Digital Education Equity Framework Using AI-Supported Learning Systems, Digital Inclusion Assessment, and Socioeconomic Learning Analytics for Inclusive Education and Sustainable Social Development
Authors
- Amna Nazir PhD Scholar, Department of Education and Research, Kohat University of Science and Technology, Kohat, Khyber Pakhtunkhwa, Pakistan.
- Muhammad Aslam Kamboh Assistant Professor, Department of Education, SZABIST University, Campus Larkana, Sindh, Pakistan.
- Adil Mehmood PhD Scholar, Department of Education and Research, Kohat University of Science and Technology, Kohat, Khyber Pakhtunkhwa, Pakistan.
-
Asad Ullah
Visiting Lecturer, Department of Educational Research & Assessment, University of Okara, Okara, Punjab, Pakistan.
https://orcid.org/0009-0001-1823-5743
- Ashraf Zia Lecturer, Department of Computer Science, Abdul Wali Khan University, Mardan, Khyber Pakhtunkhwa, Pakistan.
DOI:
https://doi.org/10.55737/trt/v-vi.348Keywords:
Digital Education Equity, AI-Supported Learning, Digital Inclusion, Socioeconomic Learning Analytics, Inclusive Education, SDG4Abstract
Digital education equity is one of the most pressing 21st century issues. While AI-powered learning systems can provide great potential to support inclusive education, they can also exacerbate socioeconomic achievement gaps if access, infrastructure, and pedagogical integration are not sufficiently supported. In this study, a Digital Education Equity Framework is developed and tested in practice that combines AI-based adaptive learning systems, a multidimensional digital inclusion assessment tool, and socioeconomic learning analytics, in order to promote inclusive education and sustainable social development in line with SDG 4. A mixed methods design was used with 1,247 learners from a variety of socio-economic backgrounds in urban, peri-urban and rural education, and interviews with 42 education administrators and technology coordinators. It was rolled out in 5 school districts, each having different levels of digital infrastructure. Quantitative results revealed that learners in the lowest socioeconomic quintile had a 34.2% increase in learning outcomes during the 14-week intervention while those in the conventional instruction group had a 12.7% increase. The scores of digital inclusions were significantly correlated with learning gains, where the best positive predictors were the scores of infrastructure adequacy and digital literacy training. The gaps were lowest for those students who were assigned targeted AI tutoring and had teacher professional development. Administrator interviews were analyzed thematically, revealing structural funding inequities, limited teacher digital competency, and fragmented policy coordination. Overall, it is found that the framework is an evidence-based approach to address digital learning disparities and that it can inform education policy, investment in ICT infrastructure, and teacher professional development.
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