The Use of Artificial Intelligence in Biology Education: A Bibliometric Content Analysis

Yıl 2025, Cilt: 16 Sayı: 32, 301 - 324, 19.12.2025

Mihrican Balaban Zor

https://doi.org/10.58689/eibd.1728713

Öz

Abstract: The rapid advancements in artificial intelligence have significantly impacted the field of education. This study aims to identify and analyze research on the use of artificial intelligence in biology education, exploring how AI is utilized, its implementation in schools, and the advantages and disadvantages it brings. Furthermore, it reveals the different aspects addressed by studies in this field and the progression of AI use in biology education. The research adopts a bibliometric content analysis, a mixed-methods approach. Relevant articles were obtained from “Google Scholar,” “Scopus,” and “Web of Science” databases using keywords such as “biology education,” “artificial intelligence,” “AI,” “ChatGPT,” and “LLM.” After necessary filtering, a total of 40 articles were used for analysis. The review indicates that the highest number of publications on AI in biology education occurred in the years 2023, 2024, and the ongoing 2025. Additionally, while the results highlight the benefits of using AI in biology education, they also indicate potential drawbacks, especially for middle and high school students, if not supervised properly.

Anahtar Kelimeler

biology education , artificial ıntelligence , chatgpt , secondary education , content analysis.

Biyoloji Eğitiminde Yapay Zeka Kullanımı: Bibliyometrik İçerik Analizi

Öz

Öz: Yapay zeka ile ilgili gelişmelerin hız kazanması, eğitim alanını da oldukça etkilemektedir. Bu araştırma, Biyoloji eğitiminde yapay zekanın kullanımına yönelik yapılan çalışmalara ulaşılıp bu çalışmaların yapay zekanın biyoloji eğitiminde nasıl kullanıldığı, okullardaki uygulamalarını, kullanımının saplayacağı avantaj ve dezavantajları ortaya koymak amacıyla yapılmıştır. Ayrıca, bu alanda yapılan çalışmaların ele aldığı farklı yönler ve yapay zekanın biyoloji eğitiminde kullanımının nasıl ilerlediği de ortaya çıkarılmıştır. Araştırmada karma yöntemlerden olan bibliyometrik içerik analizi benimsenmiştir. Analize ait verileri elde etmek için araştırma konusuna uyan makalelere “Google Scholar”, “Scopus” ve “web of science” veri tabanlarından ulaşılmıştır. Bu veri tabanlarında “biology education”, “artifiicial intellengence” “AI”, “ChatGPT”, “LLM” gibi anahtar kelimeleri ile yapılan taramada gerekli ayıklamalar yapıldıktan sonra toplam 40 makale araştırma için kullanılmıştır. Analizin yapıldığı çalışmalar incelendiğinde biyoloji eğitiminde yapay zeka ile ilgili en fazla yayının yapıldığı yıllar 2023, 2024 ve devam eden 2025 yılı olarak görülmektedir. Ayrıca çalışmaların sonuçlarına bakıldığında yapay zekanın biyoloji eğitiminde kullanılmasının sağladığı avantajların yanı sıra denetimli bir şekilde yapılmadığında özellikle orta okul ve lise öğrencileri için dezavantajlarının da olduğu görülmektedir.

Anahtar Kelimeler

biyoloji eğitimi , yapay zeka , chatGBT , lise eğiitimi , içerik analizi

Etik Beyan

Çalışma etik kurul izni gerektirmemektedir.

Destekleyen Kurum

Bu çalışmada herhangi bir resmi, ticari ya da kâr amacı gütmeyen organizasyondan fon desteği alınmamıştır.

