AI-Driven Learning Tools and Gender Equity: Rethinking Inclusive Digital Pedagogies in Higher Education

Authors

  • Adelfa Cabigas Silor
  • Faith Stephanny Cabigas Silor

Keywords:

Artificial Intelligence in Education; Digital Engagement; Gender Equity; Higher Education; Inclusive Pedagogy

Abstract

The effect of AI empowerment was further explored regarding academic performance, digital interaction, and gender equity in the tertiary education sector. Through an explanatory sequential mixed-method research design, 210?undergraduate students and six faculty members of a Philippine state university were engaged in the study. Quantitative data came from pre- /post-test results, a digital engagement survey, and an emerging Gender-Inclusive Pedagogy Perception Scale (GIPPS) scale; qualitative data include the focus group interviews with students, follow-up interviews with faculty, and classroom?observations. The results indicated that the learning gain of students who were instructed with AI-integrated knowledge was statistically higher (M = 5.40) than that of students in traditional instruction lessons (M = 2.10), d = 1.06, which had a large effect size. AI?users also indicated significantly more digital engagement, t (208) = 5.02, p < 001, d =.70, as well as more positive views of gender-inclusive pedagogy, t(208) = 3.41, p =?001, d = 0.47. A one-way ANOVA was significant?for gender identity on GIPPS scores, F(2, 207) = 4.15, p = 017, ?² =. 04, and the?highest perceived inclusivity came from LGBTQ+ students. Qualitative findings indicated that AI was perceived as a non-judgmental feedback partner, that consistent AI responses may diminish gendered expectations, and that AI-mediated lifelong feedback can bolster learning confidence with faculty mediation. Findings were used to design an Inclusive AI Pedagogy Framework grounded in Social Cognitive Theory, Gender Schema Theory, and Feminist Pedagogy. Results add to evidence that AI-infused?tools can hold promise for learning success and fostering gender-responsive and inclusive DLEs when used with critical teacher mediation and equity-sensitive design.

https://doi.org/10.26803/ijlter.25.2.6

References

Adiyono, & Fernando, D. E. (2025). The influence of the use of artificial intelligence by students in answering online exam questions on academic integrity and teachers’ perceptions. International Journal of Learning, Teaching and Educational Research, 24(1), 149–164. https://doi.org/10.26803/ijlter.24.1.8

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922

Bem, S. L. (1981). Gender schema theory: A cognitive account of sex typing. Psychological Review, 88(4), 354–364. https://doi.org/10.1037/0033-295X.88.4.354

Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Emergency remote teaching in higher education: A systematic review. Computers and Education, 170, 104225. https://doi.org/10.1016/j.compedu.2021.104225

Canuto, L. M., & Espique, R. E. (2023). Gender-responsive approaches in science teaching and learning: Enhancing girls’ engagement in STEM. International Journal of Learning, Teaching and Educational Research, 22(13), 127–143. https://doi.org/10.26803/ijlter.22.13.7

Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002

Cheryan, S., Master, A., & Meltzoff, A. N. (2019). Cultural stereotypes as gatekeepers. Educational Psychologist, 54(3), 185–204. https://doi.org/10.1080/00461520.2019.1632366

Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22. https://doi.org/10.1186/s41239-023-00392-8

Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., Johnson, E. E., & Baah, P. K. (2022). The impact of a virtual teaching assistant (chatbot) on students’ learning in Ghanaian higher education. International Journal of Educational Technology in Higher Education, 19(1), 57. https://doi.org/10.1186/s41239-022-00362-6

Ferrara, E. (2024). Fairness and bias in artificial intelligence: A brief survey of sources, impacts, and mitigation strategies. Sci, 6(1), 3. https://doi.org/10.3390/sci6010003

Floridi, L., & Cowls, J. (2020). A unified framework for AI ethics and governance. Minds and Machines, 30(1), 77–97. https://doi.org/10.1007/s11023-020-09501-5

Gaber, H. R., El-Nakla, S., Elsayad, A., & Elshamy, E. (2023). University instructors’ awareness of AI applications and their impact on technology acceptance in higher education. International Journal of Learning, Teaching and Educational Research, 22(8), 1–20. https://doi.org/10.26803/ijlter.22.8.1

Granström, M., & Oppi, P. (2025). Student engagement with AI tools in learning: Evidence from a large-scale Estonian survey. Frontiers in Education, 10, 1688092. https://doi.org/10.3389/feduc.2025.1688092

Hall, P., & Ellis, D. (2023). A systematic review of socio-technical gender bias in AI algorithms. Online Information Review, 47(7), 1–22. https://doi.org/10.1108/oir-08-2021-0452

Holmes, W., Porayska-Pomsta, K., & Holstein, K. (2022). Ethics in AIED. International Journal of Artificial Intelligence in Education, 32(4), 935–957. https://doi.org/10.1007/s40593-022-00288-0

Jin, S. H., Im, K., Yoo, M., Roll, I., & Seo, K. (2023). Supporting students’ self-regulated learning in online learning using artificial intelligence applications. International Journal of Educational Technology in Higher Education, 20(1), Article 63. https://doi.org/10.1186/s41239-023-00406-5

Kalim, U., Kanwar, A., Sha, J., & Huang, R. (2025). Barriers to AI adoption for women in higher education: A systematic review of the Asian context. Smart Learning Environments, 12, Article 3. https://doi.org/10.1186/s40561-025-00390-5

Kolil, V. K., Muthupalani, S., & Achuthan, K. (2020). Virtual experimental platforms in chemistry laboratory education and their impact on experimental self-efficacy. International Journal of Educational Technology in Higher Education, 17(1), 30. https://doi.org/10.1186/s41239-020-00204-3

Kumar, A., & Choudhury, S. (2022). Feminist perspectives on artificial intelligence in education. Journal of Gender and Education Studies, 14(2), 45–59.

