G, Assessing the Level of Using Machine Learning Approaches in Higher Educational Institutions of Bangladesh: A Study of Three Science and Technology Universities
Keywords:
Machine learning, Higher education, Bangladesh, Challenges.Abstract
This study aimed to assess the current state of machine learning (ML) adoption in Bangladesh’s higher education system. A survey involving 156 student respondents from three science and technology universities revealed that 55% of students found ML techniques unsatisfactory, with major challenges including a lack of skilled manpower, budget constraints, high artificial intelligence (AI) costs, and insufficient government support. However, 68.4% of students believed that ML presents an opportunity, while 26.5% did not. To address these challenges, the study proposed three recommendations: organizing seminars, securing funding, and procuring technology. By investing in skilled manpower, resources, and technology, Bangladesh can become better prepared for ML-driven digital learning and unlock the potential of AI and ML in higher education. Future research should focus on evaluating the effectiveness of the proposed solutions and exploring additional strategies to ensure the successful integration of ML techniques into higher education, ultimately improving teaching and learning outcomes.
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