A contingency table derived method for analyzing course data

Alireza Ahadi, Arto Hellas, Raymond Lister

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

We describe a method for analyzing student data from online programming exercises. Our approach uses contingency tables that combine whether or not a student answered an online exercise correctly with the number of attempts that the student made on that exercise. We use this method to explore the relationship between student performance on online exercises done during semester with subsequent performance on questions in a paper-based exam at the end of semester. We found that it is useful to include data about the number of attempts a student makes on an online exercise.

Original languageEnglish
Article number13
Number of pages19
JournalACM Transactions on Computing Education
Volume17
Issue number3
DOIs
Publication statusPublished - Aug 2017
Externally publishedYes

Keywords

  • data mining
  • programming novices
  • Java

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