Baseball , to the NFL’s “deflategate,” our students are surrounded by examples of dishonest acts.

What’s worse, society seemingly rewards these individuals for their dishonest behaviors. Students then come to believe that dishonest behavior is rewarded and often do not hesitate to engage in it.

My experience shows students engage in a cost/benefit analysis that goes like this: “If I cheat and don’t get caught, the reward is an ‘A’ in the class, admission to a graduate/professional school of my choice or a great job. If I get caught, it isn’t as bad as what Enron did, so the consequence won’t be so bad.”

The example we set as a society is what I have found to be the most significant reason for students cheating.

This also gets combined with a pressure to succeed. These students have grown up in a culture where even the team that scores the least gets a trophy. So they are not prepared for failure.

When they believe they are going to fail (which nowadays is often anything less than an “A”), students will do whatever it takes to avoid it, because they don’t want to let others (often family) down.

High schools are not teaching research

Another reason for student cheating is being unprepared for college level work. Over my many years addressing the issue of plagiarism, I have seen student after student who has written a research paper and not given proper attribution. This is not because they were taking credit for someone else’s words, but simply because they were never taught how to write a research paper.

I have had many conversations over the years with students who truly don’t understand how to write a research paper. So much of high school these days is teaching to the large number of standardized tests. As a result, learning how to research is being lost.

Also, students aren’t being taught how to paraphrase. So, they just cut and paste from the articles they read on the internet – it is easy, quick and takes very little effort to do this.

Some others don’t have any confidence in their own thoughts. So when given the chance to write a paper in which they must share their own ideas, they simply go to the internet and cut and paste someone else’s words or ideas, thinking they are worth more than their own.

I once had a student who cut and pasted large parts of her paper from the internet. When she was asked why she did it, she stated that the author had said what she wanted to say much more eloquently. She said she was afraid of changing it using her own words, as it could be an incorrect interpretation.

This student lacked confidence in her ability to interpret what she read and then translate it in her own words. Another student once shared that he didn’t know as much as the author he took his information from. He concluded, “Why would the professor want to hear the student’s own thoughts?”

This has been a potential downfall of teaching to the test, as many of our secondary educators are being forced to do – students aren’t able to think and problem-solve for themselves.

And when they are forced to do so, they simply take someone else’s ideas.

Cheating could be a cry for help

Some others cheat because they have poor time management skills. College work is challenging, and some students underestimate how long it will take them. When they run out of time, they panic and take a shortcut.

Sometimes these students also have inappropriately prioritized social or extracurricular events over their academic work.

Finally, some students cheat because it is a cry for help. I will never forget a student I met with many years ago for a cheating case.

He admitted responsibility and accepted the consequence of a failing grade in his class. I felt convinced that he truly learned from this incident. However, within the week, he was accused of engaging in the very same behavior in the same class again.

This was very early in my career, and I was ready to remove him from our institution. However, as I found out more, I learned that his girlfriend had just broken up with him, his grandmother (to whom he was very close) had recently passed away and his mother had been recently diagnosed with terminal cancer (I did actually have proof of every one of these events).

The combination made it impossible for this student to focus on his academics. While these incidents certainly didn’t excuse his behavior, they helped explain why he made such bad choices.

He was afraid to ask for help. It was only when there appeared to be no other option, did he open up about what he was dealing with. I was able to hold him accountable appropriately while also making sure he had access to the resources that would help him address his current emotional state.

He went on to graduate from the institution once he was able to get his life back together. Had his faculty not bothered to address the behavior, he would have likely dropped out.

I have never forgotten the lesson this student taught me.

What can administrators, faculty do to help?

I learned to ask more questions. Now, I try to dig a little deeper when trying to find out why a student made a certain choice. Additionally, it has shaped how I present to faculty on the importance of reporting cheating.

So often I hear from faculty either that they don’t want to be the reason a student gets into trouble, or that they shouldn’t have to deal with these issues.

When I tell the story of this student, it reframes for faculty the importance of reporting. It really isn’t about getting the student in trouble; rather, it is about making sure someone with training can interact with the student to help and set the student up for success when dealing with life’s challenges.