Kaynakça

• Almasri, A. (2024). Artificial intelligence and STEM education: Opportunities and ethical challenges. Journal of Educational Innovation, 12(1), 22–36.
• Al-Muqbil, A. (2024). Enhancing sustainable thinking through AI-supported teacher training. Saudi Journal of Science Education, 15(4), 203–220.
• Alpaydın, E. (2013). Yapay öğrenme. Boğaziçi Üniversitesi Yayınları.
• Aria, M. ve Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mappinganalysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
• Aydoğan, A. ve Karcı, E. (2018). Eğitimde yapay zekâ uygulamaları: Kavramsal çerçeve ve örnekler. Eğitim Teknolojileri Araştırmaları Dergisi, 9(1), 55–74.
• Bae, J. ve Son, H. (2025). Integrating AI into high school biology: Pedagogical innovations and challenges. Asian Journal of Biology Education, 18(2), 117–134.
• Bilgin, E. A. ve Hızarcı, S. (2022). Artırılmış gerçeklik destekli istatistik öğretiminin lise öğrencilerinin akademik başarılarına ve teknolojiye yönelik tutumlarına etkisinin incelenmesi. Turkish Studies Education, 17(1), 23-47. https://doi.org/10.47423/TurkishStudies.52138
• Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. https://doi.org/10.3316/QRJ0902027
• Burgsteiner, H., Kandlhofer, M. ve Steinbauer, G. (2016). IRobot: teaching the basics of artificial intelligence in high schools. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.9864
• Byeon, H. (2022). AI applications in secondary science education: A Korean perspective. Korean Journal of Educational Technology, 38(3), 145–162.
• Chen, L., Chen, P. ve Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
• Choi, E. ve Park, N. (2021). Demonstration of gamification in education for understanding artificial intelligence principles at elementary school level, Elementary Education Online, 20(3), 709–715. doi: 10.17051/ilkonline.2021.03.74
• Çiloplu, N. (2022). Lise öğrencilerinin artırılmış gerçeklik ve yapay zekâ uygulamalarına yönelik görüşleri. Eğitimde Teknoloji Araştırmaları Dergisi, 14(2), 98–111.
• Çolak Yazıcı, T. ve Erkoç, H. (2024). Teachers’ perceptions on AI integration in biology education. Journal of Educational Technology and Teacher Education, 9(1), 67–85.
• Çulha, H. ve Ünaldı, Ü. C. (2025). ChatGPT ile biyoloji öğrenimi: Lise öğrencilerinin görüşleri. Biyoloji Eğitimi Araştırmaları Dergisi, 7(1), 29–49
• Dao, M. T. ve Le, H. T. (2023). A comparative study of AI-supported biology teaching strategies. Vietnam Journal of Science Education, 11(2), 78–93.
• De Winter, J. (2023). AI in classrooms: Trends, challenges, and outcomes. Educational Technology Horizons, 26(1), 45–63.
• Dikmen, S. ve Bahçeci, F. (2024). Eğitim bilimleri alanında yapay zekâ konulu bilimsel yayınların eğilimleri: bibliyometrik bir inceleme. Socrates Journal of Interdisciplinary Social Studies, 10, 98-111. DOI: 10.5281/zenodo.13981118
• Donthu, N., Kumar, S., Mukherjee, D., Pandey, N. ve Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296.
• Elizondo-García, C., Hernández-Bravo, J. A. ve Hernández-Bravo, J. (2025). Perceptions of AI use in challenge-based biology learning contexts. International Journal of Educational Research, 113, 102134.
• Fütterer, T., Schneider, S. ve Kunz, T. (2023). AI literacy in K-12 education: Perceptions of ChatGPT in science classrooms. International Journal of STEM Education, 10(1), 45 60.
• García, H., López, R. ve Sánchez, P. (2020). Cognitive development through AI-supported simulations. AI in Education Journal, 8(2), 31–49.
• Gibson, D., Kovanovic, V., Ifenthaler, D., Dexter, S. ve Feng, S. (2023). Learning theories for artificial intelligence promoting learning processes. British Journal of Educational Technology, 54, 1125–1146. https://doi.org/10.1111/bjet.13341
• Gil de Zúñiga, H., Goyanes, M. ve Durotoye, T. (2024). A scholarly definition of Artificial Intelligence (AI): advancing AI as a conceptual framework in communication research. Political Communication, 41(2), 317–334.
• Han, Y. (2020). Connecting the past to the future of computer-assisted language learning: theory, practice, and research”, Issues and Trends in Learning Technologies 8(1). doi:https://doi.org/10.2458/azu_itlt_v8i1_han
• Heinzinger, M. ve Rost, B. (2025). From protein language models to education: Teaching bioinformatics with AI. Bioinformatics Education, 19(1), 112–128.
• Holmes, W., Bialik, M. ve Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
• Hong, J. C. ve Kim, H. (2020). High school students' attitudes toward AI-supported learning environments. Journal of Learning Sciences, 29(4), 357–370.
• Huang, Y., Ling, L. ve Liı, Y. (2024). Teaching classification algorithms with mushroom datasets in secondary biology. Computational Science Education, 8(2), 92–105.
• Kim, H. ve Kang, S. (2024). Promoting creative thinking through AI-supported writing and model eliciting activities in biology education. Asia-Pacific Science Education, 10(2), 187–209.
• Kim, M. ve Kim, J. (2022). Barriers to AI implementation in Korean secondary schools: A mixed-methods study. Korean Journal of Educational Research, 60(1), 89–108.
• Kore Eğitim Bakanlığı, (2023). https://english-moe gokr.translate.goog/sub/infoRenewal.do?m=0301&page=0301&s=english&_x_tr_sl &_x_tr_tl=tr&_x_tr_hl=tr&_x_tr_pto=tc
