The present work proposes a system to automatically grade computer programs using machine learning. To facilitate the same, we design an objective rubric and a novel set of fea-tures that capture the program's functionality.

Aug 24, 2014 · In this paper, we present a system to grade computer programs automatically. In addition to grading a program on its programming practices and complexity, the key kernel of the system is a machine-learning based algorithm which determines closeness of the logic of the given program to a correct program.

This paper expands upon an ongoing systematic literature review to provide an in-depth analysis of how machine learning (ML) has been used to grade and give feedback on programming assignments.

Machine learning auto-graders use various techniques to grade or provide feedback on the correctness and maintainability of a student’s submission. Walker and Russell [48] trained a feed-forward neural network to grade the design quality and provide personalised feedback.

In this research, we introduce an automated grading model LetGrade. LetGrade is a super-vised machine learning-based mechanism for automatically identifying the approach of solving and grading a student’s submission.

This study introduces an automated grading and feedback system powered by machine learning to tackle these difficulties. The system utilises supervised learning to forecast grades with 98.5% precision, including test case analysis, structural validation, and natural language processing for feedback production.

In this paper, we present a machine learning framework to automatically grade computer programs. We propose a set of highly-informative features, derived from the abstract representations of a given program, that capture the program's functionality.

An automated proposed approach that utilizes Graph Neural Networks, a machine learning algorithm, to generate class diagrams from source code within the context of Model Driven Architecture (MDA) and reverse engineering is presented.

Jul 1, 2022 · In this research, we introduce an automated grading model LetGrade. LetGrade is a supervised machine learning-based mechanism for automatically identifying the approach of solving and grading...

We propose a new machine learning work ow to grade open-response problems, which includes automatic cre-ation of structurally invariant features, normalization, a joint learning across questions with these features, and using them to predict labels for responses to …