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

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, η² =. 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.