Discovering Multiple Design Approaches in Programming Assignment Submissions
Nikhila KN, Sujit Kumar Chakrabarti, Manish Gupta

TL;DR
This paper introduces an automated evaluation method that identifies multiple solution approaches in programming assignment submissions without prior knowledge of possible solutions, enhancing current evaluation practices.
Contribution
It presents a novel automated approach that detects diverse student solution strategies without requiring instructor foresight or extensive human intervention.
Findings
Successfully identified multiple solution approaches in various datasets
Demonstrated effectiveness on practical, real-world data
Improves automated evaluation by recognizing diverse solutions
Abstract
In this paper, we present a novel approach of automated evaluation of programming assignments~(AEPA) the highlight of which is that it automatically identifies multiple solution approaches to the programming question from the set of submitted solutions. Our approach does not require the instructor to foresee all the possible solution approaches and accomplishes this task with little or no human intervention. This paves the way to multiple fundamental improvements in the way automated evaluation of programming assignments is done today. We have applied our method on multiple data sets of practical scale. In all cases, our method was able to detect the solution approaches employed by the students.
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Taxonomy
TopicsTeaching and Learning Programming · Software Testing and Debugging Techniques · Software Engineering Research