When faculty see it as potentially helping the student, they become much more willing to report.

Cheating is a challenge for our society, both at the high school and college levels. We need to remember, however, that it is rarely a thought-out, premeditated act. More often, it is an impulsive act.

To have a real impact, we need to address the underlying issues.

Tomorrow: Students cheat for good grades. Why not make the classroom about learning and not testing?

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Pippa Biddle

AI Is Making It Extremely Easy for Students to Cheat

Denise Garcia knows that her students sometimes cheat, but the situation she unearthed in February seemed different. A math teacher in West Hartford, Connecticut, Garcia had accidentally included an advanced equation in a problem set for her AP Calculus class. Yet somehow a handful of students in the 15-person class solved it correctly. Those students had also shown their work, defeating the traditional litmus test for sussing out cheating in STEM classrooms.

Garcia was perplexed, until she remembered a conversation from a few years earlier. Some former students had told her about an online tool called Wolfram|Alpha that could complete complicated calculations in seconds. It provided both the answers and the steps for reaching them, making it virtually undetectable when copied as homework.

For years, students have turned to CliffsNotes for speedy reads of books, SparkNotes to whip up talking points for class discussions, and Wikipedia to pad their papers with historical tidbits. But today’s students have smarter tools at their disposal—namely, Wolfram|Alpha, a program that uses artificial intelligence to perfectly and untraceably solve equations. Wolfram|Alpha uses natural language processing technology, part of the AI family, to provide students with an academic shortcut that is faster than a tutor, more reliable than copying off of friends, and much easier than figuring out a solution yourself.

Since its release, Wolfram|Alpha has trickled through the education system, finding its way into the homework of college and high school students. Use of Wolfram|Alpha is difficult to trace, and in the hands of ambitious students, its perfect solutions are having unexpected consequences. It works by breaking down the pieces of a question, whether a mathematical problem or something like "What is the center of the United States?", and then cross-referencing those pieces against an enormous library of datasets that is constantly being expanded. These datasets include information on geodesic schemes, chemical compounds, human genes, historical weather measurements, and thousands of other topics that, when brought together, can be used to provide answers.

The system is constrained by the limits of its data library: It can’t interpret every question. It also can’t respond in natural language, or what a human would recognize as conversational speech. This is a stumbling block in AI in general. Even Siri, which relies heavily on Mathematica—another Wolfram Research product and the engine behind Wolfram|Alpha—can only answer questions in programmed response scripts, which are like a series of Mad Libs into which it plugs answers before spitting them out of your speaker or onto your screen.

Using Wolfram|Alpha is similar to executing a Google search, but Wolfram|Alpha delivers specific answers rather than endless pages of potentially relevant results. Anyone can go to the Wolfram|Alpha website, type a question or equation into a dialogue box, hit enter, and receive an answer. If you’re trying to solve x2 + 5x + 6 = 0, Wolfram|Alpha will give you the root plot, alternate forms, and solutions. If you are looking for a step-by-step explanation, there is a pro version available for $6.99/month with discounted options for students and educators.

I first heard about Wolfram|Alpha in my parents' kitchen. My father had come home from his job at a private school in Dobbs Ferry, New York. He dropped his bag on the floor, and asked me what I thought about Wolfram|Alpha. Earlier that day he had been confronted by STEM teachers who were frustrated with their students' use of the tool. It was, they said, blatant cheating. My father had left the office unsure of how to proceed. Should the school crack down on Wolfram|Alpha? Or did the school need to catch up to this new beat in education?

Reece Rogers

Steven Levy

Brenda Stolyar

I’d never heard of it, but a quick post to Facebook revealed that many of my friends had—especially those studying math. Some had used it to get through college calculus, while a few were still using it at their jobs as engineers or quantitative analysts. The rise of Wolfram|Alpha had completely passed over my humanities-minded head, just as, for millions of minds, it had become ubiquitous. Turning to the tech for answers was, they said, normal. At the same time, all made it clear that they didn’t want their use of Wolfram|Alpha to be made public.

