Faculty readiness and attitudes toward AI integration in university teaching: A Developing Country’s Perspective

Basak, Ashish and Yeasin, SK Muhammad and Shahnaj, Sanjana and Shurovi, Zakia Zohra (2025) Faculty readiness and attitudes toward AI integration in university teaching: A Developing Country’s Perspective. World Journal of Advanced Engineering Technology and Sciences, 16 (1). 041-048. ISSN 2582-8266

Background: Artificial Intelligence (AI) is increasingly transforming higher education globally, yet its integration remains limited in developing countries. Faculty readiness and attitudes play a critical role in successful AI adoption in university teaching. This study investigates these factors in the context of Bangladesh. Methods: A descriptive cross-sectional survey was conducted among 100 university faculty members across various disciplines in Bangladesh. A structured questionnaire measured faculty readiness and attitudes using Likert-scale and categorical items. Descriptive statistical methods were applied to analyze the data. Results: Findings reveal low levels of faculty readiness for AI integration. Mean scores indicate limited familiarity with AI concepts (M=2.51) and low institutional support (M=1.20). Few faculty had received AI training (M=1.71), resulting in low confidence using AI in teaching (M=2.78). Despite these gaps, attitudes were moderately positive: faculty agreed that AI could enhance teaching (M=3.62) and would become essential in the future (M=3.59). Major challenges include lack of time, training, and institutional backing. Workshops and incentives were identified as key support needs. Conclusion: While faculty in Bangladesh show interest in AI, low readiness and inadequate support hinder adoption. Strategic investments in training, infrastructure, and policy development are essential to advance AI integration in higher education.