GRAD-AI: An automated grading tool for code assessment and feedback in programming course

The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation...

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Vydané v:Education and information technologies Ročník 30; číslo 7; s. 9859 - 9899
Hlavní autori: Gambo, Ishaya, Abegunde, Faith-Jane, Gambo, Omobola, Ogundokun, Roseline Oluwaseun, Babatunde, Akinbowale Natheniel, Lee, Cheng-Chi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.05.2025
Springer Nature B.V
Predmet:
Artificial Intelligence
Automation
Computer Appl. in Social and Behavioral Sciences
Computer Science
Computers and Education
Education
Educational Technology
Feedback
Grading
Information Systems Applications (incl.Internet)
Plagiarism
Programming
User interface
User Interfaces and Human Computer Interaction
Programming assignments
Automated
Feedback
Assessment
User Interface
Manual
Python programming
Automated grading tool
Characteristic extraction
Artificial intelligence
K-means clustering
Plagiarism detection
ISSN:1360-2357, 1573-7608
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Shrnutí:The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading, timely feedback, and personalized support, enhancing the education process. This paper aims to develop "GRAD-AI," an automated grading tool for computer programming assignments. The objective is to overcome the limitations of manual grading by harnessing AI's capabilities to deliver accurate and timely assessments, thus creating a more interactive and supportive learning environment. The results show that GRAD-AI provides unbiased grading and timely and accurate feedback delivery for programming assignments by using the Halstead Complexity Measure, Term Frequency – Inverse Document Frequency Measure, Abstract Syntax Tree Process, and K-means Clustering. GRAD-AI marks a substantial stride in improving grading and feedback delivery within the education sector. Its real-time feedback provision and gap identification contribute to enhanced learning outcomes. As AI's role expands, integrating automated grading tools like GRAD-AI becomes crucial for fostering personalized learning and adaptability. The paper underscores AI's potential to revolutionize assessment and grading processes, supporting global students' growth and development.
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ISSN:1360-2357
1573-7608
DOI:10.1007/s10639-024-13218-5