Though Wolfram|Alpha was designed to be an educational asset — a way to explore an equation from within— academia has found itself at a loss over how to respond. What some call cheating, others have heralded as a massive step forward in how we learn, what we teach, and what education is even good for. They say that Wolfram|Alpha is the future. Unsurprisingly, its creator agrees.

Stephen Wolfram, the mind behind Wolfram|Alpha, can’t do long division and didn’t learn his times tables until he’d hit 40. Indeed, the inspiration for Wolfram|Alpha, which he released in 2009, started with Wolfram’s own struggles as a math student. Growing up, Wolfram’s obsession was physics. By 12, he’d written a dictionary on physics, by his early teens he’d churned out three (as yet unpublished) books, and by 15 he was publishing scientific papers.

Despite his wunderkind science abilities, math was a constant stumbling block. He could come up with concepts, but executing calculations was hard. His solution was to get his hands on a computer. By programming it to solve equations and find patterns in data, he could leave the math to the machine and focus his brain on the science. It worked. In 1981, Wolfram became the youngest person to ever receive a MacArthur Fellowship. He was only 21.

Yet the tool that helped Wolfram build his reputation with physics ended up pulling him away from science. Wolfram became obsessed with complex systems and how computers could be used to study them. Five years after receiving his MacArthur Fellowship, Wolfram began developing Mathematica, and in 1988 Wolfram Research announced the release of its flagship product.

Wolfram never planned for his tool to become highbrow CliffsNotes, but he’s not too concerned about it, either. “Mechanical math,” Wolfram argues, “is a very low level of precise thinking.” Instead, Wolfram believes that we should be emphasizing computational thinking —something he describes as “trying to formulate your thoughts so that you can explain them to a sufficiently smart computer.” This has also been called computer-based math. Essentially, knowing algebra in today’s technology-saturated world won’t get you very far, but knowing how to ask a computer to do your algebra will. If students are making this shift, in his mind, they’re just ahead of the curve.

Alan Joyce, the director of content development for Wolfram Alpha, says that cheating is “absolutely the wrong way to look at what we do.” But the staff understands what might make teachers uncomfortable. Historically, education had to emphasize hand calculations, says John Dixon, a program manager at Wolfram Research. That’s because there wasn’t tech to fall back on and, when tech did start to appear, it wasn’t reliable. Only recently can computers calculate things automatically and precisely, and it’ll take some time for curriculums, and the teachers that are beholden to them, to catch up. Wolfram Research, Dixon says, wants to engage with teachers like Garcia, who are frustrated by the tool, to help them understand how it can help their students.

Indeed, the people who are directing the tool’s development view it as an educational equalizer that can give students who don’t have at-home homework helpers—like tutors or highly educated and accessible parents—access to what amounts to a personal tutor. It also has enormous potential within the classroom. A "show steps" button, which reveals the path to an answer, allows teachers to break down the components of a problem, rather than getting bogged down in mechanics. The "problem generator" can pull from real datasets to create relevant examples. “When you start to show educators the potential,” Dixon says, “you can see points where their eyes light up.”

For every teacher who’s converted to Dixon’s camp, there are multitudes of students who have been there for a while. As Alexander Feiner, an aspiring engineer and high school freshman told me, Wolfram|Alpha is a study aid, not a way of avoiding work — something that Dixon insists is the norm when it comes to out-of-classroom student use.

Still, the prevailing notion that Wolfram|Alpha is a form of cheating doesn’t appear to be dissipating. Much of this comes down to what homework is. If the purpose of homework is build greater understanding of concepts as presented in class, Joyce is adamant that teachers should view Wolfram|Alpha as an asset. It’s not that Wolfram Alpha has helped students “‘get through’ a math class by doing their homework for them,” he says, “but that we helped them actually understand what they were doing” in the first place. Dixon believes that Wolfram|Alpha can build confidence in students who don’t see themselves as having mathematical minds. Homework isn’t really about learning to do a calculation, but rather about learning to find and understand an answer regardless of how the calculation is executed.

That’s the route down which education appears to be headed. Once upon a time, education was all about packing as much information as possible into a human brain. Information was limited and expensive, and the smartest people were effectively the deepest and most organized filing cabinets. Today, it’s the opposite.“The notion of education as a transfer of information from experts to novices—and asking the novices to repeat that information, regurgitate it on command as proof that they have learned it—is completely disconnected from the reality of 2017,” says David Helfand, a Professor of Astronomy at Columbia University.

