Class association rules mining from students’ test data (Abstract)

C. Romero, S. Ventura, E. Vasilyeva, M. Pechenizkiy

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

13 Citations (Scopus)


In this paper we propose the use of a special type of association rules mining for discovering interesting relationships from the students’ test data collected in our case with Moodle learning management system (LMS). Particularly, we apply Class Association Rule (CAR) mining to different data matrices such as the score-matrix, the relationship-matrix and the knowledge-matrix. These matrices are constructed based on the data relate to students’ performance in the test and on the domain knowledge provided by the instructor. We describe how to obtain these matrices and then we have applied a CAR mining algorithm.
Original languageEnglish
Title of host publicationEducational Data Mining 2010 (3rd International Conference, Pittsburgh PA, USA, June 11-13, 2010. Proceedings)
EditorsR.S.J. Baker, de, A. Merceron, P.I. Pavlik Jr.
Publication statusPublished - 2010


Dive into the research topics of 'Class association rules mining from students’ test data (Abstract)'. Together they form a unique fingerprint.

Cite this