We reviewed data from 19 studies, including 25 samples totaling 4672 participants. We found that a substantial proportion of students, 44.7%, were willing to admit to cheating in online summative exams. This total number masks a finding that cheating in online exams appeared to increase considerably during the COVID-19 pandemic, from 29.9–54.7%. These are concerning findings. However, there are a number of methodological considerations which influence the interpretation of these data. These considerations all lead to uncertainty regarding the accuracy of the findings, althoughr a common theme is that, unfortunately, the issues highlighted seem likely to result in an under-reporting of the rate of cheating in online exams.
There are numerous potential sources of error in survey-based research, and these may be amplified where the research is asking participants to report on sensitive or undesirable behaviours. One of these sources of error comes from non-respondents, i.e. how confident can we be that those who did not respond to the survey would have given a similar pattern of responses to those that did (Goyder et al., 2002; Halbesleben & Whitman, 2013; Sax et al., 2003). Two ways to minimize non-respondent error are to increase the sample size as a percentage of the population, and then simply to maximise the percentage of the invited sample who responds to the survey. However only nine of the samples reported sufficient information to even allow the calculation of a response rate, and only two reported the total population size. Thus for the majority of samples reported here, we cannot even begin to estimate the extent of the non-response error. For those that did report sufficient information, the response rate varied considerably, from 12.2% to 100, with an average of 55.6%. Thus a substantial number of the possible participants did not respond.
Most of the surveys reviewed here were conducted using convenience sampling, i.e. participation was voluntary and there was no attempt to ensure that the sample was representative, or that the non-respondents were followed up in a targeted way to increase the representativeness of the sample. People who voluntarily respond to survey research are, compared to the general population, older, wealthier, more likely to be female and educated (Curtin et al., 2000). In contrast, individuals who engage in academic misconduct are more likely to be male, younger, from a lower socioeconomic background and less academically able (reviewed in (Newton, 2018). Thus the features of the survey research here would suggest that the rates of online exam cheating are under-reported.
A second source of error is measurement error – for example, how likely is it that those participants who do respond are telling the truth? Cheating in online exams is clearly a sensitive subject for potential survey participants. Students who are caught cheating in exams can face severe penalties. Measurement error can be substantial when asking participants about sensitive topics, particularly when they have no incentive to respond truthfully. Curtis et al conducted an elegant study to investigate rates of different types of contract cheating and found that rates were substantially higher when participants were incentivized to tell the truth, compared to traditional self-report (Curtis et al., 2022). No studies reviewed here reported any incentivization, and many did not report IRB approval or that participants were guaranteed anonymity in their responses. Absence of evidence is not evidence of absence, but it again seems reasonable to conclude that the majority of the measurement error reported here will also lead to an under-reporting of the extent of online exam cheating.
However, there are very many variables associated with likelihood of committing academic misconduct (also reviewed in (Newton, 2018). For example, in addition to the aforementioned variables, cheating is also associated with individual differences such as personality traits (Giluk & Postlethwaite, 2015; Williams & Williams, 2012), motivation (Park et al., 2013), age and gender (Newstead et al., 1996) and studying in a second language (Bretag et al., 2019) as well as situational variables such as discipline studied (Newstead et al., 1996). None of the studies reviewed here can account for these individual variables, and this perhaps explains, partly, the wide variance in the studies reported here, where the percentage of students willing to admit to cheating in online exams ranges from essentially none, to all students, in different studies. However, almost all of the variables associated with differences in likelihood of committing academic misconduct were themselves determined using convenience sampling. In order to begin to understand the true nature, scale and scope of academic misconduct, there is a clear need for studies using large, representative samples, with appropriate methodology to account for non-respondents.
There are some specific issues which must be considered when determining the accuracy of the data showing an increase in cheating during COVID. In general, the pre-COVID group appears to be a more homogenous set of samples, for example, 11 of the 16 samples are from students studying business, and 15 of the 16 pre-COVID samples are from the USA. The post-COVID samples are from a much more diverse range of disciplines and countries. However the increase in self-reported cheating was replicated in the one study which directly asked students about their behaviour before, and during, the pandemic; Jenkins and co-workers found that 28.4% of respondents were cheating pre-COVID, nearly doubling to 58.4% during the pandemic (Jenkins et al., 2022), very closely mirroring the aggregate results.
It is difficult to quantify the potential impact of these issues on the accuracy of the data analysed here, since objective measures of cheating in online exams are difficult to obtain in higher education settings. One way to achieve this is to set up traps for students taking closed-book exams. One study tested this in the context of a 2.5 hour online exam administered for participants to obtain credit from a MOOC. The exams was set up in such a way that participants would “likely not benefit from having access to third-party reference materials during the exam”. Students were instructed not to access any additional materials or to communicate with others during the exam. The authors built a ‘honeypot’ website which had all of the exam questions on, with a button ‘click to show answer’. If exam participants went online and clicked that button then the site collected information which allowed the researchers to identify the unique i.d. of the test-taker. This approach was combined with a more traditional analysis of the originality of the free-text portions of the exam. Using these methods, the researchers estimated that ~ 30% of students were cheating (Corrigan-Gibbs et al., 2015b). This study was conducted in 2014-15, and the data align well with the pre-COVID estimates of cheating found here.