The technology isn’t going anywhere: Like copying out of the back of a book or splitting a problem set among friends, students aren’t likely to stop using Wolfram|Alpha just because a teacher says so. Even Garcia can see a future where Wolfram|Alpha fits in. “I think, in an ideal world, teachers, myself included, need to do a better job of incorporating technology…and finding ways of using it in productive ways,” she says.

Just as robotics has transformed manufacturing, tools like Wolfram|Alpha are forcing us to rethink an educational system by challenging it to rise to the new technological standard. Either we reshape our schools to embrace tools like Wolfram|Alpha, or we risk becoming living artifacts in a rapidly progressing world.

Rachel Lance

Kathy Gilsinan

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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

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By Kathryn Hulick

April 12, 2023 at 7:00 am

“We need to talk,” Brett Vogelsinger said. A student had just asked for feedback on an essay. One paragraph stood out. Vogelsinger, a ninth grade English teacher in Doylestown, Pa., realized that the student hadn’t written the piece himself. He had used ChatGPT.

The artificial intelligence tool, made available for free late last year by the company OpenAI, can reply to simple prompts and generate essays and stories. It can also write code.

Within a week, it had more than a million users. As of early 2023, Microsoft planned to invest $10 billion into OpenAI , and OpenAI’s value had been put at $29 billion, more than double what it was in 2021.

It’s no wonder other tech companies have been racing to put out competing tools. Anthropic, an AI company founded by former OpenAI employees, is testing a new chatbot called Claude. Google launched Bard in early February, and the Chinese search company Baidu released Ernie Bot in March.

A lot of people have been using ChatGPT out of curiosity or for entertainment. I asked it to invent a silly excuse for not doing homework in the style of a medieval proclamation. In less than a second, it offered me: “Hark! Thy servant was beset by a horde of mischievous leprechauns, who didst steal mine quill and parchment, rendering me unable to complete mine homework.”

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 students at the university, 17 percent said they had used ChatGPT on assignments or exams at the end of 2022. Some admitted to submitting the chatbot’s writing as their own. For now, these students and others are probably getting away with it. That’s because ChatGPT often does an excellent job.

“It can outperform a lot of middle school kids,” Vogelsinger says. He might not have known his student had used it, except for one thing: “He copied and pasted the prompt.”

The essay was still a work in progress, so Vogelsinger didn’t see it as cheating. Instead, he saw an opportunity. Now, the student and AI are working together. ChatGPT is helping the student with his writing and research skills.

“[We’re] color-coding,” Vogelsinger says. The parts the student writes are in green. The parts from ChatGPT are in blue. Vogelsinger is helping the student pick and choose a few sentences from the AI to expand on — and allowing other students to collaborate with the tool as well. Most aren’t turning to it regularly, but a few kids really like it. Vogelsinger thinks the tool has helped them focus their ideas and get started.

This story had a happy ending. But at many schools and universities, educators are struggling with how to handle ChatGPT and other AI tools.

In early January, New York City public schools banned ChatGPT on their devices and networks. Educators were worried that students who turned to it wouldn’t learn critical-thinking and problem-solving skills. They also were concerned that the tool’s answers might not be accurate or safe. Many other school systems in the United States and around the world have imposed similar bans.

Keith Schwarz, who teaches computer science at Stanford, said he had “switched back to pencil-and-paper exams,” so students couldn’t use ChatGPT, according to the Stanford Daily .

Yet ChatGPT and its kin could also be a great service to learners everywhere. Like calculators for math or Google for facts, AI can make writing that often takes time and effort much faster. With these tools, anyone can generate well-formed sentences and paragraphs. How could this change the way we teach and learn?

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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Remote Learning and Cheating: Professors and Students Weigh In

By Maya Eashwaran

Lengthy time differences, technical difficulties, and Zoom fatigue: These are just three challenges of pandemic-era higher education. And another problem surfaced in a big way during the 2020 AP exams : the ease of cheating from home, when answers to tests and homework problems are often just a click away. 

