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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]

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Promoting Academic Integrity 

While it is each student’s responsibility to understand and abide by university standards towards individual work and academic integrity, instructors can help students understand their responsibilities through frank classroom conversations that go beyond policy language to shared values. By creating a learning environment that stimulates engagement and designing assessments that are authentic, instructors can minimize the incidence of academic dishonesty.

Academic dishonesty often takes place because students are overwhelmed with the assignments and they don’t have enough time to complete them. So, in addition to being clear about expectations and responsibilities related to academic integrity, instructors should also invite students to  plan accordingly and communicate with them in the event of an emergency. Instructors can arrange extensions and offer solutions in case that students have an emergency. Communication between instructors and students is vital to avoid bad practices and contribute to hold on to the academic integrity values. 

The guidance and strategies included in this resource are applicable to courses in any modality (in-person, online, and hybrid) and includes a discussion of addressing generative Artificial Intelligence (AI) tools like ChatGPT with students. 

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Cite this resource: Columbia Center for Teaching and Learning (2020). Promoting Academic Integrity. Columbia University. Retrieved [today’s date] from https://ctl.columbia.edu/resources-and-technology/resources/academic-integrity/

According to the  International Center for Academic Integrity , academic integrity is “a commitment, even in the face of adversity, to six fundamental values: honesty, trust, fairness, respect, responsibility, and courage.” We commit to these values to honor the intellectual efforts of the global academic community, of which Columbia University is an integral part.

Academic dishonesty in the classroom occurs when one or more values of academic integrity are violated. While some cases of academic dishonesty are committed intentionally, other cases may be a reflection of something deeper that a student is experiencing, such as language or cultural misunderstandings, insufficient or misguided preparation for exams or papers, a lack of confidence in their ability to learn the subject, or perception that course policies are unfair (Bernard and Keith-Spiegel, 2002).

Some other reasons why students may commit academic dishonesty include:

• Cultural or regional differences in what comprises academic dishonesty
• Lack or poor understanding on how to cite sources correctly
• Misunderstanding directions and/or expectations
• Poor time management, procrastination, or disorganization
• Feeling disconnected from the course, subject, instructor, or material
• Fear of failure or lack of confidence in one’s ability
• Anxiety, depression, other mental health problems
• Peer/family pressure to meet unrealistic expectations

Understanding some of these common reasons can help instructors intentionally design their courses and assessments to pre-empt, and hopefully avoid, instances of academic dishonesty. As Thomas Keith states in “Combating Academic Dishonesty, Part 1 – Understanding the Problem.” faculty and administrators should direct their steps towards a “thoughtful, compassionate pedagogy.”

The CTL is here to help!

The CTL can help you think through your course policies and ways to create community, design course assessments, and set up CourseWorks to promote academic integrity. Email [email protected] to schedule your 1-1 consultation .

In his research on cheating in the college classroom, James Lang argues that “the amount of cheating that takes place on our campuses may well depend on the structures of the learning environment” (Lang, 2013a; Lang, 2013b). Instructors have agency in shaping the classroom learning experience; thus, instances of academic dishonesty can be mitigated by efforts to design a supportive, learning-oriented environment (Bertam, 2017 and 2008).

Understanding Student’s Perceptions about Cheating 

It is important to know how students understand critical concepts related to academic integrity such as: cheating, transparency, attribution, intellectual property, etc. As much as they know and understand these concepts, they will be able to show good academic integrity practices.

1. Acknowledge the importance of the research process, not only the outcome, during student learning.

Although the research process is slow and arduous, students should understand the value of the different processes involved during academic writing: investigation, reading, drafting, revising, editing and proof-reading. For Natalie Wexler, using generative Artificial Intelligence tools like ChatGPT as a substitute of writing itself is beyond cheating, an act of self cheating: “The process of writing itself can and should deepen that knowledge and possibly spark new insights” (“‘ Bots’ Can Write Good Essays, But That Doesn’t Make Writing Obsolete” ).

Ways to understand the value of writing their own work without external help, either from external sources, peers or AI, hinge on prioritizing the process over the product:

• Asking students to present drafts of their work and receive feedback can help students to gain confidence to continue researching and writing.
• Allowing students the freedom to choose or change their research topic can increase their investment in an assignment, which can motivate them to conduct their own writing and research rather than relying on AI tools. 

2. Create a supportive learning environment

When students feel supported in a course and connected to instructors and/or TAs and their peers, they may be more comfortable asking for help when they don’t understand course material or if they have fallen behind with an assignment.

Ways to support student learning include:

• Convey confidence  in your students’ ability to succeed in your course from day one of the course (this may ease student anxiety or  imposter syndrome ) and through timely and regular feedback on what they are doing well and areas they can improve on. 
• Explain the relevance  of the course to students; tell them why it is important that they actually learn the material and develop the skills for themselves. Invite students to connect the course to their goals, studies, or intended career trajectories. Research shows that students’ motivation to learn can help deter instances of academic dishonesty (Lang, 2013a). 
• Teach important skills  such as taking notes, summarizing arguments, and citing sources. Students may not have developed these skills, or they may bring bad habits from previous learning experiences. Have students practice these skills through exercises (Gonzalez, 2017). 
• Provide students multiple opportunities to practice challenging skills  and receive immediate feedback in class (e.g., polls, writing activities, “boardwork”). These frequent low-stakes assessments across the semester can “[improve] students’ metacognitive awareness of their learning in the course” (Lang, 2013a, pp. 145). 
• Help students manage their time  on course tasks by scheduling regular check-ins to reduce students’ last minute efforts or frantic emails about assignment requirements. Establish weekly online office hours and/or be open to appointments outside of standard working hours. This is especially important if students are learning in different time zones. Normalize the use of campus resources and academic support resources that can help address issues or anxieties they may be facing.  (See the Columbia University Resources section below for a list of support resources.)
• Provide lists of approved websites and resources  that can be used for additional help or research. This is especially important if on-campus materials are not available to online learners. Articulate permitted online “study” resources to be used as learning tools (and not cheating aids – see McKenzie, 2018) and how to cite those in homework, writing assignments or problem sets. 
• Encourage TAs (if applicable) to establish good relationships  with students and to check-in with you about concerns they may have about students in the course. (Explore the  Working with TAs Online  resource to learn more about partnering with TAs.)

3. Clarify expectations and establish shared values

In addition to including Columbia’s  academic integrity policy  on syllabi, go a step further by creating space in the classroom to discuss your expectations regarding academic integrity and what that looks like in your course context. After all, “what reduces cheating on an honor code campus is not the code itself, but  the dialogue about academic honesty that the code inspires. ” (Lang, 2013a, pp. 172)

Ways to cultivate a shared sense of responsibility for upholding academic integrity include: 

• Ask students to identify goals and expectations  around academic integrity in relation to course learning objectives. 
• Communicate your expectations  and explain your rationale for course policies on artificial intelligence tools, collaborative assignments, late work, proctored exams, missed tests, attendance, extra credit, the use of plagiarism detection software or proctoring software, etc. It will make a difference to take the time at the beginning of the course to explain differences between quoting, summarizing and paraphrasing. Providing examples of good and bad quotation/paraphrasing will help students to know what constitutes good academic writing. 
• Define and provide examples  for what constitutes plagiarism or other forms of academic dishonesty in your course.
• Invite students to generate ideas  for responding to scenarios where they may be pressured to violate the values of academic integrity (e.g.: a friend asks to see their homework, or a friend suggests using chat apps during exams), so students are prepared to react with integrity when suddenly faced with these situations. 
• State clearly when collaboration and group learning is permitted  and when independent work is expected. Collaboration and group work provide great opportunities to build student-student rapport and classroom community, but at the same time, it can lead students to fall into academic misconduct due to unintended collaboration/failure to safeguard their work.
• Discuss the ethical, academic, and legal repercussions  of posting class recordings, notes and/or class materials online (e.g., to sites such as Chegg, GitHub, CourseHero – see Lederman, 2020).
• Partner with TAs  (if applicable) and clarify your expectations of them, how they can help promote shared values around academic integrity, and what they should do in cases of suspected cheating or classroom difficulties

4. Design assessments to maximize learning and minimize pressure

High stakes course assessments can be a source of student anxiety. Creating multiple opportunities for students to demonstrate their learning, and spreading assessments  throughout  the semester can lessen student stress and keep the focus on student learning (see  Darby, 2020  for strategies on assessing students online). As Lang explains, “The more assessments you provide, the less pressure you put on students to do well on any single assignment or exam. If you maintain a clear and consistent academic integrity policy, and ensure that all students caught cheating receive an immediate and substantive penalty, the benefit of cheating on any one assessment will be small, while the potential consequences will be high” (Lang, 2013a and Lang, 2013c). For support with creating online exams, please please refer to our  Creating Online Exams resource .

Ways to enhance one’s assessment approach:

• Design assignments  based on authentic problems in your discipline. Ask students to  apply  course concepts and materials to a problem or concept. 
• Structure assignments into smaller parts  (“scaffolding”) that will be submitted and checked throughout the semester. This scaffolding can also help students learn how to tackle large projects by breaking down the tasks. 
• Break up a single high-stakes exam  into smaller, weekly tests. This can help distribute the weight of grades, and will lessen the pressure students feel when an exam accounts for a large portion of their grade. 
• Give students options  in how their learning is assessed and/or invite students to present their learning in creative ways (e.g., as a poster, video, story, art project, presentation, or oral exam).
• Provide feedback prior to grading  student work. Give students the opportunity to implement the feedback. The revision process encourages student learning, while also lowering the anxiety around any one assignment. 
• Utilize multiple low-stakes assignments  that prepare students for high-stakes assignments or exams to reduce anxiety (e.g., in-class activities, in-class or online discussions)
• Create grading rubrics and share them  with your students and TAs (if applicable) so that expectations are clear, to guide student work, and aid with the feedback process.  
• Use individual student portfolio folders  and provide tailored feedback to students throughout the semester. This can help foster positive relationships, as well as allow you to watch students’ progress on drafts and outlines. You can also ask students to describe how their drafts have changed and offer rationales for those decisions.
• For exams , consider refreshing tests every term, both in terms of organization and content. Additionally, ground your assignments by having students draw connections between course content and the unique experience of your course in terms of time (unique to the semester), place (unique to campus, local community, etc. ), personal (specific student experiences), and interdisciplinary opportunities (other courses students have taken, co-curricular activities, campus events, etc.). (Lang, 2013a, pp. 77).

Since its release, ChatGPT has raised concern in universities across the country about the opportunity it presents for students to cheat and appropriate AI ideas, texts, and even code as their own work. However, there are also potential positive uses of this tool in the learning process–including as a tool for teachers to rely on when creating assessments or working with repetitive and time-consuming tasks.

Possible Advantages of ChatGPT

Due to the novelty of this tool, the possible advantages that might present in the teaching-learning process should be under the control of each instructor since they know exactly what they expect from students’ work. 

Prof. Ethan Mollick teaches innovation and entrepreneurship at the Wharton School of the University of Pennsylvania, and has been openly sharing on his Twitter account his journey incorporating ChatGPT into his classes. Prof. Mollick advises his students to experiment with this tool, trying and retrying prompts. He recognizes the importance of acknowledging its limits and the risks of violating academic honesty guidelines if the use of this tool is not stated at the end of the assignment.