Lee, Y. F., Hwang, G. J., & Chen, P. Y. (2022). Impacts of an AI-based chatbot on college students’ after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational Technology Research and Development, 70(5), 1843–1865. https://doi.org/10.1007/s11423-022-10142-8

Luo, J., Zheng, C., Yin, J., & Teo, H. H. (2025). Design and assessment of AI-based learning tools in higher education: A systematic review. International Journal of Educational Technology in Higher Education, 22(1), 1–27. https://doi.org/10.1186/s41239-025-00540-2

Ma, D., Akram, H., & Chen, I. H. (2024). Artificial intelligence in higher education: A cross-cultural examination of students’ behavioral intentions and attitudes. The International Review of Research in Open and Distributed Learning, 25(3), 134–155. https://doi.org/10.19173/irrodl.v25i3.7703

Manasi, A., Panchanadeswaran, S., Sours, E., & Lee, S. J. (2022). Mirroring the bias: Gender and artificial intelligence. Gender, Technology and Development, 26(3), 1–20. https://doi.org/10.1080/09718524.2022.2128254

Melo-López, L., Torres, J., & Ríos, P. (2024). Artificial intelligence for inclusive learning: A systematic review. Computers & Education, 205, 104885.

Møgelvang, A., Bjelland, C., Grassini, S., & Ludvigsen, K. (2024). Gender differences in the use of generative artificial intelligence chatbots in higher education: Characteristics and consequences. Education Sciences, 14(12), 1363. https://doi.org/10.3390/educsci14121363

Mok, K. H., Xiao, H., & Ye, H. (2023). AI and inclusive education: Opportunities and challenges. Education and Information Technologies, 28, 567–586. https://doi.org/10.1007/s10639-022-11464-6

Radzi, N. M., & Mahmud, M. S. (2025). Inclusive mathematics pedagogy through technology: A PRISMA systematic review. International Journal of Learning, Teaching and Educational Research, 24(2), 88–105. https://doi.org/10.26803/ijlter.24.2.5

Rahiman, H. U., & Kodikal, R. (2023). Revolutionizing education: Artificial intelligence empowered learning in higher education. Cogent Education, 11(1), 2293431. https://doi.org/10.1080/2331186X.2023.2293431

Salas-Pilco, J., Yang, Y., & Zhang, Z. (2022). Artificial intelligence in inclusive education: Opportunities and challenges. British Journal of Educational Technology, 53(6), 1539–1556.

Salas-Pilco, S. Z., Xiao, K., & Oshima, J. (2022). Artificial intelligence and new technologies in inclusive education for minority students: A systematic review. Sustainability, 14(20), 13572. https://doi.org/10.3390/su142013572

Samarakoon, T. (2025). Critical AI mediation in feminist classrooms: Reimagining power, agency, and voice. Feminist Pedagogy Review, 10(1), 55–72.

Schunk, D. H., & DiBenedetto, M. K. (2020). Motivation and social cognitive theory. Contemporary Educational Psychology, 60, 101832. https://doi.org/10.1016/j.cedpsych.2019.101832

Shrestha, S., & Das, S. (2022). Exploring gender biases in ML and AI academic research through a systematic literature review. Frontiers in Artificial Intelligence, 5, 976838. https://doi.org/10.3389/frai.2022.976838

Stöhr, C., Ou, A. W., & Malmström, H. (2024). Perceptions and usage of AI chatbots among students in higher education across genders, academic levels, and fields of study. Computers and Education: Artificial Intelligence, 5, 100259. https://doi.org/10.1016/j.caeai.2024.100259

Tatman, R. (2020). Gender and dialect bias in YouTube’s automatic captions. Proceedings of the Linguistic Society of America, 5(1), 53–65. https://doi.org/10.3765/plsa.v5i1.4734

UNESCO. (2023). AI and gender equality: Guidance for policymakers. UNESCO Publishing.

Wang, F., & Young, G. (2022). Bias, fairness, and equity in AI-based educational systems. Computers and Education: Artificial Intelligence, 3, 100068. https://doi.org/10.1016/j.caeai.2022.100068

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence in higher education. International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0

Downloads

Published

2026-02-28

How to Cite

Silor, A. C. ., & Silor, F. S. C. (2026). AI-Driven Learning Tools and Gender Equity: Rethinking Inclusive Digital Pedagogies in Higher Education. International Journal of Learning, Teaching and Educational Research, 25(2), 111–129. Retrieved from https://ijlter.myres.net/index.php/ijlter/article/view/2700