Roughly a year after college campuses were evacuated due to the COVID-19 pandemic, academic integrity remains an issue for students and professors alike. With professors struggling to curb rampant cheating during online exams and students wrestling with the often confusing and stressful realities of online learning, the college classroom has never been more tense. 

Websites like Chegg and Slader have been cited in cheating scandals across the country, including at Georgia Tech , Boston University , Texas A&M , North Carolina State , and Princeton University . These websites provide homework help and study tools, but many professors and academic integrity directors believe these services are inadvertently undermining honest learning. 

Teen Vogue has spoken with academics and students to learn more about what kind of cheating is happening during remote learning, and what they think should be done about it.

University battles with help sites have peaked during the COVID-19 crisis, but the root of the problem has been years in the making. “I call it a game of whack-a-mole,” says David Rettinger, president emeritus of the International Center for Academic Integrity (ICAI) and director of academic integrity at the University of Mary Washington. New sites are constantly rising in popularity, he explains, making it harder for professors to prevent students from seeking answers online, especially now. 

Institutions like the ICAI do not maintain school-by-school records of cheating cases, but the current president of the ICAI, Camilla Roberts, says the organization has seen an uptick in violations that deal with online tutoring sites. “We have seen a drastic increase of violations dealing with these types of ‘help sites,’” says Roberts, who also serves as the director of honor and integrity at Kansas State University.  

She says the switch to online learning has helped administrators identify how widespread academic integrity violations are at K-State. In spring 2019, the college recorded 97 cases for the entire spring semester; during the online half of spring 2020, it saw a stunning 238 cases. 

This trend has also been noticeable at smaller schools like Florida’s Jacksonville University, which has around 4,100 total graduate and undergraduate students . Relative to the spring and fall semesters in 2019, cases rose by 65% and 38%, respectively, in 2020, according to director of academic integrity Lee Ann Clements. “The faculty had this perception that online students are more likely to cheat than students in face-to-face classes,” she says. “And it's just not true.”

The problem lies in the pedagogy, Clements explains. In traditionally online programs, cheating cases did not increase — it was only the classes that transitioned from in-person to online learning that experienced the issue.

Rettinger’s colleagues who typically work at online-only universities are “laughing at us,” he says. “They’re saying, ‘What you’re trying to do in 20 minutes is what we took 10 years to build.’ It’s like trying to win a bike race without a bike.”

When teaching and learning shifted to Zoom last spring, Tyler Johnson, a lecturer at North Carolina State’s department of statistics, found himself filing an unusually high number of academic integrity reports. 

Through the latter half of the spring semester, Johnson found exam questions from his introductory statistics course posted to Chegg. He eventually identified some 200 violations in the course of 800 students, he says. In response, students launched a petition claiming that the professor had neglected to clearly explain what was and was not permitted during the testing period. (Johnson says he was explicit that only course materials and personal notes were allowed.)

For the final exam, Johnson monitored the site during the exam window (which he typically extended to 48 hours to accommodate students’ unique living situations) to quickly identify and remove test questions, but says it was more difficult than expected. He tried to contact Chegg to report the posts but didn’t get traction.

In a statement to Teen Vogue , Candace Sue, Chegg’s director of academic relations, says that faculty need to provide signed letters from deans or student conduct officials to initiate honor code violation investigations. This is required to protect student privacy, she says.

“Students need help, and the vast majority of Chegg users are honest and use our platform to supplement their learning,” Sue's statement continues. “However, we take extremely seriously any attempts to cheat by those who abuse our offerings and invest heavily to prevent misuse of our learning platform.”

“In addition, we understand the enormous strain both faculty and students are under during this pandemic,” says Sue's statement. “Leading academic integrity experts regularly cite stress and anxiety as key reasons students cheat. Reducing student stressors and evolving traditional assessment mechanisms is the best path to mitigating academic misconduct.”

