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Academic integrity: a literature review

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T1 - Academic integrity: a literature review

AU - MacFarlane, Bruce

AU - Zhang, Jingjing

AU - Pun, Annie

N2 - This article provides a literature review on academic integrity, which encompasses the values, behaviour and conduct of academics in all aspects of their practice. This is a growing area of academic research as a result of the expansion of higher education on a global basis and concerns about standards of professional conduct. The article maps the main strands of research on academic integrity by reference to teaching, research and service using 115 articles derived from both western and Chinese literature. The review indicates that much of the literature is framed in terms of misconduct or academic corruption with research ethics the dominant focus. Researchers investigating academic integrity draw predominantly on multivariate analysis using surveys/questionnaires, documentary analysis and, more occasionally, interviews. While there has been rapid growth in the literature, a stronger focus is needed on identifying ?ethical? as well as ?unethical? practice despite the methodological challenges in overcoming social desirability reporting

AB - This article provides a literature review on academic integrity, which encompasses the values, behaviour and conduct of academics in all aspects of their practice. This is a growing area of academic research as a result of the expansion of higher education on a global basis and concerns about standards of professional conduct. The article maps the main strands of research on academic integrity by reference to teaching, research and service using 115 articles derived from both western and Chinese literature. The review indicates that much of the literature is framed in terms of misconduct or academic corruption with research ethics the dominant focus. Researchers investigating academic integrity draw predominantly on multivariate analysis using surveys/questionnaires, documentary analysis and, more occasionally, interviews. While there has been rapid growth in the literature, a stronger focus is needed on identifying ?ethical? as well as ?unethical? practice despite the methodological challenges in overcoming social desirability reporting

KW - academic integrity

KW - literature

KW - methodology

KW - ethics

U2 - 10.1080/03075079.2012.709495

DO - 10.1080/03075079.2012.709495

M3 - Article (Academic Journal)

SN - 0307-5079

JO - Studies in Higher Education

JF - Studies in Higher Education

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Academic integrity: a review of the literature

Author(s) : Macfarlane, Bruce; Zhang, JingJing Zhang; Pun, Annie

Imprint : 2012

Collation : p. 339-358

Series : Studies in higher education, v. 39, no. 2

This article provides a literature review on academic integrity, which encompasses the values, behaviour and conduct of academics in all aspects of their practice. This is a growing area of academic research as a result of the expansion of higher education on a global basis and concerns about standards of professional conduct. The article maps the main strands of research on academic integrity by reference to teaching, research and service using 115 articles derived from both western and Chinese literature. The review indicates that much of the literature is framed in terms of misconduct or academic corruption with research ethics the dominant focus. Researchers investigating academic integrity draw predominantly on multivariate analysis using surveys/questionnaires, documentary analysis and, more occasionally, interviews. While there has been rapid growth in the literature, a stronger focus is needed on identifying ‘ethical’ as well as ‘unethical’ practice despite the methodological challenges in overcoming social desirability reporting.

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Academic integrity: A review of the literature

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Research output : Contribution to journal › Articles › peer-review

• Academic integrity
• Methodology

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• 10.1080/03075079.2012.709495

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Review article, academic integrity in online assessment: a research review.

• Department of Psychology, Queen’s University, Kingston, ON, Canada

This paper provides a review of current research on academic integrity in higher education, with a focus on its application to assessment practices in online courses. Understanding the types and causes of academic dishonesty can inform the suite of methods that might be used to most effectively promote academic integrity. Thus, the paper first addresses the question of why students engage in academically dishonest behaviours. Then, a review of current methods to reduce academically dishonest behaviours is presented. Acknowledging the increasing use of online courses within the postsecondary curriculum, it is our hope that this review will aid instructors and administrators in their decision-making process regarding online evaluations and encourage future study that will form the foundation of evidence-based practices.

Introduction

Academic integrity entails commitment to the fundamental values of honesty, trust, fairness, respect, responsibility, and courage ( Fishman, 2014 ). From these values, ethical academic behavior is defined, creating a community dedicated to learning and the exchange of ideas. For a post-secondary institution, ensuring that students and staff are acting in an academically integrous manner reinforces an institution's reputation such that an academic transcript, degree, or certificate has a commonly understood meaning, and certain knowledge and skills can be inferred of its holder. In turn, individual students benefit from this reputation and from the inferences made based on their academic accomplishments. At a broader level, understanding the fundamental values of academic integrity that are held within a community—and behaving in accordance with them—instills a shared framework for professional work, making explicit the value of the mastery of knowledge, skills, and abilities.

Fair and effective methods for promoting academic integrity have long been considered within postsecondary education. Yet, there is a widespread belief that departures from integrity are on the rise (e.g. Hard et al., 2006 ). With the introduction of technology into the classroom and the popularity of online classes, new opportunities for “e-cheating” exist (e.g. Harmon and Lambrinos, 2008 ; King and Case, 2014 ). Demonstrating the importance of considering “e-cheating,” prior to 2020, reports suggest that 30% of students in degree-granting U.S. colleges and universities enrolled in at least one online course ( Allen and Seaman, 2017 ), and 44% of faculty respondents reported teaching at least one fully online course ( Jaschik and Lederman, 2018 ). In 2020 and as of this writing, the COVID-19 pandemic has caused widespread changes to higher education, resulting in many institutions adopting online learning formats. As the development of fully online courses is expected to continue to expand (e.g., Allen and Seaman, 2010 ; Johnson, 2019 ), faculty and administrators are faced with the challenge of developing methods to adequately assess student learning in an online environment while maintaining academic honesty.

There are many new ways to cheat, some that are unique to the online course environment and some that are also observed within in-person courses; these include but are not limited to: downloading papers from the internet and claiming them as one’s own work, using materials without permission during an online exam, communicating with other students through the internet to obtain answers, or having another person complete an online exam or assignment rather than the student who is submitting the work ( Jung and Yeom, 2009 ; Moten et al., 2013 ; Rogers, 2006 ; Underwood and Szabo, 2003 ). In particular, both faculty and students perceive online testing to offer more cheating opportunities than in traditional, live-proctored classroom environments ( Kennedy et al., 2000 ; Rogers, 2006 ; Stuber-McEwen et al., 2005 , Smith, 2005 ; Mecum, 2006 ), with the main concerns being student collaboration and use of forbidden resources during the exam ( Christe, 2003 ).

The goal of this paper is to review and synthesize current research on academic integrity in higher education, considering its specific application to assessment practices in online education. Understanding the varied and complex types and causes of academic dishonesty can inform the suite of methods that might be used to most effectively promote academic integrity. Thus, we will address the question of why students engage in academically dishonest behaviours ( Why do Students Engage in Academic Dishonesty? ), and we will review methods to reduce academically dishonest behaviours (Section 3). We will do this with intentional consideration of four factors: individual factors, institutional factors, medium-related factors, and assessment-specific factors. Given the increasing use of online courses within the postsecondary curriculum, it is our hope that this review will aid instructors and administrators in their decision-making process regarding online evaluations and encourage future study that will form the foundation of evidence-based practices 1 .

Why do Students Engage in Academic Dishonesty?

Academic dishonesty (or “cheating”) 2 includes behaviors such as the use of unauthorized materials, facilitation (helping others to engage in cheating), falsification (misrepresentation of self), and plagiarism (claiming another’s work as one’s own; e.g., Akbulut et al., 2008 ; Şendağ et al., 2012 ), providing an unearned advantage over other students ( Hylton et al., 2016 ). Broadly, these behaviors are not consistent with an established University’s Standards of Conduct ( Hylton et al., 2016 ), which communicates expected standards of behavior ( Kitahara and Westfall, 2007 ). “E-dishonesty” has been used to refer to behaviors that depart from academic integrity in the online environment, and e-dishonesty raises new considerations that may not have been previously considered by instructors and administrators. For example, concerns in relation to online exams typically include ‘electronic warfare’ (tampering with the laptop or test management system), impersonation, test item leakage, and the use of unauthorized resources such as searching the internet, communicating with others over a messaging system, purchasing answers from others, accessing local/external storage on their computer, or accessing a book or notes directly (e.g. Frankl et al., 2012 ; Moten et al., 2013 ; Wahid et al., 2015 ). All of these types of behaviours are also considered under the broader umbrella term of ‘academic dishonesty’ ( Akbulut et al., 2008 ; Namlu and Odabasi, 2007 ), and we highlight them here to broaden the scope of considerations with respect to academic integrity.

There are many reasons why individuals may choose to depart from academic integrity. Here, we synthesize existing research with consideration of individual factors, institutional factors, medium-related factors, and assessment-specific factors. Much of the research to date considers the on-campus, in-person instructional context, and we note the applicability of much of this literature to online education. Where appropriate, we also note where research is lacking, with the aim of encouraging further study.

Individual Factors

Research based on what is referred to as the “fraud triangle” proposes that in order for cheating to occur, three conditions must be present: 1) opportunity, 2) incentive, pressure, or need, and 3) rationalization or attitude (e.g. Becker et al.2006 ; Ramos, 2003 ). These three conditions are all positive predictive factors of student cheating behavior ( Becker et al., 2006 ). Opportunity occurs when students perceive that there is the ability to cheat without being caught; this perception can occur, for example, if instructors and administrators are thought to be overlooking obvious cheating or if students see others cheat or are given answers from other students ( Ramos, 2003 ). The second condition, incentive, pressure, or need , can come from a variety of different sources such as the self, parents, peers, employers, and universities. The pressure felt by students to get good grades and the desire to be viewed as successful can create the incentive to cheat. Lastly, the rationalization of cheating behavior can occur when students view cheating as consistent with their personal ethics and believe that their behavior is within the bounds of acceptable conduct ( Becker et al., 2006 ; Ramos, 2003 ). Similar to the “cheating culture” account (detailed more fully in Institutional Factors ), rationalization can occur if students believe that other students are cheating, perceive unfair competition, or perceive an acceptance of, or indifference to, these behaviors by instructors ( Varble, 2014 ).

Though accounts based on the fraud triangle are well supported, other researchers have taken a more fine-grained approach, further considering the second condition related to incentive, pressure, or need . Akbulut et al. (2008) , for example, propose that psychological factors are the most significant factors leading students to e-dishonesty. Feeling incompetent and/or not appreciating the quality of personal works or one’s level of mastery ( Jordan, 2001 ; Warnken, 2004 ; Whitaker, 1993 ), a sense of time pressure ( DeVoss and Rosati, 2002 ; Sterngold, 2004 ), a busy social life ( Crown and Spiller, 1998 ), personal attitudes toward cheating ( Diekhoff et al., 1996 ; Jordan, 2001 ), and the desire to get higher grades ( Antion and Michael, 1983 ; Crown and Spiller, 1998 ) can cause an increase in academic dishonesty, including e-dishonesty.

In particular relation to online courses, some authors contend that the online medium may serve as a deterrent for academic dishonesty because it often supports a flexible schedule and does not lend itself to panic cheating ( Grijalva et al., 2006 ; Stuber-McEwen et al., 2009 ). Indeed, often, a reason why students enroll in online courses is the ease and convenience of an online format. However, if students become over-extended, they may use inappropriate resources and strategies to manage (e.g. Sterngold, 2004 ). In addition, the isolation that students may experience in an online course environment can also increase stress levels and lead them to be more prone to dishonest behaviors ( Gibbons et al., 2002 ).

Institutional Factors

Individual students are part of larger university culture. By some accounts, a primary contributor to academic dishonesty is the existence of a “cheating culture” ( Tolman, 2017 ). If a university has an established culture of cheating—or at least the perception of a culture of cheating—students may be tolerant of cheating, believe that cheating is necessary in order to succeed, and believe that all students are cheating ( Crittenden et al., 2009 ). Students directly shape cheating culture, and thus subsets of students in a university population may have their own cheating cultures ( Tolman, 2017 ). It is plausible, then, for online students to have their own cheating culture that differs from the rest of the student population. However, if this subset of students is identified as being at risk for academic dishonesty, there is the opportunity for the university to proactively address academic integrity in that student group ( Tolman, 2017 ).

We note, however, the peculiar situation of current the COVID-19 pandemic, particularly for universities that transitioned to mostly online courses. A university’s cheating culture may change, as large numbers of students may be faced with increased pressures and as online courses are designed—and assessments developed—with atypical rapidity. It will be necessary for future research on university cheating culture, both on campus and online, to consider the potential long-term impacts of the pandemic on “appropriate” student behaviors. For example, there appear to be many new opportunities for students to share papers and coursework with peers in online forums. In some cases this sharing may be appropriate, whereas in others it may not. Determining effective methods for communication of boundaries related to academic honesty—especially when boundaries can vary depending on the nature of an assignment—will be especially important.

Institutional policies related to the academic standards of the university also impact academic honesty on campus. Some institutional policies may be too lax, with insufficient sanctions and penalization of academic dishonesty (e.g., Akbulut et al., 2008 ). Further, even when sanctions and penalization are adequate, a lack of knowledge of these policies within staff, administrators, and students—or insufficient effort made to inform students about these policies—can result in academic dishonesty (see also Jordan, 2001 ). For example, McCabe et al. (2002) found a significant correlation such that academic dishonesty decreased as students’ and staff’s perceived understanding and acceptance of academic integrity policies increased. Additionally, academic dishonesty was found to be inversely related to the perceived certainty of being reported for academic dishonesty and the perceived severity of the university’s penalties for academically dishonest behavior. Relatedly, universities with clear honor codes had lower academic dishonesty than universities without honor codes ( McCabe et al., 2002 ). Given these findings, universities should make academic conduct policies widely known and consider implementing honor codes to minimize the cheating culture(s). Specifically, for online courses, these findings suggest that the university’s academic conduct policies and honor codes should be directly stated on course sites.

Medium of Delivery

The belief that cheating occurs more often in online courses than in in-person courses—particularly for high-stakes assessments like exams—is widespread, with approximately 42–74% of students believing it to be easier to cheat in an online class ( King et al., 2009 ; Watson and Sottile, 2010 ). Thus, the question of whether students are cheating at greater rates in online classes is paramount in evaluating the reliability of online assessments as measurements of mastery in higher education. Though there have been many studies of academic dishonesty in in-person classes, few studies have attempted to compare cheating rates between in-person and online classes. In those that do, the results appear to be inconsistent with some studies demonstrating that cheating occurs more often in online classes than in in-person classes ( Lanier, 2006 ; Khan and Balasubramanian, 2012 ; King and Case, 2014 ; Watson and Sottile, 2010 ), others demonstrating equivalent rates of cheating ( Grijalva et al., 2006 ; Ladyshewsky, 2015 ), and some demonstrating that cheating occurs more often in-person ( Stuber-McEwen et al., 2009 ). Table 1 provides a summary of these studies, and we highlight some of them below.

TABLE 1 . Studies Comparing Academic Dishonesty in Online Classes and In-Person Classes .

Four studies to date have found cheating rates to be higher in online courses than in in-person courses. Lanier (2006) , for example, surveyed college students ( n = 1,262) in criminal studies and legal studies courses and found that 41.1% of respondents admitted to cheating in an online course while 21.3% admitted to cheating in an in-person course. The study also found some preliminary evidence for differences in cheating rates between majors, though the sample sizes for some groups were too low to be reliable: business majors were the most likely to cheat ( n = 6, 47.1%), followed by “hard sciences” ( n = 20, 42.6%), and “social sciences” ( n = 282, 30%). Though clearly tentative given the small sample sizes, these data suggest that there may be different cheating cultures that exist within universities, demonstrating the importance of considering group-level culture differences with respect to cheating ( Institutional Factors above). Further supporting an increased rate of cheating in online assessments, Khan and Balasubramanian (2012) surveyed undergraduate students attending universities in the United Arab Emirates ( N = 224) and found that students admitted to higher cheating rates using technology or e-cheating. Although this study did not differentiate between online and in-person course formats, it does suggest an increase in cheating via the use of online technology.

