Mukesh Kumar Yadav
Singh University, Farrukhabad (India)

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AI-Supported Learning and Its Relationship with Academic Procrastination and Academic Anxiety among Students with Visual Impairment Mukesh Kumar Yadav; Dhapu Kumari Sen; Raj Kumar
Jurnal Pendidikan Amartha Vol. 5 No. 2 (2026): November 2026
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/jpa.v5i2.9168

Abstract

Artificial Intelligence (AI) has emerged as a transformative technology in higher education, offering innovative solutions to improve accessibility, personalized learning, and academic support for students with disabilities. The present study investigated the influence of AI utilization on academic procrastination and academic anxiety among students with visual impairment. A longitudinal mixed-methods research design was employed involving 24 students with visual impairment from higher educational institutions in Kanpur, Uttar Pradesh, India. Participants were selected through purposive sampling and observed over one academic semester. Quantitative data were collected using standardized measures of AI utilization, academic procrastination, and academic anxiety at three different time points, while qualitative data were gathered through semi-structured interviews, reflective audio journals, and AI usage logs. Quantitative data were analysed using descriptive statistics, Pearson correlation, hierarchical linear modelling, and multiple regression analysis, whereas qualitative data were analysed using thematic analysis. The findings revealed that AI utilization increased progressively throughout the semester, while both academic procrastination and academic anxiety demonstrated a steady decline. Correlation analysis indicated strong negative relationships between AI utilization and academic procrastination (r = –0.92) and between AI utilization and academic anxiety (r = –0.88). Regression analysis further confirmed that AI utilization significantly predicted reductions in both academic procrastination and academic anxiety. Qualitative findings supported the quantitative results by identifying accessibility, improved time management, better assignment planning, increased learning confidence, and reduced academic anxiety as the major perceived benefits of AI-assisted learning. Although a few participants expressed concerns regarding excessive dependence on AI, the overall educational benefits substantially outweighed these concerns. The study concludes that AI-assisted learning has considerable potential to promote accessible, independent, and inclusive education for students with visual impairment. By enhancing academic organization, reducing psychological barriers, and improving learner confidence, AI contributes to both academic success and emotional well-being. The findings highlight the importance of integrating AI-based educational technologies into inclusive higher education while promoting responsible and ethical AI use through appropriate institutional support and digital literacy initiatives.