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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Published in:	Education and information technologies Vol. 30; no. 7; pp. 9859 - 9899
Main Authors:	Gambo, Ishaya, Abegunde, Faith-Jane, Gambo, Omobola, Ogundokun, Roseline Oluwaseun, Babatunde, Akinbowale Natheniel, Lee, Cheng-Chi
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.05.2025 Springer Nature B.V
Subjects:	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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Abstract	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.
AbstractList	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.
Author	Gambo, Omobola Ogundokun, Roseline Oluwaseun Abegunde, Faith-Jane Lee, Cheng-Chi Babatunde, Akinbowale Natheniel Gambo, Ishaya
Author_xml	– sequence: 1 givenname: Ishaya surname: Gambo fullname: Gambo, Ishaya organization: Department of Computer Science and Engineering, Obafemi Awolowo University – sequence: 2 givenname: Faith-Jane surname: Abegunde fullname: Abegunde, Faith-Jane organization: Department of Computer Science and Engineering, Obafemi Awolowo University – sequence: 3 givenname: Omobola surname: Gambo fullname: Gambo, Omobola organization: Department of Arts and Social Science Education, Lead City University – sequence: 4 givenname: Roseline Oluwaseun surname: Ogundokun fullname: Ogundokun, Roseline Oluwaseun email: ogundokun.roseline@lmu.edu.ng organization: Department of Software Engineering, Kaunas University of Technology, Department of Computer Science, Landmark University, Department of Computer Systems Engineering, Tshwane University of Technology (TUT) – sequence: 5 givenname: Akinbowale Natheniel surname: Babatunde fullname: Babatunde, Akinbowale Natheniel organization: Department of Computer Science, Kwara State University – sequence: 6 givenname: Cheng-Chi orcidid: 0000-0002-8918-1703 surname: Lee fullname: Lee, Cheng-Chi email: cclee@mail.fju.edu.tw organization: Dept. of Library and Information Science, Fu Jen Catholic University, Dept. of Computer Science and Information Engineering, Asia University
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SubjectTerms	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
Title	GRAD-AI: An automated grading tool for code assessment and feedback in programming course
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