In recent years, growing attention has been directed toward the use of Artificial Intelligence (AI) to support the development of metacognitive skills in students, particularly in the formulation of effective questions. This research examines studies published between 2019 and 2025 on the concept of "meta-prompting" in education, analyzing how AI can serve as a tool to enhance students' ability to reflect on their own learning and pose quality questions. The main strategies and theoretical models for integrating AI into metacognitive processes are identified, along with empirical evidence of benefits achieved (improved self-regulation, question generation capacity, and academic performance). At the same time, emerging challenges are discussed, including the risk of AI dependency and "metacognitive laziness," and the pedagogical implications of such technologies. The results suggest that AI, if designed and used consciously, can facilitate meta-prompting and promote more self-reflective learning, contributing to the development of more autonomous students who are aware of their own cognitive process.
Meta-prompting in Education: the role of Artificial Intelligence in students' metacognitive development for effective question formulation / Maria Ranieri; Gabriele Biagini. - In: Q-TIMES WEBMAGAZINE. - ISSN 2038-3282. - ELETTRONICO. - 17:(2025), pp. 3.606-3.621.
Meta-prompting in Education: the role of Artificial Intelligence in students' metacognitive development for effective question formulation
Maria Ranieri;Gabriele Biagini
2025
Abstract
In recent years, growing attention has been directed toward the use of Artificial Intelligence (AI) to support the development of metacognitive skills in students, particularly in the formulation of effective questions. This research examines studies published between 2019 and 2025 on the concept of "meta-prompting" in education, analyzing how AI can serve as a tool to enhance students' ability to reflect on their own learning and pose quality questions. The main strategies and theoretical models for integrating AI into metacognitive processes are identified, along with empirical evidence of benefits achieved (improved self-regulation, question generation capacity, and academic performance). At the same time, emerging challenges are discussed, including the risk of AI dependency and "metacognitive laziness," and the pedagogical implications of such technologies. The results suggest that AI, if designed and used consciously, can facilitate meta-prompting and promote more self-reflective learning, contributing to the development of more autonomous students who are aware of their own cognitive process.| File | Dimensione | Formato | |
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