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Cheating in university exams: the relevance of social factors

Abstract

We implemented an online anonymous survey targeted to current and former students, where the interviewed indicate whether and to what extent they cheated during written university examinations. We find that 61% of respondents have cheated once or more. Cheaters are more likely to report that their classmates and friends cheated and that in general people can be trusted. Two different cheating styles emerge: ‘social cheaters,’ who self-report that they have violated the rules interacting with others; ‘individualistic’ cheaters, who self-report that they have used prohibited materials. Only social cheaters exhibit higher levels of trust compared to individualistic cheaters.

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Fig. 1

Data availability

The data that support the findings of this study are available from the corresponding author upon request.

Notes

  1. 1.

    Since the definition of cheating varies across studies (in some cases encompassing only cheating in written examinations—see, e.g., Harpp and Hogan (1993)—and in other cases also including plagiarism—see, e.g., Griffin et al. 2015), comparisons of magnitudes of cheating rates across studies are not very informative, although magnitudes themselves are suggestive of a highly widespread phenomenon. Most statistics show that more than half of students have engaged in academic dishonesty at least once (Jones 2011), but some studies report much higher peaks, around 75% (Baird 1980).

  2. 2.

    See, for instance, Cohn et al. (2015), Dai et al. (2018), Hanna and Wang (2017), Kröll and Rustagi (2017) and Potters and Stoop (2016).

  3. 3.

    This culture is present in our sample as well. In our questionnaire, we included a question on reporting others’ cheating (Question Q9; see Appendix). We found that just 0.7% of those who witnessed dishonest behavior chose to report it to the professor.

  4. 4.

    One may argue that the choice of individual versus social cheating can be also driven by the size of social network in the classroom. Yet, we cannot control for social networks in university courses. Also, there is high heterogeneity in the structure of social networks at university across faculties and across Bachelor’s vs. Master’s courses, mainly due to (1) the number of students attending the lectures and (2) how many other courses students share and attend together. It is possible that higher trust in others correlates with a larger social network in the classroom and hence that the relationship between trust and social cheating is also mediated by the extent of the social network.

  5. 5.

    To elicit generalized trust, we use the question from the World Value Survey (Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people?) and from the US General Social Survey (Do you think most people would try to take advantage of you if they got the chance, or would they try to be fair?).

  6. 6.

    To elicit merit, we defined the following question: ‘Generally speaking, do you think that merit is rewarded in the public sector and in the private sector’. To elicit risk attitude, we used the question from the SOEP (‘Do you consider yourself a person who is willing to take risks or a person that avoids taking risks? Mark one of the underlying numbers, where 0 means “absolutely not willing to take risks” and 10 means “totally willing to take risks”’).

  7. 7.

    Note that the sum of the two frequencies is slightly higher than that of the variable ‘ever cheated’ because in the questionnaire it was possible to report more than one way of cheating. Overall, 61.4% of the subjects report any form of cheating. Specifically, 48.3% report just one type of cheating, while 13.1% report both types of cheating.

  8. 8.

    As a robustness check, we defined the index from a factor analysis based on raw variable Q12, Q13 and Q14. This index is highly correlated (0.69) with the one used in this analysis, and results based on it are in line with our benchmark findings. Evidence is available upon request.

  9. 9.

    The ‘Merit rewarded first job’ dummy is equal to one if variable Q17 is higher than 6; the ‘Not religious’ dummy is equal to one if variable Q13 reports ‘No, I am atheist/agnostic’. All the other dummy variables are set equal to one if the corresponding variable indicates any of the two ‘Yes’ options.

  10. 10.

    The result may also depend on the fact that Italy is one of the EU countries with the highest youth unemployment rate (32.2% against the EU average of 15.2%. Source: Eurostat).

  11. 11.

    The sanction is varying across universities and departments. Typical sanctions include automatic failure at the examination, skipping the following examination session, and a dishonorable mention to the faculty head.

  12. 12.

    If the degree still has to be obtained, i.e., if the respondent is a student, we keep his or her current age. This change affects 21.19% of the respondents that on average are 29 years old.

  13. 13.

    In 2016, across all universities and fields, the average graduate was 26.1 years old, female in 59.2% of cases, and immigrate in 3.5%. Source (Accessed February 8 2019): http://www2.almalaurea.it/en/cgi-php/lau/sondaggi/intro.php?lang=en&config=profilo. We only notice some geographical concentration, with 46.9% of the answers coming from three regions (Friuli-Venezia Giulia, Lazio and Veneto) whose population accounts for about 20% of the total population in Italy. In a separate robustness check, we perform our analysis using sample weights proportional to the population size of each region (source: ISTAT). This way statistics on the distribution of the observations are consistent with the actual distribution of the population. The results, available upon request, confirm our key findings.

  14. 14.

    The two types of cheating are not mutually exclusive. Overall, 13.1% of the respondents report to implement both types of cheating. We do not find different results when separately considering single-type cheaters.

  15. 15.

