Drawbacks and solutions of applying association （缺点和解决方案应用协会）.pdf

Drawbacks and solutions of applying association rule mining in learning management systems 1 1 1 2 Enrique García , Cristóbal Romero , Sebastián Ventura , Toon Calders 1Córdoba University, Campus Universitario de Rabanales, 14071, Córdoba, Spain {egsalcines,cromero,sventura}@uco.es 2Eindhoven University of Technology (TU/e), PO Box 513, Eindhoven, The Netherlands toon.calders@ua.ac.be Abstract. In this paper, we survey the application of association rule mining in e-learning systems, and especially, learning management systems. We describe the specific knowledge discovery process, its mains drawbacks and some possible solutions to resolve them. 1 Introduction Nowadays, Learning Management Systems (LMS) are being installed more and more by universities, community colleges, schools, businesses, and even individual instructors in order to add web technology to their courses and to supplement traditional face-to-face courses [1]. LMS systems accumulate a vast amount of information which is very valuable for analyzing the students’ behavior and could create a gold mine of educational data [2]. They can record whatever student activities it involves, such as reading, writing, taking tests, performing various tasks, and even communicating with peers. However, due to the vast quantities of data these systems can generate daily, it is very difficult to analyze this data manually. A very promising approach towards this analysis objective is the use of data mining techniques. Data mining or knowledge discovery in databases (KDD) is the automatic extraction o