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Title: Using artificial intelligence teaching assistants to guide students in solar energy engineering design
Engineering projects, such as designing a solar farm that converts solar radiation shined on the Earth into electricity, engage students in addressing real-world challenges by learning and applying geoscience knowledge. To improve their designs, students benefit from frequent and informative feedback as they iterate. However, teacher attention may be limited or inadequate, both during COVID-19 and beyond. We present Aladdin, a web-based computer-aided design (CAD) platform for engineering design with a built-in artificial intelligence teaching assistant (AITA). We also present two curriculum units (Solar Energy Science and Solar Farm Design), where students explore the Sun-Earth relationship and optimize the energy output and yearly profit of a solar farm with the help of the AITA. We tested the software and curriculum units with over 100 students in two Midwestern high schools. Pre- and post-survey data showed improvements in understanding of science concepts and self-efficacy in engineering design. Pre-post analysis of design performance gains reveals that AI helped lower achievers more than higher achievers. Interviews revealed students’ values and preferences when receiving feedback. Our findings suggest that AITAs may be helpful as an additional feedback mechanism for geoscience and engineering education. Future efforts should focus on improving the usability of the software and providing multiple types of feedback to promote inclusive and equitable use of AI in education.  more » « less
Award ID(s):
2301164 2131097 2105695
PAR ID:
10530861
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
Taylor & Francis
Date Published:
Journal Name:
Journal of Geoscience Education
ISSN:
1089-9995
Page Range / eLocation ID:
1 to 20
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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