Prof. Mollick uncovers four possible uses of this AI tool, ranging from using ChatGPT as an all-knowing intern, as a game designer, as an assistant to launch a business, or even to “hallucinate” together ( “Four Paths to the Revelation” ). For Prof. Mollick, ChatGPT is a useful technology to craft initial ideas, as long as the prompts are given within a specific field, include proper context, step-by-step directions and have the proper changes and edits.

Resources for faculty: 

• Academic Integrity Best Practices for Faculty (Columbia College & School of Engineering and Applied Sciences)
• Faculty Statement on Academic Integrity (Columbia College)
• FAQs: Academic Integrity from Columbia Student Conduct and Community Standards 
• Ombuds Office for assistance with academic dishonesty issues. 
• Columbia Center of Artificial Intelligence Technology

Resources for students: 

• Policies from Columbia Student Conduct and Community Standards
• Understanding the Academic Integrity Policy (Columbia College & School of Engineering and Applied Sciences)

Student support resources:

• Maximizing Student Learning Online (Columbia Online)
• Center for Student Advising Tutoring Service (Berick Center for Student Advising)
• Help Rooms and Private Tutors by Department (Berick Center for Student Advising
• Peer Academic Skills Consultants (Berick Center for Student Advising)
• Academic Resource Center (ARC) for School of General Studies
• Center for Engaged Pedagogy (Barnard College)
• Writing Center (for Columbia undergraduate and graduate students)
• Counseling and Psychological Services
• Disability Services

For graduate students: 

• Writing Studio (Graduate School of Arts and Sciences)
• Student Center (Graduate School of Arts and Sciences)
• Teachers College

Columbia University Information Technology (CUIT) CUIT’s Academic Services provides services that can be used by instructors in their courses such as Turnitin , a plagiarism detection service and online proctoring services such as Proctorio , a remote proctoring service that monitors students taking virtual exams through CourseWorks. 

Center for Teaching and Learning (CTL) The CTL can help you think through your course policies, ways to create community, design course assessments, and setting up CourseWorks to promote integrity, among other teaching and learning facets. To schedule a one-on-one consultation, please contact the CTL at [email protected] . 

References 

Bernard, W. Jr. and Keith-Spiegel, P. (2002).  Academic Dishonesty: An Educator’s Guide . Mahwah, NJ: Psychology Press.

Bertram Gallant, T. (2017).  Academic Integrity as a Teaching and Learning Issue: From Theory to Practice .  Theory Into Practice,  56(2), 88-94.

Bertram Gallant, T. (Ed.). (2008).  Academic Integrity in the Twenty-First Century: A Teaching and Learning Imperative .  ASHE Higher Education Report . 33(5), 1-143. 

Columbia Center for Teaching and Learning (2020).  Creating Online Exams . 

Columbia Center for Teaching and Learning (2020).  Working with TAs online . 

Darby, F. (2020).  7 Ways to Assess Students Online and Minimize Cheating .  The Chronicle of Higher Education.  

Gonzalez, J. (2017, February).  Teaching Students to Avoid Plagiarism . Cult of Pedagogy, 26.

International Center for Academic Integrity (2023).  Fundamental Values of Academic Integrity .

International Center on Academic Integrity (2023).  https://academicintegrity.org/

Keith, T. Combating Academic Dishonesty, Part 1 – Understanding the Problem. The University of Chicago. (2022, Feb 16).

Lang, J.M. (2013a).  Cheating Lessons: Learning from Academic Dishonesty . Harvard University Press.

Lang, J. M. (2013b).  Cheating Lessons, Part 1 .  The Chronicle of Higher Education. 

Lang, J. M. (2013c).  Cheating Lessons, Part 2 .  The Chronicle of Higher Education. 

Lederman, D. (2020, February 19).  Course Hero Woos Professors . Inside Higher Ed. 

McKenzie, L. (2018, May 8).  Learning Tool or Cheating Aid?   Inside Higher Ed.

Marche, S. (2022, Dec 6). The College Essay is Dead. The Atlantic.

Mollick, E. (2023, Jan 17). All my Classes Suddenly Became AI Classes. One Useful Thing.

Mollick, Ethan. (2022, Dic 8). Four Paths to the Revelation. One Useful Thing.

Wexler, N. Bots’ Can Write Good Essays, But That Doesn’t Make Writing Obsolete. Minding the Gap.

Additional Resources

Bretag, T. (Ed.). (2016). Handbook of Academic Integrity. Singapore: Springer Publishing.

Ormand, C. (2017 March 6).  SAGE Musings: Minimizing and Dealing with Academic Dishonesty . SAGE 2YC: 2YC Faculty as Agents of Change.

WCET (2009).  Best Practice Strategies to Promote Academic Integrity in Online Education .

Thomas, K.  (2022 February 16). Combating Academic Dishonesty, Part 1 – Understanding the Problem. The University of Chicago. Academic Technology Solutions.

______. (2022 February 25). Combating Academic Dishonesty, Part 2: Small Steps to Discourage Academic Dishonesty. The University of Chicago. Academic Technology Solutions.

______.  (2022 April 28). Combating Academic Dishonesty, Part 3: Towards a Pedagogy of Academic Integrity. The University of Chicago. Academic Technology Solutions.

______.  (2022 June 7). Combating Academic Dishonesty, Part 4: Library Services to Support Academic Honesty. The University of Chicago. Academic Technology Solutions.

Acknowledgement

This resource was adapted from the faculty booklet  Promoting Academic Integrity & Preventing Academic Dishonesty: Best Practices at Columbia University  developed by Victoria Malaney Brown, Director of Academic Integrity at Columbia College and Columbia Engineering, Abigail MacBain and Ramón Flores Pinedo, PhD students in GSAS. We would like to thank them for their extensive support in creating this academic integrity resource.

Want to communicate your expectations around AI tools?

See the CTL’s resource “Considerations for AI Tools in the Classroom.”

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Central to any academic writing project is crediting (or citing) someone else' words or ideas. The following sites will help you understand academic writing expectations.

Academic integrity is truthful and responsible representation of yourself and your work by taking credit only for your own ideas and creations and giving credit to the work and ideas of other people. It involves providing attribution (citations and acknowledgments) whenever you include the intellectual property of others—and even your own if it is from a previous project or assignment. Academic integrity also means generating and using accurate data.

Responsible and ethical use of information is foundational to a successful teaching, learning, and research community. Not only does it promote an environment of trust and respect, it also facilitates intellectual conversations and inquiry. Citing your sources shows your expertise and assists others in their research by enabling them to find the original material. It is unfair and wrong to claim or imply that someone else’s work is your own.

Failure to uphold the values of academic integrity at the GSD can result in serious consequences, ranging from re-doing an assignment to expulsion from the program with a sanction on the student’s permanent record and transcript. Outside of academia, such infractions can result in lawsuits and damage to the perpetrator’s reputation and the reputation of their firm/organization. For more details see the Academic Integrity Policy at the GSD. 

The GSD’s Academic Integrity Tutorial can help build proficiency in recognizing and practicing ways to avoid plagiarism.

• Avoiding Plagiarism (Purdue OWL) This site has a useful summary with tips on how to avoid accidental plagiarism and a list of what does (and does not) need to be cited. It also includes suggestions of best practices for research and writing.
• How Not to Plagiarize (University of Toronto) Concise explanation and useful Q&A with examples of citing and integrating sources.

This fast-evolving technology is changing academia in ways we are still trying to understand, and both the GSD and Harvard more broadly are working to develop policies and procedures based on careful thought and exploration. At the moment, whether and how AI may be used in student work is left mostly to the discretion of individual instructors. There are some emerging guidelines, however, based on overarching values.

Since policies are changing rapidly, we recommend checking the links below often for new developments, and this page will continue to update as we learn more.

• Generative Artificial Intelligence (AI) from HUIT Harvard's Information Technology team has put together this webpage explaining AI and curating resources about initial guidelines, recommendations for prompts, and recommendations of tools with a section specifically on image-based tools.
• Generative AI in Teaching and Learning at the GSD The GSD's evolving policies, information, and guidance for the use of generative AI in teaching and learning at the GSD are detailed here. The policies section includes questions to keep in mind about privacy and copyright, and the section on tools lists AI tools supported at the GSD.
• AI Code of Conduct by MetaLAB A Harvard-affiliated collaborative comprised of faculty and students sets out recommendations for guidelines for the use of AI in courses. The policies set out here are not necessarily adopted by the GSD, but they serve as a good framework for your own thinking about academic integrity and the ethical use of AI.
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Academic Integrity Perspectives: Insights from Africa

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• Stella-Maris Orim 2 &
• Anirejuoritse Awala-Ale 3  

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Integrity is crucial to the pursuit of academic knowledge in learning institutions, and the need for the increasing spotlight on academic integrity in the African context cannot be overemphasized. This is because, although several pockets of good practice have been identified over the last decade, there are still instances of higher institutions that are replete with reported and unreported cases of academic integrity breaches, making the goal of achieving academic integrity a major challenge. This could be, in part, as a result of various perspectives of what constitutes academic integrity in the African context, in light of diverse cultural perspectives.

A number of factors have been identified as being responsible for this variation, including the education system, pedagogy, sociocultural environment, economic environment, infrastructure, technology, institutional policies, and management systems.

This chapter focuses on the perspectives drawn from available authors focusing on academic integrity in diverse higher institutions in Africa. The prevailing academic integrity themes are then grouped, providing a synopsis of the different perspectives of academic integrity in Africa. An evaluation of the identified key themes and relevant theoretical frameworks is carried out while examining the impact of the different perspectives on the academic climate and academic integrity-related issues. It also provides an overview of the development and findings of research and practice in the field of academic integrity in African higher institutions, highlighting the unique issues.

It concludes by presenting an overview of the major challenges associated with academic integrity and possible ways of instituting a culture of integrity in the African academic system.

• Academic climate
• Academic integrity
• Academic integrity-related issues
• African academic system
• African higher institutions
• Culture of integrity
• Perspectives
• Policies and practices
• Theoretical frameworks

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Orim, SM., Awala-Ale, A. (2023). Academic Integrity Perspectives: Insights from Africa . In: Eaton, S.E. (eds) Handbook of Academic Integrity. Springer, Singapore. https://doi.org/10.1007/978-981-287-079-7_9-2

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Impact of academic integrity on workplace ethical behaviour

• Jean Gabriel Guerrero-Dib   ORCID: orcid.org/0000-0003-3150-9363 1 ,
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Corruption is a serious problem in Mexico and the available information regarding the levels of academic dishonesty in Mexico is not very encouraging. Academic integrity is essential in any teaching-learning process focussed on achieving the highest standards of excellence and learning. Promoting and experiencing academic integrity within the university context has a twofold purpose: to achieve the necessary learnings and skills to appropriately perform a specific profession and to develop an ethical perspective which leads to correct decision making. The objective of this study is to explore the relationship between academic integrity and ethical behaviour, particularly workplace behaviour. The study adopts a quantitative, hypothetical and deductive approach. A questionnaire was applied to 1203 college students to gather information regarding the frequency in which they undertake acts of dishonesty in different environments and in regards to the severity they assign to each type of infraction. The results reflect that students who report committing acts against academic integrity also report being involved in dishonest activities in other contexts, and that students who consider academic breaches less serious, report being engaged in academic misconduct more frequently in different contexts. In view of these results, it is unavoidable to reflect on the role that educational institutions and businesses can adopt in the development of programmes to promote a culture of academic integrity which: design educational experiences to foster learning, better prepare students to fully meet their academic obligations, highlight the benefits of doing so, prevent the severity and consequences of dishonest actions, discourage cheating and establish clear and efficient processes to sanction those students who are found responsible for academic breaches.

