Title: Learning Outcomes Graph Optimization
Abstract:
In this presentation we cover the motivation, basic concepts, and some recent work related to applying learning outcome graph optimization in the area of curricular analytics. First, we review our previous work in curricular complexity including its definition and a simulation result that relates student performance and curricular complexity. The curricular analytics toolbox will be introduced briefly in order to provide visualizations and to compute metrics that will be used in this talk. Second, we introduce the concept of learning outcome graphs and we consider their relationship to curriculum graphs. We then demonstrate how learning outcomes can be organized into the courses that make up a curriculum, and how this can be done so as to reduce curricular complexity. Third, we present the objective function and multiple constraints in the learning outcome graph optimization problem, and we demonstrate its application on a real ECE curriculum. Finally, we discuss our future plans including obtaining more practical datasets, designing a balanced graph partitioning algorithm, and considering more dimensional information in the optimization.
Speaker:
Yiming Zhang
PhD Student
University of Arizona
Date/Time: July 30, 2021, 2pm PDT, 5pm EDT
Video: https://www.youtube.com/watch?v=24BszQmisto&ab_channel=HigherEducationAnalytics
Slides: https://drive.google.com/file/d/1yKev1h0WWUe6Z6vJP214XIkU4_xzWdF7/view?usp=sharing