Cheating Detection in Online Assessments via Timeline Analysis

Abstract

The potential for academic integrity violations increases in online courses and instructors must place extra attention on academic integrity, since cheating techniques and costs are different than in the physical classroom. Although students are less supervised and able to study in a self-paced mode in online learning, unauthorized collaboration is still considered to be a serious integrity violation. However, online learning platforms have the advantage that they may capture detailed timelines of student activity. Analysis of these can enable instructors to detect many patterns of collaboration, e.g., working on assessments together, or copying solutions from unauthorized web pages. In this paper, we describe detection methods for several common patterns of alignment between work timelines of pairs of students, and these patterns' relationship with corroborative evidence such as similar answers and unusually fast completion times. We describe data collection necessary to apply the timeline analysis technique to weekly quiz assessments and project submissions, and discuss the strength of evidence the technique can provide in different situations. We have been applying these techniques in an online project-based course over several years, and it has helped instructors to successfully identify potential cheating cases.