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Students’ Acceptance and Adoption of Generative AI Tools: Evidence from a Bangladeshi Engineering University
(Department of Technical and Vocational Education (TVE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh, 2025-10-25) Asag, Mazen Abdulwahab Mahyoub Salem
Generative AI is quickly spreading across higher education, but adoption remains inconsistent in low-resource settings where institutional support and infrastructure lag behind student demand. This study explores how social cues and cognitive evaluations affect engineering students’ adoption of generative AI at an international university in Bangladesh. Using an integrated UTAUT–TAM2 framework, weanalyzethecombinedeffectsofsubjective norms andstudent imagewithjobrelevance, output quality, result demonstrability, perceived usefulness, and perceived ease of use on the intention to use. A cross-sectional survey of 378 undergraduate and graduate engineering students employed 31 validated Likert-scale items; data were analyzed in SmartPLS using PLS-SEM with 5,000-sample bootstrapping after establishing reliability and validity. Group comparisons tested for gender and domestic–international differences. The model explained 64% of the variance in usage behavior. Sixteen of twenty hypotheses were supported: subjective norms significantly influenced perceived usefulness and perceived ease of use, and had a small direct effect on intention; student image affected perceived usefulness only; job relevance strongly predicted perceived usefulness, perceived ease of use, and intention; output quality impacted perceived usefulness and perceived ease of use (but not intention); result demonstrability increased intention and perceived ease of use (but not perceived usefulness). Aligned with TAM, perceived usefulness and perceived ease of use influenced intention, which was the strongest predictor of Usage Behavior. Gender effects were minimal, while domestic students reported higher perceived usefulness, perceived ease of use, job relevance, demonstrability, intention, and use than international peers. Findings underscore the importance of integrating AI into authentic coursework, fostering faculty and peer support, and offering inclusive training to close participation gaps. Limitations include the cross-sectional, single-site design.
An Investigation of Students’ Perception of Generative AI as a Learning Tool in Computer Science and Engineering
(Department of Technical and Vocational Education (TVE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh, 2025-10-25) Njie, Ida
The study investigates students’ perception of generative AI as a learning tool in computer Science Engineering (CSE) with specific attention to two universities in two different regions: the University of The Gambia and the Islamic University of Technology in Bangladesh. The Technology Acceptance Model (TAM) positioned the research because there are four key inputs: perceived usefulness, perceived ease of use, and intention to use shape students’ learning outcomes. The responses were analysed using descriptive statistics, validity and reliability testing, and structural equation modelling (SEM) after the data were collected through a structured survey. The results show that most students hold a positive view of generative AI, often describing it as helpful for their studies and relatively easy to use. At the same time, many raised concerns about ethical issues and the risk of depending too heavily on AI tools. The research, therefore, points to the need for clear training and guidance on how to apply these technologies responsibly in education. Finally, the study draws attention to the lack of research in South Asia and West Africa, suggesting that further work in these regions could deepen our understanding of how students experience AI in their academic journeys.
A Study on the Challenges and Opportunities of Using Project-Based Learning in Renewable Energy Technology at TVET Institutions in Bangladesh and the Gambia
(Department of Technical and Vocational Education (TVE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh, 2025-10-25) Jallow, Amadou AK
This study investigates the opportunities and challenges of implementing Project-Based Learning in teaching and learning Renewable Energy Technology at Technical and Vocational Education and Training institutions in Bangladesh and The Gambia. The study was guided by a qualitative research design and employed thematic analysis; data collected from educators through semi structured interviews. The findings reveal that PjBL is widely perceived in both contexts as a student-centered, practice-oriented approach that effectively bridges theoretical concepts with real-world application, which promotes critical thinking, problem-solving skills, technical competence, and workforce readiness. Opportunities are identified, including enhanced student engagement, innovation, and alignment with industry needs. However, implementation is also hindered by substantial challenges, including inadequate laboratory facilities, limited funding, a lack of modern equipment, and time constraints in balancing theory and practice. Additional barriers include varying levels of student readiness and both countries' insufficient teacher training and weaker policy support to fully leverage PjBL’s potential in advancing RET education. These findings contribute to the growing body of literature on PjBL in resource-constrained settings and offer actionable insights for policymakers, educators, and industry stakeholders seeking to improve renewable energy skills in TVET systems.
Engineering Students’ Perceptions of using Artificial Intelligence Tools in Higher Education: A Phenomenographic Study
(Department of Technical and Vocational Education (TVE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh, 2025-10-30) Jaiteh, Jainaba
Artificial Intelligence (AI) has become an integral part of teaching and learning practices in higher education. This research investigates how engineering students perceive the use of AI within their academic environment. Guided by a phenomenographic approach, the study employed semi structured interviews to explore variations in students’ conceptions. Participants were drawn from different engineering departments Electrical and Electronic Engineering (EEE), Mechanical and Production Engineering (MPE), Computer Science and Engineering (CSE), and Civil and Environmental Engineering (CEE) at the Islamic University of Technology. Analysis of the interview data revealed five distinct ways students understand and experience AI in their studies. They viewed AI as a) an essential academic aid, b) a facilitator of personalized learning, c) as an administrative and teaching tool, d) an inhibitor to critical thinking, and e) an ethical challenger. These insights carry theoretical, pedagogical, and institutional implications for developing responsible and inclusive AI integration policies in higher education.
Investigating the Factors Influencing International Students’ Satisfaction in Foundation Course and their success in academic Courses: A case of IUT
(Department of Technical and Vocational Education (TVE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh, 2025-10-30) Nasser , Najm Mogalli Nasser
Foundation programs are considered as essential preparatory stage in higher education, especially for international students who come from a different country and required to adapt to new academic, linguistic, and cultural environments. Before enrolling to the main academic stream, preparatory programs, such as Foundation Program plays a vital role to be succeed in their academic programs. This study investigated the factors influencing international students’ satisfaction with the Foundation Program at the Islamic University of Technology (IUT) in Bangladesh and also explored the relationship between foundation performance and subsequent academic achievement. The research was guided by two hypotheses: that course content, instructional quality, and academic support significantly predict student satisfaction, and that foundation course results positively corelate to performance in later academic programs. A quantitative research design was employed, drawing on survey responses from 104 international students who had completed the Foundation Program and progressed into undergraduate studies. Data were analyzed using descriptive statistics, correlation, regression, and t-tests. Results showed that all measurement scales demonstrated acceptable reliability (Cronbach’s α between .76 and .80). Correlation analysis revealed that student satisfaction was strongly related to course content (r = .63), instructional quality (r = .67), and academic support (r = .76). However, regression results indicated that only instructional quality (β = .28, p < .01) and academic support (β = .54, p < .001) were significant predictors of satisfaction, while course content was not. Together, these variables explained 63.3% of the variance in satisfaction. In addition, foundation course marks were positively correlated with cumulative GPA (r = .416, p < .01), accounting for 17.3% of the variance in later academic performance. Gender differences were not significant. The findings highlight the importance of strong instructional practices and robust academic support systems in shaping international student satisfaction. They also confirm the preparatory value of foundation programs by linking early achievement with later success. The study offers practical recommendations for program improvement and contributes to the broader literature on international student experiences in foundation education.