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Estimating programming knowledge with Bayesian knowledge tracing

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Published:06 July 2009Publication History

ABSTRACT

In this paper we present a concept for three-phase measuring method, which can be used to obtain data on student learning. The focus of this method lies on the technical aspects of learning programming, answering questions like which programming constructs students applied and how large portion of the students understood the concepts of programming language.

The model is based on three consecutive measurements, which are used to observe the student errors, applied programming structures and an application of a Bayesian learning model to determine the programming knowledge. So far the model has produced results which confirm prior knowledge on student learning, indicating that the concept is feasible for further development. Despite of the early development phase of the method, it offers a straightforward way for teacher to assess the course contents and student performance.

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    • Published in

      cover image ACM Conferences
      ITiCSE '09: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education
      July 2009
      428 pages
      ISBN:9781605583815
      DOI:10.1145/1562877

      Copyright © 2009 ACM

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      New York, NY, United States

      Publication History

      • Published: 6 July 2009

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      ITiCSE '09 Paper Acceptance Rate66of205submissions,32%Overall Acceptance Rate552of1,613submissions,34%

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