TY - JOUR AU - Amigud, Alexander AU - Arnedo-Moreno, Joan AU - Daradoumis, Thanasis AU - Guerrero-Roldan, Ana-Elena PY - 2017/08/15 Y2 - 2024/03/28 TI - Using Learning Analytics for Preserving Academic Integrity JF - The International Review of Research in Open and Distributed Learning JA - IRRODL VL - 18 IS - 5 SE - Research Articles DO - 10.19173/irrodl.v18i5.3103 UR - https://www.irrodl.org/index.php/irrodl/article/view/3103 SP - AB - <p class="3">This paper presents the results of integrating learning analytics into the assessment process to enhance academic integrity in the e-learning environment. The goal of this research is to evaluate the computational-based approach to academic integrity. The machine-learning based framework learns students’ patterns of language use from data, providing an accessible and non-invasive validation of student identities and student-produced content. To assess the performance of the proposed approach, we conducted a series of experiments using written assignments of graduate students. The proposed method yielded a mean accuracy of 93%, exceeding the baseline of human performance that yielded a mean accuracy rate of 12%. The results suggest a promising potential for developing automated tools that promote accountability and simplify the provision of academic integrity in the e-learning environment.</p> ER -