2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) 2018
DOI: 10.1109/ipdpsw.2018.00063
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ParallelAR: An Augmented Reality App and Instructional Approach for Learning Parallel Programming Scheduling Concepts

Abstract: Parallel programming has rapidly moved from a special-purpose technique to standard practice. This newfound ubiquity needs to be matched by improved parallel programming education. As parallel programming involves higher level concepts, students tend to struggle with turning the abstract information into concrete mental models. Analogies are known to aid in this knowledge transfer, by providing an existing schema as the basis for the formation of a new schema. Additionally, technology has been proven to increa… Show more

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Cited by 8 publications
(2 citation statements)
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“…Finally, this paper extends the initial work introduced with ParallelAR [39], which provided an augmented reality mobile app for demonstrating parallel scheduling policies. The contributions made beyond this earlier work includes an in-depth evaluation of the learning impact of using short visual analogy videos in a PDC course.…”
Section: Related Workmentioning
confidence: 81%
See 1 more Smart Citation
“…Finally, this paper extends the initial work introduced with ParallelAR [39], which provided an augmented reality mobile app for demonstrating parallel scheduling policies. The contributions made beyond this earlier work includes an in-depth evaluation of the learning impact of using short visual analogy videos in a PDC course.…”
Section: Related Workmentioning
confidence: 81%
“…The short videos presented to students were based on an analogy that has been used in an existing augmented reality (AR) app [39]. The core elements of the analogy are illustrated in Figure 2, showing the mapping of technical content (threads and cores) to the analogy (workers and desks): The number of workers and the tasks assigned to workers differ, depending on the scheduling policy.…”
Section: Analogy Videosmentioning
confidence: 99%