Book Review: Digital Certificates

Abstract

Assessment is an integral part of online education, much like traditional classroom education. During the online assessment, evaluation of the learning outcomes presents challenges mainly due to academic dishonesty among students that may lead to unfair evaluations. This systematic review examines the research on online assessment security involving studies completed between 2016 and 2021. The review investigates the literature, around four critical themes - reasons for student engagement in dishonest behavior, mechanisms used for dishonesty, integrity strategies to handle dishonesty and the role of machine learning in integrity strategies. The results indicate that readily available opportunities provided by environmental factors like Internet availability, shadow individual characteristics of the student; the students with high moral values also often succumb to dishonesty. We found that among the five types of dishonest behaviors identified in online students, researchers have shown more interest in studying collusion and plagiarism. It is interesting to note that technology, a pre-requisite for the conduct of online assessments, is exploited by the students for dishonest behaviors vis-a-vis technology also plays a key role in mitigation. The integrity strategies fall under two approaches- prevention and detection. We propose an Academic Dishonesty Mitigation Plan (ADMP) that encompasses strategies from both prevention and detection approaches for effective security and integrity of online assessments. ADMP also necessitates the involvement of major stakeholders - platform owners, institutions, teachers and students, to establish a secure online assessment system. We find an increasing use of machine learning techniques to automate the detection of dishonest behavior. The findings provide a holistic understanding of academic dishonesty that could help preserve integrity in current online assessments.