A Framework for course pathway recommendation system in nonformal E-learning Kavitha S.*, Khanaa V. Department of Faculty of Computer Applications, Aarupadai veedu Institute of Technology, Chennai, India Dean-IT, Bharat University, Chennai, India *Corresponding author: kavithasomu_99@yahoo.com
Online published on 16 May, 2016. Abstract Data Mining is the extraction of hidden predictive information from large database which can be used in various commercial applications like bioinformatics, E-commerce etc. Association Rule, classification and clustering are three different algorithms in data mining. Course Recommender System plays an important role in identifying the behavior of students interested in particular set of courses. We collect the data regarding the course enrollment for specific set of data. For collecting this data, we use the learning management system like Moodle. After collecting the data, we apply the different combination of data mining algorithm like classification & association rule algorithm, clustering & association rule algorithm, association rule mining in classified & clustered data, combining clustering & classification algorithm in association rule algorithms or simply the association rule algorithm. Here in this paper we use ADTree classification algorithm, Simple K-means Algorithm & Apriori Association Rule algorithm as different machine learning algorithm. So we propose the five different methods to find the best combination of algorithm in recommending the courses to students in E-learning. We compare the result of this combined approach as well as only the association rule algorithm & present the best combination of algorithm for recommendation of courses in E-learning according to our simulation. Top Keywords Weka, Machine Learning Algorithm, Simple K-meansAlgorithm, ADTree Classification Algorithm, Apriori Association Rule Algorithm, Moodle. Top |