Decision tree algorithms in Educational Data Mining (EDM) emerges as a powerful method for student classification according to their learning station. This article emphasizes the necessity classify students due changing scenario of China's higher education system, which has shifted from elitist popularization, and lead university students' differences abilities. For specialty characteristics ed...

Despite space, time, and financial limitations, people who want to receive education participate intensively in online programs that have emerged with the development of technology. With Covid-19 outbreak, this interest has increased exponentially. In today's societies, where education, which is preferred for different reasons, become essential, examining factors affecting success learning a ve...

Educational data mining is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from the educational context. This work is a survey of the specific application of data mining in learning management systems and a case study tutorial with the Moodle system. Our objective is to introduce it both theoretically and practically to all users intere...

Data Mining Technique can be used in different fields to extract knowledge from large data. Data Mining is very useful in educational field to find important pattern from the data. The educational institutes are always insists on giving quality education. By using prediction method a model can be developed which can be used to predict students‘ performance. Prediction can be done by using stude...

Among other applications of educational data mining, evaluation of student models is essential for an adaptive educational system. This paper describes the evaluation of a Bayesian model of student misconceptions in the domain of decimals. The Bayesian model supports a remote adaptation service for an Intelligent Tutoring System within a project focused on adaptively presenting erroneous exampl...

Applying data mining (DM) in education is an emerging interdisciplinary research field also known as educational data mining (EDM). It is concerned with developing methods for exploring the unique types of data that come from educational environments. Its goal is to better understand how students learn and identify the settings in which they learn to improve educational outcomes and to gain ins...

Education and learning stand out among many application areas of cognitive computing due to their practical appeal as well as their research challenge. We can gauge the level of research challenge once we recognize the broad spectrum of human learning, the complex and not fully understood human learning process, and various influencing factors of learning, such as pedagogy, technology, and soci...

The application of educational data mining (EDM) techniques to interactive learning software is increasingly being used to broaden the range of constructs typically incorporated in student models, moving from traditional assessment of student knowledge to the assessment of engagement, affect, strategy, and metacognition. Researchers are also broadening the range of environments within which the...

This paper reports an application to educational intervention of Principal Stratification, a statistical method for estimating the effect of a treatment even when there are different rates of dropout in experimental and control conditions. We consider the potential value for using principal stratification to identify “Tough Love Interventions” – interventions that have a large effect but also i...