Educational data mining and learning analytics for 21st century higher education: A review and synthesis
The potential influence of data mining analytics on the students' learning processes and
outcomes has been realized in higher education. Hence, a comprehensive review of …
outcomes has been realized in higher education. Hence, a comprehensive review of …
Educational data mining: a review of the state of the art
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 …
with the development of methods to explore data originating in an educational context. EDM …
Participation-based student final performance prediction model through interpretable Genetic Programming: Integrating learning analytics, educational data mining …
Building a student performance prediction model that is both practical and understandable
for users is a challenging task fraught with confounding factors to collect and measure. Most …
for users is a challenging task fraught with confounding factors to collect and measure. Most …
Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques
R Pelánek - User modeling and user-adapted interaction, 2017 - Springer
Learner modeling is a basis of personalized, adaptive learning. The research literature
provides a wide range of modeling approaches, but it does not provide guidance for …
provides a wide range of modeling approaches, but it does not provide guidance for …
Performance factors analysis–a new alternative to knowledge tracing
PI Pavlik, H Cen, KR Koedinger - Artificial intelligence in …, 2009 - ebooks.iospress.nl
Abstract Knowledge tracing (KT)[1] has been used in various forms for adaptive
computerized instruction for more than 40 years. However, despite its long history of …
computerized instruction for more than 40 years. However, despite its long history of …
Fuzzy cognitive diagnosis for modelling examinee performance
Recent decades have witnessed the rapid growth of educational data mining (EDM), which
aims at automatically extracting valuable information from large repositories of data …
aims at automatically extracting valuable information from large repositories of data …
Comparing knowledge tracing and performance factor analysis by using multiple model fitting procedures
Student modeling is very important for ITS due to its ability to make inferences about latent
student attributes. Although knowledge tracing (KT) is a well-established technique, the …
student attributes. Although knowledge tracing (KT) is a well-established technique, the …
[PDF][PDF] Cognitive modelling for predicting examinee performance
Cognitive modelling can discover the latent characteristics of examinees for predicting their
performance (ie scores) on each problem. As cognitive modelling is important for numerous …
performance (ie scores) on each problem. As cognitive modelling is important for numerous …
Predicting students' GPA and developing intervention strategies based on self-regulatory learning behaviors
Predicting students' grades has emerged as a major area of investigation in education due
to the desire to identify the underlying factors that influence academic performance. Because …
to the desire to identify the underlying factors that influence academic performance. Because …
Learning styles assessment and theoretical origin in an E-learning scenario: a survey
L Jegatha Deborah, R Baskaran, A Kannan - Artificial Intelligence Review, 2014 - Springer
The performance of the learners in E-learning environments is greatly influenced by the
nature of the posted E-learning contents. In such a scenario, the performance of the learners …
nature of the posted E-learning contents. In such a scenario, the performance of the learners …