    There are, however, few exceptions in the gendered pattern of academic cheating, pointing out no difference between males and females (Naghdipour and Emeagwali 2013), or males cheating less than females (Kervliet 1994). Interestingly, McCabe et al. (2012) note that female students (in some majors such as engineering) appear to have narrowed the gap with their male counterparts in cheating. The authors believe that this pattern can be attributed to female students trying to play by ‘men’s rules’ to be successful in that major, with engineering as a historically male-dominated field.

  16. 16.

    Further information, not used for this analysis, refers to the frequency of detection of the dishonest behavior by instructors: in 89% of the cases respondents report that instructor(s) never noticed the dishonest behavior.

  17. 17.

    Interactive cheating, however, may also occur from someone who has more knowledge to someone who needs help. The person with better knowledge may not be interested in committing cheating for her own benefit.

  18. 18.

    We do not have any information about how seats are assigned at university examinations, although we recognize that this could be an interesting input in the analysis of individualistic versus social cheating for future research.

References

  1. Aljurf S, Kemp LJ, Williams P (2019) Exploring academic dishonesty in the middle east: a qualitative analysis of students’ perceptions. Stud High Educ (in press)

  2. Ashworth P, Bannister P, Thorne P, Students on the Qualitative Research Methods Course Unit (1997) Guilty in whose eyes? University students’ perceptions of cheating and plagiarism in academic work and assessment. Stud High Educ 22(2):187–203

    Google Scholar 

  3. Atanasov P, Dana J (2011) Leveling the playing field: dishonesty in the face of threat. J Econ Psychol 32(5):809–817

    Google Scholar 

  4. Baird JS (1980) Current trends in college cheating. Psychol Sch 17(4):515–522

    Google Scholar 

  5. Bisping T, Patron H, Roskelley K (2008) Modelling academic dishonesty: the role of student perceptions and misconduct type. J Econ Educ 39(1):4–21

    Google Scholar 

  6. Bjørnskov C (2009) Social trust and the growth of schooling. Econ Educ Rev 28(2):249–257

    Google Scholar 

  7. Carrell SE, Malmstrom FV, West JE (2008) Peer effects in academic cheating. J Hum Resour 43(1):173–207

    Google Scholar 

  8. Cohn A, Maréchal MA (2018) Laboratory measure of cheating predicts school misconduct. Econ J 128(615):2743–2754

    Google Scholar 

  9. Cohn A, Maréchal MA, Noll T (2015) Bad boys: how criminal identity salience affects rule violation. Rev Econ Stud 82(4):1289–1308

    Google Scholar 

  10. Crown DF, Spiller MS (1998) Learning from the literature on collegiate cheating: a review of empirical research. J Bus Ethics 17(6):683–700

    Google Scholar 

  11. Currarini S, Jackson MO, Pin P (2009) An economic model of friendship: homophily, minorities, and segregation. Econometrica 77(4):1003–1045

    Google Scholar 

  12. Dai Z, Galeotti F, Villeval MC (2018) Cheating in the lab predicts fraud in the field: an experiment in public transportation. Manage Sci 64(3):1081–1100

    Google Scholar 

  13. Davis SF, Ludvigson HW (1995) Additional data on academic dishonesty and a proposal for remediation. Teach Psychol 22(2):119–121

    Google Scholar 

  14. Frippiat D, Marquis N, Wiles-Portier E (2010) Web surveys in the social sciences: an overview. Population 65(2):285–311

    Google Scholar 

  15. Gächter S, Schulz JF (2016) Intrinsic honesty and the prevalence of rule violations across societies. Nature 531(7595):496–499

    Google Scholar 

  16. Gino F, Ayal S, Ariely D (2009) Contagion and differentiation in unethical behavior: the effect of one bad apple on the barrel. Psychol Sci 20(3):393–398

    Google Scholar 

  17. Griebeler MDC (2017) Friendship and in-class academic dishonesty. Econ Lett 150:1–3

    Google Scholar 

  18. Griebeler MDC (2019) “But everybody’s doing it!”: a model of peer effects on student cheating. Theory Decis 86:1–23

    Google Scholar 

  19. Griffin DJ, Bolkan S, Goodboy AK (2015) Academic dishonesty beyond cheating and plagiarism: students’ interpersonal deception in the college classroom. Qual Res Rep Commun 16(1):9–19

    Google Scholar 

  20. Gullifer JM, Tyson GA (2014) Who has read the policy on plagiarism? Unpacking students’ understanding of plagiarism. Stud High Educ 39(7):1202–1218

    Google Scholar 

  21. Hanna R, Wang SY (2017) Dishonesty and selection into public service: evidence from India. Am Econ J Econ Policy 9(3):262–290

    Google Scholar 

  22. Harpp DN, Hogan JJ (1993) Crime in the classroom: detection and prevention of cheating on multiple-choice exams. J Chem Educ 70(4):306

    Google Scholar 

  23. Hildreth JAD, Anderson C (2018) Does loyalty trump honesty? Moral judgments of loyalty-driven deceit. J Exp Soc Psychol 79:87–94

