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

Title:
An Open edX Extension for Parallel Programming Assignments with Automatic Configurable Grading
Authors:
Luis Germán García, Emanuel Montoya, Sebastian Isaza, Ricardo A. Velasquez
Source:
International Journal of Engineering Pedagogy (iJEP), Vol 11, Iss 4, Pp 7-22 (2021)
Publisher Information:
International Association of Online Engineering (IAOE)
Publication Year:
2021
Collection:
Directory of Open Access Journals: DOAJ Articles
Subject Terms:
parallel programming, automatic grading, open edx, Special aspects of education, LC8-6691, Theory and practice of education, LB5-3640
Document Type:
Fachzeitschrift article in journal/newspaper
Language:
English
Relation:
https://online-journals.org/index.php/i-jep/article/view/20097; https://doaj.org/toc/2192-4880; https://doaj.org/article/4ae9ab0a2ea8471d9c45f07a54cf3ea1
DOI:
10.3991/ijep.v11i4.20097
Availability:
https://doi.org/10.3991/ijep.v11i4.20097
https://doaj.org/article/4ae9ab0a2ea8471d9c45f07a54cf3ea1
Accession Number:
edsbas.3AB9549B
Database:
BASE

Weitere Informationen

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.