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Access, Engagement, and Equity Challenges in AI-Driven Educational Tools: A Socio-Technical Analysis of Higher Education Students in Quetta, Balochistan | Journal of Education And Humanities Research (JEHR), University of Balochistan, Quetta JEHR Journal of Education And Humanities Research, University of Balochistan

Access, Engagement, and Equity Challenges in AI-Driven Educational Tools: A Socio-Technical Analysis of Higher Education Students in Quetta, Balochistan

Authors

  • Shumaila Dad University of Balochistan, Quetta
  • Bahram Nazeer University of Balochistan, Quetta
  • Nadia Ali University of Balochistan, Quetta

Keywords:

Access, Digital Divide, Student Engagement, Equity, Artificial Intelligence in Education, Multilingual Learning, Balochistan

Abstract

Artificial intelligence (AI) is frequently proposed as a solution to the geographic and infrastructural barriers that constrain higher education in Balochistan, Pakistan's largest and least densely served province. Yet the promise of AI-driven educational tools is conditioned on students' actual access to reliable connectivity, devices, and linguistically appropriate systems, and on whether access translates into sustained engagement rather than superficial novelty. This study examines student engagement with AI-driven educational tools in Quetta, Balochistan, and interprets the results against the socio-technical literature on access, the digital divide, and equity in AI-enabled education. A quantitative, cross-sectional survey was administered to students at the University of Balochistan and BUITEMS. Using Cochran's (1977) formula for finite populations, a minimum sample of 196 was required from a population of 400; 220 questionnaires were distributed via simple random sampling, yielding 199 valid responses. A five-point Likert-scale Engagement subscale (Items 21–30), reverse-coded for a negatively phrased item, achieved a Cronbach's alpha of 0.759. Descriptive results indicated a positive mean engagement level (M = 3.77, SD = 0.63), confirmed by a one-sample t-test against the neutral midpoint, t(197) = 17.03, p < .001. A one-way ANOVA found no statistically significant gender difference in engagement, F(1, 196) = 0.20, p = .66. Despite this generally positive picture, engagement scores contained noticeable pockets of neutrality, which, read against the literature on linguistic barriers, connectivity gaps, and gendered access constraints in Balochistan, suggest that sustained engagement is not guaranteed by access alone. The study concludes that engagement with AI-driven educational tools in Balochistan is shaped as much by infrastructural and linguistic equity as by individual motivation, and that localized, offline-capable, and multilingual AI systems are necessary to convert access into durable engagement.

References

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Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications. Center for Curriculum Redesign.

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Sajja, R., Sermet, Y., Cikmaz, M., Cwiertny, D., & Demir, I. (2023). Artificial intelligence-enabled intelligent assistant for personalized and adaptive learning in higher education. arXiv. https://doi.org/10.48550/arXiv.2309.10892

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Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), Article 39. https://doi.org/10.1186/s41239-019-0171-0

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Published

2026-07-01

How to Cite

Dad, S. ., Nazeer, B. ., & Ali, N. . (2026). Access, Engagement, and Equity Challenges in AI-Driven Educational Tools: A Socio-Technical Analysis of Higher Education Students in Quetta, Balochistan. Journal of Education And Humanities Research (JEHR), University of Balochistan, Quetta, 21(1), 42–50. Retrieved from http://journal.uob.edu.pk/journal/index.php/jehr/article/view/583