GENERATIVE ARTIFICIAL INTELLIGENCE IN THE TEACHING OF BIOLOGY: CREATING PHOTOREALISTIC IMAGES OF INSECTS OBSERVATIONS OF WATER ANIMALS IN SCHOOL AQUARIUM XXIII: AMERICAN TADPOLE SHRIMP (TRIOPS LONGICAUDATUS)

Volume 34 (2025), issue 4 pp. 2–21 published online 23 April 2026 Czech

DOI https://doi.org/10.14712/25337556.2025.4.1

PDF preview

Abstract

Artificial Intelligence (AI) is gradually changing the nature of education and offering new opportunities to support the teaching of natural sciences more effectively. In this paper, we focus on the use of generative artificial intelligence (GenAI) in the creation of photorealistic images of insects, which can serve as an innovative didactic tool in the teaching of biology. Although insects represent a significant share of global animal diversity and play key roles in ecosystems, teaching this topic is often challenging and may be unattractive for teachers and students. As part of the study, we generated a set of images of ten representatives of insects, focusing on the quality of the outputs and identifying the most common errors created by artificial intelligence during generation. Our results show that GenAI is able to create high-quality visual materials suitable for teaching, and at the same time, due to the presence of errors of varying severity in the depiction of insect representatives, it offers new possibilities for verifying students' knowledge. We therefore used the generated insect images to create a practical lesson called “Oh, insect! Is it real or fake?” to support the development of the students' critical thinking and their knowledge about the body structure of insects. Materials for this practical lesson are available for download in the electronic appendix of the paper. In our opinion, this method of using generative artificial intelligence can significantly enrich the teaching of biology dedicated to insects and other topics.

Keywords

artificial intelligence · generative artificial intelligence · entomological literacy · photorealistic images · insects · biology teaching

How to cite

Hrušková, P., Hruška, A., & Mourek, J. (2025). GENERATIVNÍ UMĚLÁ INTELIGENCE VE VÝUCE BIOLOGIE: TVORBA FOTOREALISTICKÝCH SNÍMKŮ HMYZU. Biologie-Chemie-Zeměpis, 34(4), 2–21. https://doi.org/10.14712/25337556.2025.4.1

References (52)

