Cheating Academic Integrity. Группа авторов

possible battleground in the next arms race between technologies that facilitate cheating and technologies that may deter or detect cheating is artificial intelligence and machine learning. It has been reported that artificial intelligence can be used to create “passable” academic writing automatically (e.g. Abd‐Elaal et al., 2019). Automatic paraphrasing tools can potentially revise unoriginal work sufficiently to evade detection by text‐matching software (Rogerson and McCarthy, 2017). Artificial intelligence may also be used by contract cheating providers to find potential “customers” among students based, for example, on their social media posts (Amigud, 2020). By the same token, artificial intelligence and machine learning may be used to detect plagiarism, outsourcing, and machine‐written work and to verify students’ identity in online learning environments (Amigud et al., 2017). Additionally, artificial intelligence can be used to automate searches for files students inappropriately share online and have these taken down where necessary (Redden, 2021). Whether such an arms race results in a change in the prevalence of student plagiarism and cheating will depend on how fast and effectively cheating and anti‐cheating forces manage to bamboozle each other and respond in kind.

CONCLUSION

      This chapter has demonstrated a downward trend in the prevalence of higher education students’ self‐reported plagiarism and cheating behavior in the 30 years 1990–2020. This downward trend is not attributable to a switch to commercial contract cheating, which appears to have remained at a steady, low prevalence in the past 30 years. However, there is evidence to suggest that text‐matching software, academic integrity and writing education, and honor codes may have contributed to the downward trend. Nonetheless, higher education teachers and administrators cannot afford to become complacent. The achievements of the past 30 years may not be permanent without continuing efforts to promote academic integrity and deal with emerging threats.

      Funding Details

      No funding was received to support this research.

      Disclosure Statement

      The author does not have any conflicts of interest associated with this chapter.

REFERENCES

      1 Abd‐Elaal, E. S., Gamage, S. H. and Mills, J. E. (2019). ‘Artificial intelligence is a tool for cheating academic integrity’. In 30th Annual Conference for the Australasian Association for Engineering Education (AAEE 2019): Educators Becoming Agents of Change: Innovate, Integrate, Motivate (p. 397). Engineers Australia.

      2 Abukari, Z. (2016). Awareness and incidence of plagiarism among students of higher education: A case study of Narh‐Bita College. (Doctoral dissertation, University of Ghana). http://ugspace.ug.edu.gh/handle/123456789/21270

      3 Amigud, A. (2020). ‘Cheaters on Twitter: an analysis of engagement approaches of contract cheating services’, Studies in Higher Education, 45(3), pp. 692–705.

      4 Amigud, A., Arnedo‐Moreno, J., Daradoumis, T., and Guerrero‐Roldan, A. E. (2017). ‘A robust and non‐invasive strategy for preserving academic integrity in an open and distance learning environment’. In 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT) (pp. 530–532). IEEE. Available at: https://doi.org/10.1109/ICALT.2017.23(Accessed November 11, 2021).

      5 Anderman, E. M. and Won, S. (2019). ‘Academic cheating in disliked classes’, Ethics & Behavior, 29(1), pp. 1–22.

      6 Ariely, D. (2012). The (honest) truth about dishonesty. Harper Collins.

      7 Awdry, R. (2020). ‘Assignment outsourcing: Moving beyond contract cheating’, Assessment & Evaluation in Higher Education, pp. 1–16.

      8 Barnhardt, B. (2016). ‘The “epidemic” of cheating depends on its definition: A critique of inferring the moral quality of “cheating in any form” ’, Ethics & Behavior, 26(4), pp. 330–343.

      9 Barrett, R. and Malcolm, J. (2006). ‘Embedding plagiarism education in the assessment process’, International Journal for Educational Integrity, 2(1), pp. 38–45.

      10 Baskin, P. (2021). ‘Famed Duke expert on human dishonesty suspected of fraud’, Times Higher Education, 23 August. Available at: https://www.timeshighereducation.com/news/famed‐duke‐expert‐human‐dishonesty‐suspected‐fraud (Accessed Novemner 11, 2021).

      11 Batane, T. (2010). ‘Turning to Turnitin™ to fight plagiarism among university students’, Journal of Educational Technology & Society, 13(2), pp. 1–12.

      12 Belter, R.W. and du Pré, A. (2009). ‘A strategy to reduce plagiarism in an undergraduate course’, Teaching of Psychology, 36(4), pp. 257–261.

      13 Bertram Gallant, T. and M. Stephens, J. (2020). ‘Punishment is not enough: The moral imperative of responding to cheating with a developmental approach’, Journal of College and Character, 21(2), pp. 57–66.

      14 Birks, M., Mills, J., Allen, S. and Tee, S. (2020). ‘Managing the mutations: Academic misconduct Australia, New Zealand, and the UK’, International Journal for Educational Integrity, 16, p. 6.

      15 Bowers, W. J. (1964). Student dishonesty and its control in college. Bureau of Applied Social Research, Columbia University.

      16 Bretag, T. (2019). ‘Contract cheating will erode trust in science’, Nature, 574(7780), pp. 599–600.

      17 Bretag, T., Harper, R., Burton, M., Ellis, C., Newton, P., Rozenberg, P., Saddiqui, S. and van Haeringen, K. (2019). ‘Contract cheating: A survey of Australian university students’, Studies in Higher Education, 44(11), pp. 1837–1856.

      18 Champagne, E. and Granja, A. D. (2021). ‘How the COVID‐19 pandemic may have changed university teaching and testing for good’, The Conversation, 7 April. Available at: https://theconversation.com/how‐the‐covid‐19‐pandemic‐may‐have‐changed‐university‐teaching‐and‐testing‐for‐good‐158342 (Accessed November 11, 2021).

      19 Clarke, R. and Lancaster, T. (2006). ‘Eliminating the successor to plagiarism? Identifying the usage of contract cheating sites’. In proceedings of 2nd international plagiarism conference (June, pp. 19–21). Northumbria Learning Press.

      20 Charumilind, S., Craven, M., Lamb, J., Sabow A. and Wilson, M. (2020). When will the COVID‐19 pandemic end? https://www.mckinsey.com/industries/healthcare‐systems‐and‐services/our‐insights/when‐will‐the‐covid‐19‐pandemic‐end# (Accessed November 11, 2021).

      21 Cornish, D. B. and Clarke, R.V. (1987). ‘Understanding crime displacement: An application of rational choice theory’, Criminology, 25, pp. 933–948.

      22 Curtis, G. J. and Clare, J. (2017). ‘How prevalent is contract cheating and to what extent are students repeat offenders?’, Journal of Academic Ethics, 15(2), pp. 115–124.

      23 Curtis, G. J., Cowcher, E., Greene, B. R., Rundle, K., Paull, M. and Davis, M. C. (2018). ‘Self‐control, injunctive norms, and descriptive norms predict engagement in plagiarism in a theory of planned behavior model’, Journal of Academic Ethics, 16(3), pp. 225–239.

      24 Curtis, G. J., Gouldthorp, B., Thomas, E. F., O'Brien, G. M. and Correia, H. M. (2013). ‘Online academic‐integrity mastery training may improve students’ awareness of, and attitudes toward, plagiaris’, Psychology: Learning and Teaching, 12(3), pp. 282–289.

      25 Curtis,