Bustam , Mohamad Azmi
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Generative AI in Science Education: A Learning Revolution or a Threat to Academic Integrity? A Bibliometric Analysis Wirzal, Mohd Dzul Hakim; Md Nordin, Nik Abdul Hadi; Abd Halim, Nur Syakinah; Bustam , Mohamad Azmi
Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika Vol. 8 No. 3: November 2024
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/e-saintika.v8i3.2127

Abstract

The integration of generative artificial intelligence (AI) in Science, Technology, Engineering, and Mathematics (STEM) education presents transformative opportunities alongside significant challenges. This study investigates the dual impact of generative AI on STEM learning outcomes and academic integrity through a comprehensive bibliometric analysis employing co-citation, keyword analysis, and trend mapping. The results reveal that AI tools such as ChatGPT have revolutionized personalized learning by offering tailored feedback, enhancing critical thinking, and improving student engagement. However, these advancements are tempered by concerns over academic misconduct, particularly plagiarism, and the erosion of essential cognitive skills due to overreliance on AI-generated content. Ethical considerations remain critical, necessitating the development of robust policies and ethical frameworks to safeguard academic integrity. Beyond educational settings, the findings suggest broader applicability to professional training and skills development, as the benefits and challenges of AI extend beyond coursework. This research provides valuable insights for educators, policymakers, and researchers, advocating for a balanced approach to AI integration that maximizes its potential while preserving educational standards.