article

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)

Petra Hrušková, Adam Hruška, Jan Mourek

information

volume: 34
year: 2025
issue: 4
fulltext: PDF

online publishing date: 23/4/2026
DOI: 10.14712/25337556.2025.4.1
ISSN (Online): 2533-7556

Licence Creative Commons
Toto dílo podléhá licenci Creative Commons Uveďte původ 4.0 Mezinárodní License.

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

fulltext (PDF )

PDF

References

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

Aktay, S. (2022). The usability of images generated by artificial intelligence (AI) in education. International Technology and Education Journal, 6(2), 51–62.

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

Altmann, A. (1971). Didaktické zásady ve výuce biologii: (Kapitola didaktiky biologie). Určeno pro posl. pedagog. fakult. SPN.

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

Jelínek, J., & Zicháček, V. (2021). Biologie pro gymnázia. Olomouc.

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

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

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

LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. https://doi.org/10.1038/nature14539

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

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

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

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

Papáček, M., Matěnová, V., Matěna, J., & Soldán, T. (2000). Zoologie. Scientia.

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

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

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

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

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

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

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

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.

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

Smrž, J., Horáček, I., & Švátora, M. (2004). Biologie živočichů pro gymnázia. Fortuna.

Šíma, P. (2023). Biologie pro 2. ročník gymnázií. EDUKO.

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

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

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

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

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

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

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

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

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

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

Leidus, I. (2016). Apis mellifera - Brassica napus - Valingu [Fotografie]. Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Apis_mellifera_-_Brassica_napus_-_Valingu.jpg

MilanIlic553. (2022). Brachytron pratense IMG 5016.jpg [Fotografie]. Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Brachytron_pratense_IMG_5016.jpg

Wild, A. L. (2016). Periplaneta americana – American cockroach [Fotografie]. Wikimedia Commons. https://commons.wikimedia.org/wiki/File:Periplaneta_americana_-_American_cockroach_(25859665686)_(cropped).jpg


We use cookies to analyse our traffic. More information