Abstract
Being conscious of your thought processes is known as metacognition. It supports students in being more aware of their actions, motivations, and the potential applications of the skills [1]. This study investigates how different metacognitive judgment questions affect students’ metacognitive awareness in an augmented reality (AR) environment. The outcomes of this study will help us to understand what metacognitive monitoring method is more effective in the AR learning environment. According to the literature, students with high knowledge about cognition have higher test performance, while students with low regulation have a challenge during planning, organizing, and elaborating strategies. The dependent variables of the study are student learning performance and metacognitive awareness inventory (MAI) score, and one independent variable is the metacognitive judgment question Retrospective Confidence Judgment (RCJ) and Judgment of Learning (JOL). We hypothesized that the students with high performance would have improved MAI scores in both groups. The experiment was done with two groups (RCJ and JOL). Both groups responded to the pre-post metacognitive awareness inventory questionnaire. During the experiment, the MAI questionnaire was asked two times. In round one, the MAI questionnaire was asked at the beginning of lecture one; however, in round two, the questionnaire was asked at the end of lecture two. Results indicated significant differences in RCJ low performers. In RCJ, the participants whose performance was significantly reduced in lecture 2 had a higher improvement on MAI both regulation and knowledge about cognition. Overall, the result of our study could advance our understanding of how to design an advanced instructional strategy in an AR environment.
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This study was funded by the National Science Foundation (NSF).
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Mostowfi, S., Kim, J.H., Yu, CY., Seo, K., Wang, F., Oprean, D. (2023). The Effect of Metacognitive Judgments on Metacognitive Awareness in an Augmented Reality Environment. In: Schmorrow, D.D., Fidopiastis, C.M. (eds) Augmented Cognition. HCII 2023. Lecture Notes in Computer Science(), vol 14019. Springer, Cham. https://doi.org/10.1007/978-3-031-35017-7_22
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