An efficient educational data mining approach to support e-learning

The e-learning is a recent development that has emerged in the educational system due to the growth of the information technology. The common challenges involved in The e-learning platform include the collection and annotation of the learning materials, organization of the knowledge in a useful way, the retrieval and discovery of the useful learning materials from the knowledge space in a more significant way, and the delivery of the adaptive and personalized learning materials. In order to handle these challenges, the proposed system is developed using five different steps of knowledge input such as the annotation of the learning materials, creation of knowledge space, indexing of learning materials using the multi-dimensional knowledge and XML structure to generate a knowledge grid and the retrieval of learning materials performed by matching the user query with the indexed database and ontology. The process is carried out in two modules such as the server module and client module. The proposed approach is evaluated using various parameters such as the precision, recall and F-measure. Comprehensive results are achieved by varying the keywords, number of documents and the K-size. The proposed approach has yielded excellent results by obtaining the higher evaluation metric, together with an average precision of 0.81, average recall of 1 and average F-measure of 0.86 for K = 2.