Datawhys Phase 1: Problem Solving to Facilitate Data Science & STEM Learning Among Summer Interns
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Abstract
This design case details a data science summer learning experience designed by University of Memphis faculty for HBCU students (NSF #: 1918751) with recruiting assistance provided by LeMoyne-Owen College. The summer learning experience included elements of didactic and collaborative problem-solving during the first five weeks of the internship, followed by a three-week, team-based, problem-solving project using real-world data. While the course was originally designed as a face-to-face learning experience, the impact of COVID-19 necessitated a shift toward online digital spaces. The design case details the opportunities and challenges of STEM online learning and especially underscores the limitations of (a) existing data science technologies for instruction, (b) the shift toward instructional design of materials that supported more self-directed learning, and (c) collaborative problem-solving. Implications for design and practice are also considered.
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Linda Ann Payne, University of Memphis
Linda Payne is a Research Assistant in the Instructional Design & Technology Studio at the University of Memphis. Her research interests include human-computer interaction, problem-based learning, trauma-informed education, content design, informal learning, and computer-supported collaborative learning.
Andrew Tawfik, University of Memphis
Andrew Tawfik is an Assistant Professor of Instructional Design & Technology at the University of Memphis where he also serves as the director for the Instructional Design & Technology Studio. His research interests include problem-based learning, case-based reasoning, case library instructional design, and computer-supported collaborative learning.
Andrew Olney, University of Memphis
Andrew M. Olney serves as Professor in both the Institute for Intelligent Systems and the Department of Psychology at the University of Memphis. His research interests are in natural language interfaces, vector space models, dialogue systems, unsupervised grammar induction, robotics, and intelligent tutoring systems.
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