Portland, Oregon
June 23, 2024
June 23, 2024
June 26, 2024
Artificial Intelligence (AI) and Case Studies in Construction Education
Construction Engineering Division (CONST)
9
10.18260/1-2--48459
https://peer.asee.org/48459
103
MiguelAndres is an Assistant Professor in the Polytechnic College of Science and Engineering at Universidad San Francisco de Quito USFQ. He holds a BS in Civil Engineering from USFQ, a M.Sc. in Civil Engineering in Construction Engineering and Project Management from Iowa State University, a Ph.D. in Civil Engineering with emphasis in Sustainable Construction from Virginia Tech, and two Graduate Certificates from Virginia Tech in Engineering Education and Future Professoriate and from USFQ in Structures for Construction Professionals. MiguelAndres’s research includes Architectural and Civil Engineering Project Management, Sustainable and Resilient Urban Infrastructure, and the development of engineers who not only have strong technical and practical knowledge but the social awareness and agency to address global humanitarian, environmental, and social justice challenges. For him, social justice is a concept that should always be involved in discussions on infrastructure. Related to STEM education, Miguel Andres develops disruptive pedagogies for STEM courses as a tool for innovation, and assessing engineering students’ agency to address climate change. Currently, MiguelAndres is working on a framework to support and conduct undergraduate research.
Practical exposure for students in the realm of construction management topics is frequently limited due to the challenges associated with visiting real-world projects, be it due to logistical complexity, project size, or their physical locations, often underground or high above the ground. Generative Artificial Intelligence (AI) applications present a valuable tool to help students contextualize these topics. While the development of generative AI has been ongoing for several decades, its significance in higher education, particularly in engineering disciplines like Civil Engineering, has grown in recent years. This study aims to investigate how generative AI can be employed to enhance the development of critical thinking skills among students specializing in water resources and sanitary engineering. In this study, students were tasked with initiating a video prompt and using ChatGPT application to summarize the video's main points. The activity involved interactions with the AI app, posing questions and receiving responses, which aimed to foster critical thinking abilities. The types of questions asked were guided by the professor to lead students to a deeper level of critical thinking. Subsequently, students provided feedback on their perceptions of the activity through a survey. Data analysis involved the examination of student responses and their interactions with the AI app, assessing the depth of their critical thinking. The study included a sample of 28 senior students from Construction Management course and 25 junior students from Construction Costs majoring in Civil Engineering from the Universidad San Francisco de Quito USFQ. The study also explores potential factors contributing to the observed outcomes and suggests ways in which academia can integrate these results into their teaching approaches. It concludes by discussing the implications for both research and practical application.
Abril, D. E., & Guerra, M. A., & Duran Ballen, S. (2024, June), ChatGPT to Support Critical Thinking in Construction-Management Students Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--48459
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