An Open edX Extension for Parallel Programming Assignments with Automatic Configurable Grading

Luis Germán García, Emanuel Montoya, Sebastian Isaza, Ricardo A. Velasquez

Abstract


Computing devices of all types have almost converged to using central processing units featuring multiple processing cores. In order to develop efficient software for such devices, programmers need to learn how to write parallel programs. We present an infrastructure to support parallel programming assignments for online courses. We developed an extension to the Open edX platform with a backend that handles the execution of student codes on a cluster lab. The web user interface offers instructors a wide range of configuration options for the programming assignments as well as a flexible definition of criteria for automatic grading. We have successfully integrated the software with Open edX and tested it with a real parallel programming cluster lab.

Keywords


parallel programming, automatic grading, Open edX

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International Journal of Engineering Pedagogy (iJEP) – eISSN: 2192-4880
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