Fostering Learners’ Performance with On-demand Metacognitive Feedback
Journal article, Peer reviewed
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OriginalversjonLecture Notes in Computer Science (LNCS). 2019, 11722 423-435. 10.1007/978-3-030-29736-7_32
Activating learners’ deeper thinking mechanisms and reflective judgement (i.e., metacognition) improves learning performance. This study exploits visual analytics to promote metacognition and delivers task-related visualizations to provide on-demand feedback. The goal is to broaden current knowledge on the patterns of on-demand metacognitive feedback usage, with respect to learners’ performance. The results from a between-group and within-group study (N = 174) revealed statistically significant differences on the feedback usage patterns between the performance-based learner clusters. Foremost, the findings shown that learners who consistently request task-related metacognitive feedback and allocate considerable amounts of time on processing it, are more likely to handle task-complexity and cope with conflicting tasks, as well as to achieve high scores. These findings contribute to considering task-related visual analytics as a metacognitive feedback format that facilitates learners’ on-task engagement and data-driven sense-making and increases their awareness of the tasks’ requirements. Implications of the approach are also discussed.