Performance prediction and behavioral analysis of student programming ability

Computer Programming as a process that embodies the creation of an executable computer program for a given computational problem by analyzing the task and developing an algorithm that computes the desired result. Due to its complex and diverse nature, programming requires a certain level of expertise in analysis of algorithms, data structures, mathematics, formal logic as well as related tasks such as testing and debugging. Due to increasing awareness of need for programming, there exists numerous competitive programming websites where students can practice and solve problems. The aim of our work is to assess the performance of students on such platforms. This work shall not only help the learners to self-assess themselves, but it will also aid the educators to evaluate the progress of their students. To meet this objective, the data was collected from two different competitive programming environments, namely, HackerEarth-a globally accessible competitive programming website and our university's in-house programming portal, a university-based programming environment. We used supervised learning to predict the performance of students for both the datasets. The accuracy obtained for the HackerEarth dataset is 80%, while the accuracy for the University dataset was computed to be 91%. Apart from predicting the performance, rigorous analyses were done unearth hidden trends responsible for a learners programming acumen.

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