Application of Adaptive Systems with Artificial Intelligence in The Professional Training of Pre-Service Biology Teachers – Opportunities and Perspectives

Authors

  • Asya Asenova Sofia University “St. Kliment Ohridski”

DOI:

https://doi.org/10.33919/YTelecomm.25.12.12

Keywords:

digital competencies, generative AI, interactive platforms, Moodle integration, personalized learning, project-based learning

Abstract

This article examines the application of adaptive learning systems with artificial intelligence (AI) in the training of future biology teachers. These systems personalize the learning process according to students’ knowledge, interests, and pace, providing adaptive content, tasks, and real-time feedback. The OATutor platform illustrates how AI supports the acquisition of biological concepts, develops critical thinking, and enhances digital competencies. Through integration with Moodle and interactive features, an environment is created that combines automation, pedagogical support, and an individualized approach to learning. Three case studies – personalized explanations with generative AI, project-based learning with a virtual AI assistant, and virtual laboratories for experimental learning – demonstrate how adaptive systems foster critical thinking, engagement, and the development of professional and digital competencies in students. The article emphasizes that intelligent AI systems can be a valuable tool for contemporary biology education, combining automation, personalization, and pedagogical expertise in a single integrated environment.

References

SLAVOV, V., YOTOVSKA, K., and A. ASENOVA. Research on the attitudes of high school students for the application of artificial intelligence in education. In: Proceedings of the International Association for the Development of the Information Society (IADIS). International Conferences on e Society and Mobile Learning 2023 [online]. IADIS Press, 2023, pp. 317–326 [viewed 17.06.2026]. ISBN 978-989-8704-47-4. Available from: https://files.eric.ed.gov/fulltext/ED639391.pdf.

PARDOS, Z. A., TANG, M., ANASTASOPOULOS, I., SHEEL, S. K., and E. ZHANG. OATutor: An open-source adaptive tutoring system and curated content library for learning sciences research. In: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems [online]. 2023, № 416, pp. 1–17 [viewed 17.06.2026]. ISBN 978-1-4503-9421-5. Available from: https://doi.org/10.1145/3544548.3581574

HOLMES, W., BIALIK, M., and C. FADEL. Artificial intelligence in education: Promise and implications for teaching and learning. Center for Curriculum Redesign, 2019 [viewed 17.06.2026]. ISBN 978-1-794-29370-0. Available from: https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf

HARIYANTO, H., KRISTIANINGSIH, F. X. D., and R. MAHARANI. Artificial intelligence in adaptive education: A systematic review of techniques for personalized learning. Discover Education [online]. 2025, vol. 4, Article № 458 [viewed 17.06.2026]. еISSN 2731-5525. Available from: https://doi.org/10.1007/s44217-025-00908-6

CHEN, L., CHEN, P., and Z. LIN. Artificial intelligence in education: A review. IEEE Access [online]. 2020, vol. 8, pp. 75264–75278 [viewed 17.06.2026]. ISSN 2169-3536. Available from: https://doi.org/10.1109/ACCESS.2020.2988510

OWAN, V. J., ABANG, K. B., IDIKA, D. O., ETTA, E. O., and В. А. BASSEY. Exploring the potential of artificial intelligence tools in educational measurement and assessment. Eurasia: Journal of Mathematics, Science and Technology Education [online]. 2023, vol. 19(8), pp. 1-15 [viewed 17.06.2026]. ISSN 1305-8223. Available from: https://doi.org/10.29333/ejmste/13428

NASUTION, N. E. A. Using artificial intelligence to create biology multiple choice questions for higher education. Agricultural and Environmental Education [online]. 2023, vol. 2(1), pp. 1-15 [viewed 17.06.2026]. eISSN 2752-647X. Available from: https://doi.org/10.29333/agrenvedu/13071

ARIPIN, I., GAFFAR, A. A., JABAR, M. B. A., and D. YULIANTI. Artificial intelligence in biology and learning biology: A literature review. Jurnal Mangifera Edu [online]. 2024, vol. 8(2), pp. 41–48 [viewed 17.06.2026]. ISSN 2622-3384. Available from: https://doi.org/10.31943/mangiferaedu.v8i2.185

MAHAFDAH, R., BOUALLEGUE, S., and R. BOUALLÈGUE. Enhancing e-learning through AI: Advanced techniques for optimizing student performance. PeerJ Computer Science [online]. 2024, vol. 10, e2576 [viewed 17.06.2026]. ISSN 2167-8359. Available from: https://doi.org/10.7717/peerj-cs.2576

VILLEGAS-ESPINOZA, A. E. J. and J. I. NECOCHEA-CHAMORRO. Using deep learning in student performance prediction: A systematic review. TEM Journal [online]. 2025, vol. 14(3), pp. 2472–2482 [viewed 17.06.2026]. eISSN 2217-8333. Available from: https://doi.org/10.18421/TEM143-51

