E-learning is related to virtualised distance learning by means of electronic communication mechanisms, using its functionality as a support in the process of teaching-learning. When the learning process becomes computerised, educational data mining employs the information generated from the electronic sources to enrich the learning model for academic purposes. To provide support to e-learning ...

-------------------------------------------------------------------ABSTRACT------------------------------------------------------------Over the past decade there has been a rapid growth in higher education system. A lot of new institutions have come up both from public and private sector offering variety of courses for under graduating and post graduating students. The rates of enrolments for h...

-Data Mining is a powerful tool for academic intervention. Mining in education environment is called Educational Data Mining. Educational Data Mining is concerned with developing new methods to discover knowledge from educational database and can used for decision making in educational system. In our work, we collected the student’s data from engineering institute that have different informatio...

This paper aims to provide the reader with a comprehensive background for understanding current knowledge on Learning Analytics (LA) and Educational Data Mining (EDM) and its impact on adaptive learning. It constitutes an overview of empirical evidence behind key objectives of the potential adoption of LA/EDM in generic educational strategic planning. We examined the literature on experimental ...

The paper deals with the correlation analysis as educational data technique that is easy to interpret and simple to implement. Two datasets respectively from environment for knowledge testing and for exercise tasks modelling testing are gathered. Programming of tasks for test parameters relationships, test reliability, cheat recognition, and test validation in a specialized postprocessor tool i...

ICT-enhanced research methods such as educational data mining (EDM) have allowed researchers to effectively model a broad range of constructs pertaining to the student, moving from traditional assessments of knowledge to assessment of engagement, meta-cognition, strategy, and affect. The automated detection of these constructs allows EDM researchers to develop intervention strategies that can b...

Educational data mining and knowledge engineering methods have led to increasingly precise models of students’ knowledge as they use intelligent tutoring systems. The first stage in this progression was the development of Bayes Nets and Bayesian frameworks that could infer the probability that a student knew a specific skill at a specific time from their pattern of correct responses and non-cor...

This study examined the effectiveness of an educational data mining method – Learning Factors Analysis (LFA) – on improving the learning efficiency in the Cognitive Tutor curriculum. LFA uses a statistical model to predict how students perform in each practice of a knowledge component (KC), and identifies over-practiced or under-practiced KCs. By using the LFA findings on the Cognitive Tutor ge...

Predicting student performance (PSP), one of the task in Student Modeling, has been taken into account by educational data mining community recently. Previous works show that good results can be achieved by casting the PSP to rating prediction task in recommender systems, where students, tasks and performance scores are mapped to users, items and ratings respectively, and thus, matrix factoriza...

Educational games have the potential to be innovative methods of assessing learning. This research combines video analysis and educational data mining to measure the implicit science learning that takes place in games. By studying the video data from high school learners playtesting the game Impulse, we observed strategic moves that are consistent with an implicit understanding of relevant scie...