Perceptions of Engineering College Instructors and Their Students Towards Generative Artificial Intelligence (GenAI) Tools: A Preliminary Qualitative Analysis

Abstract

GenAI tools, such as ChatGPT, have gained significant traction in engineering colleges and are revolutionizing how students approach each assignment and project. However, integrating them into the education system introduces challenges to the core assessment criteria and the traditional grading system that has been used in these institutions for decades. To achieve a better understanding of the significant influence and disturbance caused by GenAI, this study employed semi-structured interviews to collect qualitative data from a group of six students and two instructors, chosen via stratified sampling, from a research-intensive engineering college in Southeast Asia to explore their perspectives regarding GenAI. Initially, we discussed the positive and negative effects of GenAI on engineering education. Subsequently, we explored the correlation between ChatGPT and the current assessment pattern. It turned out that the widespread adoption of GenAI tools has made it necessary to reevaluate current assessment methods at educational institutions. The conventional grading scheme also found itself increasingly incompetent against the capabilities of ChatGPT, posing a potential threat to the equilibrium of academic integrity. The adaptive strategies employed by institutions in response to GenAI are also discussed in this paper, and we have explored whether instructors restrict students' access using sophisticated detection systems or simply advocate ethical and responsible use of GenAI. The potential consequences of these policies on students' learning were also explored with an emphasis on whether students feel unfairly disadvantaged when detection systems fail or if they perceive the need to rely on GenAI tools to maintain academic competitiveness.