Classifying Pedagogical Material to Improve Adoption of Parallel and Distributed Computing Topics

Alec Goncharow, Anna Boekelheide, Matthew Mcquaigue, David Burlinson, Erik Saule, Kalpathi Subramanian, Jamie Payton
2019 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)  
The NSF/IEEE-TCPP Parallel and Distributed Computing curriculum guidelines released in 2012 (PDC12) is an effort to bring more parallel computing education to early computer science courses. It has been moderately successful, with the inclusion of some PDC topics in the ACM/IEEE Computer Science curriculum guidelines in 2013 (CS13) and some coverage of topics in early CS courses in some universities in the U.S. and around the world. A reason often cited for the lack of a broader adoption is the
more » ... difficulty for instructors who are not already knowledgable in PDC topics to learn how to teach those topics and align their learning objectives with early CS courses. There have been attempts at bringing textbook chapters, lecture slides, assignments, and demos to the hands of the instructors of early CS classes. However, the effort required to plow through all the available materials and figure out what is relevant to a particular class is daunting. This paper argues that classifying pedagogical materials against the CS13 guidelines and the PDC12 guidelines can provide the means necessary to reduce the burden of adoption for instructors. In this paper, we present CAR-CS, a system that can be used to categorize pedagogical materials according to wellknown and established curricular guidelines and show that CAR-CS can be leveraged 1) by PDC experts to identify topics for which pedagogical material does not exist and that should be developed, 2) by instructors of early CS courses to find materials that are similar to the one that they use but that also cover PDC topics, 3) by instructors to check the topics that a course currently covers and those it does not cover.
doi:10.1109/ipdpsw.2019.00060 dblp:conf/ipps/GoncharowBMBSSP19 fatcat:keskrt4dmzge7ovijh2nhxqbre