LEVERAGING AI IN SELF-DIRECTED LEARNING: A PHENOMENOLOGICAL STUDY OF MASTER’S STUDENTS’ EXPERIENCES
The rapid integration of Artificial Intelligence (AI) in education has reshaped self-directed learning (SDL), yet empirical insights into students’ experiences remain underexplored. This qualitative phenomenological study investigates master’s students’ experiences, awareness, and perceived meanings...
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| Main Authors: | , |
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| Format: | Article |
| Language: | Indonesian |
| Published: |
Universitas Negeri Surabaya
2025-05-01
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| Series: | JP (Jurnal Pendidikan) |
| Subjects: | |
| Online Access: | https://journal.unesa.ac.id/index.php/jp/article/view/39122 |
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| Summary: | The rapid integration of Artificial Intelligence (AI) in education has reshaped self-directed learning (SDL), yet empirical insights into students’ experiences remain underexplored. This qualitative phenomenological study investigates master’s students’ experiences, awareness, and perceived meanings of AI-driven SDL at Yogyakarta State University. Data from in-depth interviews with nine participants revealed three core themes: (1) AI-enhanced efficiency and personalized learning, (2) awareness of AI’s benefits (e.g., accessibility) and limitations (e.g., accuracy, dependency risks), and (3) the dual impact of AI on critical thinking and ethical concerns. While students leveraged AI for task management and information access, they emphasized the necessity of cross-verifying AI-generated content and maintaining academic autonomy. Challenges included reduced deep engagement and potential over-reliance on technology. The study highlights the imperative for balanced AI integration in higher education, advocating for ethical guidelines, educator training, and adaptive curricula that harmonize technological innovation with critical literacy development. These findings inform strategies to optimize AI’s educational potential while safeguarding academic rigor and student agency, offering a framework for institutions navigating the digital transformation of learning. |
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| ISSN: | 2527-6891 |