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Reorientation of Deep Learning Based Instruction in Enhancing Students' Metacognitive Competence Herman Pakiding; Ruth Judica Siahaan
Formosa Journal of Science and Technology Vol. 5 No. 4 (2026): April 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjst.v5i4.55

Abstract

This research is motivated by the importance of developing students' metacognitive competencies in 21st century learning that requires reflective skills and self-regulation. This study aims to analyze the influence and reorientation of deep learning-based instruction on students' metacognitive competence. The approach used was a mixed method with a sequential explanatory design, involving 120 respondents and 12 informants, with data collection techniques in the form of questionnaires and interviews as well as inferential and thematic statistical analysis. The results showed a significant influence with a contribution of 62%, where the reflective dimension was the dominant factor, although the monitoring and technology utilization aspects were still not optimal. This study concludes that deep learning-based learning reorientation integrated with metacognitive strategies can improve the quality of learning theoretically and practically