    Google Scholar 

  24. Iberahim H, Hussein N, Samat N, Noordin F, Daud N (2013) Academic dishonesty: Why business students participate in these practices? Proc Soc Behav Sci 90:152–156

    Google Scholar 

  25. Jacobsen C, Fosgaard TR, Pascual-Ezama D (2018) Why do we lie? A practical guide to the dishonesty literature. J Econ Surv 32(2):357–387

    Google Scholar 

  26. Jones DL (2011) Academic dishonesty: are more students cheating? Bus Commun Q 74(2):141–150

    Google Scholar 

  27. Kerkvliet J (1994) Estimating a logit model with randomized data: the case of cocaine use. Aust J Stat 36(1): 9–20

    Google Scholar 

  28. Kerkvliet J, Sigmund CL (1999) Can we control cheating in the classroom? J Econ Educ 30(4):331–343

    Google Scholar 

  29. Kröll M, Rustagi D (2017) Got milk? Dishonesty, market power, and cheating in informal milk markets in India. Working Paper, Goethe University Frankfurt

  30. Ledwith A, Rísquez A (2008) Using anti-plagiarism software to promote academic honesty in the context of peer reviewed assignments. Stud High Educ 33(4):371–384

    Google Scholar 

  31. Lefebvre M, Pestieau P, Riedl A, Villeval MC (2015) Tax evasion and social information: an experiment in Belgium, France, and the Netherlands. Int Tax Public Finance 22(3):401–425

    Google Scholar 

  32. McCabe DL (2005) Cheating among college and university students: a North American perspective. Int J Educ Integr 1(1):1–11

    Google Scholar 

  33. McCabe DL, Trevino LK (1996) What we know about cheating in college longitudinal trends and recent developments. Change Mag High Learn 28(1):28–33

    Google Scholar 

  34. McCabe DL, Trevino LK (1997) Individual and contextual influences on academic dishonesty: a multicampus investigation. Res High Educ 38(3):379–396

    Google Scholar 

  35. McCabe DL, Butterfield KD, Trevino LK (2012) Cheating in college: why students do it and what educators can do about it. John Hopkins University Press, Baltimore

    Google Scholar 

  36. Naghdipour B, Emeagwali OL (2013) Students’ justifications for academic dishonesty: call for action. Proc Soc Behav Sci 83:261–265

    Google Scholar 

  37. Neville L (2012) Do economic equality and generalized trust inhibit academic dishonesty? Evidence from state-level search-engine queries. Psychol Sci 23(4):339–345

    Google Scholar 

  38. Newstead SE, Franklyn-Stokes A, Armstead P (1996) Individual differences in student cheating. J Educ Psychol 88(2):229

    Google Scholar 

  39. Paccagnella M, Sestito P (2014) School cheating and social capital. Educ Econ 22(4):367–388

    Google Scholar 

  40. Potters J, Stoop J (2016) Do cheaters in the lab also cheat in the field? Eur Econ Rev 87:26–33

    Google Scholar 

  41. Prelec D (2004) A Bayesian truth serum for subjective data. Science 306(5695):462–466

    Google Scholar 

  42. Rettinger DA, Kramer Y (2009) Situational and personal causes of student cheating. Res High Educ 50(3):293–313

    Google Scholar 

  43. Sattler S, Wiegel C, Veen FV (2017) The use frequency of 10 different methods for preventing and detecting academic dishonesty and the factors influencing their use. Stud High Educ 42(6):1126–1144

    Google Scholar 

  44. Scheers NJ, Dayton CM (1987) Improved estimation of academic cheating behavior using the randomized response technique. Res High Educ 26(1):61–69

    Google Scholar 

  45. Scrimpshire AJ, Stone TH, Kisamore JL, Jawahar IM (2017) Do birds of a feather cheat together? How personality and relationships affect student cheating. J Acad Ethics 15(1):1–22

    Google Scholar 

  46. Shu LL, Gino F, Bazerman MH (2011) Dishonest deed, clear conscience: when cheating leads to moral disengagement and motivated forgetting. Personal Soc Psychol Bull 37(3):330–349

    Google Scholar 

  47. Whitley BE (1998) Factors associated with cheating among college students: a review. Res High Educ 39(3):235–274

    Google Scholar 

  48. Wowra SA (2007) Academic dishonesty. Ethics Behav 17(3):211–214

    Google Scholar 

  49. Zitzewitz E (2012) Forensic economics. J Econ Lit 50(3):731–769

    Google Scholar 

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Acknowledgements

The authors thank three anonymous reviewers and the participants to the 2018 SABE-IAREP Conference in London for useful discussion.

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Correspondence to Alessandro Bucciol.

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Bucciol, A., Cicognani, S. & Montinari, N. Cheating in university exams: the relevance of social factors. Int Rev Econ 67, 319–338 (2020). https://doi.org/10.1007/s12232-019-00343-8

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Keywords

  • Academic dishonesty
  • Honesty
  • Trust
  • Online survey
  • College students

JEL Classification

  • I21
  • D01