Personalised emotion-aware e-learning systems with interventions
by Zahra Karamimehr; Mohammad Mehdi Sepehri; Soheil Sibdari; Toktam Khatibi; Hassan Aghajani
International Journal of Smart Technology and Learning (IJSMARTTL), Vol. 3, No. 3/4, 2023

Abstract: Personalised education, automated tutoring, and targeted evaluation are among the top technology-intense advances in education today. Automated intervention in online student learning is essential in the absence of human instructors. These interventions need to consider non-observable features of e-learners and offer instructions according to the system's perception of these features. In this paper, we study the intervention methods in learning process according to the emotional state of e-learner. We adopt Control-Value Theory of achievement emotions as our research basis to infer about the affective state of e-learners. We offer educational and affective strategies based on the learning behaviour of the e-learner and determine the time to intervene in addition to the type of support and materials that are required in each intervention. The efficiency of our proposed personalised system is evaluated by conducting an experiment in a real e-learning platform using three learning metrics: learning gains, course engagement, and satisfactions.

Online publication date: Wed, 28-Feb-2024

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