Open AccessValidity of a graph-based automatic assessment system for programming assignments: human versus automatic grading
Author(s) -
Soundous Zougari,
Mariam Tanana,
Abdelouahid Lyhyaoui
Publication year - 2022
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v12i3.pp2867-2875
Subject(s) - computer science , grading (engineering) , workload , artificial intelligence , machine learning , software engineering , operating system , engineering , civil engineering
Programming is a very complex and challenging subject to teach and learn. A strategy guaranteed to deliver proven results has been intensive and continual training. However, this strategy holds an extra workload for the teachers with huge numbers of programming assignments to evaluate in a fair and timely manner. Furthermore, under the current COVID-19 distance teaching circumstances, regular assessment is a fundamental feedback mechanism. It ensures that students engage in learning as well as determines the extent to which they reached the expected learning goals, in this new learning reality. In sum, automating the assessment process will be particularly appreciated by the instructors and highly beneficial to the students. The purpose of this paper is to investigate the feasibility of automatic assessment in the context of computer programming courses. Thus, a prototype based on merging static and dynamic analysis was developed. Empirical evaluation of the proposed grading tool within an introductory C-language course has been presented and compared to manually assigned marks. The outcomes of the comparative analysis have shown the reliability of the proposed automatic assessment prototype.