Discovering prediction rules in AHA! courses

Authors:
Cristóbal Romero;Sebastián Ventura;Paul de Bra;Carlos de Castro
Affiliations:
University of Córdoba, Campus Universitario de Rabanales, Córdoba, España;University of Córdoba, Campus Universitario de Rabanales, Córdoba, España;Eindhoven University of Technology, Eindhoven, The Netherlands;University of Córdoba, Campus Universitario de Rabanales, Córdoba, España
Venue:
UM'03 Proceedings of the 9th international conference on User modeling
Year:
2003

Citing 3
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Abstract

In this paper we are going to show how to discover interesting prediction rules from student usage information to improve adaptive web courses. We have used AHA! to make courses that adapt both the presentation and the navigation depending on the level of knowledge that each particular student has. We have performed several modifications in AHA! to specialize it and power it in the educational area. Our objective is to discover relations between all the picked-up usage data (reading times, difficulty levels and test results) from student executions and show the most interesting to the teacher so that he can carry out the appropriate modifications in the course to improve it.