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With the growing need for augmented reality (AR) technology, understanding and optimizing study behaviors in AR learning environments has become crucial. However, one major drawback of AR learning is the absence of effective feedback mechanisms for students. To overcome this challenge, we introduced metacognitive monitoring feedback. Additionally, we created a location-based AR learning environment utilizing a real-time indoor tracking system to further enhance student learning. This study focuses on the positive impact of metacognitive monitoring feedback in a location-based AR learning environment. Our hypothesis posits that regularly providing students with feedback on their metacognitive monitoring within this new AR learning system positively influences their metacognitive awareness. The study's findings confirm that frequent exposure to such feedback significantly enhances the Metacognitive Awareness Inventory (MAI) scores. Participants who received continuous feedback demonstrated a significant increase in MAI scores compared to those who received feedback only once after the lecture. This improvement is achieved by influencing student calibration and directly enhancing their metacognitive awareness.
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The Effect of Metacognitive Judgments on Metacognitive Awareness in an Augmented Reality Environment
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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- Award ID(s):
- 2202108
- PAR ID:
- 10513853
- Publisher / Repository:
- International Conference on Human-Computer Interaction
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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