Introduction

Corruption and dishonesty are deeply rooted problems and have a long history in many countries and communities and Mexico is no exception. There is usually more attention given to corrupt activities perpetrated by government authorities and public officers. The fact that many of these instances of corruption are carried out with the collusion of private sector businesses and individuals is largely ignored. Private citizens themselves are usually involved in corrupt activities where they can gain a personal benefit through the abuse of their position of power or authority (Rose-Ackerman and Palifka 2016 ).

Rose-Ackerman and Palifka ( 2016 ) affirm that personal ethical standards are one of the three categories of causes that promote corruption. This moral “compass” develops through a long and complex educational process which starts at home and, we could say, ends with death. Education becomes one of the key elements in the global strategy for the promotion of a culture of integrity and the fight against corruption. It is difficult to think that education can contribute efficiently if the phenomenon of academic dishonesty exists within the educational sphere. To develop a moral compass, it is not enough to know what has to be done, it is essential to do good (Amilburu 2005 ).

In almost every educational system in the world, it is a widely held view that all people must receive mandatory basic education, thus, almost all children and youths are subject to experience -or not experience- academic integrity during their education, a period that is long enough to develop habits. Daily behaviours during these mainly formative years may be considered as the standard that can perpetuate itself over time (Programa de las Naciones Unidas para el Desarrollo 2015 ).

In addition to the work carried out by the basic educational system, the university must fully form and develop the moral vision and purpose of its students, since it is not possible to consider professional education separate from ethical formation. Being a professional must include not only mastery of technical, practical and/or theoretical competencies, but also personal integrity and ethical professional behaviour that helps to give an ethical meaning to all university endeavours (Bolívar 2005 ). In so doing, academic integrity is necessary to learn and an essential requirement of academic quality.

Academic integrity is much more than avoiding dishonest practices such as copying during exams, plagiarizing or contract cheating; it implies an engagement with learning and work which is well done, complete, and focused on a good purpose – learning. It also involves using appropriate means, genuine effort and good skills. Mainly it implies diligently taking advantage of all learning experiences. From this perspective, experiencing and promoting academic integrity in the university context has a twofold purpose: achieving the learning intended to develop the necessary competencies and skills for a specific profession and, more importantly, developing an ethical perspective for principled decision making applicable to any context (Bolívar 2005 ).

Orosz et al. ( 2018 ) identified a strong relationship between academic dishonesty and the level of corruption of a country. Other studies (Blankenship and Whitley 2000 ; Harding et al. 2004 ; Laduke 2013 ; Nonis and Swift 2001 ; Sims 1993 ) demonstrate that students who engage in dishonest activities in the academic context, particularly undergraduate students, are more likely to demonstrate inappropriate behaviours during their professional life and vice versa.

From this point of view one can say that: the individual who is used to cheating in college, has a higher probability of doing so in the professional and work fields (Harding et al. 2004 ; Payan et al. 2010 ; Sims 1993 ).

Taking these studies in other parts of the world as a reference, the objective of the current work is to determine the relationship between the most frequent academic dishonesty practices, or lack of academic integrity amongst college students, and their predisposition to demonstrate ethical behaviour at work and in their daily lives within the Mexican context.

This research paper is divided into four sections. The first one presents a brief review of literature on academic integrity, academic dishonesty and its relationship with workplace ethical behaviour. The second section presents the methodology followed during the study, considering the design and validation of the instrument, data gathering, and the generation of academic dishonesty and ethical behaviour indexes. The third section shows the results of the analysis and its discussion. The last section displays a series of conclusions for the research presented, as well as its limitations and scope.

Literature review

• Academic integrity

According to Bosch and Cavallotti ( 2016 ), the term integrity has four common elements that are included in the different ways to describe it: justice, coherence, ethical principles and appropriate motivation. Thus, a definition in accordance to this concept would be to act with justice and coherence, following ethical principles and a motivation focused on good purposes. In the educational context, academic integrity could be understood as the habit of studying and carrying out academic work with justice and coherence, seeking to learn and to be motivated by the service that this learning can provide others. However, there has been a wide variety of interpretations about this concept (Fishman 2016 ).

The International Center for Academic Integrity (ICAI), conceptualizes academic integrity as a series of basic principles which are the foundation for success in any aspect of life and represent essential elements that allow achievement of the necessary learning which enable the future student to face and overcome any personal and professional challenges (International Center for Academic Integrity 2014 ).

Academic integrity is considered a fundamental quality for every academic endeavour, essential in any teaching-learning process focused on achieving the highest standards of excellence and learning and thus, it must represent a goal to which every academic institution, seriously engaged in quality, must aspire to (Bertram-Gallant 2016 ). Enacting academic integrity means taking action with responsibility, honesty, respect, trust, fairness, and courage in any activity related to academic work and avoiding any kind of cheating or dishonest action even when the work is especially difficult (International Center for Academic Integrity 2014 ).

The current approaches to academic integrity provide ideas offering a conceptual framework, but there is still the need to specify concrete academic integrity behaviours characteristic of students such as: speaking the truth, complying with classes and assignments, carrying out activities by their own efforts, following the instructions given, providing answers on exams with only the material approved, citing and giving credit to others’ work, and collaborating fairly during teamwork assignments (Hall and Kuh 1998 ; Von Dran et al. 2001 ). To these “observable” behaviours we must add a condition: that they must be preceded by the desire to learn in order to call them genuine manifestations of academic integrity (Olt 2002 ; Sultana 2018 ).

Despite the importance of the academic integrity concept, in most cases it is common to find an explanation of the concept in more negative terms that refers to behaviours that should be avoided. The general idea expressed in most honor codes is that academic integrity is to do academic work avoiding dishonesty, fraud or misconduct.

Dishonesty and academic fraud

Stephens ( 2016 ) argues that the problem of cheating is endemic and is at the root of human nature, thus it should not be surprising that it occurs. It is a strategy, conscious or not, used by humans to solve a problem. However, recognizing that cheating has always existed should not foster a passive and pessimistic attitude since human beings have a conscience that enables them to discern ethical behaviours from those that are not.

Understanding the phenomenon of dishonesty is important since the strategies used to try to counteract it will depend on this. For example, if dishonesty is considered a genetic disorder that some people suffer, the way to deal with it would be to identify those who suffer from it, supervise them, segregate them and/or try to “treat” them. If it is a common deficiency that everyone experiences to a greater or smaller degree, other kinds of tactics should be used to counteract it (Ariely 2013 ).

In general terms, there are different types of academic dishonesty that may be grouped into four major categories:

Copying. Copying or attempting to copy from a classmate during an examination or assessment.

Plagiarism. Copying, paraphrasing or using another author’s ideas without citing or giving the corresponding credit to them.

Collusion. Collaboration with someone else’s dishonesty, and includes not reporting dishonest actions which have been witnessed. The most representative actions of this type of misconduct are: submitting assignments on behalf of classmates, allowing others to copy from you during an exam and including the names of people who did not participate in teamwork assignments or projects.

Cheating. Among the most common actions in this category we find: using notes, technology or other forbidden materials during an exam; including non-consulted references; inventing or making up data in assignments or lab reports; contract cheating; distributing or commercializing exams or assignments; submitting apocryphal documents; impersonating another student’s identity; stealing exams; altering grades; bribing individuals to improve grades.

The list is not exhaustive since it does not include every possible type of dishonesty. Every situation creates unique circumstances and different nuances so it should not be surprising that the emergence of “new” ways to threaten academic integrity arise (Bertram-Gallant 2016 ). Students’ creativity and the continual development of technology will cause different manifestations of academic fraud (Gino and Ariely 2012 ), a fact that has been documented in university contexts in the past.

The results of recent research show that 66% of students have engaged in some type of academic misconduct at least once during their university education (Lang 2013 ). There are similar results in other studies carried out around the world. In the Mexican case, 84% of students in a Mexican university have witnessed a dishonest action during their education (UDEM 2018 ), and 6 out of 10 at another university have engaged in some kind of copying (UNAM 2013 ). In Colombia, a private university reported that 63% of the students accepted the addition of the name of a classmate that did not collaborate actively on a team assignment (EAFIT 2016 ). In England, half of the students would be willing to buy an assignment (Rigby et al. 2015 ). In Ukraine, 82% of students have used non-authorized support during exams (Stephens et al. 2010 ). While in China, 71% of students at one university admit to having copied a homework assignment from his/her classmates (Ma et al. 2013 ).

Academic dishonesty and its relationship with the lack of ethical professional behaviour

Establishing a relationship between the level of corruption in a country and the level of academic dishonesty in its educational institutions is a difficult task to carry out since fraud and corruption have many different forms and causes, particularly in complex contexts such as the social dynamics of a country (International Transparency 2017 ). However, it can be established that academic dishonesty is a manifestation of a culture in which it is easy and common to break rules and where integrity is not as valued as it should be. Under this logic, it is possible to establish a certain relationship between a poor civic culture and academic dishonesty (García-Villegas et al. 2016 ).

This poor civic culture tends to be reflected in the daily activities of the citizens, particularly within organizations, where a relationship between students who cheat and unethical behaviour in the workplace has been identified (Winrow 2015 ). From this point of view, integrity and ethical behaviour, expressed in different terms such as decision making, conflict resolution or accountability, is one of the competencies most requested by employers (Kavanagh and Drennan 2008 ) and one of the critical factors needed to efficiently develop inter-organizational relationships of trust (Connelly et al. 2018 ). This is the reason behind the study, the understanding of this relationship.

A study carried out with 1051 students from six North American universities concluded that students who considered academic dishonesty as acceptable tended to engage in such activities and the same individuals tended to show unethical behaviour later during their professional lives (Nonis and Swift 2001 ). In another study with Engineering students, it was found that those who self-reported having engaged in dishonest actions, also carried it out in the professional field, which suggests that unethical behaviour shown at the college level continued into professional life (Harding et al. 2004 ). Findings of another study carried out at a nursing school demonstrated that students who showed academic dishonesty had a greater incidence of dishonest behaviour once they worked as health professionals (Laduke 2013 ).

In a study carried out with 284 psychology students who reported having engaged in some kind of academic dishonesty, specifically having copied during exams and lying in order to meet their obligations during their college education, also reported participating in actions considered illegal or unethical within the context of the research, specifically those related to substance abuse - alcohol and drugs, risky driving, lying and other sort of illegal behaviours. This data suggests that, besides the contextual factors, there are also individual causes such as attitudes, perceptions and personality traits that can influence the individual’s behaviour in different aspects of their lives (Blankenship and Whitley 2000 ).

In one of the most recent studies, where data from 40 countries was collected, a strong relationship was identified between the self-reporting “copying in exams” of the student population and the level of corruption of the country, expressed in the corruption perception index published by Transparency International (Orosz et al. 2018 ).

