Salt Lake City, Utah
June 23, 2018
June 23, 2018
July 27, 2018
Electrical and Computer
The National Science Foundation is supporting several institutions under their “Revolutionizing Engineering and Computer Science Departments” (RED) program. The focus of RED program projects is on the middle two years of engineering or computer science programs. Our particular project proposes to remove the artificial barriers that a traditional course-based curriculum creates. As part of this process, we first seek to understand the relationships between the various required technical courses in our Electrical and Computer Engineering (ECE) Department. In particular, we examine the performance of students in their junior year and study the correlation of grades between courses and their prerequisite offerings. We also provide a Principal Component Analysis (PCA) decomposition of the grades within the junior-year courses to help explain trends in the students’ GPAs.
The junior year of our undergraduate ECE curriculum consists of three main subject areas, i.e., electronics, electromagnetics, and signals and systems, each spanning two semesters. We show that the student performance within each subject during the first semester has a moderately strong correlation to their performance during the second semester, with each relationship having a Spearman's rho greater than 0.55. Analysis of the principal components explains that 60% of the total variance in individual course grades amongst students is due to the overall performance of students prior to entering the junior year. In other words, students who had a greater overall GPA had a tendency to perform better during the junior year. The insights gained from these correlations is being used to inform how technical content from these three topical areas is temporally arranged in our new integrated delivery mode.
Robbiano, C., & Maciejewski, A. A., & Chong, E. K. P. (2018, June), Board 77 : Work in Progress: An Analysis of Correlations in Student Performance in Core Technical Courses at a Large Public Research Institution’s Electrical and Computer Engineering Department Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/30104
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