Supporting students’ self-regulated learning in online learning using artificial intelligence applications

Abstract Self-regulated learning (SRL) is crucial for helping students attain high academic performance and achieve their objectives in the online context. However, learners often face challenges properly applying SRL environments. Recent developments artificial intelligence (AI) applications have shown promise supporting learners’ self-regulation by measuring augmenting SRL, but research this area still its early stages. The purpose of study to explore students’ perceptions use AI support identify pedagogical psychological aspects that they perceive as necessary effective utilization those applications. To this, a speed dating method using storyboards was employed an exploratory design method. involved development 10 application phases areas semi-structured interviews were conducted with 16 university from various majors. results indicated perceived useful metacognitive, cognitive, behavioral regulation across different areas, not regulating motivation. Next, regarding requested consideration three aspects: learner identity, activeness, position. findings offer practical implications learning, aim SRL.