ACUE Lunch and Learn: Active learning – use of machine learning/process simulation in-class

Facilitator: Daniela Galatro; Assistant Professor, Teaching Stream. Chemical Engineering & Applied Chemistry, FASE

This session describes the workflow of mapping the ACUE modules with my research and teaching interests in incorporating machine learning and process simulation in class through my course reflections. This mapping process is followed by the design and implementation of examples illustrating the use of different learning and process simulations in class while merging with the traditional first principles. These active learning sessions vary from data-based modeling in core chemical engineering courses to simulation-based learning in optional engineering courses in different undergraduate years and are fully integrated with several subjects and tools covered in the ACUE modules that help students to enhance their learning experience. Some preliminary results on assessing the effectiveness of these initiatives are also discussed.

This session will include my intentional approach to course design, learning activities, and alignment with learning outcomes drawn from the ACUE course in Effective Teaching Practices.