Towards a Framework for Mining Students’ Programming Assignments

Ella Albrecht, Jens Grabowski

Abstract

Due to an increasing number of students, more and more learning institutions tend to use computer-supported learning tools like online learning platforms or intelligent tutoring systems. This has opened up the opportunity to collect a huge amount of students’ data. Educational Data Mining (EDM) uses mining techniques to derive information from these data about students’ knowledge, behavior and experience to improve education. In this paper, we present a framework for mining programming errors of computer science students by analyzing the students’ solutions to a programming assignment. The framework serves as both, a computer aided assessment tool as well as an immediate feedback tool about the learning progress of the students for the educator.
Keywords: 
computer aided assessment; educational data mining; programming errors
Document Type: 
Articles in Conference Proceedings
Booktitle: 
2016 IEEE Global Engineering Education Conference (EDUCON)
Language: 
English
Publisher: 
IEEE
Pages: 
1096-1100
Year: 
2016
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