Despite the increase in the number of studies related to academic integrity and ethical behaviour in the companies in different parts of the world since the 1990s, it has not been possible to identify any research in Mexico that explores the relationship between the ethical behaviour of an individual in his/her different life stages, as a college student and as a professional; or to put it differently, between academic integrity and ethical performance in the workplace.

Methodology

This study followed a quantitative approach under a hypothetic - deductive approach. Since there is no suitable instrument available that explores the relationship between academic integrity and ethical behaviour, one designed for this study was used. It was based on questions from previous research instruments.

The “International Center for Academic Integrity” (ICAI) perception survey, created by Donald McCabe and applied to more than 90,000 students in the United States and Canada (McCabe 2016 ) was adapted with the addition of a section of questions related to personal and workplace ethical behaviour.

The McCabe survey ( 2016 ) consists of 35 questions that can be grouped into four sections. The first one explores the characteristics of the academic integrity programme, the educational atmosphere in general and the way in which the community is informed and trained in regards to current regulations. The second one requests information about the students’ behaviour. It specifically asks about the frequency with which students are involved in dishonest activities at the moment and in previous academic levels, how severe they considered each kind of misconduct and their perception in regards to the level of peer participation in actions against integrity. The third section collects the opinions of the students regarding different statements related to academic work, faculty and students’ engagement in the development of an academic integrity culture, strategies to fight dishonesty, the degree of social approval towards academic fraud, its impact and the perception of fairness in managing the cases of misconduct. The last group included demographic questions that contained basic information about the person answering the survey. The students were asked to provide their age, gender, marital status, nationality, place of residence, accumulated grade point average (GPA), programme he/she studies and the number of years at the university.

A section was added to this survey (Additional file  1 ) addressing the professional ethical behavioural construct. In this section, items from questionnaires described in Table  1 were used; all related to self-reporting of ethical behaviour. An additional validation was carried out for this instrument section through the assessment of experts from the internal control area of different companies and industries.

Except for a couple of open questions, the rest of the items used responses built under a five-point Likert scale to categorize their judgments in regards to the statements suggested. There are two types of responses used specifically: from totally agree to totally disagree about the perceptions and opinions; and always or never in the case of self-reported behaviours.

The responses were recorded automatically in the data base of the SurveyMonkey technology tool and values were assigned to each one of the responses in order to calculate an index per response, assigning a value of 5 to “Totally agree” and 1 to “Totally disagree” in a positive or favorable statement, and vice-versa, 1 and 5 respectively, in a negative or unfavorable statement.

The sample considers 1203 undergraduate and graduate students from a private university in northern Mexico who chose to respond to their professors’ invitations to answer the survey as part of a diagnostic exercise that the university carries out periodically to learn about the students’ perceptions regarding the degree of academic integrity culture on their campus. The participants were 51% women and 49% men. From them, 31% were in their first year, 25% the second year, 26% the third year, 11% the fourth year and only 7% had been studying for five or more years. Nearly 70% of the students still lived in their parents’ homes and 42% reported having a good or outstanding average grade (higher than 80 over 100).

Once the data was collected, the internal validation of the instrument was done and indexes were generated for each one of the variables introduced into the model, through a factorial analysis of the main components. This type of analysis studies the relationship between a set of indicators or variables observed and one or more factors related to the research to obtain evidence and thus, validate the theoretical model (Hayton et al. 2004 ).

In order to define the indexes related to academic fraud and ethical behaviour there were three factorial analyses carried out, which took as selection criteria eigenvalues higher than one and varimax component rotation with the purpose to maximize the variances explained for each response and identify the items that represented the factors identified by the analysis itself in a linear way (Thompson 2004 ).

The first analysis considered questions related to the level of frequency with which specific dishonest actions were carried out. It included 27 items or questions in total, and five components accounted for 66.33% of the variance, with a KMO (Kaiser, Meyer and Olkin) of 0.955 and being significant for the Bartlett’s sphericity test, a fact that shows the internal consistency of the indicator and its statistical validity. The five components were classified according to the weight that each question had in the rotated and stored components matrix such as regression variables to generate an indicator for each of them (Table 5 in Appendix). These indicators were defined as frequency in: 1) cheating in general, 2) copying in any way, 3) falsifying information, 4) using unauthorized support, and 5) plagiarizing or paraphrasing without citing.

The second analysis took the same criteria of the latter, but it only included the 27 questions related to how severe the misconduct or academic dishonesty was considered. The result was three components that accounted for 67.66% of the variance observed, with a KMO of 0.962 and the Bartlett’s sphericity test was significant. The rotated components were classified and kept as a regression to generate three indicators, related to the perceived severity of: 1) cheating in general, 2) plagiarizing or copying and paraphrasing without citing, and 3) using unauthorized support (Table  6 in Appendix ).

The third factorial analysis included the 47 questions related to the behaviour or ethical attitude of the respondents. This analysis generated six components that accounted for 64.54% of the variance observed, a KMO of 0.963 and the Bartlett’s sphericity test was significant. When analyzing the components generated by the analysis, it was observed that four of them had only two questions with a weight greater than 0.4 in the rotated component matrix. Considering this situation, it was decided to eliminate these questions and a new factorial analysis was carried out considering only 39 questions. The result was two main components that accounted for 58.66% of the variance observed, with a KMO of 0.965 and the Bartlett’s sphericity test was significant. The two components were classified into two indicators: 1) workplace ethical behaviour and, 2) personal ethical behaviour (Table  7 in Appendix ).

Once the indicators for frequency and perceived severity of dishonesty or academic fraud, as well as those related to the behaviour or self-reported ethical attitude (workplace and personal) were generated, a linear regression analysis was carried out to determine how academic dishonesty influences a specific ethical behaviour.

The linear regression analysis took as dependent variables the ones related to ethical behaviour self-reported by the respondents, and the frequency and severity of the academic dishonesty acts reported by the respondents as the independent variables. This analysis was carried out in two stages; the first one considered only the variable of the frequency with which academic dishonesty was reported, and the second one considered the variables related to the severity with which the respondents perceived these actions.

The first analysis took as independent variables the frequency of each component of self-reported academic misconduct: cheating in general, copying in any way, falsifying information, using unauthorized support, and plagiarizing or paraphrasing without citing. The result of the model was significant for the case of workplace ethical behaviour (sig. = 0.001), accounting for only 3.4% of the variance observed (Table  2 ). In terms of analysis by variables, it was found that only the frequency of carrying out any kind of cheating, and copying in any way, had a significant impact on the workplace ethical behaviour of the respondents. The negative coefficient in both cases shows that a frequency reduction in academic misconduct, increased the self-reported workplace ethical behaviour (Table 2 ). The variables for falsifying information, using unauthorized support and plagiarizing didn’t show significance.

In terms of personal ethical behaviour, the model proved significant (sig. = 0.000) explaining 9% of the variance (Table 2 ) thus it may be stated that the severity of academic dishonesty influences personal ethical behaviour. In regards to the impact level that the variables have on personal ethical behaviour, we found that only using unauthorized support did not prove significant. The remaining variables were significant and with negative coefficients, thus we may conclude that the lower the frequency of academic dishonesty reported by the respondents, the higher the reported personal ethical behaviour. In this sense, the variable of cheating in general had a greater weight in this kind of behaviour, followed by falsifying information and lastly plagiarizing.

The obtained results indicate that engaging in academic dishonesty with a greater frequency is directly and negatively related to the respondent’s ethical behaviour and attitude. Therefore, it can be assumed that discouraging students from carrying out academic dishonesty will have a positive effect on their ethical behaviour, both in the work context as well as in their daily lives. In the same way, it was also found that respondents who performed academic dishonest activities less frequently, tended to have better ethical behaviour in general.

It is interesting to observe that the model does little to explain workplace ethical behaviour and that only the variable of cheating in general and copying had significant impacts on this behaviour. While in the case of personal ethical behaviour, academic dishonesty practices occurred more frequently and only the use of unauthorized support had no significant impact. This situation allows us to assume that academic dishonesty practices have a greater impact on daily ethical behaviour but less so in the workplace. This situation can be explained by the fact that organizations have codes of ethics and programmes which guide actions to be carried out by their personnel that are based on specific ethical and moral rules of conduct.

The second regression analysis took as independent variables the ones related to the perceived severity of the respondents in regards to cheating in general, copying and plagiarizing, and using unauthorized support. As in the previous case, the dependent variables were the ones related to the behaviour or ethical attitude in the workplace and in personal contexts. In regards to the workplace, we found that the model proved significant (sig. = 0.000), explaining 10% of the variance observed (Table 3 ). Despite this result, the variable analysis showed that only the cheating in general variable had a significant impact on such behaviour with a positive coefficient, which means that the greater the perceived severity of the misconduct, the better the ethical behaviour within the organization.

In the case of personal ethical behaviour, the model also proved significant (sig. = 0.001), explaining only 5% of the variance observed in the indicator. In the case of workplace ethical behaviour, only the perceived severity of cheating in general variable had a significant impact on personal ethical behaviour. The positive coefficient of this variable enables us to establish that when any type of cheating was rated as severe, respondents tended to have better personal ethical behaviour (Table 3 ).

The findings enable us to recognize the impact that the perceived severity towards cheating in general has on the ethical behaviour of the respondents, since it is the only variable that proved significant in the model. Hence, the extent to which students perceived the committing of any kind of cheating within the university as severe, their behaviour, both inside and outside the workplace, was more ethical.

Additionally, it is interesting to observe that the perception of the severity of cheating, plagiarizing or using any kind of unauthorized help does not have a significant impact on the ethical behaviour self-reported by the respondents. Therefore, it can be assumed that it is not as important to point out the severity of a specific act of academic dishonesty to influence the ethical behaviour of students and professionals, but rather to emphasize the severity of the misconduct that is associated with any act of academic dishonesty.

With the aim to identify the relationship that exists among all the variables of the model (frequency and severity), a third regression was conducted. This regression considered as independent variables, workplace ethical behaviour and personal ethical behaviour, and as dependent variables, the frequency and severity of academic misconduct. Both models, ethical behaviour in the workplace and personal, turned out to be significant. In the case of the workplace ethical behaviour, it was found that the model explains 9.1% of the variance of the indicator, while in the case of personal ethical behaviour, only 7.4% of the variance was explained (Table  4 ). Based on these results, it can be concluded that the lack of academic integrity generally affects people’s ethical behaviour.

It is interesting to note that, in the case of ethical behaviour in the workplace, the only variable that was significant and positive was the severity of widespread dishonesty. That is, those respondents who considered any type of dishonesty as a serious offense had a greater tendency to be ethical in their workplace. This situation may be supported by the fact that academic integrity is presented in institutionalized spaces, such as school, university or business, and where the perception of greater severity tends to limit unethical behaviour within these institutions or organizations.

On the other hand, personal ethical behaviour was significantly influenced by the variables related to committing any act of academic dishonesty in general (frequency and severity). The negative sign in frequency indicates that those who reported having committed less academic dishonesty - whichever it may be - have better ethical behaviour on a personal level. In the same way, those who consider that committing academic dishonesty is something serious, also have a better ethical behaviour on a personal level. Another variable that was significant was the frequency in plagiarism or paraphrasing without citing, in the personal ethical behaviour, being those that had a lower frequency the ones that reported a better ethical behaviour.

The results of this third regression complement the findings of the first two regressions and allow to evidence the specific weight of considering academic dishonesty as a serious fault in people’s ethical behaviour.