  1. Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K‑12 settings. AI and Ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7
  2. Aktay, S. (2022). The usability of images generated by artificial intelligence (AI) in education. International Technology and Education Journal, 6(2), 51–62.
  3. Al Darayseh, A. (2023). Acceptance of artificial intelligence in teaching science: Science teachers’ perspective. Computers and Education: Artificial Intelligence, 4, 100132. https://doi.org/10.1016/j.caeai.2023.100132
  4. Altmann, A. (1971). Didaktické zásady ve výuce biologii: (Kapitola didaktiky biologie). Určeno pro posl. pedagog. fakult. SPN.
  5. Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023). Transforming education: A comprehensive review of generative artificial intelligence in educational settings through bibliometric and content analysis. Sustainability, 15(17), 12983. https://doi.org/10.3390/su151712983
  6. Brandhofer, G., & Tengler, K. (2024). Acceptance of artificial intelligence in education: Opportunities, concerns and need for action. Advances in Mobile Learning Educational Research, 4(2), 1105–1113. https://doi.org/10.25082/AMLER.2024.02.005
  7. Cajaiba, R. L. (2014). Difficulty of science and biology teachers to teach entomology in elementary and high schools in the State of Pará, Northern Brazil. American Journal of Educational Research, 2(6), 389–392. https://doi.org/10.12691/education-2-6-10
  8. Dehouche, N., & Dehouche, K. (2023). What’s in a text-to-image prompt? The potential of stable diffusion in visual arts education. Heliyon, 9(6). https://doi.org/10.1016/j.heliyon.2023.e16757
  9. Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2024). Generative AI. Business & Information Systems Engineering, 66(1), 111–126. https://doi.org/10.1007/s12599-023-00834-7
  10. Galindo‑Domínguez, H., Delgado, N., Campo, L., & Losada, D. (2024). Relationship between teachers’ digital competence and attitudes towards artificial intelligence in education. International Journal of Educational Research, 126, 102381. https://doi.org/10.1016/j.ijer.2024.102381
  11. George, A. S., George, A. H., & Martin, A. G. (2023). The environmental impact of AI: a case study of water consumption by chat GPT. Partners Universal International Innovation Journal, 1(2), 97–104. https://doi.org/10.5281/zenodo.7855594
  12. Giray, L. (2023). Prompt engineering with ChatGPT: a guide for academic writers. Annals of biomedical engineering, 51(12), 2629–2633. https://doi.org/10.1007/s10439-023-03272-4
  13. Gustilo, L., Ong, E., & Lapinid, M. R. (2024). Algorithmically‑driven writing and academic integrity: Exploring educators’ practices, perceptions, and policies in AI era. International Journal for Educational Integrity, 20(1), 3. https://doi.org/10.1007/s40979-024-00153-8
  14. Haase, J., Djurica, D., & Mendling, J. (2023). The art of inspiring creativity: Exploring the unique impact of AI-generated images. In P. A. Pavlou, V. Midha, A. Animesh, T. A. Carte, A. R. Graeml, & A. Mitchell (Eds.), AMCIS 2023 Proceedings: 29th Americas Conference on Information Systems. 1–9. Association for Information Systems. https://aisel.aisnet.org/amcis2023/sig_aiaa/sig_aiaa/10
  15. Härtel, T., Randler, C., & Baur, A. (2023)˙. Using species knowledge to promote pro‑environmental attitudes? The association among species knowledge, environmental system knowledge and attitude towards the environment in secondary school students. Animals, 13(6), 972. https://doi.org/10.3390/ani13060972
  16. Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 43. https://doi.org/10.1186/s41239-023-00411-8
  17. Ingram, E., & Golick, D. (2018). The six‑legged subject: A survey of secondary science teachers’ incorporation of insects into US life science instruction. Insects, 9(1), 32. https://doi.org/10.3390/insects9010032
  18. Jančaříková, K., Brůnová, L., Hejnová, E., Hlaváčová, L., Jančařík, A., Králík, J., Krátká, M., Krejčí, J., Kroufek, R., Matějček, T., Medová, J., Pelikánová, M., Svobodová, S., Šmídl, M., Trahorsch, P., Vojíř, K. (2022). Didaktické zásady v přírodovědném vzdělávání: metodická příručka pro učitele biologie, chemie, fyziky, geografie, informatiky, matematiky a lektory environmentální výchovy. Pedagogická fakulta, Univerzita Karlova.
  19. Jelínek, J., & Zicháček, V. (2021). Biologie pro gymnázia. Olomouc.
  20. Khlewee, I. K. (2025). Image generation using generative AI: Comparison between OpenAI Art and Stable Diffusion. Babylonian Journal of Artificial Intelligence, 2025, 15–22. https://doi.org/10.58496/BJAI/2025/002
  21. Kooli, C. (2023). Chatbots in education and research: A critical examination of ethical implications and solutions. Sustainability, 15(7), 5614. https://doi.org/10.3390/su15075614
  22. Krutka, D. G., Manca, S., Galvin, S. M., Greenhow, C., Koehler, M. J., & Askari, E. (2019). Teaching “against” social media: Confronting problems of profit in the curriculum. Teachers College Record, 121(14), 1–42. https://doi.org/10.1177/016146811912101410
  23. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. https://doi.org/10.1038/nature14539
  24. Li, P., Yang, J., Islam, M. A., & Ren, S. (2023). Making AI less “thirsty”: Uncovering and addressing the secret water footprint of AI models. arXiv preprint arXiv:2304.03271. https://doi.org/10.48550/arXiv.2304.03271
  25. Lucky, A., Janštová, V., Novotný, P., & Mourek, J. (2025). Quantifying ento‑literacy: Development and validation of an international insect‑focused attitude and knowledge survey instrument. International Journal of STEM Education, 12, Article 11. https://doi.org/10.1186/s40594-025-00532-8
