Qualitative Study on Digital Classrooms, Equal Futures: Artificial Intelligence-Powered Digital Pedagogy for Closing the Gender Digital Divide in STEM
DOI:
https://doi.org/10.64348/zije.2026552Abstract
The increase in Artificial Intelligence (AI), online learning platforms and virtual instructional technologies is definitely defining the possibilities for Science, Technology, Engineering and Mathematics (STEM) education. However, benefits of digital change are not equally shared. Girls and women still face difficulties regarding access to devices and connectivity, affordability, digital skills, confidence, gender stereotypes, safety and limited representation in STEM learning and careers. These differences are critical in Nigeria, where increase in digital education and AI creates opportunity to strengthen STEM participation but somewhat risks reproducing ongoing gender differences if technology is introduced without an explicit inclusion agenda. This paper investigates how AI-enhanced online and virtual STEM instruction can help to closing the gender digital divide, with attention to tertiary education and teacher education in Nigerian universities and colleges of education. The paper conceptualises AI-powered digital pedagogy as more than the use of generative AI tools; it incorporates adaptive learning, intelligent tutoring, learning analytics, virtual laboratories, automated feedback, AI-assisted content creation, collaborative platforms and AI literacy. The paper adds that these technologies cane enhance accessibility, personalisation, feedback, participation and exposure to female STEM role models when they are fixed within gender-responsive pedagogy. However, AI can also reproduce gender bias, widen disparities through unequal shared access, compromise privacy and create new forms of exclusion. A gender-responsive AI digital pedagogy framework is further proposed, organised around six principles: equitable shared access, inclusive design, personalised learning, agency and voice, human-centred teacher support, and ethical accountability. The paper ends with recommendations for Nigerian tertiary institutions, teacher-education programmes, lecturers, policymakers and technology providers. It suffices that the objective should not merely place girls in digital classrooms, but to redesign digital classrooms so that girls can participate, belong, succeed and eventually lead in STEM.
References
Almasri, F. (2024). Exploring the impact of artificial intelligence in teaching and learning of science: A systematic review of empirical research. Research in Science Education, 54, 977–997. https://doi.org/10.1007/s11165-024-10176-3.
Ayua, G. A. (2018b, July). Science education and values for societal renewal in Nigeria. Paper presented at Primary and Tertiary Teacher Education Association of Nigeria (PATTEN) 15th Annual National Conference on Education and National Values: Trends and Imperatives, held at Usmanu Danfodiyo University, Sokoto State, Nigeria.
Ayua, G. A. & Akaabo, M. J. (2016). Perceived impact of social networks on commitment to studies and academic performance of undergraduates. Africa Journal of Sustainable Professional Development, 2(2), 180 - 188. https://www.researchgate.net/publication/336892126
Ayua, G. A., & Kwagh, T. C. (2026). Fostering honesty and integrity in the age of gen-AI: Rethinking ethical scientific attitudes in science education research. Journal of Studies in Science and Mathematics Education, 6(1), 362-369. https://jossme.org.ng/articles?page=4
Ayua, G. A., Ijauka, P., Okanche, S., Obonga, I. J., Obu, R. O., & Iorpenda, N. P. (2026a). Gender differences in AI chatbots utilization and research knowledge acquisition among final-year science education undergraduates. Benue State University Journal of Science, Mathematics and Computer Education, 6(1), 40-52. https://bsum.edu.ng/journals/jsmce/v6n1/download.php?id=375
Ayua, G. A., Kwagh, T. C., Okanche, S., Obonga, I. J., Obu, R. O., & Tavershima, U. A. (2026b). Perceived influence of artificial intelligence chatbots on self-efficacy and attitude in science education research among undergraduate students in Makurdi, Benue State, Nigeria. Zamfara International Journal of Education, 6(4), 260-266. https://doi.org/10.64348/zije.2026485
Ayua, G. A., Taangahar, B. A., Ikyernum, G. S., Iorkase, R. N., & Kwaghtongu, R. T. (2026c). Exploring gender as a correlate of undergraduates’ interest in science and technology education. British Journal of Contemporary Research, 1(1), Article 006. https://bexfordpublishing.co.uk/journals/bjcr/articles/BEX_MAY_26_009
Basilotta-Gómez-Pablos, V., Matarranz, M., Casado-Aranda, L.-A., & Otto, A. (2022). Teachers' digital competencies in higher education: A systematic literature review. International Journal of Educational Technology in Higher Education, 19, 8. https://doi.org/10.1186/s41239-021-00312-8.
Caena, F. (2019). Aligning teacher competence frameworks to 21st century challenges: The case for the European Digital Competence Framework for Educators (DigCompEdu). European Journal of Education, 54(3), 356–369. https://doi.org/10.1111/ejed.12345.
Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., & Barro, S. (2023). AI literacy in K-12: A systematic literature review. International Journal of STEM Education, 10, 29. https://doi.org/10.1186/s40594-023-00418-7.
Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2024). Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies. Computers & Education, 222, 105224. https://doi.org/10.1016/j.compedu.2024.105224.
Dawson, J., et al. (2020). STEM initiatives matter: Results from a systematic review of secondary school interventions for girls. International Journal of Science Education, 42(7). https://doi.org/10.1080/09500693.2020.1749909.
Ezurike, N., & Akinsulire, T. (2024). Investigating the awareness and adoption of ChatGPT as a learning tool among undergraduates in Lagos State Nigeria. International Journal of Education, Learning and Development, 12(9), 134–154. https://doi.org/10.37745/ijeld.2013/vol12n9134154.
Federal Ministry of Education. (2023). National Digital Learning Policy. Federal Republic of Nigeria.
Federal Republic of Nigeria. (2024). National Artificial Intelligence Strategy 2024. National Centre for Artificial Intelligence and Robotics/NITDA.
García, A., et al. (2020). Girls in STEM: Is it a female role-model thing? Frontiers in Psychology, 11.
García-Holgado, A., et al. (2022). The gender gap in higher STEM studies: A systematic literature review. Heliyon, 8, e10300. https://doi.org/10.1016/j.heliyon.2022.e10300.
Gladstone, J. R., & Cimpian, A. (2021). Which role models are effective for which students? A systematic review and four recommendations for maximizing the effectiveness of role models in STEM. International Journal of STEM Education, 8, 59. https://doi.org/10.1186/s40594-021-00315-x.
Groupe Spécial Mobile Association (GSMA). (2024). The Mobile Gender Gap Report 2024. GSMA.
International Telecommunication Union. (2023). Facts and Figures 2023: The gender digital divide. ITU.
Iroaganachi, M., Opeke, R., Babalola, Y., & Soyemi, O. (2021). Digital literacy skills and STEM career path choice intentions among junior secondary school girls in North-Central Nigeria. Covenant Journal of Informatics and Communication Technology, 8(2), 25-40.
Jomen, E. O., & Ayua, G. A., (2026). Effect of AI-personalised learning strategy on critical thinking of Integrated Science undergraduates in Makurdi: The role of gender. Benue State University Journal of Science, Mathematics and Computer Education, 6(1),114-124. https://bsum.edu.ng/journals/jsmce/v6n1/download.php?id=381
Kube, D., Weidlich, J., Jivet, I., Kreijns, K., & Drachsler, H. (2022). Gendered differences versus doing gender: A systematic review on the role of gender in computer-supported collaborative learning. Unterrichtswissenschaft, 50, 661–688. https://doi.org/10.1007/s42010-022-00153-y.
Lucas, M., Bem-Haja, P., Siddiq, F., Moreira, A., & Redecker, C. (2021). The relation between in-service teachers' digital competence and personal and contextual factors: What matters most? Computers & Education, 160, 104052. https://doi.org/10.1016/j.compedu.2020.104052.
Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: Guidance for policy-makers. UNESCO. https://doi.org/10.54675/PCSP7350.
Musso, P. M., Ligorio, M. B., Ibe, E., Annese, S., Semeraro, C., & Cassibba, R. (2022). STEM-gender stereotypes: Associations with school empowerment and school engagement among Italian and Nigerian adolescents. Frontiers in Psychology, 13, 879178. https://doi.org/10.3389/fpsyg.2022.879178.
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2022). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041.
Organisation for Economic Co-operation and Development (OECD, 2021). OECD Digital Education Outlook 2021: Pushing the frontiers with AI, blockchain and robots. OECD Publishing. https://doi.org/10.1787/589b283f-en.
Reisoğlu, İ., & Çebi, A. (2020). How can the digital competences of pre-service teachers be developed? Examining a case study through the lens of Dig Comp and Dig Comp Edu. Computers & Education, 156, 103940. https://doi.org/10.1016/j.compedu.2020.103940.
United Nations Entity for Gender Equality and Empowerment of Women (UN Women, 2024). Artificial intelligence and gender equality. UN Women Knowledge Portal.
United Nations Educational, Scientific and Cultural Organisation (UNESCO, 2024). 2024 Gender Report: Technology on her terms. Global Education Monitoring Report.
United Nations Educational, Scientific and Cultural Organisation (UNESCO, 2025). Closing the digital divide for women and girls in Africa through education. UNESCO.
United Nations International Children’s Emergency Fund (UNICEF, 2024). Reaching and empowering adolescent girls in North West Nigeria. UNICEF Nigeria.
World Bank. (2025). Digital skills in Nigeria: Device ownership, accessibility, and utilization as enablers for digital skills. World Bank.