Based on the results generated in the previous section, some reflections and conclusions can be drawn related to academic integrity, academic misconduct, and ethical behaviour.

The respondents’ ethical behaviour shows a relationship to the practice of academic dishonesty, both in terms of the frequency with which they carry out these acts, as well as the severity they assign to them. The more severe the students consider an act of academic dishonesty, the more ethically they behave outside of the university. Likewise, it is important to establish measures to discourage or reduce the number of acts of academic misconduct, since the habitual practice of unethical actions may promote a normalization of these behaviours, and reduces a student’s interest in practising ethical behaviours after graduating from college. It is important to disclose a basic assumption, that a person faces ethical dilemmas first, in an educational environment and later, in a workplace context. This situation suggests that, since academic integrity is usually experienced earlier than workplace ethical behaviour in a person’s life, the former may influence the latter.

These results encourage the reflection on the importance of student perceptions about academic dishonesty and the opportunities they have to act on these dishonest practices. Interestingly, in terms of perception, students who have developed a conscience about the severity of any kind of cheating in an academic setting, exhibit a greater degree of ethical behaviour. Likewise, when a student frequently practices academic misconduct shows less ethical behaviour within other contexts. These findings add another reason why higher education institutions should establish systematic programmes focused on promoting a culture of academic integrity to convince students of the severity of these unethical actions, to discourage them from committing them and to punish them if the previous endeavours do not work.

The results of this study suggest that it is not enough to teach academic integrity in a theoretical or conceptual way, but that it is learned and acquired through real contexts and practices, where the prevention or discouragement of gaining benefits through misconduct contributes to student learning and development. This learning goes beyond the classroom and the university context and becomes an ethical behavioural pattern in the work and personal environments. Likewise, organizations should have ethical codes and other elements of a business ethics and compliance programme to foster a culture of integrity and continue the formative process started within educational institutions.

It can be stated that a part of a professional’s ethical behaviour is related to their awareness of the risks or severity of getting involved in academic dishonesty, as well as having the opportunity to engage in these acts. For this reason, it is not enough to convince students of the importance of following integrity criteria, it is also necessary to create an environment where cheating or deceptions are very difficult to practice. It is essential that students are convinced to act with integrity during their college years and that they are made aware of the risks or penalties that come with not doing so. This will strengthen a positive behavioural pattern in different contexts of their lives, and encourage them to become ethical professionals, business people, and citizens.

It is essential for higher education institutions to demonstrate a commitment to building a culture of academic integrity, both in terms of their awareness and their practice, since through them the ethical behaviour of students and future graduates is strengthened and forged. In this respect, the university campus is featured as a favourable environment to train individuals and promote ethical behaviour within and outside the university, meeting its commitment to the community and the world to develop more ethical and engaged citizens who do things well in all aspects of their lives.

Conclusions

There has been little research published regarding the relationship of students perceptions about their behaviour on academic integrity in schoolwork, and on professional performance. This study, like the ones identified previously, points out a relationship that can and should be explored in greater depth. Academic integrity - concept, benefits, strategies - and its counterpart, academic dishonesty - frequency causes, consequences, management - have not received, in México and Latin America, the attention they have earned in other countries and regions.

Considering that corruption is a major problem afflicting Mexican society and that academic dishonesty is related one way or another with corruption, it becomes particularly important to understand the academic dishonesty phenomenon in depth.

In order to achieve this, it is necessary to invest resources to identify the strategies which most effectively promote academic integrity, because doing so, not only prevents fraud and economic losses, but also builds the foundations of a more humane and fair society, resulting in a common interest. Viewed from this perspective, academic integrity is not an issue that should be addressed only within educational institutions, but it should also awaken the interest and the action of the business and production sectors.

Limitations of the research

The instrument used to collect information for this research project was a survey created with the support of others and thus the questions have only been validated in this exercise.

It is a self-reporting tool regarding ethical behaviour, that is, it reflects the self-reported participants’ perceptions of themselves and not about their own behaviours. This situation shows two limitations. The first one is that it does not discuss behaviours per se, but the perception participants have about them. The second limitation is that the results are subjected to the biases of the same person who self-reports. The results depend not only on the “objectivity” of respondent’s perception but also on the sincerity with which each question is answered. Despite the prevailing atmosphere of illegality, it is still desirable to seem somewhat honest to others. Additionally, the application of the survey was done via an electronic format on the personal devices of the participants, which can raise suspicions about the true anonymity of the participants’ responses.

Self-reported surveys leave aside the profound answers related to the causes of correlations found. A qualitative approach to the phenomenon could complement our results and lead to a more in depth analysis of the relationship between corruption and/or unethical behaviour and academic dishonesty in the Mexican context.

Another important limitation of the study, derived from its exploratory perspective, is that the instrument did not consider as a relevant variable the employment situation, years of work experience or hierarchical level of the respondents. This limitation causes the self-report of ethical behaviour in the workplace to be presented in a general way and not with a greater level of depth. However, the results found in this research and the identification of the relationship between academic integrity and ethical work behaviour in an exploratory way, open the door for studies where it is sought to deepen the understanding of this relationship that was identified by this study, as mentioned in the next section.

Implications for future investigations

As mentioned in the previous section, the following works related to the study of the academic integrity and ethical behaviour of individuals could point to the confirmation of the results found in this research. These future studies could be based on the causal relationships found in this research, which were generated based on the review of the literature and the assumptions that arise from it. In this sense, the use of structural equations is necessary as a method of confirmation from a quantitative perspective, as well as the use of a qualitative approach that contribute to a better understanding of this phenomenon. This study is a first step towards the realization of scientific research that demonstrates the impact that efforts to promote academic integrity in universities have on the ethical behaviour of its students and graduates.

It would be useful to replicate the research by gathering information periodically to validate the results and/or conduct a longitudinal study that allows monitoring of the “real-time” habits of the different graduating classes over time. Thereby, self-reporting of what happened at each moment in time would be collected and would enable researchers to explore different associations.

Many questions still remain unanswered in the Mexican context: What is academic integrity? How is it experienced? How is it perceived? How is it assessed? What are the benefits in doing so? What are the most appropriate strategies? What are the levels of academic dishonesty? Who carries it out? Why do they do it? What are the reasons that cause it? What is the mindset of people that behaves ethically? What are the reasons why someone turns out to be more or less ethical? How should it be addressed and managed? What consequences does it trigger? What role do professors and other educational stakeholders play? What is the impact of technology?

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Standardized coefficients

Non-standardized coefficients

International Center for Academic Integrity

Kaiser, Meyer and Olkin

Adjusted R squared

Significance

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G-D designed the study and collected the data, P-D performed the statistical analysis, H-E contributed with results analysis. All authors discussed the results and contributed to the final manuscript. All authors read and approved the final manuscript.

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Guerrero-Dib, J.G., Portales, L. & Heredia-Escorza, Y. Impact of academic integrity on workplace ethical behaviour. Int J Educ Integr 16 , 2 (2020). https://doi.org/10.1007/s40979-020-0051-3

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More Studies by Columbia Cancer Researchers Are Retracted

The studies, pulled because of copied data, illustrate the sluggishness of scientific publishers to address serious errors, experts said.

By Benjamin Mueller

Scientists in a prominent cancer lab at Columbia University have now had four studies retracted and a stern note added to a fifth accusing it of “severe abuse of the scientific publishing system,” the latest fallout from research misconduct allegations recently leveled against several leading cancer scientists.

A scientific sleuth in Britain last year uncovered discrepancies in data published by the Columbia lab, including the reuse of photos and other images across different papers. The New York Times reported last month that a medical journal in 2022 had quietly taken down a stomach cancer study by the researchers after an internal inquiry by the journal found ethics violations.

Despite that study’s removal, the researchers — Dr. Sam Yoon, chief of a cancer surgery division at Columbia University’s medical center, and Changhwan Yoon, a more junior biologist there — continued publishing studies with suspicious data. Since 2008, the two scientists have collaborated with other researchers on 26 articles that the sleuth, Sholto David, publicly flagged for misrepresenting experiments’ results.

One of those articles was retracted last month after The Times asked publishers about the allegations. In recent weeks, medical journals have retracted three additional studies, which described new strategies for treating cancers of the stomach, head and neck. Other labs had cited the articles in roughly 90 papers.

A major scientific publisher also appended a blunt note to the article that it had originally taken down without explanation in 2022. “This reuse (and in part, misrepresentation) of data without appropriate attribution represents a severe abuse of the scientific publishing system,” it said .

Still, those measures addressed only a small fraction of the lab’s suspect papers. Experts said the episode illustrated not only the extent of unreliable research by top labs, but also the tendency of scientific publishers to respond slowly, if at all, to significant problems once they are detected. As a result, other labs keep relying on questionable work as they pour federal research money into studies, allowing errors to accumulate in the scientific record.

“For every one paper that is retracted, there are probably 10 that should be,” said Dr. Ivan Oransky, co-founder of Retraction Watch, which keeps a database of 47,000-plus retracted studies. “Journals are not particularly interested in correcting the record.”

Columbia’s medical center declined to comment on allegations facing Dr. Yoon’s lab. It said the two scientists remained at Columbia and the hospital “is fully committed to upholding the highest standards of ethics and to rigorously maintaining the integrity of our research.”

The lab’s web page was recently taken offline. Columbia declined to say why. Neither Dr. Yoon nor Changhwan Yoon could be reached for comment. (They are not related.)

Memorial Sloan Kettering Cancer Center, where the scientists worked when much of the research was done, is investigating their work.

The Columbia scientists’ retractions come amid growing attention to the suspicious data that undergirds some medical research. Since late February, medical journals have retracted seven papers by scientists at Harvard’s Dana-Farber Cancer Institute . That followed investigations into data problems publicized by Dr. David , an independent molecular biologist who looks for irregularities in published images of cells, tumors and mice, sometimes with help from A.I. software.

The spate of misconduct allegations has drawn attention to the pressures on academic scientists — even those, like Dr. Yoon, who also work as doctors — to produce heaps of research.

Strong images of experiments’ results are often needed for those studies. Publishing them helps scientists win prestigious academic appointments and attract federal research grants that can pay dividends for themselves and their universities.

Dr. Yoon, a robotic surgery specialist noted for his treatment of stomach cancers, has helped bring in nearly $5 million in federal research money over his career.

The latest retractions from his lab included articles from 2020 and 2021 that Dr. David said contained glaring irregularities . Their results appeared to include identical images of tumor-stricken mice, despite those mice supposedly having been subjected to different experiments involving separate treatments and types of cancer cells.

The medical journal Cell Death & Disease retracted two of the latest studies, and Oncogene retracted the third. The journals found that the studies had also reused other images, like identical pictures of constellations of cancer cells.

The studies Dr. David flagged as containing image problems were largely overseen by the more senior Dr. Yoon. Changhwan Yoon, an associate research scientist who has worked alongside Dr. Yoon for a decade, was often a first author, which generally designates the scientist who ran the bulk of the experiments.

Kun Huang, a scientist in China who oversaw one of the recently retracted studies, a 2020 paper that did not include the more senior Dr. Yoon, attributed that study’s problematic sections to Changhwan Yoon. Dr. Huang, who made those comments this month on PubPeer, a website where scientists post about studies, did not respond to an email seeking comment.

