Artificial Intelligence for Inclusivity: Exploring Strategies for Increasing Access to AI tutors for Underprivileged Students in Kano State Colleges of Education

Abstract

The study explores strategies for increasing access to artificial intelligence (AI) tutors among underprivileged students in Kano state colleges of education. Using descriptive survey and quasi-experimental design, the study sampled 317 students from three institutions. The reliability of the instrument was established at 0.78. Results from T-test indicated a statistically significant difference in performance, with students using AI tutors (Mean = 64.27, SD = 7.12) outperforming those in traditional settings (t(315) =0.41, MD = 0.31,), with Mean = 56.14, SD = 6.95. Findings indicate that AI tutors significantly improved the academic performance of underprivileged students in Kano State Colleges of Education compared to traditional teaching methods. Pre-test results confirmed that both groups were academically equivalent before the intervention. Post-test findings showed that AI tutors enhanced learning through personalized and adaptive instruction. Overall, AI tutors was identified as an effective strategy for promoting educational inclusivity and equity. Significant barriers such as high data cost and lack of indigenous language support remain. The study recommended that Colleges of Education in Kano State should integrate AI tutors as a complementary instructional tool to enhance inclusive learning, Government and institutional stakeholders should provide adequate ICT infrastructure and continuous training for lecturers to support effective implementation, Policies should also be developed to ensure equitable access to AI-based learning technologies for underprivileged students.