Browsing by Author "Bizhanova A."

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    AI-Powered Technology in Enhancing Biology Education
    (SDU University, 2026) Bizhanova A.
    This study investigated the impact of AI-supported learning on academic achievement, student perceptions, engagement, independent learning, and AI literacy in university biology education. The research was conducted among 52 undergraduate students enrolled in a biology course focusing on nervous system anatomy. A quasiexperimental design was employed, involving a control group receiving traditional instruction and an experimental group participating in AI-supported learning activities. Data were collected using pre-tests, post-tests, and a student perception questionnaire. The results demonstrated significant improvements in academic achievement within both groups. Although the AI-supported group achieved higher mean post-test scores, the difference between groups was not statistically significant according to independent-samples t-tests and ANCOVA analyses. Questionnaire findings revealed highly positive student perceptions of AI-supported learning. Students reported that AI facilitated understanding of complex biological concepts, supported independent learning, enhanced engagement, and helped identify knowledge gaps. Participants also demonstrated awareness of AI-related challenges, including misinformation, inaccuracies, and excessive reliance on AI-generated content. The findings suggest that AI-supported learning represents a valuable complement to traditional biology instruction. While no statistically significant achievement advantage was identified, AI contributed positively to student engagement, independent learning, conceptual understanding, and responsible.