Unrevealing the digital thread: Exploring students’ LMS digital behavior and its impact on academic performance in Kuwait higher education

Almutairi, Ibtisam, McKenna, Brad ORCID: https://orcid.org/0000-0002-2219-7508 and Benfell, Adrian ORCID: https://orcid.org/0000-0001-9825-4532 (2024) Unrevealing the digital thread: Exploring students’ LMS digital behavior and its impact on academic performance in Kuwait higher education. In: International Conference on Information Resources Management. UNSPECIFIED. (In Press)

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Abstract

This study aimed to investigate the influence of students' digital behavior in the Learning Management System (LMS) on their academic performance. Educational Data Mining (EDM) algorithms, specifically clustering analysis, will be used to analyze student log data, specifically within the context of Kuwait University (KU). By utilizing EDM algorithms, various aspects of students' actual digital behavior will be analyzed, including forum posts and views, frequency of logins, files downloaded, attempts and finalization at exams, and quizzes. Then multiple linear regression will be applied to examine the influence of students' digital behavior in the LMS on their academic performance represented by their grades in LMS log data. The findings of this research could help to better understand students' digital behavior through LMS, which can assist in formulating strategies to enhance student engagement and optimize the learning experience. In addition, these findings can inform the design and implementation of LMS at KU, ensuring that it is more closely aligned with the preferences and expectations of students. Since this alignment comes at a cost, it would be wise to invest in it only if it ultimately contributes to enhancing student academic performance which is the question that will be answered in this study.

Item Type: Book Section
Faculty \ School: Faculty of Social Sciences > Norwich Business School
UEA Research Groups: Faculty of Social Sciences > Research Groups > Employment Systems and Institutions
Faculty of Social Sciences > Research Groups > Innovation, Technology and Operations Management
Depositing User: LivePure Connector
Date Deposited: 04 Jun 2024 15:30
Last Modified: 04 Jun 2024 15:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/95386
DOI:

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