But the more senior Dr. Yoon has long been made aware of problems in research he published alongside Changhwan Yoon: The two scientists were notified of the removal in January 2022 of their stomach cancer study that was found to have violated ethics guidelines.

Research misconduct is often pinned on the more junior researchers who conduct experiments. Other scientists, though, assign greater responsibility to the senior researchers who run labs and oversee studies, even as they juggle jobs as doctors or administrators.

“The research world’s coming to realize that with great power comes great responsibility and, in fact, you are responsible not just for what one of your direct reports in the lab has done, but for the environment you create,” Dr. Oransky said.

In their latest public retraction notices, medical journals said that they had lost faith in the results and conclusions. Imaging experts said some irregularities identified by Dr. David bore signs of deliberate manipulation, like flipped or rotated images, while others could have been sloppy copy-and-paste errors.

The little-noticed removal by a journal of the stomach cancer study in January 2022 highlighted some scientific publishers’ policy of not disclosing the reasons for withdrawing papers as long as they have not yet formally appeared in print. That study had appeared only online.

Roland Herzog, the editor of the journal Molecular Therapy, said that editors had drafted an explanation that they intended to publish at the time of the article’s removal. But Elsevier, the journal’s parent publisher, advised them that such a note was unnecessary, he said.

Only after the Times article last month did Elsevier agree to explain the article’s removal publicly with the stern note. In an editorial this week , the Molecular Therapy editors said that in the future, they would explain the removal of any articles that had been published only online.

But Elsevier said in a statement that it did not consider online articles “to be the final published articles of record.” As a result, company policy continues to advise that such articles be removed without an explanation when they are found to contain problems. The company said it allowed editors to provide additional information where needed.

Elsevier, which publishes nearly 3,000 journals and generates billions of dollars in annual revenue , has long been criticized for its opaque removals of online articles.

Articles by the Columbia scientists with data discrepancies that remain unaddressed were largely distributed by three major publishers: Elsevier, Springer Nature and the American Association for Cancer Research. Dr. David alerted many journals to the data discrepancies in October.

Each publisher said it was investigating the concerns. Springer Nature said investigations take time because they can involve consulting experts, waiting for author responses and analyzing raw data.

Dr. David has also raised concerns about studies published independently by scientists who collaborated with the Columbia researchers on some of their recently retracted papers. For example, Sandra Ryeom, an associate professor of surgical sciences at Columbia, published an article in 2003 while at Harvard that Dr. David said contained a duplicated image . As of 2021, she was married to the more senior Dr. Yoon, according to a mortgage document from that year.

A medical journal appended a formal notice to the article last week saying “appropriate editorial action will be taken” once data concerns had been resolved. Dr. Ryeom said in a statement that she was working with the paper’s senior author on “correcting the error.”

Columbia has sought to reinforce the importance of sound research practices. Hours after the Times article appeared last month, Dr. Michael Shelanski, the medical school’s senior vice dean for research, sent an email to faculty members titled “Research Fraud Accusations — How to Protect Yourself.” It warned that such allegations, whatever their merits, could take a toll on the university.

“In the months that it can take to investigate an allegation,” Dr. Shelanski wrote, “funding can be suspended, and donors can feel that their trust has been betrayed.”

Benjamin Mueller reports on health and medicine. He was previously a U.K. correspondent in London and a police reporter in New York. More about Benjamin Mueller

How the Flint water crisis set schoolchildren back

School-age children affected by the water crisis in Flint, Mich., nearly a decade ago suffered significant and lasting academic setbacks, according to a study released Wednesday , showing the disaster’s profound impact on a generation of children.

The study, published in Science Advances, found that after the crisis, students faced a substantial decline in math scores, losing the equivalent of five months of learning progress that they hadn’t recovered by 2019, according to Brian Jacob, one of the study’s authors. The learning gap was especially prevalent among younger students in third through fifth grades and those of lower socioeconomic status. There was also an 8 percent increase in the number of students with special needs, especially among school-age boys. But the study notes that there remain many questions about whether it was the lead in the water directly or broader community trauma that contributed to the academic decline.

In the study, researchers analyzed standardized test scores from kindergarten through 12th grade across 10 Michigan districts, looking at student outcomes from 2007 through 2019.

Researchers found negative academic effects in these areas for years to come after the crisis, though they found limited or no effects on reading achievement or daily attendance.

“It’s a substantial reduction in their achievement. It’s a tragedy,” said Jacob, a professor of education policy and economics at the University of Michigan. “It’s a massive case of government failure in one of its basic jobs to help ensure the physical well-being of its citizens.”

In 2014, Flint’s emergency manager switched the city’s water source to save money, but officials did not ensure there were corrosion-control chemicals in the new water supply. Residents quickly began complaining of contaminated water coming from their taps. But the majority-Black city, where a third of the population lives in poverty, was ignored. Nearly 100,000 Flint residents were exposed to lead through their home water sources, according to the Centers for Disease Control and Prevention.

It has been long known that lead is a dangerous neurotoxin with no safe level of exposure. Even low levels of lead in blood are associated with developmental delays, difficulty learning and behavioral issues, according to the CDC . In more severe cases, the effects of lead poisoning can be permanent and disabling. Childhood exposure to lead can cause long-term harm.

Reached by The Washington Post on Wednesday, Flint Community Schools said it could not make a representative available to comment on the study by the time of publication.

Since learning is a cumulative process, when a student’s learning is severely disrupted — due to circumstances outside of their control — it can affect the child’s ability to learn more advanced material in the future, Jacob said. It can create a vicious cycle that could be a challenge to remediate.

But researchers were puzzled to find that children who weren’t directly exposed to contaminated water at home still faced academic challenges, suggesting there were society-wide ripple effects. Communities that go through crises like this may have mental and traumatic scars, including for children. It can have an impact on students’ ability to succeed academically, regardless of whether their homes had contaminated pipes, the study found.

While there could be other reasons to explain why there were no differences in impact for those in homes with higher levels of lead in drinking water and those in homes with the safer copper pipes — for example, people may have consumed contaminated water from outside sources — researchers also pointed to stress, anxiety, depression and fear following the crisis, which could have had negative impacts on students’ ability to succeed.

Mary Rourke, a psychologist who has worked with children and families, said all people are sensitive to their environments and situations around them, especially children.

“They haven’t yet built up a sophisticated arsenal of coping strategies, and they’re actually more affected by their environment. They have less of an independent ability to navigate the world,” said Rourke, who is an associate professor of clinical psychology at Widener University.

The Flint water crisis may have forced children and parents into survival mode, which might have made things like the everyday routine of school less of a priority, she said, especially if they were more worried about whether they were going to have the most basic of needs, such as clean water.

Rourke said children’s care systems may have been compromised during the crisis, because the parents responsible for the children’s environment were facing their own fear, panic and anger.

“The adults in the world at the time that this crisis broke, and probably for a good deal of time afterward, were paying attention to things that can feel more important in the moment than schoolwork and homework,” said Rourke, who was not involved in the study. “Education is critically important, but survival and making sure that the water system isn’t poisoned is a pretty big deal.”

Young children tend to be more impacted by lead’s toxicity compared with adults because they absorb more proportionally and because their bodies are rapidly growing and developing, said Katarzyna Kordas, an associate professor in the department of epidemiology and environmental health at the University at Buffalo.

People are generally exposed to lead through deteriorating lead-based paint, lead-contaminated dust in older buildings, and contaminated water, soil and air, according to the Mayo Clinic.

The new study is just the latest in the growing literature linking childhood lead exposure to developmental delays and a child’s subsequent ability to thrive. Some research links early childhood lead exposure to lower IQ points, while low levels of lead in children’s blood can negatively affect test scores for years to come, especially for poor, minority children, according to other studies.

Kordas, who was not involved in the study and who has also researched toxic metals and child development, was not surprised by the findings. She cited previous research explaining how socioeconomic factors can determine neurodevelopmental outcomes as much as lead exposure can.

“Lead exposure is still important, but other factors matter a lot, especially those that stem from disadvantage or social injustice,” she said. “In Flint, especially as the crisis continued, impacts on the social fabric of the community are a strong potential explanation for the declining scores and climbing special needs.”

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Article Contents

Combined protection of vaccination and nirmatrelvir-ritonavir against hospitalization in adults with covid-19.

Melissa Briggs Hagen, MD and Jacqueline L. Gerhart, MD contributed equally to this work.

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Melisa M Shah, Brendan Joyce, Ian D Plumb, Sam Sahakian, Leora R Feldstein, Eric Barkley, Mason Paccione, Joseph Deckert, Danessa Sandmann, Melissa Briggs Hagen, Jacqueline L Gerhart, Combined protection of vaccination and nirmatrelvir-ritonavir against hospitalization in adults with COVID-19, Clinical Infectious Diseases , 2024;, ciae105, https://doi.org/10.1093/cid/ciae105

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Among U.S. adults at risk for severe COVID-19 in Epic Cosmos, the lowest rate of hospitalization was among those receiving three or more mRNA vaccine doses and nirmatrelvir-ritonavir (aHR 0.22, 95%CI: 0.19–0.24). Adults who are at high-risk of severe COVID-19 disease, including vaccinated persons, should be considered for antiviral treatment.

This graphical abstract is also available at Tidbit: https://tidbitapp.io/tidbits/combined-protection-of-vaccination-and-nirmatrelvir-ritonavir-against-hospitalization-in-adults-with-covid-19

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National Research Council (US) and Institute of Medicine (US) Committee on Assessing Integrity in Research Environments. Integrity in Scientific Research: Creating an Environment That Promotes Responsible Conduct. Washington (DC): National Academies Press (US); 2002.

Integrity in Scientific Research: Creating an Environment That Promotes Responsible Conduct.

• Hardcopy Version at National Academies Press

2 Integrity in Research

The pursuit and dissemination of knowledge enjoy a place of distinction in American culture, and the public expects to reap considerable benefit from the creative and innovative contributions of scientists. As science becomes increasingly intertwined with major social, philosophical, economic, and political issues, scientists become more accountable to the larger society of which they are a part. As a consequence, it is more important than ever that individual scientists and their institutions periodically reassess the values and professional practices that guide their research as well as their efforts to perform their work with integrity.

Society's confidence in and support of research rest in large part on public trust in the integrities of individual researchers and their supporting institutions. The National Academies' report On Being a Scientist states: “The level of trust that has characterized science and its relationship with society has contributed to a period of unparalleled scientific productivity. But this trust will endure only if the scientific community devotes itself to exemplifying and transmitting the values associated with ethical scientific conduct” (NAS, 1995, preface). It is therefore incumbent on all scientists and scientific institutions to create and nurture a research environment that promotes high ethical standards, contributes to ongoing professional development, and preserves public confidence in the scientific enterprise (Grinnell, 1999; IOM, 2001; Resnik, 1998; Yarborough and Sharp, 2002).

Government oversight of scientific research is important, but such oversight, often in the form of administrative rules, typically stipulates what cannot be done; it rarely prescribes what should be done (see Chapter 4 for further discussion of the strengths and limitations of a regulatory approach). In essence, government rules define the floor of expected behavior. More, however, should be expected from scientists when it comes to the responsible conduct of research. By appealing to the conscience of individual scientists, the scientific community as a whole should seek to evoke the highest possible standard of research behavior. When institutions committed to promoting integrity in research support those standards, the likelihood of creating an environment that advances responsible research practices is greatly enhanced. It is essential that institutions foster a culture of integrity in which students and trainees, as well as senior researchers and administrators, have an understanding of and commitment to integrity in research.