The challenges of interpreting data from small convenience samples will also affect the analysis of the other measures made here; that students are more likely to commit misconduct on their own, because they can. The overall pattern of findings though does align somewhat, suggesting that concerns may be with the accuracy of the numbers rather than a fundamental qualitative problem (i.e. it seems reasonable to conclude that students are more likely to cheat individually, but it is challenging to put a precise number to that finding). For example, the apparent increase in cheating during COVID is associated with a rapid and near-total transition to online assessment. Pre-covid, the use of online exams would have been a choice made by education providers, presumably with some efforts to secure the security and integrity of the assessment. During COVID lockdown, the scale and speed of the transition to online exams made it much more challenging to put security measures in place, and this would therefore almost certainly have increased the opportunities to cheat.
Thus an aggregate portrayal of the findings here is that students are committing misconduct in significant numbers, and that this has increased considerably during COVID. Students appear to be more likely to cheat on their own, rather than in groups, and most commonly motivated by the simple fact that they can cheat. What can we do about it?
One obvious suggestion is to increase the use of remote proctoring, wherein student behaviour during online exams is monitored, for example, through a webcam, and/or their online activity is monitored or restricted. We were unable to draw meaningful conclusions about the effectiveness of remote proctoring or other software such as lockdown browsers to reduce cheating in online exams, since very few studies stated definitively that the exams were, or were not, proctored. The two studies that examined this question did appear to show a substantial reduction in the frequency of cheating when proctoring was used. Confidence in these results is bolstered by the fact that these studies both directly compared unproctored vs proctored/lockdown browser. Other studies have used proxy measures for cheating, such as time engaged with the exam, and changes in exams scores, and these studies have also found evidence for a reduction in misconduct when proctoring is used (e.g. (Dendir & Maxwell, 2020)). The effectiveness (or not) of remote proctoring to reduce academic misconduct seems like an important area for future research. However there is considerable controversy about the use of remote proctoring, including legal challenges to its use and considerable objections from students as reviewed in the introduction, and so it remains an open question whether this is a viable option for widespread general use.
Honour codes are a commonly cited approach to promoting academic integrity, and so (in theory) reducing academic misconduct. However, empirical tests of honour codes show that they do not appear to be effective at reducing cheating in online exams (Corrigan-Gibbs et al., 2015a, b). In these studies the authors likened them to ‘terms and conditions’ for online sites, which are largely disregarded by users in online environments. However in those same studies the authors found that replacing an honour code with a more sternly worded ‘warning’, which specifies the consequences of being caught, was effective at reducing cheating. Thus a warning may be a simple, low-cost intervention to reduce cheating in online exams.
Another potential approach to deterring cheating could be to deliberately set traps, of ‘honeypots’; websites which appear to show students the answers to an exam but which are actually a way of catching students who commit academic misconduct. This approach has been used to quantify cheating in online exams, as described above (Corrigan-Gibbs et al., 2015b). There are some obvious ethical issues associated with such an approach, and from a practical perspective it seems reasonable to assume that students would get wise to this, and that the identity and nature of any honeypot could be easily shared by students cheating collaboratively.
Another option to reduce cheating in online exams is to use open-book exams. This is often suggested as a way of simultaneously increasing the cognitive level of the exam (i.e. it assesses higher order learning) (e.g. (Varble, 2014), and was suggested as a way of reducing the perceived, or potential increase in academic misconduct during COVID (e.g. (Nguyen et al., 2020; Whisenhunt et al., 2022). This approach has an obvious appeal in that it eliminates the possibility of some common forms of misconduct, such as the use of notes or unauthorized web access (Noorbehbahani et al., 2022; Whisenhunt et al., 2022), and can even make this a positive feature, i.e. encouraging the use of additional resources in a way that reflects the fact that, for many future careers, students will have access to unlimited information at their fingertips, and the challenge is to ensure that students have learned what information they need and how to use it. This approach certainly fits with our data, wherein the most frequently reported types of misconduct involved students acting alone, and cheating ‘because they could’. Some form of proctoring or other measure may still be needed in order to reduce the threat of collaborative misconduct. Perhaps most importantly though, it is unclear whether open-book exams truly reduce the opportunity for, and the incidence of, academic misconduct, and if so, how might we advise educators to design their exams, and exam question, in a way that delivers this as well as the promise of ‘higher order’ learning. These questions are the subject of ongoing research.
In summary then, there appears to be significant levels of misconduct in online examinations in Higher Education. Students appear to be more likely to cheat on their own, motivated by assessment design and delivery which makes it easy for them to do so. Future research in academic integrity would benefit from large, representative samples using clear and unambiguous survey questions and guarantees of anonymity. This will allow us to get a much better picture of the size and nature of the problem, and so design strategies to mitigate the threat that cheating poses to assessment validity.