After filing reports through the university’s office of student conduct channels, Johnson was able to access information about student activity on the site and remove test questions. Other professors who spoke with Teen Vogue say that Chegg provides information on request from academic integrity offices. Rife with details like IP addresses, names of email accounts, and the exact time stamps for when accounts accessed site information, these reports allow professors to identify which students posted and accessed test answers during exams. Johnson says he was shocked to find that 250 to 300 unique accounts had their digital fingerprints on official exam questions. 

At Purdue University in Indiana, Chuck Krousgrill and his colleagues in the School of Mechanical Engineering have written roughly 800 original homework problems for their courses. It was “unnerving,” he says, to find the bulk of those questions on Chegg.

These sites make cheating simple for students, Krousgrill argues. “It is drop-dead easy to get a solution for your homework assignment back in less than one hour and for $15 a month,” he says. “Students might say, 'Okay, I'm busy,' or, 'I don't really have time to do this one set, so I'll go to Chegg and see if I can get an answer.' And then it gets worse. It snowballs, and then they find themselves too busy, ever. So they continue to do it.”

By Donya Momenian

By Kristi Kellogg

By Sara Delgado

But it may not be the pandemic and its related stressors that are driving an increase in reports of academic dishonesty. After all, students have been taking advantage of the plethora of available online help sites since they first appeared. The difference, Johnson posits, is that dishonesty is a lot easier to detect now that schooling is mostly online. “Now I actually have a concrete record of access,” he says. “It's harder to gather data in an in-person proctored exam on to what extent cheating is occurring.”

Students have found innovative ways to circumvent the watchful eyes of administrators while professors attempt to patch up leaks in the system. As Teen Vogue has reported , some schools are also using remote proctoring tools that students say are distracting, overly invasive, and have mistakenly accused them of cheating. It’s a complex game of cat and mouse, where the tech-savvy players often win the prize. 

Rettinger mentions a new application that is being developed for professors, which automatically posts their exams online. When students Google the question, they are directed to a fake page, and then if they click on the question, anticipating an answer, the software records their IP address for the professor’s records. 

Some professors have attempted to stamp copyright symbols on exam and homework questions, as sites will more regularly remove explicitly copyrighted material, explains Krousgrill. Students, however, always seem to find a way — even if it includes photoshopping over symbols and watermarks pixel-by-pixel before posting the material online. 

“The problem is that it only takes one person to post it,” says Krousgrill. “And then hundreds can cheat.” 

As remote learning continues, the use of online help sites will continue to blur the lines between what is “fair” for students, professors, and university administrators. 

Last May, the Daily Princetonian reported an incident in which a teacher’s assistant (TA) in the math department posted a purposefully incorrect solution to a homework question on Slader, a popular website promising “step-by-step textbook solutions.” The TA used the pseudonym “Arthur Dent,” a reference to the protagonist in The Hitchhiker’s Guide to the Galaxy.

The course, MAT202: Linear Algebra, is commonly taken by first- and second-year students pursuing degrees in majors like economics, engineering, or the sciences. Students who turned in problem sets containing evident similarities with the posted answer were reported to the Committee on Discipline for violating the explicit ban on the use of sites like Slader, as the newspaper reported. Accused students underwent an investigation process, with appointments scheduled in the spring, during the university’s grueling finals period. 

Princeton students are required to abide by the university honor code, a pledge that binds them to reporting incidents of cheating they are privy to as well as embracing the tenets of academic integrity in their own work. If found guilty, students can face charges ranging from warnings to suspension or expulsion. The stakes are high — and student anxieties are even higher. 

All students interviewed for this story have spoken on the condition of anonymity, and faculty members involved with the investigation have declined to comment.  Teen Vogue has reached out to Slader for comment but has not received a response.

Accused students express anger and disappointment with the course instructors’ decision to pursue cheaters through Slader. “Most of my family had been affected by the coronavirus and it was just a really stressful time.…" one student tells Teen Vogue . "I remember, I was using [Slader] to get an idea of how to do some of the problems, but I didn’t expect it to escalate into all of this.” 

Another accused student describes what they feel is an “unsympathetic” lack of leniency when it comes to requests for extensions on assignments and other accommodations. While battling a low grade in the course, she recalls asking her TA for advice on whether or not she should take the class “pass,” “fail,” or accept a D grade, options that were made available to all students during the latter half of the semester. Her TA brushed off her request, she says, stating that the grade shouldn’t be her focus. 

