Abstract
Despite achieving gender parity in higher education enrolment (60% female), Malaysia faces an emerging digital divide in how students use artificial intelligence. This study examined whether gender predicts task-specific ChatGPT usage patterns among Malaysian students (n = 443), employing latent profile analysis and multinomial logistic regression on CC BY 4.0 licensed Global ChatGPT Student Survey data (October 2024–February 2025). Four distinct usage profiles emerged: Selective Users (14.9%), Moderate Adopters (31.8%, coding-focused), Academic Enthusiasts (33.0%, text-focused), and Comprehensive Users (20.3%). Gender significantly predicted specialized profile membership (χ² = 19.47, p < .001). Males concentrated in coding-focused use (OR = 0.48 for females, p = .007), females in text-focused use (OR = 1.89, p = .020), while Comprehensive Users exhibited gender parity. Exploratory analyses indicate a tentative pattern of larger gender gaps in technical AI use in STEM fields (33.4 percentage points in Applied Sciences) versus Social Sciences (12.7 points), though small cell sizes (n=3 for female Natural Sciences students) prevent definitive conclusions. Profiles predicted domain-specific skill development with large effects (η² = .18-.33). Findings reveal that equal access masks unequal functional engagement, with implications for gender-segregated occupational pathways that warrant further investigation with larger samples.
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APA 7th edition
In-text citation: (Raza et al., 2026)
Reference: Raza, F. A., Singh, A. D., Anwar, R., Kovilpillai, J. J. S., Hamdan, A. B., Konno, F., Rajaratnam, V., Raman, M., & Razami, H. H. (2026). Gender and functional differentiation in generative AI usage among Malaysian higher education student.
European Journal of STEM Education, 11(1), Article 17.
https://doi.org/10.20897/ejsteme/18267
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Raza FA, Singh AD, Anwar R, et al. Gender and functional differentiation in generative AI usage among Malaysian higher education student.
European Journal of STEM Education. 2026;11(1), 17.
https://doi.org/10.20897/ejsteme/18267
Chicago
In-text citation: (Raza et al., 2026)
Reference: Raza, Fahd Ali, Abtar Darshan Singh, Rabia Anwar, Jonathan Jeevan Strivinas Kovilpillai, Analisa Binti Hamdan, Fumiko Konno, Vaikunthan Rajaratnam, Murali Raman, and Husna Hafiza Razami. "Gender and functional differentiation in generative AI usage among Malaysian higher education student".
European Journal of STEM Education 2026 11 no. 1 (2026): 17.
https://doi.org/10.20897/ejsteme/18267
Harvard
In-text citation: (Raza et al., 2026)
Reference: Raza, F. A., Singh, A. D., Anwar, R., Kovilpillai, J. J. S., Hamdan, A. B., Konno, F., . . . Razami, H. H. (2026). Gender and functional differentiation in generative AI usage among Malaysian higher education student.
European Journal of STEM Education, 11(1), 17.
https://doi.org/10.20897/ejsteme/18267
MLA
In-text citation: (Raza et al., 2026)
Reference: Raza, Fahd Ali et al. "Gender and functional differentiation in generative AI usage among Malaysian higher education student".
European Journal of STEM Education, vol. 11, no. 1, 2026, 17.
https://doi.org/10.20897/ejsteme/18267
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Raza FA, Singh AD, Anwar R, Kovilpillai JJS, Hamdan AB, Konno F, et al. Gender and functional differentiation in generative AI usage among Malaysian higher education student. European Journal of STEM Education. 2026;11(1):17.
https://doi.org/10.20897/ejsteme/18267