Using the Student Ethical Behavior instrument with undergraduate students enrolled in a business course ( n = 1867), King and Case (2014) found higher cheating rates in online exams than in in person-exams. Specifically, researchers found that 15% of students admitted to cheating on an in-person exam, at about 2.9 times a semester, while 29% admitted to cheating on an online exam, at about 3.3 times a semester. Thus, not only were students cheating at higher rates in online exams as compared to in-person exams, but those that did admit to cheating were also cheating more frequently during a semester. Consistent with this finding, Varble (2014) analyzed the test scores of students enrolled in an online or an in-person, undergraduate marketing course. Students took exams either online or in person. The study found higher mean test scores in the online test group with the exception of one test, than test scores in the in-person test group. The difference in scores was largely attributed to “remember” type questions which rely on a student’s ability to recall an answer, or alternatively, questions which could be looked up in unauthorized resources. Given these findings, Varble (2014) concluded that cheating may have taken place more often in the online tests than in-person tests.

In contrast to studies reporting increases in academic dishonesty in online assessments, other studies have found lower rates of cheating in online settings as compared to in-person. Grijalva et al. (2006) used a randomized response survey method with 725 undergraduate students taking an online course and estimated that only 3–4% of students cheated. Consistent with this finding, Stuber-McEwen et al. (2009) surveyed in-person ( n = 225) and online students ( n = 138) using the Student Academic Dishonesty Survey and found that online students reported engaging in less academic misconduct than in-person students. An important methodological feature to consider, however, is that the sample of online students consisted of more mature distance study learners than the in-person sample; this study may not be applicable to the general university population. 3

Although some studies have found cheating rates to be higher or lower in online classes, some have not found significant differences. Watson and Sottile (2010) , for example, used the Academic Dishonesty Assessment with a sample of undergraduate and graduate students from different faculties ( n = 635). The study found that 32.7% of respondents admitted to cheating in an online course while 32.1% admitted to cheating in an in-person course. However, the data also demonstrated that students were significantly more likely to cheat by obtaining answers from others during an online quiz or test than in an in-person quiz or test (23.2–18.1%) suggesting that students in an online course tended to cheat more in an online exam, while students in an in-person course tended to cheat through other assignments. Additionally, students admitted that they were four times more likely to cheat in an online class in the future compared to an in-class format (42.1–10.2%) ( Watson and Sottile, 2010 ). This study points to a potential importance of addressing cheating particularly in online exams in order to ensure academic honesty in online courses, though we note that Ladyschewsky (2015) found that in a sample of post-graduate students ( n = 136), multiple-choice test scores in an unproctored online format were not different from scores from a proctored, in-person exam.

Assessment-specific Factors

Research varies in the context in which cheating is explored. For example, some studies examine cheating within some or all types of online assessments, whereas others specifically focus on exams. The type of assessment likely matters when it comes to academic behaviors. For example, though Lanier (2006) found higher reporting of cheating in online courses, the study did not distinguish among assessments, and instead focused on cheating across all assignments in classes. Yet, in Watson and Sottile (2010) ; described above, students were significantly more likely to cheat by obtaining answers from others during an online quiz or test than in an in-person quiz or test (23.2–18.1%), suggesting that students in an online course tended to cheat more in an online exam, while students in an in-person course tended to cheat through other assignments.

If students are more likely to engage in academic dishonesty on high-stakes summative assessments (e.g., exams) rather than formative assessments throughout the term—and if online exams offer more opportunities for dishonesty—then rates of cheating would be expected to differ depending on the assessment type. Additionally, when comparing dishonesty in online and on-campus courses, the differences might be minimal in relation to assessments that allow for plagiarism (e.g., essays that may be completed “open book” over an extended time period; e.g., Watson & Sottile, 2010 ). We thus encourage future research to consider the type of assessment when comparing cheating in online vs. in-person course environments.

Methods for Reducing Academic Dishonesty in Online Assessment

Just as the reasons for why students cheat are varied, so too are methods for reducing academic dishonesty. We again organize the topic in relation to factors related to the individual student, the institution, the medium of delivery, and the assessments themselves. Throughout, we focus primarily on summative assessments that may have various formats, from multiple-choice questions to take-home open-book essays. Though the methods for preventing cheating are discussed separately from the reasons why students cheat in this paper, we emphasize that the methods must be considered in concert with consideration of the reasons and motivations that students may engage in academic dishonesty in the first place.

Individual- and Institutional-Level Methods

We discuss both individual- and university-level methods to reduce academic dishonesty together here, as current methods consider the bi-directional influence of each level. As highlighted in Institutional Factors , institutional factors that can increase academic dishonesty include lax or insufficient penalization of academic dishonesty, insufficient knowledge of policies and standards across students, instructors, and administrators, and insufficient efforts to inform students about these policies and standards ( Akbulut et al., 2008 ; Jordan, 2001 ). In order to ensure academic honesty at universities, administrators and staff must clearly define academic dishonesty and what behaviors are considered academically dishonest. Students often demonstrate confusion about what constitutes academic dishonesty, and without a clear definition, many students may cheat without considering their behaviors to be academically dishonest. Thus, the more faculty members discuss academic honesty, the less ambiguity students will have when confronting instances of academic dishonesty ( Tatum and Schwartz, 2017 ). In addition to making students aware of what constitutes academic dishonesty, it is also important to make students aware of the penalties that exist for academically dishonest behavior. Academic dishonesty is inversely related to the perceived severity of the university’s penalties for academically dishonest behavior ( McCabe et al., 2002 ). When faculty members are aware of their institutions policies against academic dishonesty and address all instances of dishonesty, fewer academically dishonest behaviors occur ( Boehm et al., 2009 ).

Faculty and staff can influence the cheating culture of their university simply by discussing the importance of academic honesty with their students. These discussions can help shape and change a student’s beliefs on cheating, hopefully reducing their ability to rationalize academically dishonest behavior. Discussions with students on the importance of academic honesty may help reduce feelings of overestimated cheating frequency among peers, and may prevent students from rationalizing cheating behavior. Honor codes, for example, are effective at reducing academic dishonesty when they clearly identify ethical and unethical behavior ( Jordan, 2001 ; McCabe and Trevino, 1993 ; McCabe and Trevino, 1996 ; McCabe et al., 2001 ; McCabe et al., 2002 ; Schwartz et al., 2013 ), and are associated with perceptions of lower cheating rates among peers ( Arnold et al., 2007 ; Tatum and Schwartz, 2017 ). Further, these codes reduce students’ ability to rationalize cheating ( Rettinger and Kramer, 2009 ), increase the likelihood that faculty members and students will report violations ( Arnold et al., 2007 ; McCabe and Trevino, 1993 ), and increase the perceived severity of sanctions ( McCabe and Trevino, 1993 ; Schwartz et al., 2013 ). In addition to implementing honor codes school-wide, honor codes can also be implemented into specific courses and have been shown to reduce cheating and improve communication between students and faculty by increasing feelings of trust and respect among the students ( Konheim-Kalkstein, 2006 ; Konheim-Kalkstein et al., 2008 ).

Methods in Relation to the Medium of Delivery

Multiple methods to combat academic dishonesty in online assessments focus on the manner in which the assessment is delivered and invigilated. One view is that an in-person proctored, summative exam at a testing center is the best practice for an otherwise online course because of the potential ease of cheating in an unproctored environment or an online-proctored environment ( Edling, 2000 ; Rovai, 2000 ; Deal, 2002 ). Another view is that with the correct modifications and security measures, online exams offer a practical solution for students living far from campus or other testing facilities while still maintaining academic integrity. However, both proposed solutions come with their own disadvantages. Requiring students to travel to specific exam sites may not be feasible for remote students, and hiring remote proctors can be expensive ( Rosen and Carr, 2013 ). Indeed, in the current context of the global COVID-19 pandemic, in-person proctoring has been unfeasible in many regions.

In Methods in Relation to the Medium of Delivery , we focus on methods that do not require in-person proctoring. The assessment type we focus on is the summative exam, though we note the variability in the style that such assessments can take. There are currently various means of detecting cheating in online exams, and we have chosen to discuss these means of detection separately from methods use to prevent cheating as the implementation tends to occur at a different level and for a different purpose (e.g., technological systems that detect cheating while it is occurring or shortly after, rather than solutions at the level of assessment format that are designed to promote academic integrity). However, we do note that if students are aware of the cheating detection systems in place, the systems may have a preventative effect.

Online Cheating Detection

The exam cheating detection systems described below have been developed, in part, because holding exams in-person at a registered location with live proctors is often not feasible due to financial, travel, or other logistical reasons ( Cluskey et al., 2011 ). The general types of online proctoring include video summarization, web video recording, and live online proctoring; each is described below and in Figure 1 .

FIGURE 1 . Four types of proctoring: (A) in-person, (B) video summarization, (C) web video recording, and (D) live online proctoring.

Though online proctoring provides some intuitive advantages for detecting cheating behaviours, and it maps closely onto familiar face-to-face proctoring processes, many have raised concerns in media outlets about both the ethics and efficacy of these systems. For example, concerns have been raised about student invasion of privacy and data protection (e.g., Dimeo, 2017 ; Lawson, 2020 ), and breeches have occurred (e.g., Lupton, 2020 ). In addition to concerns related to privacy, cases have been reported where students were discriminated against by a proctoring software as a result of their skin colour (e.g., Swauger, 2020 ). Not only are there concerns about ethics regarding online proctoring software, but there are also concerns about whether these methods are even effective, and if so, for how long. For example, there have long been readily available guides that demonstrate how to “cheat” the cheating software (e.g., Binstein, 2015 ). If an instructor deems online proctoring effective and necessary, prior to using online proctoring, instructors should explicitly consider whether students are treated justly and equitably, just as they should in any interaction with students. Instructors are also encouraged to carefully investigate privacy policies associated with online cheating detection software, and any applicable institution policies (e.g., data access and retention policies), prior to using such technology.

Video Summation

Video summarization software, also referred to as video abstraction , utilizes artificial intelligence to detect cheating events that may occur during the exam ( Truong and Venkatesh, 2007 ). Students are video recorded using their own webcam throughout the exam. If a cheating event is detected, the program will flag the video for future viewing by a proctor. Thus, the time demands of proctors are reduced, yet students are monitored. Video summarization programs can generate either keyframes (a collection of images extracted from the video source) or video skims (video segments extracted from the video source) to represent potential cheating behavior (e.g. Truong and Venkatesh, 2007 ). Both of these forms convey the potential cheating event in order for future determination by a human proctor. However, video skims have an advantage over keyframes in that they have an ability to include audio and motion elements which convey pertinent information in the process of invigilation ( Cote et al., 2016 ).

The main advantage of choosing an invigilation service like this one is that it reduces the hours that proctors must put in into invigilating the exam. However, detecting cheating behavior without live human interaction is a difficult process. Modeling suspicious behavior is complex in that cheating behavior does not typically follow a pattern or type, thus making it difficult to recognize accurately ( Cote et al., 2016 ). Therefore, some suspicious activity may not be detected, and administrators may not be able to guarantee that all cheating behavior has been deterred or detected. Further, there is no opportunity for a live proctor to intervene or gather more information if atypical behaviour is occurring, limiting the ability to mitigate a violation of academic integrity if it is occurring, or about to occur.

Web Video Recording

In relation to online exams, web video recording refers to situations in which the student is video recorded throughout the entirety of the exam for later viewing by an instructor. Like video summarization methods, detection software can be used in order to flag any suspicious activity for later viewing. Administrators and instructors may feel more confident in this service as they can view the entire exam, not only the flagged instances. However, reviewing all exams individually may not be feasible, and most exams are not reviewed in full. Unlike video summarization programs, web video recording programs do not have specific proctors review all flagged instances, and instead rely on review by the administrators and instructors themselves. Knowing that the recording is occurring may deter students, but as with detection based on artificial intelligence, it is not guaranteed that all cheating behavior will be detected. It is important to note that with this method, as with the previous method, there is no opportunity for intervention by a proctor if an event is flagged as a possible violation of academic integrity. Thus, there may be ambiguous situations that have been flagged electronically with no opportunity to further investigate, and missed opportunities for prevention.

Live Online Proctoring

The final type of online proctoring, and arguably the most rigorous, is referred to as live online proctoring or web video conference invigilation . This method uses the student’s webcam and microphone to allow a live-proctor to supervise students during an online exam. Services can range from one-on-one invigilation sessions to group invigilation sessions where one proctor is supervising many students. Many administrators may feel the most comfortable using this kind of service as it is closest to an in-person invigilated exam. However, even with a live proctor supervising the student(s), cheating behavior can go undetected. At the beginning of a session, students are typically required to show their testing environment to their proctor; however, cheating materials can be pulled out during an exam unnoticed in the surrounding environment. If the proctor does not suspect cheating behaviors, they will not request another view of the entire room. Live online proctoring is also typically the most expensive of the options.

Online Cheating Detection: Other Solutions

Though online proctoring is one method for cheating detection, others also exist. Just as with online proctoring, instructors are encouraged to understand all applicable policies prior to using detection methods. Challenge questions, biometrics, checks for text originality, and lockdown browsers, are currently available technological options that instructors and institutions might consider.

Challenge Questions

Challenge or security questions are one of the simplest methods for authenticating the test taker. This method requires personal knowledge to authenticate the student and is referred to as a ‘knowledge-based authentication’ method ( Ullah et al., 2012 ). Students are asked multiple choice questions based on their personal history, such as information about their past home addresses, name of their high school, or mother(s) maiden name ( Barnes and Paris, 2013 ). Students must answer these questions in order to access the exam, and the questions may also be asked randomly during the assessment ( Barnes and Paris, 2013 ). These questions are often based on third-party data using data mining systems ( Barnes and Paris, 2013 ; Cote et al., 2016 ) or can be entered by a student on initial log-in before any examination. When a student requests an examination, the challenge questions are generated randomly from the initial profile set-up questions or third-party information, and answers are compared in order to verify the student’s identity ( Ullah et al., 2012 ). This relatively simple method can be used for authenticating the test taker; however, it cannot be used to monitor student behavior during the exam. Additionally, students may still be able to bypass the authentication process by providing answers to others to have another person take the exam, or to collaborate with others while taking the test. Thus, if chosen, this method should be used in concert with other test security methods in order to ensure academic honesty.

The use of biometrics, the measurement of physiological or behavioral features of an individual, is an authentication method that allows for continuous identity verification ( Baca and Rabuzin, 2005 ; Cote et al., 2016 ). This method of authentication compares a registered biometric sample against the newly captured biometrics in order to identify the student ( Podio and Dunn, 2001 ). When considering the use of biometric data, potential bias in identification, data security, and privacy must be carefully considered. It may be that the risks associated with the use of biometric data, given the intimate nature of these data, outweigh the benefits for an assessment.

There are two main types of biometric features: those that require direct physical contact with a scanner, such as a fingerprint, and those that do not require physical contact with a scanner such as hair color ( Rabuzin et al., 2006 ). Biometrics commonly use “soft” traits such as height, weight, age, gender, and ethnicity, physiological characteristics such as eyes, and face, and behavior characteristics such as keystroke dynamics, mouse movement, and signature ( Cerimagic and Rabiul Hasan, 2019 ). Combining two or more of the above characteristics improves the recognition accurateness of the program and is necessary to ensure security ( Cerimagic and Rabiul Hasan, 2019 ; Rabuzin et al., 2006 ).

Biometric-based identification is often preferred over other methods because a biometric feature cannot be faked, forgotten, or lost, unlike passwords and identification cards ( Prabhakar and Jain, 2002 ; Rudrapal et al., 2012 ). However, the biometric features that are considered should be universal, unique, permanent, measurable, accurate, and acceptable ( Frischholz and Dieckmann, 2000 ). Specifically, ideal biometric features should be permanent and inalterable, and the procedure of gathering features must be inconspicuous and conducted by devices requiring little to no contact. Further, the systems are ideally automated, highly accurate, and operate in real time ( Jain et al., 1999 ). However, no biometric feature to date meets all of the above criteria to be considered ideal, thus, it is important to measure multiple features in order to get the most accurate verification of identity (see Rabuzin et al., 2006 for an overview of all biometric features). Multimodal biometric systems use several biometric traits and technologies at the same time in order to verify the identity of the user ( Rabuzin et al., 2006 ). The multimodal system tends to be more accurate, as combining two or more features improves recognition accurateness ( Cerimagic and Rabiul Hasan, 2019 ).

