MOCSIDE: An open-source and scalable online IDE and auto-grader for computer science education

Date
2022-03
Authors
Cazalas, Jonathan
Barlow, Max
Cazalas, Ibraheem
Robinson, Chase
Journal Title
Journal ISSN
Volume Title
Publisher
Association for Computing Machinery
Abstract
Programming is learned through practice, with said practice in introductory programming courses often translating to a prohibitively large number of assignments, increasing the grading workload for faculty and/or teaching assistants. In short, this is unsustainable. Several publishers and a few notable companies have provided meritable auto-grading solutions, although most are plagued with problems including minimal problem sets, limited customization options, high cost, and at times even a disconnect with the pedagogical needs of academia. This poster presents our newly-developed web application, MOCSIDE, an open-source and scalable online IDE and auto-grader for computer science education. Results indicate a positive user experience from students and instructors alike, with cost savings, ease of use, and code collaboration highlighted as key features.
Description
Keywords
Computer science--Study and teaching, Web applications, Auto-grading
Citation
Cazalas, J., Barlow, M., Cazalas, I., & Robinson, C. (2022, March 3-5). MOCSIDE: An open-source and scalable online IDE and auto-grader for computer science education [Conference poster]. 53rd Annual ACM Technical Symposium on Computer Science Education (SIGCSE 2022), Virtual Conference. https://www.doi.org/10.1145/3478432.3499125
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