Educational Data Mining (EDM) is an emerging interdisciplinary research area that deals with the development of methods to explore data originating in an educational context. EDM uses different computational approaches to analyze educational data in order to study educational questions. Different data mining techniques has been applied in this area. One of the most widely used techniques in EDM...

Augmented Graph Grammars provide a robust formalism for representing and evaluating graph structures. With the advent of robust graph libraries such as AGG, it has become possible to use graph grammars to analyze realistic data. Prior studies have shown that graph rules can be used to evaluate student work and to identify empirically-valid substructures using hand-authored rules. In this paper ...

Data mining is about explaining the past and predicting the future by means of data analysis. Educational Data Mining is a promising discipline which has an imperative impact on predicting students’ academic performance. Thousands of students take admissions in Universities and colleges every year, at the time of admissions they collect the students’ data. In the same way while the Teachers joi...

It is important to study and analyse educational data especially students’ performance. Educational Data Mining (EDM) is the field of study concerned with mining educational data to find out interesting patterns and knowledge in educational organizations. This study is equally concerned with this subject, specifically, the students’ performance. This study explores multiple factors theoreticall...

Knowledge Discovery and Data Mining (KDD) is a multidisciplinary area focusing upon methodologies for extracting useful knowledge from data and there are several useful KDD tools to extracting the knowledge. This knowledge can be used to increase the quality of education. But educational institution does not use any knowledge discovery process approach on these data. Data mining can be used for...

The emerging fields of academic analytics and educational data mining are rapidly producing new possibilities for gathering, analyzing, and presenting student data. Faculty might soon be able to use these new data sources as guides for course redesign and as evidence for implementing new assessments and lines of communication between instructors and students. This essay links the concepts of ac...

The Educational Data Mining (EDM) community has experienced many benefits from the open sharing of data. Efforts such as the Pittsburgh Science of Learning Center Datashop have helped in the development of learning data storage and standards in the educational community. In other fields, standards of comparison have been created through publication, sharing, and competition on identical dataset...

Now-a-days the amount of data stored in educational database increasing rapidly. These databases contain hidden information for improvement of students’ performance. The performance in higher education in India is a turning point in the academics for all students. This academic performance is influenced by many factors, therefore it is essential to develop predictive data mining model for stude...