Pembelajaran Berbasis Kecerdasan Buatan Terhadap Motivasi Belajar Peserta Didik dalam Pembelajaran Biologi: Sistem Literatur Review - Zahren; Yogica, Relsas; Fitri, Rahmadhani (CAHAYA: Journal of Research on Science Education, 2025)
Biology learning currently faces challenges in the form of complex material, abstract concepts, and difficult-to-understand language, which impacts students' low learning motivation. This study aims to examine the impact of the application of artificial intelligence (AI) on students' learning motivation in biology education through the Systematic Literature Review (SLR) method. Data were obtained from the Google Scholar, ScienceDirect, and ERIC databases, using the keywords "artificial intelligence," "AI," and "learning motivation" in publications from 2020–2025. Five main articles were analysed and showed that the application of AI consistently has a positive impact on students' learning motivation. The findings show a 75% increase in learning motivation, a significant relationship between AI usage and learning motivation (r = 0.969; p = 0.000), as well as improved learning outcomes. AI contributes through personalised learning, immediate feedback, extensive information access, and more engaging interactions. Chatbots and applications like ChatGPT have proven effective in increasing student engagement and understanding of the material. Overall, the use of AI in biology education can enhance student learning motivation and serve as a potential solution to current biology education challenges.