Fingerprint recognition is one of the most broadly used biometric features as it is a unique identifier ( Aggarwal et al., 2008 ) and has a history of use in many different professional fields, most notably by the police. Additionally, fingerprints have become a commonly used identifier for personal handheld devices like phones. However, the use of fingerprint biometrics for student identification during online examinations can require additional resources such as fingerprint scanners, cellphones equipped with fingerprint technology, or other software at the student’s location, which may limit its current practicality ( Ullah et al., 2012 ). Similarly, face recognition uses image recognition and pattern matching algorithms to authenticate the student’s identity ( Zhao and Ye, 2010 ). This biometric is also good candidate for online exams; however, it may not always be reliable due to the complexity of recognition technology and variability in lighting, facial hair, and facial features ( Agulla et al., 2008 ; Ullah et al., 2012 ).

Audio or voice biometrics are used for speech recognition as well as authentication of the speaker. Human voice can be recognized via an automated system based on speech wave data ( Ullah et al., 2012 ). A voice biometric is highly unique, in fact it is as unique to an individual as a fingerprint ( Rudrapal et al., 2012 ). However, as with facial recognition, varying conditions such as speech speed, environmental noises, and the quality of recording technology may result in unreliable verification ( Ullah et al., 2012 ). Finally, the analysis of an individual’s typing patterns (e.g., error patterns, speed, duration of key presses) can be used to authenticate the user ( Bartlow and Cukic, 2009 ).

Checks for Text Originality

When using assessments that require a written answer, software that checks for the originality of text (such as “TurnItIn”) can help to identify work that was taken from sources without proper citation. With this method, submitted work is compared against other work held in the software’s bank to check for originality. Benefits of this method include being able to compare submitted work against work that is publicly available (as defined by the software company) to check for important degrees of overlap, as well as comparing submitted work against other assignments that have been previously submitted.

Although checking for text originality can be helpful in detecting both accidental and intentional plagiarism, there are concerns about the ethics of this practice, including copyright infringement of student work (e.g., Horovitz, 2008 ). Instructors are typically able to specify within the software whether submitted work will be stored for later comparisons (or not), and this information, along with the broader use policies, should be included specifically in the syllabus or other relevant communications with students. Additionally, when using originality-checking software, it is important to know that high overlap with other works is not necessarily indicative of plagiarized work, and there can be high rates of false positives. For example, submissions with high rates of appropriate references can return a high score for overlap simply because those references are standard across many works. Thus, instructors should refer to the full originality report so that they can use judgment as to whether high scores are actually reflective of plagiarism.

Lockdown Browsers

Lockdown browsers prevent the use of additional electronic materials during exams by blocking students from visiting external websites or using unauthorized applications on the same device as the one being used to take the assessment ( Cote et al., 2016 ). These programs take control of the entire computer system by prohibiting access to the task manager, copy and paste functions, and function keys on that device ( Percival et al., 2008 ). Though likely helpful, lockdown browsers cannot guarantee that external information will not be accessed. Students may still access information using another computer, a cell phone, class notes, etc., during an assessment. In addition to using external material, students may also cheat by making the lockdown browser program inoperative ( Percival et al., 2008 ). For these reasons, it is proposed that these programs should be used in concert with other exam security measures in order to prevent and detect cheating behaviors during exams.

Assessment-Based Methods

Given the financial and logistical concerns that may make cheating detection through online proctoring and other technological solutions unfeasible (e.g. Cluskey et al., 2011 ), and given concerns with privacy and data security, some advocate instead for changes to exam formatting (structure, presentation) that can, in turn, prevent and deter cheating at little cost ( Vachris, 1999 ; Shuey, 2002 ; , 2003 ). Below and in Table 2 , we highlight considerations for both assessment structure and assessment presentation, with particular focus on online exams, that may promote academic integrity behaviors. It is also important to note that many of these considerations are closely related, and many of these work in tandem to facilitate an honest assessment.

TABLE 2 . Preventing cheating and facilitating academic integrity through assessment structure and presentation.

The considerations provided in Table 2 have been discussed at length by other scholars. For example, Cluskey et al. (2011) have proposed online exam control procedures (OECPs), or non-proctor alternatives, to promote academic honesty. These OECPs include: offering exams at one set time, offering an exam for a brief period of time, randomizing the question sequence, presenting only one question at a time, designing the exam to occupy a limited period of time allowed for the exam, allowing access to the exam only one time, requiring the use of a lockdown browser, and changing at least one third of exam questions every term. These methods will likely not eliminate cheating entirely; however, the inclusion of these methods may decrease rates of cheating.

Ideally, online assessments are designed in such a way to reduce academic dishonesty through exam format by reducing the opportunity, incentive/pressure , and the rationalization/attitude for cheating. As discussed previously, the academic fraud triangle posits that all three of these factors lead to academic dishonesty ( Ramos, 2003 ; Becker et al., 2006 ; Varble, 2014 ). Thus, in relation to online exams, minimizing these factors may serve to encourage academic honesty. Though many of the procedures described below work well in tandem, of course, some of these procedures are incompatible with one another; for example, limiting the number of exam attempts may limit the opportunity to cheat, but allowing for multiple exam attempts may reduce the pressure to cheat. We suggest that it is important to consider a balance; cheating prevention methods will be limited in their success if students’ needs or attitudes have not also been addressed with the methods described in Individual- and Institutional-Level Methods .

This paper began by providing a review of current thought regarding the reasons why students may feel motivated to engage in behaviors that violate academic integrity. We approached this question by considering four “levels” from which to consider academic integrity: the student, the institution, the medium of delivery, and the assessment. We suggest that when examining academic integrity in the online environment, it will be necessary for continued research exploring cheating culture and the nature of, and motivation for, cheating on different types of assessments. Further, as shown, research to date has produced mixed findings in relation to whether academic dishonesty may be more or less prevalent in the online environment, and we have called for further research that examines assessment type, field of study, and student demographics (e.g., age and reason for enrolling in the course). In the latter half of this review, we detailed methods for both preventing and detecting cheating behavior, with a focus on online summative assessments. We emphasize again, though, that these methods must be considered in concert with broader consideration of the reasons and motivations that students may engage in academic dishonesty in the first place, and with explicit attention and care to student privacy and fair treatment.

Academic integrity remains an integral element of higher education. The principle values that constitute academic integrity not only uphold the reputation of a university and the value and meaning of the degrees it confers, but they also create a shared framework for professional work that is extended beyond the academy. Thus, as online studies continue to expand in post-secondary education, we believe that it will be important to have evolving scholarship and discussion regarding the maintenance of academic integrity in the online environment.

Author Contributions

All authors conceived of and outlined the project. OH completed the majority of the literature review and wrote the first draft. MN and VK added to the literature review and edited subsequent drafts.

This work was supported by an Insight Grant from the Social Sciences and Humanities Research Council of Canada to VK. MN is the current Undergraduate Chair, and VK was the past Associate Head (Teaching and Learning), of the Department of Psychology at Queen’s University.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Queen’s University is situated on traditional Anishinaabe and Haudenosaunee Territory.

1 As a supplement to this paper, we have made two infographics available via https://osf.io/46eh7/ with a Creative Commons licence allowing reuse and distribution with attribution.

2 Given that the literature reviewed for this paper often uses the terms “academic dishonesty," “departures from academic integrity," and “cheating” interchangeably, this paper will follow this convention and not attempt to distinguish these terms.

3 In typical research conducted on academic dishonesty across online and in-person mediums, researchers define their samples as consisting of “undergraduate” and/or “graduate” students. An important consideration for future research is to specify the age ranges of the sample. It is possible that the frequency and type of cheating behavior by mature, nontraditional students and by traditional students may differ. One might hypothesize that mature students may be less motivated or have fewer opportunities to cheat than traditional students.

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Keywords: academic integrity, academic dishonesty, cheating, online courses, remote teaching

Citation: Holden OL, Norris ME and Kuhlmeier VA (2021) Academic Integrity in Online Assessment: A Research Review. Front. Educ. 6:639814. doi: 10.3389/feduc.2021.639814

Received: 09 December 2020; Accepted: 30 June 2021; Published: 14 July 2021.

Reviewed by:

Copyright © 2021 Holden, Norris and Kuhlmeier. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Valerie A. Kuhlmeier, [email protected]

• Open access
• Published: 15 April 2021

Academic integrity at doctoral level: the influence of the imposter phenomenon and cultural differences on academic writing

• Jennifer Cutri   ORCID: orcid.org/0000-0002-5328-5332 1 ,
• Amar Freya   ORCID: orcid.org/0000-0003-2147-6959 1 ,
• Yeni Karlina   ORCID: orcid.org/0000-0002-6989-2516 1 ,
• Sweta Vijaykumar Patel   ORCID: orcid.org/0000-0002-9363-9262 1 ,
• Mehdi Moharami   ORCID: orcid.org/0000-0001-6435-8501 1 ,
• Shaoru Zeng   ORCID: orcid.org/0000-0001-8884-0968 1 ,
• Elham Manzari   ORCID: orcid.org/0000-0003-2323-5614 1 &
• Lynette Pretorius   ORCID: orcid.org/0000-0002-8998-7686 1  

International Journal for Educational Integrity volume  17 , Article number:  8 ( 2021 ) Cite this article

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This conceptual review seeks to reframe the view of academic integrity as something to be enforced to an academic skill that needs to be developed. The authors highlight how practices within academia create an environment where feelings of inadequacy thrive, leading to behaviours of unintentional academic misconduct. Importantly, this review includes practical suggestions to help educators and higher education institutions support doctoral students’ academic integrity skills. In particular, the authors highlight the importance of explicit academic integrity instruction, support for the development of academic literacy skills, and changes in supervisory practices that encourage student and supervisor reflexivity. Therefore, this review argues that, through the use of these practical strategies, academia can become a space where a culture of academic integrity can flourish.

Introduction

In the contemporary higher education environment, issues of academic integrity and credibility are turning matters of learning into matters of surveillance and enforcement. Increasingly, higher education institutions are relying on text-matching software (such as Turnitin) and the monitoring or scrutiny of students (e.g., through practices such as online proctoring) as a proxy to measure their level of academic integrity (Dawson 2021 ). Indeed, failure to adhere to these often contextually and socially constructed rules of academic integrity is termed academic misconduct or dishonesty and can lead to severe consequences for students. As Dawson ( 2021 ) notes, this approach is adversarial, focussing on detection rather than encouraging academic integrity. This adversarial approach is also reflected in recent changes to Australian federal legislation (see the Prohibiting Academic Cheating Services Act 2020 ), with provision of an academic cheating service now attracting criminal or civil penalties. There is also increasing concern about the “ threats to academic integrity [ …] due to the wide-spread growth of commercial essay services and attempts by criminal actors to entice students into deceptive or fraudulent activity” (Tertiary Education Quality and Standards Agency (TEQSA) 2021 para. 2 emphasis added). Despite this often adversarial language, however, TEQSA also acknowledges that there is a need to promote academic integrity practices by, for example, working with experts to create an Academic Integrity Toolkit (TEQSA 2021 ).

Interestingly, the higher education environment now appears to lead educators to a dichotomous choice to either be “pro-integrity” or “anti-cheating” (Dawson 2021 p. 3). In this conceptual review, we seek to challenge this perception. We focus on how doctoral education programs can foster academic integrity skills development to create an environment where policies and surveillance strategies are incorporated into pedagogical practice. East ( 2009 ) highlights the importance of viewing academic integrity development as a holistic and aligned approach that supports the development of an honest community within the university. Furthermore, Clarence ( 2020 ) argues that doctoral education is underpinned by the axiological belief that graduates should be confident scholars who value integrity in research, authenticity, and ethics. Therefore, it is our argument that it is the responsibility of educators to explicitly teach these skills as part of doctoral education programs in order to encourage a culture of academic integrity among both staff and students (see, for example, Nayak et al. 2015 ; Richards et al. 2016 ). The long-term benefits of such a culture of academic integrity will include greater awareness of academic integrity for both staff and students, the involvement of students in creating and managing their own academic integrity, a reduction in academic integrity breaches, and improved institutional reputations (Richards et al. 2016 ).

Contextualising our review within the Australian higher education setting, our view of academia is representative of an all-encompassing global space which welcomes the skills, knowledge, values, and practices of all scholars regardless of their background. In this review, we highlight how practices within academia create an environment where feelings of inadequacy thrive, leading to behaviours of unintentional academic misconduct. In particular, we explore the impact of the imposter phenomenon and cultural differences on academic integrity practices in doctoral education. We conclude this review by providing practical suggestions to help educators and institutions support doctoral student writing in order to avoid forms of unintentional academic misconduct. Therefore, in this review we argue that, through the use of these practical strategies, academia can become a space where a culture of academic integrity can flourish.

Key concepts in academic integrity

As Bretag ( 2016 ) stresses, definitions of integrity terms matter, as researchers have previously fallen into the trap of synonymously linking concepts together. The notion of academic integrity is multifaceted and complex, so defining the concept is an ongoing and contestable debate amongst researchers (Bretag 2016 ). In general, academic integrity is considered the moral code of academia that involves “a commitment to five fundamental values: honesty, trust, fairness, respect, and responsibility” (International Center for Academic Integrity 2014 p. 16). Therefore, we consider academic integrity as a researcher’s investment in, and commitment to, the values of honesty, trust, fairness, respect, and responsibility in the culture of academia. In this review, we adopt the following interpretation of academic integrity (Exemplary Academic Integrity Project 2013 section 15 para. 2):

Academic integrity means acting with the values of honesty, trust, fairness, respect and responsibility in learning, teaching and research. It is important for students, teachers, researchers and all staff to act in an honest way, be responsible for their actions, and show fairness in every part of their work. Staff should be role models to students. Academic integrity is important for an individual’s and a school’s reputation.

An important component of academic integrity for doctoral students is integrity in the research process. We consider ethical research practice to involve conducting research in a fair, respectful and honest manner, and reporting findings responsibly and honestly.

In contrast, academic misconduct (also termed academic dishonesty) involves behaviours that are contrary to academic integrity, most notably plagiarism, collusion, cheating, and research misconduct. In this review, plagiarism refers to presenting someone else’s published work as your own without appropriate attribution. Drawing on the work of Fatemi and Saito ( 2020 ), we stress that plagiarism can be either intentional or unintentional. We consider intentional plagiarism as purposely using other people’s work and promoting it as your own. In contrast , we define unintentional plagiarism as not acknowledging another researchers’ ideas by, for example, forgetting to insert a reference, not inserting the reference for every sentence from a source, or placing the reference in the wrong place within the text (Fatemi and Saito 2020 ). In this review, collusion is defined as unauthorised collaboration with someone else on assessed tasks while cheating is defined as seeking an unfair advantage in an assessed task, including resubmission of work from another unit. Notably, academic settings have seen a rise in what has been termed contract cheating , where assignments are completed by outside actors in a fee-for-service type arrangement (Bretag et al. 2019 ; Bretag et al. 2020 ; Clarke and Lancaster 2006 ; Dawson 2021 ; Newton 2018 ). Finally, we consider research misconduct to be misrepresenting the study design or methodology, falsifying or fabricating data, and/or breaching ethical research requirements. Academic institutions often have a range of responses, policies, and procedures to identify academic misconduct; these range from official warnings to loss of marks on an assignment or expulsion from the institution for the most severe cases.

Academic integrity and the imposter phenomenon

It is important to note that, for this review, the authors have agreed upon the term imposter phenomenon , although the expression imposter syndrome is often used synonymously in the literature. The term imposter syndrome was initially coined by Clance and Imes ( 1978 ) to describe individuals who felt like frauds and perceived themselves as unworthy of their achievements, despite objective evidence to the contrary. To avoid stigmatisation of these feelings as a pathological syndrome, the term imposter phenomenon is more commonly used in modern thinking. Imposter phenomenon can therefore be defined as “the persistent collection of thoughts, feelings and behaviours that result from the perception of having misrepresented yourself despite objective evidence to the contrary” (Kearns 2015 p. 25).

