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Direct linkEan Teng Khor; Dave Darshan – International Journal of Information and Learning Technology, 2024
Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
Ben Soussia, Amal; Labba, Chahrazed; Roussanaly, Azim; Boyer, Anne – International Journal of Information and Learning Technology, 2022
Purpose: The goal is to assess performance prediction systems (PPS) that are used to assist at-risk learners. Design/methodology/approach: The authors propose time-dependent metrics including earliness and stability. The authors investigate the relationships between the various temporal metrics and the precision metrics in order to identify the…
Descriptors: Performance, Prediction, Student Evaluation, At Risk Students
Joseph-Richard, Paul; Uhomoibhi, James; Jaffrey, Andrew – International Journal of Information and Learning Technology, 2021
Purpose: The aims of this study are to examine affective responses of university students when viewing their own predictive learning analytics (PLA) dashboards, and to analyse how those responses are perceived to affect their self-regulated learning behaviour. Design/methodology/approach: A total of 42 Northern Irish students were shown their own…
Descriptors: Prediction, Learning Analytics, Student Behavior, Affective Behavior
