Teaching artificial intelligence and machine learning to materials engineering students through plastic 3D printing

Computational tools in conjunction with Artificial Intelligence (AI) and Machine Learning (ML) have the potential to play significant roles in the future of Materials Science and Engineering (MS&E).These concepts need to be introduced to students throughout existing MS&E curricula.There is currently a lack of datasets and tools that are appropriate for introducing the complex topics of AI and ML to engineering students with little to no knowledge of computer science or programming.In this paper, we report on the background, development, and application of a new 3D printed plastic dataset and related active learning exercise.This exercise was performed on a relatively new "no-code" software platform (developed by Citrine Informatics) that uses AI and ML to solve real-world materials engineering problems.Our approach places an emphasis on the importance of materials engineering domain knowledge and structured material data for the successful application of AI and ML in solving materials engineering problems.Student perceptions of the approach and its outcomes were shown to be largely positive.In particular, the exercise was shown to enable students to understand the role of AI and ML in MS&E problem solving.The implications of this work are to share our efforts and findings with educators, to get feedback and to inspire ideas for teaching AI and ML to engineering students without a programming background.