Artificial intelligence in science education: A systematic review of applications, impacts, and challenges
1 Kazan (Volga Region) Federal University, Kazan, RUSSIA
2 I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, RUSSIA
3 Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University), Moscow, RUSSIA
4 Almetyevsk State Technological University «Petroleum High School», Almetyevsk, RUSSIA
* Corresponding Author
This systematic review investigates the incorporation of artificial intelligence (AI) into science education by analyzing 17 studies published from 2020 to 2024. The paper examines the utilization of AI in different scientific fields and educational settings and assesses its influence on the methods of teaching and learning. The findings demonstrate a diverse range of AI applications, including chatbots, intelligent tutoring systems, and AI-enhanced textbooks. These apps serve many functions, from being educational tools to assisting in assessments. The investigation demonstrates the favorable impact of AI on student performance, motivation, and engagement in science education, particularly in the areas of personalized learning and the development of self-regulated learning skills. Additionally, issues related to technological infrastructure, obstacles to the sensitivity and reliability of AI systems, and ethical issues were also examined. The study emphasizes the importance of teacher preparation in achieving the successful integration of AI and expresses the necessity of comprehensive professional development. Potential areas for future research encompass investigating the enduring consequences of AI utilization, exploring its applicability in diverse educational settings, and fostering the growth of AI literacy. The study’s findings indicate that while AI has the potential to greatly improve science education, its successful application necessitates thoughtful evaluation of technological, pedagogical, ethical, and social elements to ensure fair and efficient integration across all educational levels.
Fayzullina, A. R., Filippova, A. A., Garnova, N. Y., Astakhov, D. V., Kalmazova, N., & Zaripova, Z. F. (2025). Artificial intelligence in science education: A systematic review of applications, impacts, and challenges.
Contemporary Educational Technology, 17(4), ep613.
https://doi.org/10.30935/cedtech/17519
Fayzullina, A. R., Filippova, A. A., Garnova, N. Y., Astakhov, D. V., Kalmazova, N., and Zaripova, Z. F. (2025). Artificial intelligence in science education: A systematic review of applications, impacts, and challenges.
Contemporary Educational Technology, 17(4), ep613.
https://doi.org/10.30935/cedtech/17519
Fayzullina AR, Filippova AA, Garnova NY, Astakhov DV, Kalmazova N, Zaripova ZF. Artificial intelligence in science education: A systematic review of applications, impacts, and challenges.
CONT ED TECHNOLOGY. 2025;17(4), ep613.
https://doi.org/10.30935/cedtech/17519
Fayzullina, Albinа R., Alla A. Filippova, Natalya Y. Garnova, Dmitry V. Astakhov, Nadezhda Kalmazova, and Zulfiya F. Zaripova. "Artificial intelligence in science education: A systematic review of applications, impacts, and challenges".
Contemporary Educational Technology 2025 17 no. 4 (2025): ep613.
https://doi.org/10.30935/cedtech/17519
Fayzullina, Albinа R. et al. "Artificial intelligence in science education: A systematic review of applications, impacts, and challenges".
Contemporary Educational Technology, vol. 17, no. 4, 2025, ep613.
https://doi.org/10.30935/cedtech/17519
Fayzullina AR, Filippova AA, Garnova NY, Astakhov DV, Kalmazova N, Zaripova ZF. Artificial intelligence in science education: A systematic review of applications, impacts, and challenges. CONT ED TECHNOLOGY. 2025;17(4):ep613.
https://doi.org/10.30935/cedtech/17519