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Teaching Computer Architecture with Spatial Ability Considerations

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

Broadening Participation through Access, Equity, Inclusion in ECE

Tagged Division

Electrical and Computer Engineering Division (ECE)

Tagged Topic

Diversity

Page Count

17

DOI

10.18260/1-2--44409

Permanent URL

https://peer.asee.org/44409

Download Count

122

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Paper Authors

biography

Geoffrey L. Herman University of Illinois at Urbana - Champaign Orcid 16x16 orcid.org/0000-0002-9501-2295

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Dr. Geoffrey L. Herman is the Severns Teaching Associate Professor with the Department of Computer Science at the University of Illinois at Urbana-Champaign.

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biography

Muahmmad Suleman Mahmood

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Suleman Mahmood is a Ph.D. student in the Department of Computer Science at the University of Illinois, Urbana Champaign. Suleman completed his MS in Computer Science from Lahore University of Management Sciences and BS in Electrical Engineering from University of Engineering and Technology. He is interested in exploring how students learn computer science concepts and developing tools to assist them in the learning process

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Abstract

Spatial ability is the ability to reason about visual images. High spatial ability is correlated with success and retention in STEM fields. Spatial ability is also correlated with gender and minority status. Therefore, spatial ability may be a factor in lower participation and retention for women and minorities in STEM fields. For our computer architecture course, we observed that the topics of caches and number representations had the highest correlation with spatial ability. Students with high spatial ability performed significantly better. A closer inspection of the course material showed heavy use of visual aids to communicate the concepts and solve problems. This can be taxing for students with low spatial ability. A known method for reducing the effect of spatial ability on student performance for a topic is to change the instruction methods to focus on algorithmic approaches. In this study, we modified our instructional materials to add algorithmic methods in two topics in computer architecture course. The topic of number representation was modified to emphasize the use of modular arithmetic to model fixed width arithmetic in computers. We also changed the instruction material for caches to use modular arithmetic for hashing functions to map addresses to caches.

Our research questions focus on assessing the effects of the changes. Our results show that there is no statistically significant change in overall performance of students on number systems. Students' performance on caches showed a statistically significant improvement with a small effect size of 0.19. Low- and high-spatial-ability students were affected similarly by the instructional changes. Additional analysis of our data suggests that modification in instruction material changed which sub-tasks students find difficult to perform when analyzing cache performance. Although we did not manage to close the gap between students with high and low spatial ability, the data suggests further changes that may help in achieving this goal and help students learn caches generally.

Herman, G. L., & Mahmood, M. S. (2023, June), Teaching Computer Architecture with Spatial Ability Considerations Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44409

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