The committee's task was to define integrity for the particular activity of research as conducted within contemporary society. Integrity has two general senses. The first sense concerns wholeness; the second, soundness of moral principle ( Oxford English Dictionary , 1989). Plato and subsequent philosophers have argued that leading the good life depends on a person's success in integrating moral, religious, and philosophical convictions. In conversations with experts in ethics and others, the committee found no consensus regarding whether a person could exhibit high integrity in research but not in other aspects of his life. Consequently, the committee decided to focus on the second aspect of integrity—namely, soundness of moral principle in the specific context of research practice.

• INTEGRITY IN RESEARCH

Integrity characterizes both individual researchers and the institutions in which they work. For individuals, it is an aspect of moral character and experience. 1 For institutions, it is a matter of creating an environment that promotes responsible conduct by embracing standards of excellence, trustworthiness, and lawfulness that inform institutional practices.

For the individual scientist, integrity embodies above all a commitment to intellectual honesty and personal responsibility for one's actions and to a range of practices that characterize responsible research conduct. These practices include:

• intellectual honesty in proposing, performing, and reporting research;
• accuracy in representing contributions to research proposals and reports;
• fairness in peer review;
• collegiality in scientific interactions, including communications and sharing of resources;
• transparency in conflicts of interest or potential conflicts of interest;
• protection of human subjects in the conduct of research;
• humane care of animals in the conduct of research; and
• adherence to the mutual responsibilities between investigators and their research teams.

Individual scientists work within complex organizational structures. (These structures and their interactions are described in detail in Chapter 3 .) Factors that promote responsible conduct can exert their influences at the level of the individual; at the level of the work group (e.g., the research group); and at the level of the research institution itself. These different organizational levels are interdependent in the conduct of research. Institutions seeking to create an environment that promotes responsible conduct by individual scientists and that fosters integrity must establish and continuously monitor structures, processes, policies, and procedures that:

• provide leadership in support of responsible conduct of research;
• encourage respect for everyone involved in the research enterprise;
• promote productive interactions between trainees and mentors;
• advocate adherence to the rules regarding all aspects of the conduct of research, especially research involving human subjects and animals;
• anticipate, reveal, and manage individual and institutional conflicts of interest;
• arrange timely and thorough inquiries and investigations of allegations of scientific misconduct and apply appropriate administrative sanctions;
• offer educational opportunities pertaining to integrity in the conduct of research; and
• monitor and evaluate the institutional environment supporting integrity in the conduct of research and use this knowledge for continuous quality improvement.

Leadership by individuals of high personal integrity helps to foster an environment in which scientists can openly discuss responsible research practices in the face of conflicting pressures. All those involved in the research enterprise should acknowledge that integrity is a key dimension of the essence of being a scientist and not a set of externally imposed regulatory constraints.

• INTEGRITY OF THE INDIVIDUAL SCIENTIST

As noted above, the committee has identified a range of key practices that pertain to the responsible conduct of research by individual scientists. The following sections elucidate the practices. 2

Intellectual Honesty in Proposing, Performing, and Reporting Research

Intellectual honesty in proposing, performing, and reporting research refers to honesty with respect to the meaning of one's research. It is expected that researchers present proposals and data honestly and communicate their best understanding of the work in writing and verbally. The descriptions of an individual's work found in such communications frequently present selected data from the work organized into frameworks that emphasize conceptual understanding rather than the chronology of the discovery process. Clear and accurate research records must underlie these descriptions, however. Researchers must be advocates for their research conclusions in the face of collegial skepticism and must acknowledge errors.

Accuracy in Representing Contributions to Research Proposals and Reports

Accuracy in representing one's contributions to research proposals and reports requires the assignment of credit. It is expected that researchers will not report the work of others as if it were their own. This is plagiarism. Furthermore, they should be honest with respect to the contributions of colleagues and collaborators. Decisions regarding authorship are best anticipated at the outset of projects rather than at their completion. In publications, it should be possible in principle to specify each author's contribution to the work. It also is expected that researchers honestly acknowledge the precedents on which their research is based.

Fairness in Peer Review

Fairness in peer review means that researchers should agree to be peer reviewers only when they can be impartial in their judgments and only when have revealed their conflicts of interest. Peer review functions to maintain the excellence of published scientific work and ensure a merit-based system of support for research. A delicate balance pervades the peer-review system, because the best reviewers are precisely those individuals who have the most to gain from “insider information”: they are doing similar work and they will be unable to “strike” from memory and thought what they learn through the review process. Investigators serving as peer reviewers should treat submitted manuscripts and grant applications fairly and confidentially and avoid using them inappropriately.

Collegiality in Scientific Interactions, Including Communications and Sharing of Resources

Collegiality in scientific interactions, including communications and sharing of resources requires that investigators report research findings to the scientific community in a full, open, and timely fashion. At the same time, it should be recognized that the scientific community is highly competitive. The investigator who first reports new and important findings gets credited with the discovery.

It is not obvious that rapid reporting is the approach that is always the most conducive to progress. Intellectual property provisions and secrecy allow for patents and licensure and encourage private investment in research. Furthermore, even for publicly funded research, a degree of discretion may permit a research group to move ahead more efficiently. Conversely, an investigator who delays reporting important new findings risks having others publish similar results first and receiving little recognition for the discovery. Knowing when and how much to tell will always remain a challenge in scientific communication.

Once scientific work is published, researchers are expected to share unique materials with other scientists in a reasonable fashion to facilitate confirmation of their results. (The committee recognizes that there are limits to sharing, especially when doing so requires a time or cost commitment that interferes with the function of the research group.) When materials are developed through public funding, the requirement for sharing is even greater. Public funding is based on the principle that the public good is advanced by science conducted in the interest of humanity. This commitment to the public good implies a responsibility to share materials with others to demonstrate reproducibility and to facilitate the replication and validation of one's work by responding constructively to inquiries from other scientists, particularly regarding methodologies.

Collegiality and sharing of resources is also an important aspect of the interaction between trainees and their graduate or postdoctoral advisers. Students and fellows will ultimately depart the research team, and discussion of and planning for departure should occur over the course of their education. Expectations about such issues as who inherits intellectual property rights to a project or to the project itself upon the trainee's departure should be discussed when the trainee first joins the research group and should be revisited periodically over the course of the project (NAS, 2000).

Transparency in Conflicts of Interest or Potential Conflicts of Interest

A conflict of interest in research exists when the individual has interests in the outcome of the research that may lead to a personal advantage and that might therefore, in actuality or appearance, compromise the integrity of the research. The most compelling example is competition between financial reward and the integrity of the research process. Religious, political, or social beliefs can also be undisclosed sources of research bias.

Many scientific advances that reach the public often involve extensive collaboration between academia and industry (Blumenthal et al., 1996; Campbell et al., 1998; Cho et al., 2000). Such collaborations involve consulting and advisory services as well as the development of specific inventions, and they can result in direct financial benefit to both individuals and institutions. Conflicts of interest reside in a situation itself, not in any behavior of members of a research team. Thus, researchers should disclose all conflicts of interest to their institutions so that the researchers and their work can be properly managed. They should also voluntarily disclose conflicts of interest in all publications and presentations resulting from the research. The committee believes that scientific institutions, including universities, research institutes, professional societies, and professional and lay journals, should embrace disclosure of conflicts of interest as an essential component of integrity in research.

Protection of Human Subjects in the Conduct of Research

The protection of individuals who volunteer to participate in research is essential to integrity in research. The ethical principles underlying such research have been elaborated on in international codes and have been integrated into national regulatory frameworks (in the United States, 45 C.F.R. § 46, 2001). Elements included in such frameworks pertain to the quality and importance of the science, its risks and benefits, fairness in the selection of subjects, and, above all, the voluntary participation and informed consent of subjects. To ensure the conformance of research efforts with these goals, institutions carry out extensive research subject protection programs. To be successful, such programs require high-level, functioning institutional review boards, knowledgeable investigators, ongoing performance assessment through monitoring and feedback, and educational programs (IOM, 2001). The IOM report Preserving Public Trust (IOM, 2001) focuses specifically on the important topic of research involving human subjects, and further discussion is not included here.

Humane Care of Animals in the Conduct of Research

The humane care of animals is essential for producing sound science and its social benefits. Researchers have a responsibility to engage in the humane care of animals in the conduct of research. This means evaluating the need for animals in any particular protocol, ensuring that research animals' basic needs for life are met prior to research, and carefully considering the benefits of the research to society or to animals versus the likely harms to any animals included as part of the research protocol. Procedures that minimize animal pain, suffering, and distress should be implemented. Research protocols involving animals must be reviewed and approved by properly constituted bodies, as required by law (Animal Welfare Act of 1966 [PL 89-544], inclusive of amendments passed in 1970 [PL 91-579], 1976 [PL 94-279], 1985 [PL 99-198], and 1990 [PL 101-624] and subsequent amendments) and professional standards (AAALAC, 2001; NRC, 1996).

Adherence to the Mutual Responsibilities Between Investigators and Their Research Teams

Adherence to the mutual responsibilities between investigators and members of their research teams refers to both scientific and interpersonal interactions. The research team might include other faculty members, colleagues (including coinvestigators), and trainees (undergraduate students, graduate and medical students, postdoctoral fellows), as well as employed staff (e.g., technicians, statisticians, study coordinators, nurses, animal handlers, and administrative personnel). The head of the research team should encourage all members of the team to achieve their career goals. The interpersonal interactions should reflect mutual respect among members of the team, fairness in assignment of responsibilities and effort, open and frequent communication, and accountability. In this regard, scientists should also conduct disputes professionally (Gunsalus, 1998). (The American Association of University Professors (AAUP) guidelines on academic freedom and professional ethics articulate the obligation of members of the academic community to root their statements in fact and to respect the opinions of others [AAUP, 1987, 1999].)

Mentoring and Advising

Mentor is often used interchangeably with faculty adviser . However, a mentor is more than a supervisor or an adviser (Bird, 2001; Swazey and Anderson, 1998). 3 An investigator or research adviser may or may not be a mentor. Some advisers may be accomplished researchers but do not have the time, training, or ability to be good mentors (NAS, 2000). For a trainee, “a mentoring relationship is a close, individualized relationship that develops over time between a graduate student (or other trainee) and a faculty member (or others) that includes both caring and guidance” (University of Michigan, 1999, p. 5). A successful mentoring relationship is based on mutual respect, trust, understanding, and empathy (NAS, 1997). Mentoring relationships can extend throughout all phases of a science career, and, as such, they are sometimes referred to as mentor-protégé or mentor-apprentice relationships, rather than mentor-trainee relationships.

The committee believes that mentor should be the dominant and usual role of the laboratory director or research advisor in regard to his or her trainee. With regard to such mentor-trainee relationships, responsibilities include a commitment to continuous education and guidance of trainees, appropriate delegation of responsibility, regular review and constructive appraisal of trainees, fair attribution of accomplishment and authorship, and career guidance, as well as help in creating opportunities for employment and funding. For the trainee, essential elements include respect for the mentor, loyalty to the research group, a strong commitment to science, dedication to the project, careful performance of experiments, precise and complete record keeping, accurate reporting of results, and a commitment to oral and written presentations and publication. It should be noted that most academic research institutions play a dual role. On the one hand, they are concerned with producing original research; on the other, with educating students. The two goals are compatible, but when they come in conflict, it is important that the educational needs of the students not be forgotten. If students are exploited, then they will learn by example that such behavior is acceptable.