  26. Morrison, J., Na, C., Fernandez, J., Dettmers, T., Strubell, E., & Dodge, J. (2025). Holistically evaluating the environmental impact of creating language models. arXiv preprint arXiv:2503.05804. https://doi.org/10.48550/arXiv.2503.05804
  27. Noroozi, O., Soleimani, S., Farrokhnia, M., & Banihashem, S. K. (2024). Generative AI in education: Pedagogical, theoretical, and methodological perspectives. International Journal of Technology in Education, 7(3), 373–385. https://doi.org/10.46328/ijte.845
  28. Papáček, M., Matěnová, V., Matěna, J., & Soldán, T. (2000). Zoologie. Scientia.
  29. Playfoot, D., Quigley, M., & Thomas, A. G. (2024). Hey ChatGPT, give me a title for a paper about degree apathy and student use of AI for assignment writing. The Internet and Higher Education, 62, 100950. https://doi.org/10.1016/j.iheduc.2024.100950
  30. Pollock, P. H., Hamann, K., & Wilson, B. M. (2011). Learning through discussions: Comparing the benefits of small-group and large-class settings. Journal of Political Science Education, 7(1), 48–64. https://doi.org/10.1080/15512169.2011.539913
  31. Reed, J., Alterio, B., Coblenz, H., O’Lear, T., & Metz, T. (2023). AI image‑generation as a teaching strategy in nursing education. Journal of Interactive Learning Research, 34(2), 369–399. https://doi.org/10.70725/729255gdiorw
  32. Ruiz‑Rojas, L. I., Acosta‑Vargas, P., De‑Moreta‑Llovet, J., & Gonzalez‑Rodriguez, M. (2023). Empowering education with generative artificial intelligence tools: Approach with an instructional design matrix. Sustainability, 15(15), 11524. https://doi.org/10.3390/su151511524
  33. Salvi, M., Branciforti, F., Molinari, F., & Meiburger, K. M. (2024). Generative models for color normalization in digital pathology and dermatology: Advancing the learning paradigm. Expert Systems with Applications, 245, 123105. https://doi.org/10.1016/j.eswa.2023.123105
  34. Sardinha, T. B. (2024). AI‑generated vs human‑authored texts: A multidimensional comparison. Applied Corpus Linguistics, 4(1), 100083. https://doi.org/10.1016/j.acorp.2023.100083
  35. Selvam, A. A. A. (2024). Exploring the Impact of Artificial Intelligence on Transforming Physics, Chemistry, and Biology Education. Journal of Science with Impact. https://doi.org/10.21428/a70c814c.747297aa
  36. Shukla, R. P., & Taneja, S. (2024). Ethical considerations and data privacy in artificial intelligence. In Integrating Generative AI in Education to Achieve Sustainable Development Goals. 86–97.
  37. Sieg, A. K., Teibtner, R., & Dreesmann, D. (2018). Don’t know much about bumblebees?—A study about secondary school students’ knowledge and attitude shows educational demand. Insects, 9(2), 40. https://doi.org/10.3390/insects9020040
  38. Smrž, J., Horáček, I., & Švátora, M. (2004). Biologie živočichů pro gymnázia. Fortuna.
  39. Šíma, P. (2023). Biologie pro 2. ročník gymnázií. EDUKO.
  40. Tanner, K. D. (2009). Talking to learn: why biology students should be talking in classrooms and how to make it happen. CBE—Life Sciences Education, 8(2), 89–94. https://doi.org/10.1187/cbe.09-03-0021
  41. Tognetti, L., Miracapillo, C., Leonardelli, S., Luschi, A., Iadanza, E., Cevenini, G., Rubegni, P., & Cartocci, A. (2024). Deep learning techniques for the dermoscopic differential diagnosis of benign/malignant melanocytic skin lesions: From the past to the present. Bioengineering, 11(8), 758. https://doi.org/10.3390/bioengineering11080758
  42. van Wynsberghe, A. (2021). Sustainable AI: AI for sustainability and the sustainability of AI. AI and Ethics, 1(3), 213–218. https://doi.org/10.1007/s43681-021-00043-6
  43. Vartiainen, H., & Tedre, M. (2023). Using artificial intelligence in craft education: Crafting with text‑to‑image generative models. Digital Creativity, 34(1), 1–21. https://doi.org/10.1080/14626268.2023.2174557
  44. von Garrel, J., & Mayer, J. (2023). Artificial intelligence in studies—Use of ChatGPT and AI‑based tools among students in Germany. Humanities and Social Sciences Communications, 10, Article 799, 1–9. https://doi.org/10.1057/s41599-023-02304-7
  45. Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21(1), 15. https://doi.org/10.1186/s41239-024-00448-3
  46. Yu, H., & Guo, Y. (2023). Generative artificial intelligence empowers educational reform: Current status, issues, and prospects. Frontiers in Education, 8, 1183162. Frontiers Media SA. https://doi.org/10.3389/feduc.2023.1183162
  47. Bartz, R. (2007). A Formica rufa sideview [Fotografie]. Wikimedia Commons. https://cs.wikipedia.org/wiki/Soubor:A_Formica_rufa_sideview.jpg#/media/Soubor:A_Formica_rufa_sideview.jpg
  48. Descouens, D. (2014). Palomena prasina MHNT Léguevin Blanc [Fotografie]. Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Palomena_prasina_MHNT_L%C3%A9guevin_Blanc.jpg
  49. Graham, J. (2011). Dasysyrphus albostriatus, Trawscoed, North Wales, Sept 2011 2 [Fotografie]. Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Dasysyrphus_albostriatus,_Trawscoed,_North_Wales,_Sept_2011_2_(16894897664).jpg
  50. Leidus, I. (2016). Apis mellifera – Brassica napus – Valingu [Fotografie]. Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Apis_mellifera_-_Brassica_napus_-_Valingu.jpg
  51. MilanIlic553. (2022). Brachytron pratense IMG 5016.jpg [Fotografie]. Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Brachytron_pratense_IMG_5016.jpg
  52. Wild, A. L. (2016). Periplaneta americana – American cockroach [Fotografie]. Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Periplaneta_americana_-_American_cockroach_(25859665686)_(cropped).jpg

Licence

This work is licensed under a Creative Commons Attribution 4.0 International License.