This notion of feeling like a fraud is frequently experienced by doctoral students. Indeed, half (50.6%) of the PhD students in the study by Van de Velde et al. ( 2019 ) reported experiencing the imposter phenomenon. Similarly, Wilson and Cutri ( 2019 ) revealed how novice academics experienced constant disbelief in their success. This is because the imposter phenomenon is linked to an identity crisis which is commonly experienced by novice academics (Wilson and Cutri 2019 ). For instance, Lau’s ( 2019 ) autoethnographic reflection as a medical doctoral student highlighted how self-imposed pressures during his PhD journey led to feelings of inadequacy. This was due to a prevailing perception of what “the perfect PhD student” was and the feeling that he was not meeting this perceived standard, leading to self-sabotaging behaviours (Lau 2019 p. 52). Thus, from a doctoral student perspective, Lau ( 2019 p. 50) defines the imposter phenomenon as:

feelings of inadequacy experienced by those within academia that indicate a fear of being exposed as a fraud. These feelings are not ascribed to external measures of competence or success (e.g., publishing papers or winning prizes), but internal feelings of not being good enough for their chosen role (e.g., being a PhD student or academic staff member).

Lau ( 2019 ) warns that, if these feelings are left unchecked, it could lead to low self-confidence and high anxiety.

The imposter phenomenon is increasingly recognised as a significant issue by higher education institutions, but this is often considered a mental health concern affecting productivity and success (see, for example, University of Cambridge 2021 ; University of Waterloo 2021 ). It is important to note, though, that the feelings of fraudulence and negative self-confidence can be attributed to the socio-political and cultural environment of academia in which doctoral students are immersed. As Hutchins ( 2015 ) notes, the imposter phenomenon thrives in environments where there are expectations of perfectionism, highly competitive work cultures, and stressful environments. Academia is a high-stakes, competitive environment where a person’s success is measured by the quantity and quality of their research output, commonly referred to as an environment of publish or perish . Indeed, Moosa ( 2018 ) notes that academics must obey the rules of the publish or perish environment if they are to progress through their career. With an emphasis on scholarly dissemination, doctoral students are thrown into a new context of public critique through the peer review and publication process. While this is an opportunity for academics to showcase their research, Parkman ( 2016 ) notes that such public scrutiny invokes the common imposter phenomenon fear of being found out as a fraud. This is because doctoral candidates are constantly exposed to the final product, while the process of writing has been devalued (Wilson and Cutri 2019 ). The doctoral journey, however, should be about the process , as candidates are developing their skills and building their academic identities as future researchers in their fields.

When academic institutions focus on polished products, doctoral students who are currently engaged in the writing process feel a sense they are not good enough (Wilson and Cutri 2019 ). This is because the writing process and expectations at doctoral level are complex and challenging, requiring students to develop specific academic skill sets that are different from their previous studies (see Level 10 of the Australian Qualifications Framework for a list of the expected skills of doctoral graduates in Australia, Australian Qualifications Framework Council 2013 ). Facing these new challenges can be overwhelming and students compensate by engaging in sabotaging behaviours (such as procrastination, perfectionism, or avoidance) because they feel they must write like the experts in their field. Cisco ( 2020a ) found that imposter phenomenon feelings became more prevalent with the challenge of these new and more complex academic tasks. This struggle during the reading and writing process can be attributed to a need for further development of the necessary academic literacy skills for a specific discipline. In this review, we consider literacy to refer to the socially constructed use of language within a particular context (Barton and Hamilton 2012 ; Lea 2004 ; Lea and Street 1998 , 2006 ; Street 1984 , 1994 ). Consequently, it is important to note that literacy is continuously constructed and includes elements of both power and privilege (Lea 2004 ; Lea and Street 1998 , 2006 ). The term academic literacy skills , therefore, reflect a broad range of practices that are involved in the practice of communicating scholarly research (for example, learning the differences in academic writing for literature reviews, methodology, data analysis, and discussion of findings sections to answer the all-important so what question). These more advanced academic literacy skills are relatively new aspects for doctoral students, as the production of new knowledge is what makes a PhD candidature unique.

When doctoral students commence their studies, they transfer their prior understandings regarding appropriate academic conduct. Students enter doctoral training programs through a variety of pathways. For example, some students enter a PhD after completing an Honours degree, while others first complete a Masters or other graduate research degree. Increasingly, doctoral programs are also seeing students who return to study after several years away from university. Hence, students who enter doctoral studies, regardless of their prior educational experience, bring their discourses of academic understanding and what they perceive as appropriate with them.

It is likely that doctoral students have, at some point in their studies, encountered the concept of academic integrity at some level. While students may have encountered the concept of academic integrity in the past, this previous knowledge does not necessarily translate into an understanding of how to demonstrate academic integrity in their work at a doctoral level. There are also institutional and cultural differences that play a significant part in how academic integrity is applied in practice. Understanding how to apply this academic integrity knowledge in academic writing practice should, therefore, be considered a threshold concept – it is a concept which, when understood, leads to a permanent change of perspective (see Meyer and Land 2006 ). Pretorius and Ford ( 2017 ) describe threshold concepts as “gatekeepers to deeper knowledge, understanding and thinking [ …] that allow students to genuinely see new perspectives and think in different ways” (p. 151). Tyndall et al. ( 2019 ) notes that if doctoral students do not move across the threshold to understand how to apply academic integrity in their writing, it can lead to academic misconduct behaviours including mimicry and plagiarism.

Mimicking the sophisticated genre of academic writing seen in published works is often done in an effort to sound academic . The disciplinary discourse in which a person finds themselves contributes to the social construction of identity (Ivanič 1998 ). Furthermore, a person’s identity is inscribed in their writing practices (Ivanič 1998 ) – we write ourselves into our text as we interact with the social context in which we find ourselves. Ivanič ( 1998 ) notes that this discursive identity construction provides a useful lens through which to view academic integrity. Instead of condemning students for academic integrity breaches such as plagiarism, Ivanič ( 1998 ) argues that this type of behaviour can be seen as a function of “students’ struggles to achieve membership of the academic discourse community” (p. 197). For example, Fatemi and Saito ( 2020 ) note that, in the absence of appropriate academic literacy skills, postgraduate students can engage in what Howard ( 1992 ) termed patchwriting (i.e., poor paraphrasing, also termed source-reliant composition) where some words are synonymously replaced while the original sentence structure is maintained. While such an action is deemed as plagiarism, the students’ intentions are usually not to cheat but rather to try and write in what they perceive to be an academic style (Fatemi and Saito 2020 ; Pecorari 2003 ). Consequently, if doctoral students, engage in a form of academic misconduct other than contract cheating, we argue this is a form of unintentional academic dishonesty.

We have developed a model to highlight how the imposter phenomenon influences doctoral students’ academic integrity which we have termed the IPAIR model (the imposter phenomenon and academic integrity relationship model, see Fig.  1 ). We argue that feelings of being discovered as a fraud lead students to mimic academic practices, including textual plagiarism, academic dishonesty, and research misconduct (Fig. 1 ). The first component of this model, textual plagiarism , involves taking credit for another person’s published work without referencing the source, by providing inaccurate citation details, or by engaging in poor paraphrasing such as patchwriting. The second component, academic dishonesty , consist of the other elements of academic misconduct such as reusing previous work, collusion, and contract cheating. The final component of our model, research misconduct , includes misrepresenting the study design or methodology, falsifying or fabricating data, and breaching ethical requirements. It is important to note that the academic integrity breaches in our model are not necessarily intentional. Furthermore, it should be noted that the forms of academic misconduct highlighted in our model would also likely further exacerbate doctoral students’ feelings of inadequacy.

The Imposter Phenomenon and Academic Integrity (IPAIR) Model

Academic integrity and cultural differences

We have argued that there is a relationship between the imposter phenomenon and academic integrity in relation to doctoral student writing. We further contend that cultural differences may impact academic integrity during a doctoral student’s candidature. In Australia, domestic and international students from a wide variety of cultural backgrounds study PhDs (see, for example, Cutri and Pretorius 2019 ; Pretorius and Macaulay 2021 ). In this paper we define a domestic student as someone who is an Australian or New Zealand citizen, or who holds a permanent residency or humanitarian visa. The term international student refers to someone who has a temporary visa to study in Australia. It is important to note that, in using the terms domestic and international , we do not intend to create a dichotomy between these student cohorts. Rather, these two terms can be considered representative of the often-times different sociocultural characteristics and power relationships that influence these students’ experiences (Cutri and Pretorius 2019 ; Pretorius and Macaulay 2021 ). It is also important to note that cultural differences exist between domestic students as well.

Today’s contemporary research context reflects a globalised academic landscape comprising expert, early career, and novice academics. The increase of internationally diverse doctoral scholars can be attributed to the process of globalisation (Cutri and Pretorius 2019 ). For this review, we have chosen to draw upon Holton’s ( 2005 ) definition of globalisation: “the intensified movement of goods, money, technology, information, people, ideas and cultural practice across political and cultural boundaries” (pp. 14–15). Globalisation has impacted higher education through an increased movement of international students which has also resulted in a higher number of international doctoral students enrolling at higher education institutions (Cutri and Pretorius 2019 ; Marginson and van der Wende 2007 ; Nerad 2010 ). In fact, many universities promote the mobility of higher education and offer scholarships for people around the world to continue their studies. This has led to the emergence of various cultural differences in expectations and understandings of academic integrity causing universities to reconsider their academic integrity practices and support structures for students.

Importantly, globalised movements describe not only people migrating from one country to another but also the movement of people’s ideas, beliefs and culture (see, for example, Appadurai 1990 ). Culture offers a lens through which people see and understand the world in which they live (Garcia and Dominguez 1997 ). Hence, culture includes “shared values, beliefs, perceptions ideals, and assumptions about life that guide specific behaviour” (Garcia and Dominguez 1997 p. 627). Hofstede et al. ( 2010 ) state that culture programs people’s behaviour, reaction and understanding and thus call it the “software of the mind” (p. 5). Culture is dynamic, persists over time, and, therefore, guides an individual’s capacity to make meaning of their world and experiences (Garcia and Dominguez 1997 ). Most importantly, Bourdieu ( 1984 ) argues that people can be unaware of their own cultural influences and how it shapes their decisions. Thus, the cultural practices, values and beliefs guiding an individual’s decisions appear natural and intuitive, but are in fact culturally driven. Consequently, culture plays a crucial role in influencing and guiding an individual’s decisions and meaning making capacity.

Cultural difference can be a leading cause for academic dishonesty amongst international postgraduate students as academic integrity has different definitions for different cultures (Velliaris and Breen 2016 ). This highlights that international postgraduate students may have different standards of academic integrity and plagiarism than the domestic students at their host universities. Students bring their pre-existing beliefs into academia while they, at the same time, grapple with newly formed expectations to be experts in their fields (see, for example, Cutri 2019 ). Indeed, as authors of this literature review, we found that we had several different pre-existing beliefs of academic integrity due to our own cultural backgrounds. For example, one of the authors of this literature review notes:

While in Australia, especially in doctoral studies, one of the key functions of an academic is to contribute to knowledge by identifying and filling gaps in existing knowledge. This requires advanced yet complex skills in reading existing literature, questioning the ontological and epistemological existence of knowledge along with arguing or critiquing studies respectfully. As an individual, who has experienced the [education system in my country] that worship textbooks, I find it extremely challenging to critique other studies and fail to recognise the limitations in the findings, methodology or methods employed in the study. Culturally, this practice of reviewing other academics work and addressing the limitations and gaps was not preached, experienced or expected. Therefore, I tend to use a lot of direct quotes from original writing.

As highlighted above, an array of cultural differences exists in understanding academic integrity. These differences in academic expectations can be wide-reaching, including a lack of language proficiency, as well as an unfamiliarity with the myriad of research and writing practices of their host universities (Cisco 2020a ; Fatemi and Saito 2020 ). These differences can negatively affect postgraduate international students’ transition into academia, potentially leading to academic dishonesty (Fatemi and Saito 2020 ). It is, therefore, hardly surprising that Bretag et al. ( 2014 ) found that international students received three times more formal notifications of academic integrity breaches compared with domestic students. International students were also more than twice as likely to report feeling ill-prepared to avoid academic integrity breaches (Bretag et al. 2014 ).

Another factor resulting in a lack of academic integrity from international doctoral students is believed to be the lack of academic support for these students (Fatemi and Saito 2020 ). The transition from their home country’s academic integrity practices to those of their host country can also mean that not all skills brought by international postgraduate students are recognised by the host university. The transfer between one educational system to another combined with a lack of familiarity with the local academic integrity practices can result in unintentional academic dishonesty by international students (Fatemi and Saito 2020 ). Without appropriate support to develop academic skills from their universities, postgraduate international students can develop negative opinions about host countries and feel that their prior academic skills are devalued. It is, therefore, imperative that international postgraduate students adapt to local academic integrity practices with the support of universities. It is equally vital that local universities honour and value the pre-existing skills and beliefs of doctoral students and assist these students with building a new set of academic integrity practices.

Building academic integrity at a doctoral level

In the previous sections, we have highlighted the influence of the impostor phenomenon, a lack of academic literacy skills, and cultural differences on the academic integrity practices of doctoral students. Based on these factors, this section explores the multifaceted measures that could be put in place to better support doctoral students in developing academic integrity in their research and writing practices. In particular, we highlight the importance of explicit academic integrity instruction, support for academic literacy development, and changes in supervisory practices.

Explicit academic integrity instruction

The key to improved academic integrity practices at any level of study is the understanding of appropriate conventions in the discipline. Once PhD students are enrolled in their studies, many Australian universities provide mandatory training components related to academic integrity in research. At our institution, for example, all doctoral students are required to complete three online doctoral induction models that cover an introduction to the University, the Faculty, and research integrity. Across institutions, however, research integrity training is offered in a variety of formats and are focussed on many different areas of research ethics. Furthermore, there appears to be a presumption that, upon completion of these modules, doctoral students will understand their responsibilities and, therefore, not engage in academic misconduct. We argue that this presumption is dangerous and that doctoral students require ongoing scaffolding and skills development throughout their candidature. Furthermore, as highlighted in our model (see Fig. 1 ), research integrity involves a specific skill set. A lack of understanding of this skill set can lead to academic misconduct if students are not adequately supported. Löfström and Pyhältö ( 2017 ) highlight that doctoral students rely on their supervisors and faculty colleagues to help learn ethical guidelines and appropriate codes of conduct. By acknowledging that doctoral students unintentionally engage in academic misconduct due to a lack of awareness, universities can offer supportive structures and educational programs to help foster a deeper understanding of the impact of the imposter phenomenon, academic literacy skills, and ethical research approaches.

Bretag et al. ( 2014 ) highlight that postgraduate research students can be disadvantaged in terms of education, training, and support for academic integrity. This calls for institutions to provide interventions in the form of direct instruction at different stages of a doctoral program. Gullifer and Tyson ( 2014 ) have highlighted the need for universities to take proactive steps by offering formal workshops that highlight the expectations and strategies to maintain academic integrity rather than expecting students to read academic integrity policies. Fatemi and Saito ( 2020 ) have also called for a more standardised approach to teaching academic integrity, including attention to the practical skills associated with citation, paraphrasing, and summarising. The skill of referencing is usually taught at the undergraduate level, so there is often the expectation that postgraduate students have acquired this knowledge in their undergraduate studies and are consequently able to reference correctly. However, a lack of awareness can be attributed to several factors, such as changing disciplinary or cultural conventions. A more nuanced understanding of referencing conventions should, therefore, be explicitly taught, particularly at the start of a doctoral student’s candidature.

Academic integrity software can also be used in a more educative manner to help scaffold students’ understanding. In our Faculty, for example, the text-matching software Turnitin is used to help doctoral students improve their approaches to academic integrity prior to submission of written work to their supervisors, academic publishers, or thesis examiners. This practice version of a Turnitin dropbox emphasises the use of the software as a learning tool, rather than a surveillance strategy, enabling students to discover where they have engaged in poor paraphrasing. While anecdotal, our experience seems to indicate that this approach, in conjunction with educational videos, tutorials, and educator guidance, can scaffold doctoral students’ understanding of academic integrity according to disciplinary conventions. This form of explicit instruction can be provided throughout a student’s doctoral journey, in order to raise an awareness of academic integrity practices as well as lay a solid foundation for the student’s future study and career.