• Lee, E. K. (2020). Development of test tool of attitude toward artificial intelligence for middle school students. Journal of The Korean Association of Information Education, 24(2), 207–213.
• Lee, J. (2021). Perceptions of AI literacy in secondary education: A national survey. Journal of Educational Innovation, 14(3), 134–152.
• Lee, K.Y., Sheehan, L., Lee, K. ve Chang, Y. (2021), The continuation and recommendation intention of artificial intelligence-based voice assistant systems (AIVAS): the influence of personal traits. Internet Research, 31(5),1899-1939. https://doi.org/10.1108/INTR 06-2020-0327.
• Lee, Y. (2019). An analysis of the influence of block-type programming language-based artificial intelligence education on the learner’s attitude in artificial intelligence. Journal of The Korean Association of Information Education. https://doi.org/10.14352/jkaie.2019.23.2.189
• Luckin, R., Holmes, W., Griffiths, M. ve Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
• McNamara, D. S., Jackson, G. T. ve Graesser, A. C. (2021). The iSTART Intelligent Tutoring System: Reading strategy training in science. Computers in Human Behavior, 114, 106531.
• Millî Eğitim Bakanlığı. (2021). Ulusal Yapay Zekâ Stratejisi 2021–2025. T.C. Sanayi ve Teknoloji Bakanlığı & Dijital Dönüşüm Ofisi.
• Mitchell, M. (2019). Artificial intelligence: A guide for thinking humans. Pelican Books.
• Moongela, H., Matthee, M., Turpin, M. ve van der Merwe, A. (2025). The effect of generative artificial intelligence on cognitive thinking skills in higher education institutions: A systematic literature review. In: Gerber, A., Maritz, J., Pillay, A.W. (eds) Artificial Intelligence Research. SACAIR 2024. Communications in Computer and Information Science, vol 2326, Springer, Cham. https://doi.org/10.1007/978-3-031-78255-8_21
• Nguyen, T. P. ve Le, M. T. (2023). Evaluating the effectiveness of ChatGPT in high school biology classrooms. Vietnam Journal of Educational Technology, 12(3), 34–48.
• Oh, K. ve Kim, H. (2020). An analysis of the influence big data analysis-based ai education on affective attitude towards artificial intelligence. Journal of The Korean Association of Information Education. https://doi.org/10.14352/jkaie.2020.24.5.463
• Page, M.J., McKenzie, J.E., Bossuyt, P.M., Boutron, I., Hoffmann, T.C., Mulrow, C.D., Shamseer, L., Tetzlaff, J.M., Akl, E.A., Brennan, S.E., Chou, R., Glanville, J., Grimshaw, J.M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372 (71).
• Passas, I. (2024). Bibliometric analysis: The main steps. Encyclopedia, 4(2), 1014–1025.
• Rudolph, J., Tan, S. ve Cohen, A. (2023). ChatGPT in the classroom: Pedagogical impacts and research directions. Journal of Educational Technology Research and Development.
• Russell, S. J. ve Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4. baskı). Prentice Hall.
• Sáez-Velasco, S., Alaguero-Rodríguez, M., Rodríguez-Cano, S. ve Delgado-Benito,V. (2025). Students’ attitudes towards aı and how they perceive the effectivenessof AI in designing video games. Sustainability, 17, 3096.
• Salas-Pilco, S. Z. (2020). Artificial intelligence in education: A systematic review. Educational Technology & Society, 23(3), 65–76.
• Shamir, A. ve Levin, I. (2020). AI education in early adolescence: Ethical and practical dimensions. Computers & Education, 145, 103729.
• Shin, D. (2021). The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI, International Journal of Human-Computer Studies, 146, 102551.
• Slimi, Z., Benayoune, A. ve Alemu, A. E. (2025). Students’ perceptions of artificial intelligence integration in higher education. European Journal of Educational Research, 14(2), 471 484. https://doi.org/10.12973/eu-jer.14.2.471
• Storey, M. A. ve Wagner, B. (2024). A framework for using AI to support formative assessment in science. Educational Measurement, 41(2), 67–91.
• Tuomi, I. (2018). The impact of artificial intelligence on learning, teaching and education: Policies for the future. European Commission Joint Research Centre.
• Vachovsky, M. E., Wu, G., Chaturapruek, S., Russakovsky, O., Sommer, R. ve Fei-Fei, L. (2016). Towards more gender diversity in CS through an artificial intelligence summer program for high school girls. SIGCSE 2016 - Proceedings of the 47th ACM Technical Symposium on Computing, 303-308.
• Winston, P. H. (1992). Artificial Intelligence (3. baskı). Addison-Wesley.
• Xie, H., Chu, H. C., Hwang, G. J. ve Wang, C. C. (2021). Trends and development in technology-enhanced adaptive/personalized learning: A systematic review of journal publications from 2007 to 2017. Computers & Education, 140, 103599.
• Zawacki-Richter, O., Marín, V. I., Bond, M. ve Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27.
• Zhai, X., Zhang, M. ve Xu, Y. (2022). Advantages and limitations of AI in science education: A systematic review. Science Education International, 33(1), 14–25.
• Zhou, Y. ve Schofield, H. (2024). Ethical risks of AI-based tutoring systems in K-12 education. Journal of Educational Ethics, 12(2), 99–118.
• Zilyas, D. ve Yılmaz, A. (2023). Makine öğrenmesi yöntemleri ile eğitim başarısının tahmini modeli. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi, 14(3), 437–447. https://doi.org/10.24012/dumf.1322273
• Zupic, I. ve Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429-472. https://doi.org/10.1177/1094428114562629.