Affect-Adaptive Activities in a Personalised Ubiquitous Learning System

Many literatures have shown the importance of emotion in learning because of their effect on learner’s performances thereby giving reasons why learners’ affective states are crucial to learning. In this light, this research work aims to identify affect-adaptive activities that would improve learning in a personalised ubiquitous learning system by detecting learning style and affective states through some patterns of   behaviours. In the study, learners’ preference are determined, learners affective states such as confidence, effort, independence and confusion are investigated. The ant colony clustering algorithm is used to determine learners’ activities. The four affective states are determined from the learners’ forum threads, content activities, assessment, timing, and discussion through learners’ engagement. The result of this research on two separate courses, Course A (Affect) and Course B (Non-Affect) shows that the four affective states influence learning. The average mean and standard deviation (SD) value for Course A (Mean=276.23, SD=272.27) over Course B (Mean=200.58, SD=210.51) showed an improvement in learning performance and the t-Test carried out between the courses suggested that students’ performance is dependent on their affective states. https://doi.org/10.26803/ijlter.17.7.3