“It seems especially insensitive to tell a student who’s concerned about whether they are going to pass the course, ‘don’t worry about your grade,’” she says. 

Several students resorted to posting on Tiger Confessions, a Facebook page where current and former Princeton students submit anonymous “confessions” on subjects including mental health and academics. 

“The unique conditions of quarantine and this pandemic placed a lot of new challenges when it came to work,” wrote one poster. “Sickness, housing instability, mental health issues, technological limits, and different time zones: All of these issues required teachers to become more flexible. In most of my classes, this happened.… MAT202, instead, seemed to offer even more restrictive policies.” 

Back in May, Princeton’s Undergraduate Student Government Survey found that 63.3% of students were “somewhat more stressed” or “substantially more stressed” about academics after transitioning to remote learning, and nearly 70% of students experienced self-reported “somewhat worse” or “significantly worse” mental health. 

The academics Teen Vogue has spoken with say they empathize with students’ stressful circumstances during the pandemic, but they argue that academic integrity is a crucial pillar of higher learning.

In an interview with Teen Vogue this past summer, Jill Dolan, dean of the College at Princeton, emphasized the university’s commitment to the honor code. “Don’t misunderstand me — I’m not saying that faculty don't care," she said. “I just think we have to be clear that the honor code is about academic integrity, not about the context in which people are learning.” 

Noting the university’s spring 2020 adjustments — expanding grading options, changing transcript notation, additional resources for students struggling academically — and the unforeseen challenges that have arisen with COVID-era schooling, deputy university spokesperson Michael Hotchkiss states definitively that “cheating is never acceptable at Princeton.” 

Some of the professors who have spoken to Teen Vogue suggest a need for structural changes in what coursework and exams look like to account for a new, virtual learning environment. Rettinger advocates for modifying exam questions and class assignments to formats that are more reliant on a student's ability to learn, rather than to Google. 

Meanwhile, Johnson of North Carolina State acknowledges that students are struggling, but believes they’re still responsible for adhering to an honor code. “Academic integrity is a big enough deal that the responsibility to behave in a manner consistent with academic integrity standards in the course is independent of any issues they were having with their instructors,” he says. “I don't like to hear that the student is not feeling supported by their instructor. That's an issue. But the remedy to that isn't to go and look up the answer to the exam question or a homework question or something like that elsewhere.”

Dina Kuttab, a Princeton senior and former chair of the Student Honor Committee, says trust has to go both ways: Professors shouldn’t assume that students are trying to cheat, and students shouldn’t take advantage of their teachers. “While every person being in their own home deepens the need for that trust and pushes it further than it has in the past,” she says, “it’s based on the same principles that we have on campus.”

Want more from Teen Vogue ? Check this out: Student Debt Relief and Joe Biden: What to Expect From His Administration

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By Rachel Janfaza

By Sarah Emily Baum

By Mary Retta

By Lex McMenamin

• Our Mission

Helping Students Use AI Creatively Without the Temptation of Cheating

Designing school-friendly chatbots with firm guardrails can spur students toward creative AI use that doesn’t do their work for them.

When ChatGPT was introduced to the public in late 2022, it sparked a significant divide in the education community. On one side, teachers recognized the potential of this tool as a means of personalizing and democratizing learning. On the other, some educators expressed concerns that it would become an ultimate cheating tool, leading to a decline in authentic and creative thought. 

In the last year, I have worked hard to take a less dichotomous view of artificial intelligence (AI) in the classroom and have looked for ways that AI might support and foster personalized learning and help educators rethink AI as just a “cheating tool.” Finding that middle ground was made easier when I was introduced to customized chatbots for the classroom , designed specifically for student use. It didn’t take long to recognize that these bots have the potential to introduce a whole new dimension of assistance for students who may be stuck or struggling. After all, we know that students may resort to cheating when they don’t know how to get started or what to do next.

So how do we find this middle ground? It starts with rethinking AI—seeing it less as a threat to critical thinking and objective truth, and more for its potential as a supportive resource to help students produce better, more meaningful work.

