Deep learning and artificial intelligence: Project collaboration across classes

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Abstract

Working in collaborative environments is an essential skill for computing professionals. In our program, students have significant team experience from previous classes; almost all of our classes in Cal Poly's Computer Science, Software Engineering and Computer Engineering programs have lab sections, and students start with team-based work early. However, they mostly work within small teams of about five members that are stable throughout a term. To stretch the students' collaborative skills and enhance their experience with more fluid team configurations, we experimented with creating teams across two related senior-level classes within Computer Science, but with different perspectives and approaches. For one particular project, shark spotting in drone video footage, the teams also collaborated with a group of Marine Biologists from the Shark Lab at CSU Long Beach, who provided the video material and acted as a customer for three teams across the two classes. This exposed our students to collaborators among different fields, with their own terminology, goals, work methods and practical approaches. Our paper reports on the initial experiment during the Fall 2019 term, involving two sections of an Artificial Intelligence class and one section of a Deep Learning class. We are planning to continue this collaboration in the future.

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APA

Kurfess, F. J., Pantoja, M., & Humer, I. (2020). Deep learning and artificial intelligence: Project collaboration across classes. In ASEE Annual Conference and Exposition, Conference Proceedings (Vol. 2020-June). American Society for Engineering Education. https://doi.org/10.18260/1-2--34370

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