Literaturnachweis - Detailanzeige
| Autor/inn/en | Amigud, Alexander; Arnedo-Moreno, Joan; Daradoumis, Thanasis; Guerrero-Roldan, Ana-Elena |
|---|---|
| Titel | Using Learning Analytics for Preserving Academic Integrity |
| Quelle | In: International Review of Research in Open and Distributed Learning, 18 (2017) 5, S.192-210 (19 Seiten)Infoseite zur Zeitschrift
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| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1492-3831 |
| Schlagwörter | Data Collection; Data Analysis; Integrity; Electronic Learning; Educational Technology; Language Usage; Identification (Psychology); Graduate Students; Writing Assignments; Online Courses; Large Group Instruction; Performance; Foreign Countries; Content Analysis; Europe |
| Abstract | 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. (As Provided). |
| Anmerkungen | Athabasca University. 1200, 10011 - 109 Street, Edmonton, AB T5J 3S8, Canada. Tel: 780-421-2536; Fax: 780-497-3416; e-mail: irrodl@athabascau.ca; Web site: http://www.irrodl.org |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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