Transformation of Graduate Engineering Education Through Artificial Intelligence Integration

Bibliographic Data

ID22006237
AuthorsZhen Yin (0000-0002-7263-0648, Sichuan Tourism University, corresponding author), Shufan Li (0000-0002-6366-7334, Zhejiang University of Science and Technology), Xiangbing Zhou (Sichuan Tourism University), Ena Bhattacharyya (SEGi University), Qingwei Zhou (Sichuan Tourism University)
Year2026
Volume16
Issue2
Publication date2026-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSAGE Open (JOURNAL)
Journal identifiersISSN: 2158-2440 • E-ISSN: 2158-2440
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/21582440261454397
OpenAlexW7162689242
LanguageEN
References cited24

This quasi-experimental study examines the impact of integrating Artificial Intelligence (AI) into graduate engineering education in Bangladesh, focusing on student learning outcomes. The study compares two groups: a treatment group that uses AI tools and methodologies in its curriculum and a comparison group that follows traditional teaching methods. The sample consists of graduate engineering students from a public university in Bangladesh, and ethical approval has been obtained for the study. Pre- and post-tests were administered to assess changes in knowledge and skills over an academic semester. A survey was conducted to gather students’ perceptions regarding the AI tools used in their classrooms. Statistical analysis, including independent and paired-sample t-tests, was performed in SPSS 26 to evaluate AI’s effectiveness. Qualitative data from interviews with students and faculty were analyzed using NVivo to explore their experiences with AI in the classroom. The results indicate significant improvements in learning outcomes for the treatment group, suggesting that AI integration may positively impact educational effectiveness. However, the study also highlights challenges related to the accessibility of technology and the adaptation of AI tools, which may limit their impact. The findings provide valuable insights into the potential of AI to enhance graduate engineering education in Bangladesh, though the study’s limitations include its non-randomized design and focus on a single institution. Future research should explore AI integration in diverse educational settings to refine implementation strategies and broaden its applicability

Curriculum · Engineering education · Focus group · Graduate students · Perception · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI · Online Learning and Analytics

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