NAYINI, P. AI and the future of education: Advancing personalized learning and intelligent tutoring systems. Frontiers in Educational Innovation and Research [online]. 2025, vol. 1(1), pp. 29-39 [viewed 17.06.2026]. ISSN 3068-5664. Available from: https://doi.org/10.62762/FEIR.2025.332098

WEITEKAMP, D., HARPSTEAD, E., and K. R. KOEDINGER. An interaction design for machine teaching to develop AI tutors. CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems [online]. 2020, pp. 1-11 [viewed 17.06.2026]. ISBN 978-1-4503-6708-0. Available from: https://doi.org/10.1145/3313831.3376226

KELLEY, M., and T. WENZEL, (2025). Advancing artificial intelligence literacy in teacher education through professional partnership inquiry. Education Sciences [online]. 2025, vol. 15(6), pp. 1-15 [viewed 17.06.2026]. ISSN 2227-7102. Available from: https://doi.org/10.3390/educsci15060659

ДЖАДЖАРОВА, З. Възможности за използване на изкуствен интелект в образователния процес. i-Продължаващо образование [онлайн]. [прегледан 17.06.2026]. Достъпен на: https://journal.deo.uni-sofia.bg/16221 [DZHADZHAROVA, Z. Vazmozhnosti za izpolzvane na izkustven intelekt v obrazovatelnia protses. i-Prodalzhavashto obrazovanie [onlayn]. [pregledan 17.06.2026]. Dostapen na: https://journal.deo.uni-sofia.bg/16221]

ПАВЛОВА, Н. и Д. МАРЧЕВ. Използване на изкуствен интелект – етични норми и приложение в подготовката на бъдещите учители. Математика и математическо образование [онлайн]. 2024, год. 53, с. 154-160 [прегледан 17.06.2026]. еISSN 2815-4002. Достъпен на: https://smb.math.bas.bg/mem/index.php/memjournal/article/view/139 [PAVLOVA, N. i D. MARChEV. Izpolzvane na izkustven intelekt – etichni normi i prilozhenie v podgotovkata na badeshtite uchiteli. Matematika i matematichesko obrazovanie [onlayn]. 2024, god. 53, s. 154-160 [pregledan 17.06.2026]. eISSN 2815-4002. Dostapen na: https://smb.math.bas.bg/mem/index.php/memjournal/article/view/139]

. PLACHKOV, D. The effect of adaptive AI systems on student motivation and performance in higher education. New Knowledge Journal of Science [online]. 2025, vol. 1(14), pp. 27-30 [viewed 17.06.2026]. еISSN 2367-4598. Available from: https://science.uard.bg/index.php/newknowledge/article/view/1095

LEE, A. V. Y. Supporting students’ generation of feedback in large-scale online course with artificial intelligence-enabled evaluation. Studies in Educational Evaluation [online]. 2023, vol. 77, №101250 [viewed 17.06.2026]. ISSN 0191-491X. Available from: https://doi.org/10.1016/j.stueduc.2023.101250

WEITEKAMP, D., HARPSTEAD, E., and K. R. KOEDINGER. An interaction design for machine teaching to develop AI tutors. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems [online]. 2020, pp. 1–11 [viewed 17.06.2026]. Association for Computing Machinery. ISBN 978-1-4503-6708-0. Available from: https://doi.org/10.1145/3313831.3376226

GOUROVA, E., KADREV, V., STANCHEVA, A., DRAGOMIROVA, M., and G. PETROV. Adapting educational programmes according to e-competence needs: The Bulgarian case. Interactive Technology and Smart Education [online]. 2014, vol. 11(2), pp. 123-145 [viewed 17.06.2026]. eISSN 1758-8510. Available from: https://doi.org/10.1108/ITSE-04-2014-0006

СТЕФАНОВА, Т., ПЕТРОВ, Г., БОГОМИЛОВ, И., и А. СЛАВИНСКИ. Анкетното проучване за обучението в бакалавърските и магистърските програми на департамент Телекомуникации на НБУ. Управление и образование (Management and Education) [онлайн]. 2014, год. 10(3), с. 146-155. ISSN 1312-6121 [прегледан 17.06.2026]. Достъпен на: https://www.conference-burgas.com/maevolumes/vol10/b3_v10.pdf [STEFANOVA, T., PETROV, G., BOGOMILOV, I., i A. SLAVINSKI. Anketnoto prouchvane za obuchenieto v bakalavarskite i magistarskite programi na departament Telekomunikatsii na NBU. Upravlenie i obrazovanie (Management and Education) [onlayn]. 2014, god. 10(3), s. 146-155. ISSN 1312-6121 [pregledan 17.06.2026]. Dostapen na: https://www.conference-burgas.com/maevolumes/vol10/b3_v10.pdf]

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Published

2025-12-30

How to Cite

Asenova, A. (2025). Application of Adaptive Systems with Artificial Intelligence in The Professional Training of Pre-Service Biology Teachers – Opportunities and Perspectives. Yearbook Telecommunications, 12, 127–140. https://doi.org/10.33919/YTelecomm.25.12.12