Abstract
In recent years, the use of electronic assessment platforms (EAPs), which allow exams to be administered on- or off-line, has become increasingly popular. A benefit of EAPs is that they capture a detailed log of an examinee’s journey through their exams. However, methods of leveraging exam logs for developing analytical insights are still under-explored. In this paper, we employ AI and analytical techniques to investigate whether exam-takers exhibit distinct behaviours while taking e-exams. We evaluate our methods using an e-exam log of 90 multiple-choice questions administrated to 463 university-level medical students. Our findings indicate that the students exhibited distinctive test-taking tactics and strategies, and some of the tactics are associated with their performance. We discuss the implications for analytical techniques to support instructors’ decisions in AI-supported EAPs and e-exams.
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Notes
- 1.
Approval from our Human Research Ethics Committee was received for conducting the study presented in this paper (2018000841).
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Lahza, H.F., Khosravi, H., Demartini, G. (2022). Incorporating AI and Analytics to Derive Insights from E-exam Logs. In: Rodrigo, M.M., Matsuda, N., Cristea, A.I., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2022. Lecture Notes in Computer Science, vol 13355. Springer, Cham. https://doi.org/10.1007/978-3-031-11644-5_78
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