A One Year Retrospective on a MOOC in Parallel, Concurrent, and Distributed Programming in Java
Much progress has been made on integrating parallel programming into the core Computer Science curriculum of top-tier universities in the United States. For example, "COMP 322: Introduction to Parallel Programming" at Rice University is a required course for all undergraduate students purs...
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| Vydáno v: | 2018 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC) s. 61 - 68 |
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IEEE
01.11.2018
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| Abstract | Much progress has been made on integrating parallel programming into the core Computer Science curriculum of top-tier universities in the United States. For example, "COMP 322: Introduction to Parallel Programming" at Rice University is a required course for all undergraduate students pursuing a bachelors degree. It teaches a wide range of parallel programming paradigms, from task-parallel to SPMD to actor-based programming. However, courses like COMP 322 do little to support members of the Computer Science community that need to develop these skills but who are not currently enrolled in a four-year program with parallel programming in the curriculum. This group includes (1) working professionals, (2) students at USA universities without parallel programming courses, or (3) students in countries other than the USA without access to a parallel programming course. To serve these groups, Rice University launched the "Parallel, Concurrent, and Distributed Programming in Java" Coursera specialization on July 31, 2017. In 2017, the authors of that specialization also wrote an experiences paper about launching the specialization. In this paper, the sequel to our previous publication, we look back at the first year of the Coursera specialization. In particular, we ask the following questions: (1) how did our assumptions about the student body for this course hold up?, (2) how has the course changed since launch?, and (3) what can we learn about how students are progressing through the specialization from Coursera's built-in analytics? |
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| AbstractList | Much progress has been made on integrating parallel programming into the core Computer Science curriculum of top-tier universities in the United States. For example, "COMP 322: Introduction to Parallel Programming" at Rice University is a required course for all undergraduate students pursuing a bachelors degree. It teaches a wide range of parallel programming paradigms, from task-parallel to SPMD to actor-based programming. However, courses like COMP 322 do little to support members of the Computer Science community that need to develop these skills but who are not currently enrolled in a four-year program with parallel programming in the curriculum. This group includes (1) working professionals, (2) students at USA universities without parallel programming courses, or (3) students in countries other than the USA without access to a parallel programming course. To serve these groups, Rice University launched the "Parallel, Concurrent, and Distributed Programming in Java" Coursera specialization on July 31, 2017. In 2017, the authors of that specialization also wrote an experiences paper about launching the specialization. In this paper, the sequel to our previous publication, we look back at the first year of the Coursera specialization. In particular, we ask the following questions: (1) how did our assumptions about the student body for this course hold up?, (2) how has the course changed since launch?, and (3) what can we learn about how students are progressing through the specialization from Coursera's built-in analytics? |
| Author | Budimlic, Zoran Sarkar, Vivek Imam, Shams Grossman, Max |
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| Snippet | Much progress has been made on integrating parallel programming into the core Computer Science curriculum of top-tier universities in the United States. For... |
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| SubjectTerms | concurrency Coursera distributed Java MOOC parallel Parallel processing Parallel programming pedagogy programming Programming profession Software Videos |
| Title | A One Year Retrospective on a MOOC in Parallel, Concurrent, and Distributed Programming in Java |
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