Support System

From the outside, interacting with a custom chatbot looks a lot like having a conversation with ChatGPT or any chat-based AI tool, but with some important differences. Teachers who create them using tools like SchoolAI and Mizou can build in firm guardrails to safely support each student, while keeping them focused. Both tools offer students access to customized AI assistants without jeopardizing their data. What sets them even further apart from other chatbots lies in the teacher’s ability to see students’ detailed interactions. 

Teachers can precisely control what the student can or cannot do while using them, making it easier to keep students focused on a specific task. It’s important to note that bots do not replace teachers, but instead offer additional assistance to students in a timely manner, helping them get started or progress effectively on their own. At any given time during the writing and brainstorming process, some students might be using AI while others are working independently.

Goodbye, Blank Page

To see how this works, let’s head into a busy middle school language arts classroom where a diverse group of learners are tasked with writing a persuasive essay. The teacher wants to let the students have “voice and choice” in picking their subject and getting started, but as we know, each student needs a different support to help get them on the right track initially. Before the lesson today, the teacher and I set up a chatbot as a student assistant to help personalize the learning experience for each student. 

When we sat down to create this chatbot, the teacher explained that one of her biggest frustrations was not being able to devote as much time to helping every student as she’d like. Invariably, during independent writing time, part of the class was often left staring at a blank page, getting little accomplished, while they waited for her to check in with them directly. To help solve this age-old problem, we created a customized bot using SchoolAI to help students start the writing process on their own. We opened up the AI assistant, called Sidekick, and input our guardrails, prompting it to help students pick a topic, get started with research, and uncover some of the angles of their persuasive essay. 

Afterward, I point out that she can use the information provided in the teacher dashboard to better understand where each student is in the process, even seeing their conversations with the chatbot itself. This way she can deliver a more tailored experience as more of a writing coach, to each student as needed.  

As I look around, the students begin quickly interacting with the chatbot, and the engagement is palpable. We hear comments like “Oh, this is so cool” and “Where has this been all my life?” and “This is helping me so much!” Another student approaches me to say, “Thank you for this. I always needed this help but didn’t want to ask.” 

The teacher, who was slightly skeptical at first, is now bouncing around the classroom from student to student, and I can see in her eyes that she has become a convert to using AI in the classroom. The students are diligently working with the help of the chatbot, and each is moving through the task of choosing an idea that they are passionate about, diving deeper into possible topic nuances, while others are getting advice on research, and still others are digging into possible counterarguments. 

On the teacher dashboard, we begin to get a summary of what is happening with the student interactions and their individual progress.

At no time during this process will the chatbot write the essay for them, as it was initially created with specific guardrails to make sure this doesn’t happen. This experience was crafted to provide just the right amount of personalized support, so that students can stay on task and not fall behind. Think of this experience as the chatbot being there to get a student unstuck. And while it was helpful for all students, it proved especially valuable for those with dyslexia and English language learners. 

Over in another classroom, students in kindergarten are using a customized chatbot to come up with sentences for sight words, and after hearing many different examples, they pick their favorite to share with their partner. In this scenario, the student eventually writes this favorite sentence, full of new and interesting words, into their notebook. 

Both of these classrooms of students will grow up knowing that chatbots can help them in more powerful ways than simply cheating or writing an essay for them. They will inherently understand how it is you communicate with AI to get lots of different information, to seek additional help, and to move past not knowing what to do next. These students aren’t left to the Wild West of AI at home with virtually no guidance. This is a huge win for education.

A More Productive Future

We know students need support not only to develop their autonomy and agency in learning but also to achieve specific learning goals. Sadly, students who struggle to grasp concepts at the exact time they are presented in class or fail to get started on time often fall behind, which leaves them frustrated and with learning gaps as the class moves on without them. When this happens, learning gaps begin to accumulate over time and can lead to learning difficulties that shouldn’t exist. This could be massively impacted with just a little targeted and timely assistance.

While still in the beginning stages, these tools offer a glimpse into a future where teachers and AI collaborate to unlock each student’s full potential. The more we work with these tools and the more powerful they get, the more helpful they will be for learners.