TL;DR
TipsC is a tool designed to assist programming MOOC students by suggesting code corrections based on analyzing correct submissions, and also visualizes submission patterns for instructors, improving grading and learning support.
Contribution
This paper introduces TipsC, a novel system that suggests logical fixes for incorrect code and visualizes submission patterns, enhancing programming education in MOOCs.
Findings
Clustering reduces variance in student grades by 47%.
TipsC effectively suggests code corrections based on similar correct submissions.
The system aids both students and instructors in large-scale programming courses.
Abstract
With the widespread adoption of MOOCs in academic institutions, it has become imperative to come up with better techniques to solve the tutoring and grading problems posed by programming courses. Programming being the new 'writing', it becomes a challenge to ensure that a large section of the society is exposed to programming. Due to the gradient in learning abilities of students, the course instructor must ensure that everyone can cope up with the material, and receive adequate help in completing assignments while learning along the way. We introduce TipsC for this task. By analyzing a large number of correct submissions, TipsC can search for correct codes resembling a given incorrect solution. Without revealing the actual code, TipsC then suggests changes in the incorrect code to help the student fix logical runtime errors. In addition, this also serves as a cluster visualization tool…
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