A framework for analyzing associativity and anonymity in conventional and electronic summative examinations

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Abstract

The prevalence of malpractices in the assessments carried by educational institutions worldwide appears to be very high. Appropriate measures to deter and prevent the malpractices during the examinations are necessary to uphold the academic integrity and to ensure the basic principles of fairness throughout the examination process. Some malpractices such as question paper leakage and collusion/plagiarism can be controlled considerably, if unique question paper is provided to each student/group of students. However, the use of unique question paper for each student/group of students brings up some security and performance challenges non-existent in the examination system with the common question paper. One specific challenge in the examinations with the unique question paper is binding the unique question paper with the answer-script produced by the student and establishing the anonymity of student and examiners from each other. The purpose of this paper is to propose a framework, that establishes and preserves the association between the given question paper and the answer-script and provide required anonymity to students and examiners during an exchange of the examination content. In order to achieve this goal, we first formalize the associativity and anonymity properties and then validate our framework by analyzing the associativity and anonymity properties for the existing conventional/electronic summative examination system.

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APA

Dessai, K. G., & Kamat, V. (2016). A framework for analyzing associativity and anonymity in conventional and electronic summative examinations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10063 LNCS, pp. 303–323). Springer Verlag. https://doi.org/10.1007/978-3-319-49806-5_16

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