Enhancing Metacognitive and Creativity Skills through AI-Driven Meta-Learning Strategies

Authors

  • Khusnul Khotimah State University of Surabaya https://orcid.org/0000-0003-3425-5063
  • Rusijono State University of Surabaya
  • Andi Mariono State University of Surabaya

DOI:

https://doi.org/10.3991/ijim.v18i05.47705

Keywords:

meta-learning, artificial intelligence, metacognitive, creativity, quality education, innovation

Abstract


This study investigates the efficacy of a meta-learning approach in improving metacognitive and creative skills. This quantitative study focused on an experimental group using a onegroup pretest-posttest research design. All participants underwent a pretest to assess their initial metacognitive abilities and were subsequently exposed to a meta-learning framework throughout the course. A post-test was conducted to assess the impact of the intervention. The findings indicate a statistically significant improvement in metacognitive skills from the pretest to the post-test. This study confirms the effectiveness of meta-learning strategies and elucidates the relationship between meta-learning and metacognition. Meta-learning enables students to comprehend their own learning processes, thereby improving their capacity to strategize, oversee, and control their cognitive functions with the assistance of artificial intelligence (AI). This approach incorporates creative elements that can stimulate metacognitive thinking, encouraging students to adjust their learning strategies and think outside the box. This research suggests that meta-learning can improve metacognitive abilities, providing valuable insights into educational technology and course design in higher education settings.

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Published

2024-03-05

How to Cite

Khusnul Khotimah, Rusijono, & Andi Mariono. (2024). Enhancing Metacognitive and Creativity Skills through AI-Driven Meta-Learning Strategies. International Journal of Interactive Mobile Technologies (iJIM), 18(05), pp. 18–31. https://doi.org/10.3991/ijim.v18i05.47705

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Section

Papers