Marking student programs using graph similarity
ARTICLE
Kevin A. Naudé, Jean H. Greyling, Dieter Vogts
Computers & Education Volume 54, Number 2, ISSN 0360-1315 Publisher: Elsevier Ltd
Abstract
We present a novel approach to the automated marking of student programming assignments. Our technique quantifies the structural similarity between unmarked student submissions and marked solutions, and is the basis by which we assign marks. This is accomplished through an efficient novel graph similarity measure (
Citation
Naudé, K.A., Greyling, J.H. & Vogts, D. (2010). Marking student programs using graph similarity. Computers & Education, 54(2), 545-561. Elsevier Ltd. Retrieved December 11, 2019 from https://www.learntechlib.org/p/67235/.
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Computers & Education
on January 30, 2019.
Computers & Education is a publication of Elsevier.
Keywords
- Assignments
- Classroom Techniques
- Computer Assisted Testing
- computer science education
- Computer Software
- Computer Software Evaluation
- Computer-assisted assessment
- Correlation
- educational technology
- EVALUATION METHODS
- Grading
- Graph similarity
- Graphs
- Interrater Reliability
- programming
- Programming and programming languages
Cited By
View References & Citations Map-
21st Century Learning: Exploring the Classroom Experience
Frantzeska Kolyda & Vassiliki Bouki, University Of Westminster, United Kingdom
EdMedia + Innovate Learning 2013 (Jun 24, 2013) pp. 1674–1682
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