Engineering students and AI in education: a TAM-based study of perceptions, acceptance, and barriers to adoption

Artificial intelligence (AI) is gradually being accepted into education and has the potential of transforming learning and teaching. It is therefore important to understand the perceptions of various stakeholders on the impact of AI in engineering education. This study is framed with the Technology Acceptance Model (TAM) and employs a mixed-method approach to assess the perception of engineering students on the adoption of AI. The quantitative analysis of the survey findings using partial least square structural equation modelling (PLS-SEM), reveals that perceived usefulness and the ease of use has a statistically significant relationship with AI adoption amongst engineering students. Moreover, their attitude towards AI did not influence their intention to use AI in their education. Through the qualitative analysis, the perceived usefulness of AI in personalized learning, solving complex problems, increasing efficiency and solving global problems were highlighted. However, it was noted that wider adoption of AI would be achieved when there are strategies to address the institutional barriers, ethical issues and funding. Another interesting finding is that students raised concern about the potential impairment in their cognitive abilities if they over-rely on AI.