Generative AI-Integrated Inquiry-Based Learning: A Preliminary Study on Science Data Literacy in Biology Learning Juju Juwita (a*), Widi Purwianingsih (b), Siti Sriyati (c)
a, b, c) Master of Biology Education, Universitas Pendidikan Indonesia, Jalan Dr. Setiabudhi 229, Bandung 40154, Indonesia
*jwt.j1221[at]upi.edu
Abstract
Science data literacy (SDL) is an essential competency in 21st-century biology education, yet empirical evidence consistently indicates that this capability remains critically low among secondary school students. This preliminary study aimed to identify gaps in SDL competency of students as well as AI usage patterns and perceptions of the teacher toward inquiry-based learning, as the empirical foundation for designing a Google Gemini-assisted inquiry-based learning intervention. The study involved 72 tenth-grade students and one biology teacher. Data were collected through three instruments: an initial SDL competency assessment administered to students, an inquiry-based learning perception questionnaire, and an AI usage questionnaire, both adapted from previously validated instruments. The study revealed three key findings: (1) approximately 70-80% of students had not yet optimally mastered SDL competencies required for data-driven biology learning- (2) the teacher demonstrated positive perceptions toward inquiry-based learning, but implementation remained constrained by time limitations, resulting in lecture-based methods still being predominantly used- and (3) although the teacher had utilized AI for instructional preparation, AI had not been integrated into direct pedagogical interactions with students. Collectively, these findings identify a critical gap while establishing the empirical foundation for further research on the effect of integrating Google Gemini in inquiry-based learning on SDL of students in biodiversity learning as an effort to achieve SDG Life on Land.
Keywords: science data literacy, AI-integrated inquiry-based learning, generative AI, Google Gemini, biodiversity
