ABSTRACT Although grading is one of the most time‐consuming things teachers do, it gives students feedback on how hard they worked to complete an assignment and provides teachers with an evaluation of how well students understood the course material. It is relatively difficult to grade coding assignments since it involves reviewing student‐written computer code, giving each student individualized feedback, and allocating partial credit in a fair and consistent manner. Because of its relative simplicity and the abundance of tools and command libraries available, MATLAB is being used in many colleges across the world. In 2018, MathWorks introduced the “MATLAB Grader” system, which allowed instructors to design their own assignment questions requiring students to write a script or a function. This system has many attractive features, such as the ability to allow multiple attempts, with grading done instantly online after each submission to help students improve their code for the next attempt. This paper introduces the MATLAB Smart Assignment Grader (MSAG) system, which includes features absent in MATLAB Grader, such as adaptive grading, plagiarism suspicion flagging, and a partial credit option. To foster the advantages of both grading systems for consistent, adaptive, and fair grading of coding assignments, this paper also proposes an approach to integrating MATLAB Grader with MSAG.
Peter L. Bishay (Sun,) studied this question.