• SUPPORT OF INTEGRITY BY THE RESEARCH INSTITUTION

The individual investigator and the laboratory or research unit carry out their functions in institutions that are responsible for the management and support of the research carried out within their domains. The institutions, in turn, are regulated by governmental and other bodies that impose rules and responsibilities (see Chapter 3 for further discussion). The vigor, resources, and attitudes with which institutions carry out their responsibilities will influence investigators' commitment and adherence to responsible research practices.

Provide Leadership in Support of Responsible Conduct of Research

It takes the leadership of an institution to promulgate a culture of responsible research. This involves the development of a vision for the research enterprise and a strategic plan. It is the responsibility of the institution leadership to develop programs to orient new researchers to institutional policies, rules, and guidelines; to sponsor opportunities for dialogue about new and emerging issues; and to sponsor continuing education about new policies and regulations as they are developed. Furthermore, institutional leaders have the responsibility to ensure that such programs are carried out, with appropriate delegation of responsibility and accountability and with adequate resources.

The observed actions of institutions in problem situations communicate as strongly (or perhaps more strongly) about responsible conduct as do any policies or programs. Institutional leaders (e.g., chancellor, president, dean, CEO) set the tone for the institutions with their own actions. Research leaders should set an example not only in their own research practices but also in their willingness to engage in dialogue about ethical questions that arise (Sigma Xi, 1999). McCabe and Pavela note that “faculty members who seek to instill a sense of social obligation without affirming personal virtues are planting trees without roots” (McCabe and Pavela, 1998, p.101).

Encourage Respect for Everyone Involved in the Research Enterprise

An environment that fosters competence and honest interactions among all participants in the investigative process supports the integrity of research. Institutions have many legally mandated policies that foster mutual respect and trust—for example, policies concerning harassment, occupational health and safety, fair employment practices, pay and benefits, protection of research subjects, exposure to ionizing radiation, and due process regarding allegations of research misconduct. State and local policies and guidelines governing research may be in effect as well. It is anticipated that through a process of self-assessment, institutions can identify issues and develop programs that further integrity in research (see Chapter 6 for further discussion). Fair enforcement of all institutional policies is a critical element of the institutional commitment to integrity in research. That is not enough, however.

Support Systems

Within the research institution, there can be multiple smaller units (e.g., departments, divisions within a department, research groups within a division). Within these institutional subunits, there will always be power differences between members of the group. Consequently, research institutions require support mechanisms—for example, ombudspersons—that research team members can turn to for help when they feel they are being treated unfairly. Institutions need to provide guidance and recourse to anyone with concerns about research integrity (e.g., a student who observes a lack of responsible conduct by a senior faculty member). Support systems should be accessible (multiple entry points for those with questions) and have a record of reaching objective, fact-based decisions untainted by personal bias or conflicts of interest (Gunsalus, 1993). Lack of recourse within the institution for those individuals who have concerns about possible misconduct will undermine efforts to foster a climate of integrity. Equally important to having support systems in place is the dissemination of information on how and where individuals may seek such support.

The ultimate goal for institutions should be to create a culture within which all persons on a research team can work effectively and realize their full potential.

Promote Productive Interactions Between Trainees and Mentors

Mentors play a special role in the development of new scientists. A mentor must consider the student's core interests and needs in preference to his or her own. Trainees and mentors are codependent and, at times, competitive. Trainees depend on their mentors for scientific education and training, for support, and, eventually, for career guidance and references. Mentors tend to be role models as well. Mentors depend on trainees for performing work and bringing fresh ideas and approaches to the research group. They can enhance the mentor's reputation as a teacher and as an investigator. Institutions should establish programs that foster productive relations between mentors and trainees, including training in mentoring and advising for faculty. Moreover, institutions should work to ensure that trainees are properly paid, receive reasonable benefits (including health insurance), and are protected from exploitation. Written guidelines, ombudspersons, and mutual evaluations can help to reduce problems and identify situations requiring remediation. As mentioned earlier in this chapter, the dual role academic research institutions play in both producing original research and educating students can be balanced, but when they come in conflict, educational interests of the student should take precedence.

Advocate Adherence to the Rules Regarding All Aspects of the Conduct of Research, Especially Research Involving Human Subjects and Animals

Effective advocacy by an institution of the rules involving the use of human subjects and animals in research involves much more than simply posting the relevant federal, state, and local regulations and providing “damage control” and formal sanctions when irregularities are discovered. At all levels of the institution, including the level of the dean, department chair, research group leader, and individual research group member, regular affirmation of the guiding principles underlying the rules is essential. The goal is to create an institutional climate such that anyone who violates these guiding principles through words or deeds is immediately made aware of the behavior and, when indicated, appropriately sanctioned.

Anticipate, Reveal, and Manage Individual and Institutional Conflicts of Interest

Research institutions must conduct their work in a manner that earns public trust. To do so, they must be sensitive to any conflict of interest that might affect or appear to affect their decisions and behavior in ways that could compromise their roles as trustworthy sources of information and policy advice or their obligations to ensure the protection of human research subjects. As research partnerships between industry and academic institutions continue to expand, with the promise of considerable public benefit, the management of real or perceived conflicts of interest in research requires that institutions have a written policy on such conflicts. The policy should apply to both institutions and individual investigators.

Institutional Conflicts of Interest

Institutions should have clearly stated policies and procedures by which they will guard against compromise by external influences. As with individual conflicts of interest, institutional leadership is not in the best position to determine whether a particular arrangement represents an unacceptable or manageable conflict of interest. Institutions should draw on independent reviews by external bodies and should have appropriate procedures for such reviews. Factors of concern include not only direct influences on institutional policy but also indirect influences on the use of resources, educational balance, and hiring of faculty, for example (AAU, 2001).

Institutional Responsibility for Investigator Conflicts of Interest

The policy on conflicts of interest should apply to individuals who are directly involved in the conduct, design, and review of research, including faculty, trainees, students, and administrators, and should clearly state their disclosure responsibilities. The policy should define conflicts of interest and should have means to convey an understanding of the term to the parties involved. It should delineate the activities and the levels and kinds of research-related financial interests that are and are not permissible, as well as those that require review and approval. The special circumstances associated with research involving human subjects should be specifically addressed. Beyond meeting their responsibility to ensure the dissemination and understanding of their policies, institutions should develop means to monitor compliance equitably. Detailed descriptions of institutional responsibilities in this area were recently reported by the Association of American Universities (AAU, 2001) and the Association of American Medical Colleges (AAMC, 2001), as described in Box 2-1 .

Definition of Institutional Conflict of Interest.

Arrange Timely and Thorough Inquiries and Investigations of Allegations of Scientific Misconduct and Apply Appropriate Sanctions

Every institution receiving federal funds for research and related activities must have in place policies and procedures for responding to allegations of research misconduct (42 C.F.R. § 50, §§ A, 1989; 45 C.F.R. § 689, 1996). Although the federal government imposes these requirements, the institutions must implement them. Their effectiveness depends on investigation of allegations of misconduct with vigor and fairness. The institution should embrace the notion that it is important to the quality and integrity of science that individuals report possible research misconduct. Means of protecting any individual who reports possible misconduct in good faith must be instituted.

In carrying out their responsibilities, institutions must ensure that faculty, students, and staff are properly informed of their rights and responsibilities. Those likely to receive allegations—for example, administrators, department chairs, and research group chiefs—must be fully informed of institutional provisions and trained in dealing with issues related to research conduct or misconduct. Mechanisms must be in place to protect the public's interest in the research record, the research subjects' health, and the financial interests of the institution, as well as to ensure notification of appropriate authorities. Clear lines of authority for management of the institution's response must exist, and, where indicated, appropriate sanctions should be applied or efforts should be made to protect or restore the reputations of innocent parties.

Offer Educational Opportunities Pertaining to Integrity in the Conduct of Research

Research institutions should provide students, faculty, and staff with educational opportunities related to the responsible conduct of research. These are mandatory for those involved in clinical research (NIH, 2000) and for recipients of Public Health Service training grants (NIH, 1989). These offerings should encourage open discussion of the values at stake and the ethical standards that promote responsible research practices. The core objective of such education is to increase participants' knowledge and sensitivity to the issues associated with integrity in research and to improve their ability to make ethical choices. It should give them an appreciation for the diversity of views that may be brought to bear on issues, inform them about the institutional rules and government regulations that apply to research, and instill in them the scientific community's expectations regarding proper research practice. Educational offerings should be flexible in their approach and be cognizant of normative differences among disciplines. Such programs should offer opportunities for the participants to explore the underlying values that shape the research enterprise and to analyze how those values are manifested in behaviors in different research environments

It is expected that effective educational programs will empower individual researchers, students, and staff in making responsible choices in the course of their research. Regular evaluation and improvement of the educational and behavioral effectiveness of these educational offerings should be a part of an institutional assessment. (See Chapter 5 for further discussion of education in the responsible conduct of research.)

Monitor and Evaluate the Institutional Environment Supporting Integrity in the Conduct of Research and Use This Knowledge for Continuous Quality Improvement

The main thrust of this report reflects the need for continuing attention toward sustaining and improving a culture of integrity in research. This requires diligent oversight by institutional management to ensure that the practices associated with integrity described above are carried out. It also requires examination of the policy-making process, the policies themselves, their execution, and the degree to which they are understood and adhered to by those affected. If researchers and administrators believe that the rules are excellent and that the institution applies them equitably, then the institutional commitment to integrity will be clear. Chapter 6 addresses ways to help identify those elements critical to establishment of the perception of moral commitment and determination of whether such commitments have been made.

The committee believes that integrity in research is essential for maintaining scientific excellence and keeping the public's trust. The concept of integrity in research cannot, however, be reduced to a one-line definition. For a scientist, integrity embodies above all the individual's commitment to intellectual honesty and personal responsibility. It is an aspect of moral character and experience. For an institution, it is a commitment to creating an environment that promotes responsible conduct by embracing standards of excellence, trustworthiness, and lawfulness and then assessing whether researchers and administrators perceive that an environment with high levels of integrity has been created. This chapter has described multiple practices that are most likely to promote responsible conduct. Individuals and institutions should use these practices with the goal of fostering a culture in which high ethical standards are the norm, ongoing professional development is encouraged, and public confidence in the scientific enterprise is preserved.

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Further discussion of moral character and behavior and the development of abilities that give rise to responsible conduct can be found in Chapter 5 .

See the section of Appendix D entitled Responsible Scientific Conduct for resources with case studies that can be used in a teaching setting to further illustrate the topics discussed here.

A special issue of Science and Engineering Ethics (7:451–640, 2001) is devoted to the relationship between mentoring and responsible conduct.

• Cite this Page National Research Council (US) and Institute of Medicine (US) Committee on Assessing Integrity in Research Environments. Integrity in Scientific Research: Creating an Environment That Promotes Responsible Conduct. Washington (DC): National Academies Press (US); 2002. 2, Integrity in Research.
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