Discovering Prediction Rules in AHA! Courses
نویسندگان
چکیده
In this paper we are going to show how to discover interesting prediction rules in student usage information, and use them to improve adaptive web courses. We have used AHA! to make a course that adapts both the presentation and the navigation depending on the level of knowledge that each particular student has. We have made several changes in AHA! to improve its power in the educational area. We use the logging information from AHA! to discover relations in the usage data (reading times, difficulty levels and test results). The most interesting relations are shown to the teacher so that he can carry out the appropriated modifications in the course to improve it.
منابع مشابه
Rule mining with GBGP to improve web-based adaptive educational systems
In this chapter we describe how to discover interesting relationships from student’s 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 use data mining methods for providing feedback to courseware authors. The discovered information is pr...
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