Qualitative Content Analysis of Programming Errors

In computer science education, the analysis of source code with errors is of interest as programming errors may give a hint to misconceptions. The analysis of misconceptions can help teachers to improve their exercises and lessons. The semantic analysis of texts or video sequences could lead to different, subjective interpretation. This problem also effects source code errors, which could contain semantic errors. In different projects, we were confronted with a lot of incorrect source codes, which were written by students of universities and secondary schools. A first analysis of these errors led to a categorization of errors regarding missing competencies. To avoid mainly subjective interpretation of source code errors a standardized method for categorizing errors, which could also be applied by a practitioner, has to be developed and justified. Categorizing texts or source code errors is a matter of semantics, because text or code elements have to be interpreted. Thus, a qualitative content analysis is most suitable. In this paper we explain the difference between errors and misconceptions and present our adaption of the qualitative content analysis of Mayring to source code errors.

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