Another consideration is that doctoral students may come from a different cultural academic context where different writing practices are valued. In designing and implementing these interventions, we consequently argue that academic integrity training should not only target the implementation of research integrity codes from above (Sarauw et al. 2019 ). We believe that the training should also be a site for doctoral students to negotiate, question, and affirm institutional codes in order to develop their individual reflexivity and responsibility as junior academics (Sarauw et al. 2019 ). By allowing reflection on professional practice, educators and supervisors will provide a space for doctoral students to discover and apply appropriate integrity practices. It is also important to note that, as Hyytinen and Löfström ( 2017 ) highlight, academic staff may also require pedagogical training on how to effectively teach research integrity and ethics. Targeting these interventions at both institutional and individual levels could help to create an institution which supports, facilitates, and provides a conducive environment for academic integrity where reflexive and responsible researchers can flourish.

Support for academic literacy development

Building confidence in writing ability by modelling the writing process is an important way to scaffold academic integrity for PhD students. Fatemi and Saito ( 2020 ) noted that a lack of self-confidence and lack of knowledge in relation to academic literacy skills were key causes of plagiarism. Cisco ( 2020b ) also reported that literacy interventions that target academic and disciplinary literacy, in addition to reading and writing academic texts, can help doctoral students develop the academic skill set required to thrive in academia. Emerson et al. ( 2005 ) highlighted that a lack of academic integrity in students’ writing is often a consequence of a lack of understanding of the academic writing process. Experienced academic writers, however, realise that academic writing is indeed a process (Wilson and Cutri 2019 ). For instance, manuscripts often undergo multiple revisions and significant editing prior to submission for publication. Peer review then leads to further changes before final publication. Modelling this process for students can be an eye-opening experience, helping students overcome some of the feelings associated with writing anxiety and the imposter phenomenon (see, for example, the experiences of Lam et al. 2019 ).

Consequently, we advocate for the establishment of learning communities such as writing groups. Doctoral writing groups offer a safe and low-risk environment where students can build their academic writing skills in a peer learning environment (Aitchison and Guerin 2014 ; Cahusac de Caux et al. 2017 ). It has been shown that the peer feedback component of these types of writing groups helps students to build their writing confidence, foster greater reflective practice, and encourage them to take ownership of their writing style (Cahusac de Caux et al. 2017 ; Lam et al. 2019 ). Encouraging doctoral students to join, or indeed set up their own, learning communities could, therefore, significantly improve students overall learning experience during their candidature. It is important to note, however, that students often tend to seek peer support from fellow students who come from a similar cultural or linguistic background. Accordingly, it is important to consider how the benefits of writing groups with members from a variety of backgrounds and perspectives can be best showcased to students.

Changes in supervisory practices

We believe that the supervision process should enable students to develop their academic integrity. The role of a research supervisor is crucial in doctoral students’ academic endeavours. Supervision entails an enculturation function in which students are encouraged to be a member of the disciplinary community in academia through role-modelling and apprenticeship (Lee and Murray 2015 ). This can be achieved through exposure to exemplary texts to analyse, encouragement for students to produce their own texts based on these exemplars, and provision of advice and constructive feedback on students’ writing.

In addition, supervision should also enable emancipation where students are encouraged to develop and question themselves and their motivation in writing (Lee and Murray 2015 ). This aspect is particularly important, as a doctoral student’s identity changes during the writing process (Clarence 2020 ; Cotterall 2011 ). Supervisors should, therefore, motivate students to reconceptualise writing not just as a method of completing a thesis, but also as a learning process. As noted by Pretorius ( 2019 p. 5),

the doctoral journey is more than just a three- to four-year timeframe where a student eventually submits a thesis as evidence of the creation of new knowledge. Rather, the doctoral experience incorporates a variety of opportunities for more in-depth personal development, particularly in terms of intrapersonal wellbeing, academic identity and sense of agency, as well as intercultural competence.

To facilitate this more in-depth personal development, writing tasks from supervisors should be more diverse. This is in line with postmodern scholars’ conception of writing as a method of inquiry (Richardson 2000 ; Richardson and St. Pierre 2005 ; St. Pierre 1997 ). Writing can be a method of self-discovery to explore doctoral students’ deepest desires in undertaking their doctoral projects and consequently their motivation in writing. Pretorius and Cutri ( 2019 ) provide a framework for doctoral student reflection based on the “What? So What? Now What” reflective practice model (see also Driscoll 2000 ; Rolfe et al. 2001 ) that can help doctoral students explore their experiences during their doctoral candidature. As guiding prompts to write about their writing process, Fernsten and Reda ( 2011 ) have also provided 35 questions that can help doctoral students become reflexive writers who can critically identify problems with their writing and texts. This shift to a more reflective approach can reduce writing anxiety because, instead of viewing writing as a high-stakes activity, writing is conceptualised as thinking, analysis, and as “a seductive and tangled method of discovery” (Richardson and St. Pierre 2005 p. 1423).

In this conceptual literature review, we have explored the key factors that are associated with academic integrity in doctoral education. We argue throughout this article that academic misconduct within doctoral studies is underpinned by two significant factors: the imposter phenomenon and cultural differences. Facing these challenges can be overwhelming for doctoral students, which we argue can lead to unintentional academic misconduct. We, therefore, emphasise that approaches ensuring academic integrity do not need to be adversarial or geared towards merely surveillance and punishment. Rather, an educative approach can help to create a culture of academic integrity in the doctoral education setting. We provide practical suggestions to help institutions support doctoral student writing in order to avoid unintentional academic misconduct. In particular, we highlight the importance of explicit academic integrity instruction, support for the development of academic literacy skills, and changes in supervisory practices that encourage student and supervisor reflexivity. We argue that, through the use of these practical strategies, academia can become a space where a culture of academic integrity can flourish.

Availability of data and materials

This literature review is based on analyses of published peer-reviewed research using standard word processing, annotation, and referencing software. No additional data were collected or analysed. No custom software or codes were used to conduct analyses.

Abbreviations

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Acknowledgements

The authors would like to thank Prasadi Hatanwila for helpful discussions during the development of this manuscript.

Notes on Contributors

Jennifer Cutri

Email: [email protected]

https://orcid.org/0000-0002-5328-5332

Twitter: @jenni_cutri

Jennifer Cutri is a current PhD student in the Faculty of Education at Monash University in Australia. She holds qualifications in Primary Education and Literacy Support. She has worked as a teacher and researcher across schools in Australia and Hong Kong. Jennifer teaches undergraduate and postgraduate students. Her interests involve international education and teacher and learner identity development within intercultural contexts.

Email: [email protected]

https://orcid.org/0000-0003-2147-6959

Twitter: @DrAmarFreya

Dr. Amar Freya recently completed their PhD in which they examined how the experiences of family violence in the Indian-Australian community are understood and how victim survivors seek formal and informal help from More Knowledgeable Others. Amar is passionate about ending gender-based violence and their interests involve research and policy surrounding gender-based violence, intersectionality, gender performativity and promoting a lived experience framework with a particular focus on honouring victim survivors' stories.

Yeni Karlina

Email: [email protected]

https://orcid.org/0000-0002-6989-2516

Twitter: @hey_yeniii

Yeni Karlina is a PhD candidate in the Faculty of Education at Monash University in Australia. She has worked as an English teacher, research assistant, and teacher educator in Indonesia. Her PhD project is on how English teachers’ professional learning experiences in a standardised teacher education program in Indonesia influence their teaching practices and identity development.

Sweta Vijaykumar Patel

Email: [email protected]

https://orcid.org/0000-0002-9363-9262

Twitter: @SwetaVijaykumar

Sweta Vijaykumar Patel is a PhD candidate in the Faculty of Education at Monash University in Australia. She is a kindergarten teacher and holds qualifications in Early Childhood Education. Sweta has worked in the field of Early Childhood Education in various capacities in both India and Australia. Currently, Sweta teaches undergraduate students and her research interests involve immigrant educators, as well as culture and pedagogy in diverse early childhood education contexts.

Mehdi Moharami

Email: [email protected]

https://orcid.org/0000-0001-6435-8501

Twitter: @MoharamiMehdi

Mehdi Moharami is a PhD candidate in the Faculty of Education at Monash University in Australia. He holds qualifications in English Translation and Teaching English. He researches the social and cultural impacts of learning English on learners’ identity negotiation and his areas of interest include language education, culture, identity, and social practices.

Shaoru Zeng

Email: [email protected]

https://orcid.org/0000-0001-8884-0968

Shaoru Zeng is a PhD candidate in the Faculty of Education at Monash University in Australia. She works as a research assistant and a teacher who teaches students from early childhood to secondary school in Australia. She has a qualification in Education and her research interests include the Australian Curriculum, the International Baccalaureate, as well as Asia studies.

Elham Manzari

Email: [email protected]

https://orcid.org/0000-0003-2323-5614

Twitter: @elliemanzari

Elham Manzari is a PhD candidate in the Faculty of Education at Monash University in Australia. She holds qualifications in Education and TESOL and has worked as an IB MYP curriculum director. Elham teaches undergraduate students at Monash University and her research interests include digital technologies in teaching and curriculum, digital sociology, and the philosophy of technology.

Dr Lynette Pretorius

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https://orcid.org/0000-0002-8998-7686

Twitter: @dr_lpretorius

Dr. Lynette Pretorius is the Academic Language and Literacy Advisor for the Faculty of Education at Monash University in Australia. She works with undergraduate, postgraduate, and graduate research students to improve their academic language and literacy skills. She has qualifications in Medicine, Science, Education, as well as Counselling, and her research interests include doctoral education, wellbeing, experiential learning, and reflective practice.

The authors did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors for the preparation or publication of this literature review. Amar Freya received a Monash Graduate Scholarship (Research Training Program) to support their PhD studies. Jennifer Cutri and Sweta Vijaykumar Patel received the Centenary Education Grant from the Graduate Women Victoria Scholarship Program to support their PhD studies. Yeni Karlina, Mehdi Moharami, and Elham Manzari received the Monash Graduate Scholarship and the Monash International Postgraduate Research Scholarship to support their PhD studies.

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Jennifer Cutri, Amar Freya, Yeni Karlina, Sweta Vijaykumar Patel, Mehdi Moharami, Shaoru Zeng, and Elham Manzari contributed to the collection, analysis, and synthesis of literature, as well as manuscript preparation, review, and editing. Dr. Lynette Pretorius conceptualized the research project, contributed to the collection, analysis, and synthesis of literature, administered and supervised the research project, validated the data analyses, developed the visualization used in the manuscript, as well as contributed to manuscript preparation, review, and editing. All authors read and approved the final manuscript.

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Cutri, J., Freya, A., Karlina, Y. et al. Academic integrity at doctoral level: the influence of the imposter phenomenon and cultural differences on academic writing. Int J Educ Integr 17 , 8 (2021). https://doi.org/10.1007/s40979-021-00074-w

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A literature review was conducted in order to study academic integrity in e-assessment. The research questions relate firstly to the prevalence of incidents that violate academic integrity and secondly to the countermeasures for addressing the challenges. In regard to prevalence, we found that e-cheating may not be as common as believed. In regard to countermeasures, we found that there are a lot of technical means to address the violations, but since technical countermeasures cannot fully ensure academic integrity, a long-term strategy should aim to redesign the learning process and to use alternative assessment methods.

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Tsigaros, T., Fesakis, G. (2021). E-assessment and Academic Integrity: A Literature Review. In: Reis, A., Barroso, J., Lopes, J.B., Mikropoulos, T., Fan, CW. (eds) Technology and Innovation in Learning, Teaching and Education. TECH-EDU 2020. Communications in Computer and Information Science, vol 1384. Springer, Cham. https://doi.org/10.1007/978-3-030-73988-1_24

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Student Perceptions of Academic Integrity: A Qualitative Study of Understanding, Consequences, and Impact

School of Psychology, University of East London, Stratford, E15 4LZ UK

Academic integrity (AI) is of increasing importance in higher education. At the same time, students are becoming more consumer-oriented and more inclined to appeal against, or complain about, a penalty imposed for a breach of AI. This combination of factors places pressure on institutions of higher education to handle alleged breaches of AI in a way acceptable to students that motivates them to continue to engage with their studies.

Students (n = 8) were interviewed to discover their perceptions of the process for dealing with breaches of AI. All students were based in one university in a very diverse area of London which has many first-generation students from non-traditional academic backgrounds.

Students reported strong emotional reactions featuring high levels of anxiety and stress. Some found the process to be threatening and demotivating and questioned continuation on their course of study, while others used more adaptive coping strategies. Students also went to great pains to make it clear that their own, and their friends’, breaches of AI were unintentional, while expressing the view that other people were deliberately cheating and should be penalised.

Key recommendations include: support for students to re-engage after the intervention; support for students to develop effective self-regulatory learning strategies and time management; provision of specific examples to clarify what is, and is not, acceptable academic practice; recognition of the strong emotions likely to be invoked, especially if accompanied by declarations of unintentionality.

Introduction

Maintaining academic integrity is a serious issue in higher education. Institutional leaders and other academic staff are concerned about the threat to the public welfare of graduates entering the professions without the skills and knowledge their degree award would suggest and the consequent damage to the reputation of higher education in general (QAA-HE, 2020 ). If academic integrity cannot be assumed then the qualifications issued by an institution have less value, as the skills, competencies, and knowledge of graduates cannot be relied on. Academic integrity can be defined as the commitment to uphold the key principles of responsibility, respect, and fairness, on the part of the academic community (e.g., International Center for Academic Integrity, 2021 ). This definition includes students, for whom observing the values of academic integrity is a part of their becoming members of the academic community.

The recent widespread move to online learning has led to increased opportunities for breaches of academic integrity (e.g., Bretag et al., 2019 ; Curtis & Clare, 2017 ; Holden et al., 2021 ). The extent of breaches of academic integrity is shown by studies in which the majority of students engaged in some form of academic dishonesty at institutions in Canada (Ternes et al., 2019 ), Sweden (Trost, 2009 ), and Australia (Brimble & Stevenson-Clarke, 2005 ). At the same time, students are becoming more aware of their power as consumers (Raaper, 2020 ) and more aware of their levels of student debt (Callender & de Gayardon, 2021 ) and may be more inclined to appeal or to withdraw from their course if they are penalised for breach of academic integrity (Delucchi & Korgen, 2002 ). The challenge to institutions of higher education is how to protect the integrity of their degrees while retaining and motivating students. In response to this challenge, the present study focused on students’ views of institutional responses to identified breaches of academic integrity (AI) at a university in London, UK.

Students’ understanding of AI was an important focus of the present research. Previous research has suggested that students may not be fully able to identify instances of plagiarism. For example, Bretag et al. ( 2014 ) in a study of over 15,000 students, reported that students would benefit from more support to enhance their understanding of the rules. The results of other studies similarly indicate that students may plagiarise because they do not fully understand what plagiarism is (e.g., Busch & Bilgin, 2014 ; Chen & Chou, 2017 ).

Another important focus was students’ perceptions of the process for dealing with breaches of academic integrity. Sustained motivation and engagement in students could depend on their confidence in the process and acceptance of the outcomes. A warning comes from Newton ( 2016 ) who reported students’ views that breaches of AI should be penalised to a lesser degree than was the case in their institution, for example, if the institution recommended failing the module, the student might recommend a mark reduction or failing the single assessment. Gullifer and Tyson ( 2004 ) similarly reported that students in their study found the penalties too severe in the absence of deliberate intent. Students in the present study were explicitly asked if they thought the outcomes were fair.

Previous experience has suggested that students can experience a range of strong emotions during the process for dealing with breaches of AI, so the interviews were designed to allow students to express their emotions. This may be especially true for students who are sensitive to punishment (e.g., Carver & White, 1994 ). Protestations of innocence are common, and while no explicit question was asked, students were given the opportunity to claim unintentionality. Relevant to this, the ‘fundamental attribution error’ states that one’s own actions, especially misconduct, are likely to be attributed to the circumstances and situation (Ross, 1977 ; Gilovich, 2022 ). Thus, an individual student whose work is deemed to be in breach of AI may insist that it was a genuine mistake, perhaps exacerbated by time pressure.

