SUMMARY

This research focuses on the enhancement of the undergraduate education in mechanical engineering using active learning techniques, and specifically, hands-on learning through the incorporation of student interaction with 3D multi-material printed and machined parts. Complex subjects that impact a person’s ability to apply knowledge in many different industries are mechanics of materials and geometric dimensioning and tolerancing (GD&T). A method has been developed to improve attributes of self-efficacy, student satisfaction, and course performance by incorporating multiple active learning-based modules into the classroom. This dissertation is comprised of two distinct engineering education development projects. Both projects provide insight into the impact of hands-on module development, active learning, and spatial tools on student performance. The first project is mechanics of materials module development for four major topics in the course and the evaluation of the impact of the modules on the students. This development process was vital to understand how the combination of curriculum activity structure, 3D printed multi-material models, and participant feedback can shape the engagement and reception of the learning activities. The second project focused on the development and evaluation of an intervention for geometric dimensioning and tolerancing using machined parts and measurement devices, based on best practices learned from the development of the mechanics of materials modules. This pedagogical approach revealed strategies for iterative design of hands-on learning activities for core engineering subjects in the undergraduate curriculum that foster engagement, encourage spatial conceptualization, and create an alternative modality for students to experience a different type of learning outside of traditional lectures. Link: https://teams.microsoft.com/l/meetup-join/19%3ameeting_ZDkzNmFiYWUtNjE2ZS00NzQ1LWIxYWQtYmUxMjljNTI5MzIz%40thread.v2/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%22791f3f21-9eee-4e87-9d72-7539450f63c8%22%7d