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Analysis of a Randomized Controlled Trial of Student Performance in Parallel Programming using a New Measurement Technique

Analysis of a Randomized Controlled Trial of Student Performance in Parallel Programming using a... There are many paradigms available to address the unique and complex problems introduced with parallel programming. These complexities have implications for computer science education as ubiquitous multi-core computers drive the need for programmers to understand parallelism. One major obstacle to student learning of parallel programming is that there is very little human factors evidence comparing the different techniques to one another, so there is no clear direction on which techniques should be taught and how. We performed a randomized controlled trial using 88 university-level computer science student participants performing three identical tasks to examine the question of whether or not there are measurable differences in programming performance between two paradigms for concurrent programming: threads compared to process-oriented programming based on Communicating Sequential Processes. We measured both time on task and programming accuracy using an automated token accuracy map (TAM) technique. Our results showed trade-offs between the paradigms using both metrics and the TAMs provided further insight about specific areas of difficulty in comprehension. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Computing Education (TOCE) Association for Computing Machinery

Analysis of a Randomized Controlled Trial of Student Performance in Parallel Programming using a New Measurement Technique

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References (41)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2020 ACM
ISSN
1946-6226
eISSN
1946-6226
DOI
10.1145/3401892
Publisher site
See Article on Publisher Site

Abstract

There are many paradigms available to address the unique and complex problems introduced with parallel programming. These complexities have implications for computer science education as ubiquitous multi-core computers drive the need for programmers to understand parallelism. One major obstacle to student learning of parallel programming is that there is very little human factors evidence comparing the different techniques to one another, so there is no clear direction on which techniques should be taught and how. We performed a randomized controlled trial using 88 university-level computer science student participants performing three identical tasks to examine the question of whether or not there are measurable differences in programming performance between two paradigms for concurrent programming: threads compared to process-oriented programming based on Communicating Sequential Processes. We measured both time on task and programming accuracy using an automated token accuracy map (TAM) technique. Our results showed trade-offs between the paradigms using both metrics and the TAMs provided further insight about specific areas of difficulty in comprehension.

Journal

ACM Transactions on Computing Education (TOCE)Association for Computing Machinery

Published: Sep 9, 2020

Keywords: Parallel programming

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