Considerable observation by the author suggests that students have different coping styles. The basic two coping styles proposed by Lazarus and Folkman ( 1984 ) were problem-focused and emotion-focused; avoidance-focused was added by Ben-Zur ( 2009 ). The problem-focused or task-focused style is considered to be an adaptive coping style (Valenti & Faraci, 2021 ) and is associated with academic success. Observation suggests that some students employ an adaptive style, engaging positively with the process, and learning valuable lessons. Other students show a lack of willingness to engage, suggesting an avoidance-focus, or display resentment and denial, suggesting an emotion-focus. It was expected that students would display different coping styles in their interviews.

The present study was conducted in an institution of higher education based in an ethnically diverse part of London, UK, with a high proportion of mature students and first-generation students. The study was designed to discover students’ understanding of AI, their experiences of the process for dealing with breaches of AI, and their interpretation of these experiences. The process for dealing with breaches of AI has two main stages in which the student is involved: the initial email to the student informing them of the allegation, and a meeting with academic members of staff to explain the problem and offer guidance on avoiding a repetition. Both the views of students who have been through the process, and those who have not, were sought, to provide a more complete understanding. Interpretative Phenomenological Analysis was chosen as an appropriate method for exploring the personal experiences of participants and the meanings they attach to events.

Interpretative Phenomenological Analysis (IPA) was chosen as the analytical method because of its suitability to answer the questions addressed in the research. The key concepts of IPA are exploring the lived experiences of participants and understanding how they interpret their experiences. The interview allows a bond to be formed with the interviewer which facilitates the exchange of personal information. The interview process is oriented around the participant and allows them to freely express themselves as they see fit (Alase, 2017 ). IPA permits the understanding and description of subjective, personal experiences and attitudes. IPA thus reflects a critical realist epistemology, accepting that the knowledge generated is not a direct account of reality but is an interpretation of a version of reality presented at a particular time and place. IPA allows the discovery of interactions between the individuals and the social and academic structures in which they are embedded.

The role of the researcher is to make sense of the participant’s account of their experiences, understanding that people are “self-interpreting beings” actively seeking to make sense of their experiences. IPA is an inductive approach, starting from a bottom-up analysis of the data to extract themes from the data. When analysing an individual's lived experience, IPA is useful as it enables the investigation of complicated issues (Smith & Osborn, 2003 ).

In the present study, the assumption was made that students hold consistent and sufficiently stable attitudes towards AI and experiences of the system for dealing with breaches of AI. At the same time, it is acknowledged that the means of gaining access to these attitudes and experiences are imperfect and necessarily limited. The researchers acknowledge their role in creating knowledge in a reflexive process. One of the interviewers had been through a breach of AI process and so had personal experience, enabling her to interact in a sympathetic and understanding way with participants. The other had not and so approached her interviews with an open mind.

The lead researcher was a member of academic staff responsible for the detection of breaches of academic integrity and for application of appropriate remedies. All contact with participants was through the two student interviewers so the lead researcher had no knowledge of, or contact with, the participants. The researchers were aware of the power imbalance within the interview process (Anyan, 2013 ) therefore no student with a breach was interviewed by someone known to them.

It is important in IPA to represent the diversity of the target population. In the present research, some participants had been through the formal process for dealing with a breach of Academic Integrity regulations while others had not. This enabled the researchers to access the views of participants from various perspectives. Those participants who had not been through the process of dealing with a breach could contribute their views about the education and guidance offered to them; could describe their understanding of AI; and could discuss their knowledge of and use of support services. They could also describe and interpret their feelings about AI and any anxiety at the prospect of a breach or its consequences. Those participants who had been through the process could contribute all this information and in addition discuss their experiences of the process and their reactions to it; how it affected their motivation and engagement; and their views on the fairness of the process and penalties.

A sample size of 8 is considered to be adequate for IPA (e.g., Hefferon & Gil-Rodriguez, 2011 ; Smith & Osborn, 2003 ). The participants were from two schools within the same institution and represented a range of age, gender, and ethnicity. All were first-generation students.

The research used semi-structured interviews to offer commonality of approach while allowing for interesting lines of discussion to be followed up. Open-ended questions were asked as generally recommended (Smith & Osborn, 2003 ) along with probe questions to encourage the participants to express themselves and provide longer answers. The interview schedule was created by the lead researcher and evolved in discussion with the two interviewers. The interviews lasted approximately 30 min, were conducted online in accordance with restrictions imposed due to the covid-19 pandemic and were recorded on Microsoft Teams. The initial automated transcription contained some errors and so it was supplemented and corrected by the interviewer.

IPA was used to analyse the interviews following the method of Smith and Osborn ( 2003 ) and guidance from Braun and Clarke ( 2006 ). In the first step, the transcripts were read several times to gain familiarity and understanding of common thoughts, feelings, and reactions. In the second step, initial codes were developed and noted alongside the corresponding passages of the transcripts. In the third step, codes were grouped into larger themes based on similarity and conceptual fit, and the themes were allocated tentative names. In the fourth step, the process of grouping codes into themes was consolidated over the set of interviews. In the fifth step, a table of themes was created, with each theme illustrated by extracts from the transcripts. At this stage some codes were dropped or moved to a different theme. In the sixth and final step, the superordinate themes were documented as a narrative account.

Participants

The characteristics of the participants are documented in Table ​ Table1. 1 . The presence of dependent children was included because it was potentially relevant to issues of time pressures and competing priorities experienced by some students. All participants were first-generation students. The participants are labelled sequentially from A to H and the second letter Y or N indicates whether they had experienced a breach of AI or not. All the breaches were a first occasion for the student.

Participant characteristics

The terms “Black” and “White” are used as categories of ethnicity in line with the UK census that uses these terms. Participants selected these terms to identify their ethnicity

The study was approved by the institution’s ethical review board. Participants were volunteers and were not paid for their participation. They were assured of their right to withdraw at any point, to withdraw their data, and that their participation would be entirely confidential and anonymous. Participants were not obliged to answer any question. If the participant became emotional during the interview they were asked if they would like to take a break and the interviewer checked that the participant was happy to continue. At the end of the interview, participants were referred to support services inside and outside the institution.

Results and Analysis

Five superordinate themes were developed: Emotion, Intentionality, Understanding, Fairness, and Self-regulation. These bear some resemblance to the themes reported by previous researchers, for example, the emotion of fear, poor understanding of AI, and unhappiness with the process and consequences (Gullifer & Tyson, 2004 ) though with additional sub-themes not found in the earlier literature.

Each of these has interconnected sub-themes that collectively define and describe the superordinate theme. The first superordinate theme of Emotion has sub-themes of anxiety, shock, intimidation, catastrophising, and demotivation vs. relief. The second theme of Intentionality had sub-themes of unintentional breach of AI by the self, intentional breach by other students, and self-presentation. The third theme, Understanding addressed the quality of understanding of AI. The fourth theme of Fairness considered perceptions of procedural fairness and the appropriateness of the penalty. The fifth theme of Self-Regulation encompasses sub-themes of engaging with support and coping styles.

Theme 1: Emotion

All the interviewees mentioned experiencing strong emotion either during the process for dealing with a breach of AI, in the case of those who had received an allegation, or at the prospect of being involved in the process, for those who had not. Typically, an interviewee returned to the theme of emotion several times during their interview.

Anxiety: A common emotion was anxiety, fear, or even panic. Students who had not received an allegation of breach of AI expressed a concern about accidental plagiarism:

I would be so scared (shocked voice, gasping). I really would be like really scared because not only would I know what's gonna happen at the university... like you know… in which ways am I gonna get told off or disciplined for this? (DN) I think it's very right you shouldn't copy other people’s work… I am paranoid about copying… inadvertently copying because we had talks… (GN) … I would be really scared. My anxiety is really bad and then I'd be worrying about all sorts of things…I was kinda worried that would happen me for the last assignment I handed in even though I know I was honest, I just worry. (HN)

Shock: For those who had received an allegation there was a mixture of emotions including shock. This suggests that students were not expecting to find their work was in breach of AI regulations, possibly due to poor understanding of academic integrity.

Uh, I was shocked because, Uh, it's something that I've never experienced before. (AY) Shocked, disappointed, I was so angry because I worked so hard on my assignment (CY) … you know it was a shock to get it especially during lectures as well (EY)

Intimidation: Some students specifically mentioned finding the process daunting or intimidating or felt that they had been accused of something reprehensible. One student who had not been through the process expected a student in this situation would feel judged.

I've never done it before, and yeah, they made me feel like I'd done something really wrong (AY) So, I got a letter by email, and I felt terrible they let make me feel as if I've done something horrible. (BY) I was disappointed because the lecture was accusing me throughout the whole process… Shocked, disappointed, I was so angry because I worked so hard on my assignment. (CY) It was pretty daunting, this one person I've never met, a lecturer who I've hardly had a conversation with. (EY) I think it's very intimidating in that sense because you're just going to feel judged, aren't you? (HN)

These emotions of anxiety, shock, and intimidation could be related to a general lack of confidence observed in first-generation students (Phillips et al., 2020 ). The university system prevalent in western industrialised nations expects students to develop their own voice as authors but this is intimidating for first-generation students who may lack the fundamental confidence to start to develop their writing skills. This fear of unintentional plagiarism was also reported by Gullifer and Tyson ( 2004 ) from students who were uncertain about where the boundaries lay between acceptable and unacceptable academic behaviour.

Catastrophising: Anxiety was sometimes connected with unrealistic fear of the consequences. Several students mentioned their fear of being expelled from the course or forced to repeat an entire year.

… I thought I was gonna get kicked off the course. Not really, just put the fear of God into me, really. (AY) I’d be really, really scared that I’d have to redo the whole year. No, I can’t think of anything more frightening than having to redo the whole year. (DN) … they gonna say oh you’re not, you know… fit to do this course, like this is not good enough… you never know. I’ve got no in previous experience of university (EY) I think it's just a really scary thing, isn't it? You just straight away think of the worst… (HN)

These students clearly experienced the phenomenon of catastrophising, also known as magnification (e.g., Ellis, 1962 ), defined as an exaggerated cognitive and emotional schema that can arise during contemplation of a negative outcome. In fact, the consequence for a first breach of AI regulations is to fail the individual component of assessment and proceed to re-sit the component with the mark capped at the pass mark. Students are informed of this. This is not described as a penalty but the inevitable consequence of submitting work that cannot receive a pass. Both the expectation of being withdrawn from the course, or being required to re-do the entire year, are magnifications.

The perception by students from non-traditional academic backgrounds that they are not valued members of the institutional community may lead them to expect worse outcomes than is in fact the case. Catastrophising has been associated with anxiety and depression (Garnefski et al., 2002 ) and so could be related to general stress in students which is likely to be higher in first-generation students (Phillips et al., 2020 ). It seems plausible that this catastrophising stems from a fundamental sense of inadequacy and lack of fit in higher education. Students who feel a strong sense of entitlement, and who are more confident of acceptance, are less likely to be anxious and to catastrophise.

Demotivation vs Relief: Students who had experienced the process for dealing with a breach of AI revealed ways in which the process had a long-term impact on their engagement with their studies. For some, the process led to demoralisation, demotivation, and a sense of not being supported by the institution.

I asked for a delay in my next course because I just felt really demotivational. (BY) The meeting was not supportive; all it did was tarnish my character and demotivated me … I left feeling sad and depressed… I felt like the University neglected me. (CY)

Others perceived the meeting to be supportive and the outcome generated relief:

Well, I mean, I felt relieved 'cause I thought I was going to be kicked off the course 'cause I know that's what I said to them, you know, and they were like no, no, no. - … You know, I felt more. I felt better doing the interview, you know, 'cause they explained to me, and they understood, you know why some students do it. (AY) I can see the silliness of it now, it's quite funny really. (EY)

Demotivation is potentially serious as it could lead to a student withdrawing from their studies. Care should be taken to present an understanding and non-judgmental approach (Bond, 2014 ) and to encourage students to remain engaged or to re-engage with their studies. Offering additional academic support may be of utility in this regard.

Theme 2: Intentionality

Intentionality, sometimes named as cheating, was a recurring theme for all eight participants, presenting itself through two distinct contexts: intentional and unintentional plagiarism. Most interviewees referred to plagiarism committed by others as deliberate cheating, while plagiarism committed by themself, or a close friend, was regarded as unintentional. It is worth noting that the standard allegation letter makes no explicit assumption of intentionality though it appears it may sometimes be received in this way.

Unintentionality: Some participants made an explicit appeal to the good character of the self or the friend and insisted they were unaware of wrongdoing. This is consistent with studies suggesting that individuals make excuses and justifications for behaviour that could attract social disgust (Snyder & Higgins, 1988 ; Zuckerman, 1979 ).

I did it without realising that I was doing it. (AY) I think there's something also very different between cheating and poor referencing, which is what I think I did. Whereas the breach refers to intentionally using somebody's material for my own benefit, and they are two different things. (BY) … I just know she's too honest to cheat… and she worked really hard. If it happened, it would have been an accident, it wouldn't have been that she just copied and pasted. (FY) Not that I would do it anyway, I'm very honest. (GN)

Social desirability may have played a part and it is possible that students presented their own (and their friends’) actions as unintentional from a desire to present themselves in a positive light. It is not possible to be certain, though there are reasons for thinking that participants spoke openly and honestly about their actions. The interviewers were students and not academic staff, and the participants were assured of anonymity, both of which factors would have encouraged honest accounts. Participants acknowledged not using support resources and not using time effectively so were not entirely concerned with presenting a good self-image. Students also mentioned their friends, who were entirely unknown and unknowable to the interviewer, hence there was no need to defend them.

Intentionality: In contrast, when contemplating breaches of AI by other students in general, there was a far more judgmental attitude, and an assumption that students must have known they were doing wrong. It is interesting that one student (FY) claims to have read essays by other students, which would be, in itself, a breach of AI.

I did suspect there were people that paid to have their essays done, after reading some of them. (FY) I would have thought they know they’ve cheated, and they know they won’t be able to write a second one. They must know they can’t weasel their way out of it (GN)

These attitudes towards cheating are consistent with the ‘fundamental attribution error’ (Ross, 1977 ) in which people tend to overstate the influence of personality, but understate the influence of situational factors, to explain the socially unacceptable behaviours of other people. In contrast, the behaviour of the self is attributed more to circumstances and constraints and less to personality traits. Similar patterns have been found in education research (e.g., Bogle, 2000 ). This could arise from over-attribution of causality to the most salient stimulus (Lassiter et al., 2002 ). When another person performs an action, the person is at the focus of attention, so the behaviour is attributed to their personality. In contrast, the individual themself is focused on their situation and circumstances, and so would attribute behaviour to these factors.

It is worth considering that the boundary between intentional and non-intentional breach of AI may be blurred. A student may regard their own breach as non-intentional in the sense that it was not planned but arose from carelessness. For example, a student may cut and paste a passage of text, intending to paraphrase it, but then run out of time; they did not plan to run out of time and in this sense their breach was unintentional. It is consistent with the fundamental attribution error that students would forgive their own mistakes as being due to situational factors but regard the same mistakes in others as intentional.

Self-presentation: Some students indicated concern about being negatively viewed by others. Even students with no breach of AI were anxious about the hypothetical prospect of being judged.

… the thing is, I had to book a day off work, I had to give him (my boss) the letter to say that I had a breach of regulations at university as he wanted to know why I was off … I’m pretty sure it got around. (EY) Mortified! Just mortified. Because I’m a very honest person and it would be very innocent. I would hate people to think I copied anything even if it was a mistake. (GN) I'd be worrying about all sorts of things… like Oh my God they must think I'm a cheat. I don’t want people thinking that of me. (HN)

These comments suggest that the attempt to make a good impression on other people by displaying only positive self-relevant information (Schlenker & Pontari, 2012 ), could be leveraged to encourage students to avoid breaches of AI. Positive self-presentation enables the individual to retain social rewards and avoid social penalties (Baumeister, 1982 ).

The sub-themes of (un)intentionality and self-presentation suggest that perhaps students could be encouraged to think about how their behaviour might be viewed by others. Though they may regard their own breach of AI as unintentional, they could be asked to realise that other people could not be so certain. If students were to take a step back and view their own behaviours objectively, they might realise there was a potential problem. Then their motive for positive self-presentation could encourage them to devote more time and attention to avoiding a breach of AI.

