Utilization of Generative Artificial Intelligence in Biology Learning: Expert and Empirical Validation Analysis in High School Students - Lizawati Lizawati; Iffa Ichwani Putri; Nurkhairo Hidayati; Yeyendra Yeyendra; Andri Hendrizal (Universitas Syiah Kuala, in collaboration with the Perkumpulan Pendidik IPA Indonesia (PPII), (MoU), 2026)
The rapid integration of generative artificial intelligence (AI) in education offers transformative potential, yet its implementation in specific subjects like biology often lacks validated evaluation instruments. This study aims to analyze the results of expert and empirical validation of the use of generative artificial intelligence in biology learning at the high school level. This study used a quantitative approach with an evaluative design. The main stages of the study consisted of expert validation and empirical testing. Data analysis was conducted descriptively and empirically. The empirical test was conducted on 35 high school students to test the validity and reliability of the items using correlation product-moment and Pearson. The results of the study indicate that the content validity index (CVI) analysis of the generative AI instrument in biology learning is highly valid, with an average indicator percentage of 94.17. The results of empirical testing of 40 questionnaires on the use of generative AI through product-moment correlation found 32 valid items (80%) and 8 invalid items (20%). Meanwhile, testing with Pearson correlation showed 22 highly significant items (55%), 6 significant items (15%), and 12 insignificant items (30%). The reliability test showed a value of 0.925 (highly reliable). Based on these findings, it can be concluded that the results of expert and empirical validation can be declared valid and reliable. Furthermore, this instrument can be implemented in schools