Analysis of Metacognitive Awareness Levels in the Application of Artificial Intelligence in Students

Abstract

This study utilized Chat GPT to apply Artificial Intelligence in the learning process. The instrument used was the MAI Jr metacognitive awareness questionnaire, adopted from Sperling et al. (2002). The research population consisted of first-semester students in the 2025/2026 academic year of the Chemistry Education program at the University of Mataram. The sampling method used was saturated sampling; thus, the research sample was taken from the entire predetermined population. The results showed that, in general, the metacognitive awareness possessed by first-semester students in the 2025/2026 academic year of the Chemistry Education program at the University of Mataram was not yet fully optimal. The sub-indicators of metacognitive knowledge that need improvement are procedural knowledge and conditional knowledge, as the percentage in the low and very low categories remains high. Furthermore, in the metacognitive regulation indicator, the aspects that need improvement are comprehension monitoring and evaluation. The comprehension aspect is still dominated by students in the low category, while in the evaluation aspect, the high and low categories have the same percentage, which needs to be improved to reach a higher category.