Theme 3: Understanding

A key aspect of promoting academic integrity is providing information to students regarding how to avoid a breach. There were mixed feelings about whether the information provided had resulted in a good understanding of AI. Some students expressed confidence in their ability to avoid a breach, although their confidence was not absolute and there was still anxiety about the possibility of making a mistake.

So yeah, I think I understand the rules quite well (confident sounding). I'm… I'm well, I'd probably say about 80% confident because like I said I do always, you know, make sure I reference everything. (DN) I’m pretty confident! I'm very confident because I'm honest but I'm paranoid that I might have done something by mistake… so yeah very confident (GN)

Other students were still confused about what constitutes plagiarism. A key point was confusing over the difference between poor referencing and plagiarism:

Uhm, I think there's a bit of confusion between what is poor referencing and what is plagiarism. (BY) … all these words like plagiarism and stuff like that I guess I'm not really aware what they actually meant yeah… or they should give examples of what it would it (plagiarism) be…(EY) I don’t even think I know what the rules are (FY) Even I’m confused in my final year, all I know is don’t have any similarity, but I don’t know what else to look out for anymore (HN)

Several students appreciated access to Turnitin, a similarity detection software facility, to check their work against other sources. Early submission was also mentioned as good practice because it allows time to rewrite problematic sections.

Turnitin is there and you can check your similarity … it alerts students if there are some parts in their work that you know… are massively highlighted then they have the opportunity to, you know, change it, and lower their similarity score. (DN) Well, I use Turnitin properly now (laughing) and I submit early. I don't play around with that now. I don't, I've not procrastinated for a while now, so basically, I submit early check it (on Turnitin). (EY) Well first of all I make sure I use own my words and I submit early… and I go look at my similarity. If there is like one sentence in there that's highlighted, I change it. I check the percentage. (FY)

The lack of confidence and confusion around what constitutes plagiarism is consistent with previous research suggesting that students’ understanding may be limited (e.g., Bretag et al., 2014 ; Busch & Bilgin, 2014 ; Chen & Chou, 2017 ). The students who breached AI regulations had received all the same guidance as those who did not, but it did not appear to have been incorporated into their practice. This might reflect an early stage of learning, sometimes known as “unconscious ignorance”. Students often lack metacognitive ability (Penn, 2019 ) and fail to recognise when their level of understanding is inadequate. Hence, they do not seek out sources of guidance to enhance their competence. According to the Dunning Kruger effect (Kruger & Dunning, 1999 ) the students whose understanding is most lacking may have the least insight into their shortfall in comprehension. The likelihood of a breach of AI has been associated with lower levels of understanding of AI (Gullifer & Tyson, 2004 ) or poorer understanding of institutional policies (e.g., Jordan, 2001 ).

These observations suggest the provision of specific examples, and access to similarity detection software, would be helpful in communicating to students what constitutes plagiarism, the most common breach of academic integrity. Boehm et al. ( 2009 ) note that specific examples are helpful in promoting academic integrity and enabling students to develop their understanding. This would add a concrete level of information to the general explanations of AI. Along similar lines, Kwong et al. ( 2010 ) noted that breaches of AI can arise when instructions from tutors are not entirely clear to students, which reinforces the utility of providing concrete examples, especially regarding complex cases (Childers & Bruton, 2016 ).

The question of how much information to provide, and when it should be offered, received mixed responses. Some students took the view that there was too much emphasis on AI, and it was repeated too often, while others tended to the view that refreshing the information was useful.

… we learn it in first year you know they talk about it throughout so you know I don't think any student could say they've never heard about it. So yeah, it's drummed into our heads, isn't it? (DN) Maybe if they put a bit more emphasis on you know… on what is important instead of overloading us with all the information. (EY) Honestly it felt like every other week was a lecture on plagiarism. People stopped showing up, people stopped caring, people switched off! (FY) It was rammed home to us in foundation year. I don't even know if we had a whole lecture covering it, we must have done… but they always went into great detail about it. (GN) … spend 15 minutes on it each year as a refresher. Tell us what plagiarism is and what you are not supposed to do because it is easy to forget. (HN)

These varied opinions suggest that perhaps the principles of AI don’t need to be repeated for every assignment. It could be sufficient to issue a brief reminder and to refer students to the location of specific examples. Simple repetition on its own seems likely to be less helpful than timely and targeted information.

Theme 4: Fairness

There were mixed feelings on the question of fairness and consistency. Some thought the process was fair, and that it was right to act against students who had breached AI. Regarding the consequences, some students agreed these were fair though others had dissenting views.

(interviewer) Do you think the penalty was too severe? (AY) It was alright I think it's a good thing, because obviously it's not fair, you know to plagiarise and steal somebody else’s hard work, so I think it is good that you to go through that process... Um, yes because you know you shouldn't be doing it (serious tone). You shouldn't be plagiarising or copying other people’s work. It's not fair, and it's not fair to yourself like why you would want to do any kind of course and then cheat like… that means that you know at the end of the day, you can't really take the credit for the work that's been done…because it was done by somebody else. So yeah, I think the rules are fair. (DN) … they're giving somebody options, which if it was a genuine mistake then that person has the option to rewrite rather than just being kicked off the course straight away… so yeah that's fair (GN) (interviewer) Do you think the regulations are applied consistently and fairly? (CY) When I spoke to my friends, some had made similar mistakes, but they only had like 5 per cent taken off their original grades. So not at all. (CY)

The perception of uneven treatment is of some concern as students’ motivation and engagement could be adversely affected by perceived lack of fairness in the AI process. For example, Chory-Assad ( 2002 ) reported that college students’ perceptions of procedural justice were correlated with their motivation for learning. Of course, we do not know whether CY’s friends had indeed submitted work with a similar degree of similarity. CY may be underestimating his own level of similarity to published work, perhaps as an example of unconscious ignorance (e.g., Kruger & Dunning, 1999 ; Penn, 2019 ) or as an act of self-presentation. This comment does, however, point to the need to maintain every appearance of consistency and to be explicit that this is an important aspect of the process.

Turning to the consequences, and the appropriateness of the penalty, the standard practice on the first occasion is to ask the student to resubmit the component of assessment, for which the mark awarded is capped at the pass mark. Students thought that the penalty should vary depending on whether the breach of AI was intentional or not. It is worth noting that the standard approach depends on an assumption of unintentionality, and there is more severe penalty where intentionality is obvious, e.g., a purchased essay. Some also thought there should be a lower penalty in the first year and a higher penalty at a more advanced level of study.

I think if it is an accident and it’s a one off and you can clearly see that it was an accident within the work. You know, maybe just a little slap on the wrist … But if you can see that you know the work is clearly being copied from somebody else, or somebody else has done it, then yeah, I think you know the punishment should be different because you're actively choosing to do that (DN) Yeah, if it was an accident of plagiarism then yeah definitely but it’s just how would they prove that? It is very hard to prove that I’d say but if they could prove it, then yeah 100% they should be treated differently. They shouldn’t get punished severely. (HN) Obviously the higher up it is, when the marks count maybe that's when you need more severe talking to … maybe just not so harsh to begin with, gently nurture us. Yeah but, if you're higher up a level, and you’re plagiarising, then there's something clearly not right. (EY)

This is consistent with the findings of Gullifer and Tyson ( 2004 ) and of Newton ( 2016 ) whose participants regarded the penalties for plagiarism as too severe in the absence of deliberate intent. Indeed, there is a common belief in society that premeditated intent should be considered when deciding on the level of a penalty. Some students even appear to equate a breach of academic integrity with deliberate intent, and in their interpretation an accidental breach is not really a breach at all. It is debatable whether an institution should take this view, but it seems clear that students’ acceptance of the principles and practices of AI may depend on the application of lesser penalties for a breach that is not clearly intentional.

The view that students at lower levels of study should be penalised less severely presumably depends on the assumption that these students have had less opportunity to develop full understanding of AI. This assumption is supported by the findings of Locquiao and Ives ( 2020 ) and of Newton ( 2016 ) that students at the start of their higher education lack understanding of AI. The belief that new students require more nurturing is an intuitively appealing view and may be worthy of consideration.

Theme 5: Self-Regulation

Students in higher education are expected to be self-directed learners who take charge of their learning strategies. In order to set and meet goals, students must take responsibility for their learning and be motivated to improve themselves (English & Kitsantas, 2013 ). The process of being able to delay gratification, pursue goals and avoid procrastination all while dealing with the constant demands of studying requires self-regulation and engagement with support services (Rahat & Ilhan, 2016 ). Other studies concur that students with strong self-regulation tend to have a better grasp on time management and are more inclined to double-check their work (McAllister & Watkins, 2012 ; Pintrich, 2004 ).

The interviews in the current study illustrate two of the key concepts involved in self-regulated learning according to Thibodeaux et al. ( 2017 ). These two concepts, discussed separately, are engaging with relevant support and coping style.

Engaging with support: A self-regulated learner is aware of their weaknesses and typically engages with resources to strengthen their academic abilities (Thibodeaux et al., 2017 ). In the present study, although students acknowledged the provision of support, they did not use the services fully, sometimes due to poor time management.

I think that resources are there; I just didn't use them …. (interviewer) Were you given sufficient information about academic integrity? (student) I probably didn't have time to read it (BY) I think all the services are there, it's up to the individual to manage their time and use them because everything is there you know … you can send off your work and someone can check it. I think I just never used it. I probably should have or could have but didn’t…probably due to lack of time (DN) Uhm, yes, the support is pretty good, I just never use it. (GN)

These findings resemble those of McNaught and Beal ( 2012 ) who found that although students agreed that the academic support was good, they did not always engage with it. These students who didn’t make use of the support offered are perhaps not displaying the most effective learning strategies. Utilising educational support programmes is considered an effective learning strategy as it can improve academic performance, reduce the risk of plagiarism, and decrease student drop-out rates (Peach, 2005 ). However, research shows that providers can struggle to engage many students on these programmes. Users of such programmes are frequently high-ability students looking to improve their grades, rather than those who are low-ability and at risk of difficulty (McNaught & McIntyre, 2011 ). The reasons for this are unknown though, it could be attributed to a lack of confidence among first-generation students in asking for support (Ramos‐Sánchez & Nichols, 2007 ). To apply effective learning strategies, the student must be able to assess their academic competencies; without this, students find it hard to understand where they need help (Thibodeaux et al., 2017 ).

This analysis suggests it might be beneficial to highlight to students the match between their learning needs and the support offered. Flexibility of provision will also be important to students who have significant time constraints, for example, by reason of caring responsibilities or paid work. This shifts the emphasis from penalty to enabling students to enhance their academic skills, using the intervention to promote students’ learning and confidence in writing assignments. The focus turns to providing support to students and helping them to develop their meta-cognitive skills – what they need to know and how they can learn it (Bertram Gallant, 2017 ). This proposes a policy of “sustainable reform” (Sutherland-Smith, 2010 ) rather than retribution.

Coping style: Turning to the issue of coping styles, there are clearly differences among the students in this study. Coping is defined as the ability to respond and adapt to the heightened arousal that comes with unfavourable situations (Zimmer-Gembeck & Skinner, 2016 ). When faced with hardship, a person may employ either an adaptive or maladaptive style of coping. Problem-focus or task-focus is considered to be an adaptive style of coping and is associated with academic success. Emotion-focus and avoidance-focus are considered to be maladaptive coping styles and are negatively associated with academic achievement (Ansarisadr & Shirazi, 2022 ; Khedmatian et al., 2022 ; Valenti & Faraci, 2021 ).

In an academic context an adaptive coping style (problem-focused style) includes the tendency to engage positively with feedback and make plans to improve based on experience. There was some evidence of an adaptive coping style in students who had been through the breach process; they resolved in the future to use Turnitin, manage their time well, and take personal responsibility for their work.

I'm not complacent now about it I'm always checking you know. I check everything as much as I can. I'm very careful about everything you know … Well, I use Turnitin properly now (laughing) and I submit early ... I mean it is up to me. I mean, at the end of day, I didn't have an argument because it is up to me to look and understand it, I suppose. (EY) Well first of all I make sure I use own my words and I submit early… and I go look at my similarity. If there is like one sentence in there that's highlighted, I change it. I check the percentage ... So, for me personally it was important to do my own work. (FY) Clearly now I understand it is wrong … Now I know that I need to paraphrase his definition (BY)

There was also evidence of students who had been through the breach process becoming demotivated, not accepting personal responsibility, not engaging with the support available to them, and not enhancing their understanding of AI; these are all examples of avoidance. This is of concern because of the risk of non-continuation for these students.

I asked for a delay in my next course because I just felt really demotivational … I think that resources are there; I just didn't use them. (BY) Overall, the process was negative. I wasted my time, to say the least. (CY) I don’t even think I know what the rules are (FY)

There is evidence that students who have adaptive coping skills are more likely to have high academic ability (Gustems-Carnicer et al., 2019 ) though cause and effect are difficult to determine. It could be either that the employment of an adaptive coping style leads to greater academic success, perhaps through perseverance and engagement in problem-solving (Moore et al., 2011 ) or academic success encourages a student to employ an adaptive coping style. Students with an adaptive coping style also tend to have stronger self-regulation (De la Fuente et al., 2015 ) and students with stronger self-regulation were found to be more likely to avoid plagiarising as they tend to be more aware of regulations within their university (McAllister & Watkins, 2012 ; also Jordan, 2001 ).

Limitations of the Study

Most of the breaches of academic integrity handled in this institution are cases of plagiarism, and this was the case for all the students interviewed in this study. Other issues may pertain to the purchase of essays, or the impersonation of a student in an exam, which could not be seen as unintentional.

Eight students were interviewed from two schools within one institution of higher education. This is considered to be an adequate sample size for an IPA study (Hefferon & Gil-Rodriguez, 2011 ; Smith & Osborn, 2003 ). Nonetheless, it should be noted that the implications may not apply equally to other institutions.

The students in this study do not represent the typical student population and over-represent mature students and first-generation students. Consequently, they may have relatively weak understanding of how to navigate the rules and regulations of higher education. Some themes may have been exaggerated as a result. For example, the emotions of anxiety, shock, and intimidation, are theorised to depend on unfamiliarity with higher education and a lack of confidence. Similarly, the tendency to catastrophise may be related to a sense of inadequacy and perception of a lack of fit in higher education. First-generation students may also have a weaker understanding of AI and weaker skills of self-regulation. Finally, lack of confidence may deter first-generation students form asking for help.

The attribution of the findings to psychological concepts of self-regulated learning, coping styles, attribution bias, catastrophising, etc., are all inferred, as students were not asked directly about these concepts. These various theories are advanced as likely explanations for the attitudes and beliefs advanced by students.

The participants in the present study mostly defined their ethnicity as White which is not representative of the population at the institution. It may be that students of colour were less confident about coming forward to be interviewed. The preponderance of students at higher levels of study may also stem from increased academic confidence of students who had already successfully navigated one or more years of study in higher education. Students at early stages of their courses might have been less confident about taking part in a research study. This would suggest that the entire population of students at the present institution might experience more negative emotion, less effective self-regulation, and poorer understanding of AI compared to the sample in this study.

Action Points

The following action points are suggested for institutions in general to consider. Some may not be applicable in particular cases but all would appear to have broad, general relevance in HE.

Students should be treated as though their breach of AI was unintentional wherever plausible. A suggestion of intentionality could lead some students to employ a defensive coping style, or a tendency to withdraw, which would hamper their ability to benefit from the intervention and decrease their likelihood of continuing to engage strongly with their course of study. This is important, as the retention of students is increasingly a priority for many institutions of higher education.

Explicit confirmation of the maximum penalty that can be awarded would help to avoid the phenomenon of catastrophising. Support after the intervention could also be offered to promote re-engagement and to enhance the perception that the institution cares for the individual student.

Some students would benefit from specific help with time management and self-regulatory strategies in general. The assumption that adult students are all competent self-motivated learners may overlook systematic and individual factors that hamper the development of effective learning strategies. Students could be offered guidance on effective studying at an early stage in their programme of study.

To assist in understanding of academic integrity regulations, and where the boundaries lie, specific examples of work that is or is not acceptable could be offered. This would be of particular help to students who are less familiar with the standards of higher education. Clarification of the difference between plagiarism and poor referencing would also be beneficial. Similarity detection tools should be made available, or even compulsory, and students should be taught how to use them, for all assessed work.

The content, and timing, of information about academic integrity should be carefully planned. Overloading of information can lead to less effective learning and to disengagement. Key points should be identified for the presentation of focused material with clear examples. Students at risk of breaching academic integrity could be signposted to academic support. The personal approach has been shown to work in previous research (e.g., McNaught & McIntyre, 2011 ) and the use of motivational words like “aspire” may be more effective.

Conclusions and Key Themes

The potential for a breach of academic integrity is a concern to many students and a cause of considerable anxiety. Clear guidance and examples to inform students would offer reassurance that an accidental breach can be avoided.

The principles of academic integrity have broad acceptance and there is agreement that breach of AI should have some consequence. It is important to distinguish between intentional and unintentional breaches of academic integrity, and to be clear that unintentional breaches are dealt with less harshly, to promote acceptance of policy and regulation.

Students are clearly concerned about self-presentation and the ‘fundamental attribution error’ (Ross, 1977 ) was apparent. Personal attributes were invoked to explain cheating by ‘others’ whereas breaches of academic integrity by selves or close friends were justified and explained by contextual reasons. To overcome this, students could be encouraged to think about how their work would look to other people.

Students vary in their self-regulation, particularly in their engagement with academic support, their understanding of academic integrity principles and policy, and generally in their acceptance of responsibility for their own learning. Some guidance and assistance in developing the skills to adopt self-regulated learning would be of benefit. To the extent that it is possible to assist students in developing effective coping styles, this could also be of benefit.

Acknowledgements

The assistance of Ms Eimear O’Reilly and Ms Patrica MacKensie with the data collection is gratefully acknowledged.

Declarations

This study was granted ethical approval by the University of East London Research Ethics Committee, reference number ETH2021-0134.

There is no known conflict of interest to disclose.

Anna Stone is a senior lecturer at the University of East London. Her responsibilities include operation of the system for handling breaches of academic integrity and education of staff and students.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Literature Review: Academic Dishonesty – What Causes It, How to Prevent It

by Thomas Keith | Nov 16, 2018 | Instructional design

Note:  For further information on academic dishonesty and academic integrity, please see our series Combating Academic Dishonesty . Part 1 | Part 2 | Part 3

Academic dishonesty, which encompasses behaviors such as cheating, plagiarism, and falsification of data or citations, is a widespread and troubling phenomenon in higher education.  (For the full spectrum of behaviors that qualify as academic dishonesty, see Berkeley City College’s What Is Academic Dishonesty? )  It may be as simple as looking over a classmate’s shoulder during a quiz or as elaborate as hiring a ghostwriter online for a course paper, but whatever the method employed, academic dishonesty harms the learning experience and gives cheaters an unfair advantage over those who abide by the rules.  This post examines some of the chief factors that lead to academic dishonesty among college students, as determined by empirical research in the field, and offers suggestions to faculty and instructors on ways to reduce the likelihood of dishonest conduct among their students.

What Causes Academic Dishonesty?

There is no single explanation for the occurrence of dishonest behavior in college.  Studies suggest that most students realize academic dishonesty is morally wrong, but various outside factors or pressures may serve as “neutralizers,” allowing students to suppress their feelings of guilt and justify their dishonest acts to themselves (Baird 1980; Haines et al. 1986; Hughes and McCabe 2006).  In certain cases, dishonest behavior may arise not from willful disregard for the rules of academic integrity, but from ignorance of what those rules are.  Some common reasons for students’ engaging in academic dishonesty are given below.

Poor time management

Particularly in their early years of college, many students have difficulties with managing their time successfully.  Faced with demands on their out-of-class time from athletics, extracurricular clubs, fraternities and sororities, etc., they may put off studying or working on assignments until it is too late for them to do a satisfactory job.  Cheating then appears attractive as a way to avoid failure (Haines et al. 1986).

Academic pressures

Sometimes a student must maintain a certain GPA in order to receive merit-based financial aid, to participate in athletics, or even to continue receiving financial support from his/her family. Even high-achieving students may turn to academic dishonesty as a way to achieve their target GPA.  Academic pressures can be worsened in courses that are graded on a curve: with the knowledge that only a fixed number of As can be awarded, students may turn to dishonest methods of surpassing their classmates (Whitley 1998; Carnegie Mellon University ).

In very large classes, students may feel anonymous; if the bulk of their interaction is with teaching assistants, they may regard the instructor as distant and unconcerned with their performance.  This can increase the temptation to cheat, as students rationalize their dishonest behavior by assuming that the instructor “doesn’t care” what they do.  Not surprisingly, this can often be a danger in online courses, since course sizes can be huge and students do not normally interact with their instructors face-to-face ( Carnegie Mellon University ).

Failure to understand academic conventions

The “rules” of academic writing often appear puzzling to students, particularly those who have not had extensive practice with academic writing in high school.  The Internet has arguably exacerbated this problem; the easy availability of information (accurate or otherwise) on websites has led many students to assume that all information sources are de facto public property and need not be cited, which leads to unintentional plagiarism.  Faculty and instructors should not take for granted that their students simply “know” when they must cite sources and how they should do so (Perry 2008).  In addition, the ready availability of websites on every topic imaginable has had a deleterious effect on students’ ability to assess sources critically.  Some students simply rely upon whichever site comes up at the top of a Google search, without considering the accuracy or potential biases of the information with which they are being presented.

Cultural factors

Related to the above, international students may face particular challenges in mastering the conventions of academic writing.  They do not necessarily share Western/American understandings of what constitutes “originality,” intellectual property rights, and so forth, and it often takes time and practice for them to internalize the “rules” fully, especially if English is not their first language.  In addition, students who come from cultures where collaborative work is common may not realize that certain assignments require them to work entirely on their own (Currie 1998; Pecorari 2003; Hughes and McCabe 2006; Abasi and Graves 2008).

The academic pressures common to all college students can be particularly acute for international students.  In some cultures (e.g. those of East Asia) excellent academic performance at the university level is vital for securing good jobs after graduation, and students may therefore believe that their futures depend upon receiving the highest possible grades.  When a student’s family is making sacrifices to send him/her overseas for college, s/he may be concerned about “letting the family down” by doing poorly in school, which can make academic dishonesty all the more tempting.

Low-Stakes Assignments

While some people may think of cheating as a risk only on high-stakes assignments (course papers, final exams, and the like), it can easily occur on low-stakes assignments as well.  In fact, the very lack of grade weight that such assignments bear can encourage dishonesty: students may conclude that since an assignment has little or no bearing on their course grade, it “doesn’t matter” whether or not they approach it honestly.  For this reason, it is vital to stress to students the importance of honest conduct on all assignments, whether big or small.  The University does not take grade weight into account when deciding whether academic dishonesty has occurred; plagiarism is plagiarism and cheating is cheating, even if the assignment in question is worth zero points.

Technology and Academic Dishonesty

The rapidly increasing sophistication of digital technology has opened up new avenues for students bent on academic dishonesty.  Beyond simply cutting-and-pasting from webpages, an entire Internet economy has sprung up that offers essays for students to purchase and pass off as their own.  Students may also use wireless technology such as Bluetooth to share answers during exams, take pictures of exams with their smartphones, and the like (McMurtry 2001; Jones, Reid, and Bartlett 2008; Curran, Middleton, and Doherty 2011).  Research suggests that the use of technology creates a “distancing” effect that makes students’ guilt about cheating less acute ( Vanderbilt University ).

How Can Faculty and Instructors Combat Academic Dishonesty?

There is no panacea to prevent all forms of dishonest behavior.  That said, at each step of the learning design process, there are steps that faculty and instructors can take to help reduce the likelihood of academic dishonesty, whether by making it more difficult or by giving students added incentive to do their work honestly.

Course Management and Syllabus Design

The sooner students are informed about the standards of conduct they should adhere to, the greater the likelihood that they will internalize those standards (Perry 2010).  This is why it is worthwhile for faculty to devote a portion of their syllabus to setting standards for academic integrity.  Consider setting the tone for your course by offering a clear definition of what constitutes academic dishonesty, the procedure you will follow if you suspect that dishonest behavior has occurred, and the penalties culprits may face.  Include a link to UChicago’s statement on Academic Honesty and Plagiarism .  If you have a Canvas course site, you can create an introductory module where students must read a page containing your academic integrity policies and “mark as done,” or take a quiz on your policies and score 100%, in order to receive credit for completing the module.

If your syllabus includes many collaborative assignments, it can also be useful to explain clearly for which assignments collaboration is permitted and which must be done individually.  You can also specify what you consider acceptable vs. unacceptable forms of collaboration (e.g. sharing ideas while brainstorming is allowed, but copying one another’s exact words is not).

Finally, consider including information in your syllabus about resources available to students who are having academic difficulties, such as office hours and tutoring.  Students who are facing difficulties with time management, executive function, and similar issues may benefit from the Student Counseling Service’s Academic Skills Assessment Program (ASAP) .   The University’s Writing Center  offers help with mastering academic writing and its conventions.  Encourage your students to avail themselves of these resources as soon as they encounter difficulties.  If they get help early on, they will be less likely to feel desperate later and resort to dishonest behavior to raise their grade (Whitley 1998).

In general, making your expectations clear at the outset of your course helps to build a strong relationship between you and your students.  Your students will feel more comfortable coming to you for help, and they will also understand the risks they would be running if they behaved dishonestly in your course, which can be a powerful deterrent.

Assignment Design

When crafting assignments such as essays and course papers, strive for two factors: originality and specificity.  The more original the topic you choose, and the more specific your instructions, the less likely it is that students will be able to find a pre-written paper on the Internet that fits all the requirements (McMurtry 2001).  Changing paper topics from year to year also avoids the danger that students may pass off papers from previous years as their own work.  You might consider using a rubric with a detailed breakdown of the factors you will be assessing in grading the assignment; Canvas offers built-in rubric functionality .

If an assignment makes up a large percentage of your students’ final grade (e.g. a course paper), you might consider using “scaffolding”.  Have the students work up to the final submission through smaller, lower-stakes sub-assignments, such as successive drafts or mini-papers.  This has the double benefit of making it harder for students to cheat (since you will have seen their writing process) and reducing their incentive to cheat (since their grade will not be solely dependent upon the final submission) ( Carnegie Mellon University ).

In the case of in-class exams, you may find it worthwhile to create multiple versions of an exam, each with a separate answer key.  Even as simple an expedient as placing the questions in a different order in different versions makes it harder for students to copy off one another’s work or share answer keys ( Carnegie Mellon University ).

Technological Tools to Prevent Academic Dishonesty

Even as students have discovered more sophisticated ways to cheat, educational professionals and software developers have created new technologies to thwart would-be cheaters.  Canvas, the University’s learning management system, includes several features intended to make cheating more difficult.

By default, the Files tab in Canvas is turned off when a new course is created.  This prevents students from accessing your course files and viewing files they should not, such as answer keys or upcoming exam questions.  If you choose to enable Files in your course, you should place all sensitive files in locked or unpublished folders to render them invisible to students.  For more details, see this post .

If you are using Canvas Quizzes in your course, you can choose from a number of options that increase the variation between individual students’ Quizzes and thus decrease the chances of cheating.  These including randomizing answers for multiple-choice questions; drawing randomly selected questions from question groups; and setting up variables in mathematical questions, so that different students will see different numerical values.  For more details, see this post .

Several different computer programs have been developed that claim to detect plagiarism in student papers, usually by comparing student submissions against the Internet, a database of past work, or both, and then identifying words and phrases that match. Viper follows a “freemium” model, while the best-known subscription-based plagiarism checker, Turnitin , is currently licensed only by the Law School at the University of Chicago.  These programs can be helpful, but bear in mind that no automatic plagiarism checker is 100% accurate; you will still need to review student work yourself to see whether an apparent match flagged by the software is genuine plagiarism or not (Jones, Reid, and Bartlett 2008).  Also be aware that Turnitin and some other plagiarism checkers assert ownership rights over student work submitted to them, which can raise issues of intellectual property rights.

In addition to detecting plagiarism after the fact, there are technological tools that can help prevent it from occurring in the first place.  Citation managers such as Endnote and Zotero are excellent ways to help students manage their research sources and cite them properly, especially when writing longer papers that draw on a wide range of source material.  The University of Chicago Library offers a detailed guide to citation managers , along with regular workshops on how to use them .

What to Do if You Suspect Academic Dishonesty

If you suspect that academic dishonesty may have occurred in one of your courses, the University has resources to which you can turn.  For undergraduates, it is best to begin by speaking to the student’s academic adviser .  You can find out which adviser is assigned to a student in your course by visiting Faculty Access and looking at the “Advisor” column in the course roster.  If you have questions about disciplinary procedures specific to the College, you can contact the Office of College Community Standards, headed by Assistant Dean of Students Stephen Scott .   For graduate students, the appropriate area Dean of Students can provide information about the correct disciplinary procedures to follow.

The fight against academic dishonesty is a difficult one, and will continue to be so for the foreseeable future.  But if faculty and instructors give careful thought to the causes of student misconduct and plan their instructional strategies accordingly, they can do much to curb dishonest behavior and ensure that integrity prevails in the classroom.

Bibliography

Journal articles.

• Abasi, Ali R., and Barbara Graves.  “Academic Literacy and Plagiarism: Conversations with International Graduate Students and Disciplinary Professors.”   Journal of English for Academic Purposes 7.4 (Oct. 2008), 221-233.  
• Baird, John S., Jr.  “Current Trends in College Cheating.”   Psychology in the Schools 17 (1980), 515-522.  
• Curran, Kevin, Gary Middleton, and Ciaran Doherty.  “Cheating in Exams with Technology.” International Journal of Cyber Ethics in Education 1.2 (Apr.-Jun. 2011), 54-62.  
• Currie, Pat.  “Staying Out of Trouble: Apparent Plagiarism and Academic Survival.”   Journal of Second Language Writing 7.1 (Jan. 1998), 1-18.  
• Haines, Valerie J., et al.  “College Cheating: Immaturity, Lack of Commitment, and the Neutralizing Attitude.”   Research in Higher Education 25.4 (Dec. 1986), 342-354.  
• Hughes, Julia M. Christensen, and Donald L. McCabe.  “Understanding Academic Misconduct.” Canadian Journal of Higher Education 36.1 (2006), 49-63.  
• Jones, Karl O., Juliet Reid, and Rebecca Bartlett. “Cyber Cheating in an Information Technology Age.” In R. Comas and J. Sureda (coords.). “Academic Cyberplagiarism” [online dossier]. Digithum: The Humanities in the Digital Era 10 (2008), n.p. UOC. [Accessed: 26/09/18] ISSN 1575-2275. 
• McMurtry, Kim.  “E-Cheating: Combating a 21st Century Challenge.”   Technological Horizons in Education Journal 29.4 (Nov. 2001), 36-40.
• Pecorari, Diane.  “Good and original: Plagiarism and patchwriting in academic second-language writing.”   Journal of Second Language Writing 12.4 (Dec. 2003), 317-345.
• Perry, Bob.  “Exploring Academic Misconduct: Some Insights into Student Behaviour.”   Active Learning in Higher Education 11.2 (2010), 97-108.  
• Whitley, Bernard E.  “Factors Associated with Cheating among College Students: A Review.”   Research in Higher Education 39.3 (Jun. 1998), 235-274.  

Web Resources

• Berkeley City College:  http://www.berkeleycitycollege.edu/wp/de/what-is-academic-dishonesty/
• Carnegie Mellon University: https://www.cmu.edu/teaching/solveproblem/strat-cheating/index.html
• University of Chicago: https://college.uchicago.edu/advising/academic-honesty |  https://studentmanual.uchicago.edu/Policies
• Colorado State University: https://tilt.colostate.edu/integrity/resourcesFaculty/whyDoStudents.cfm
• Harvard University (Zachary Goldman): https://www.gse.harvard.edu/uk/blog/youth-perspective
• Oakland University: https://www.oakland.edu/Assets/upload/docs/OUWC/Presentations%26Workshops/dont_fail_your_courses.pdf
• Vanderbilt University (Derek Bruff): https://cft.vanderbilt.edu/2011/02/why-do-students-cheat/

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Promoting a climate of academic integrity: A literature review for the Harvard College Academic Integrity Committee (AIC). [White paper].

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