An Adaptive Bayesian Student Model for Discovering the Student’s Learning Style and Preferences

2010 ◽  
pp. 515-526
Keyword(s):  
Learning Style ◽  
Student Model

Evolutionary Approach for Automatic and Dynamic Modeling of Students' Learning Styles

2015 ◽  
pp. 261-284
Author(s):  
Fabiano Azevedo Dorça
Keyword(s):  
Computer Simulation ◽  
Evolutionary Algorithms ◽  
Learning Styles ◽  
Learning Style ◽  
Learning Process ◽  
Individual Student ◽  
Educational Systems ◽  
Student Model ◽  
Student’S Performance ◽  
Adaptive Educational Systems

Most of the distance educational systems consider only little, or no, adaptivity. Personalization according to specific requirements of an individual student is one of the most important features in adaptive educational systems. Considering learning and how to improve a student's performance, these systems must know the way in which an individual student learns best. In this context, this chapter depicts an application of evolutionary algorithms to discover students' learning styles. The approach is mainly based on the non-deterministic and non-stationary aspects of learning styles, which may change during the learning process in an unexpected and unpredictable way. Because of the stochastic and dynamic aspects enclosed in learning process, it is important to gradually and constantly update the student model. In this way, the student model stochastically evolves towards the real student's learning style, considering its fine-tuned strengths. This approach has been tested through computer simulation of students, and promising results have been obtained. Some of them are presented in this chapter.

Research on Student Model of Adaptive Learning System Based on Semantic Web

2013 ◽  
Vol 739 ◽  
pp. 562-565
Author(s):  
Jian Qiong Xiao
Keyword(s):  
Semantic Web ◽  
Learning Style ◽  
Adaptive Learning ◽  
Learning System ◽  
Cognitive State ◽  
Student Model ◽  
Four Dimensions ◽  
Student Models ◽  
Adaptive Learning System ◽  
State Learning

This paper came up with introducing four dimensions: learning mood, cognitive state, learning style and interest preference and so on for the semantic web, based on the analysis the present situation student models at home and abroad. Realized to classify learners and establish student models which used an improved similarity algorithm, and the student model applied to adaptive learning system, which not only could solve the lack semantic in adaptive learning system, and greatly improves the practicability, intelligent and personalized.

An Investigation of Learning Style and Discipline in a Human Factors Course

2011 ◽  
Author(s):  
Mark C. Schall ◽  
Michelle L. Rusch ◽  
Geb Thomas ◽  
John D. Lee
Keyword(s):  
Human Factors ◽  
Learning Style

Effect of Learning Style Interventions on Course Satisfaction

2006 ◽  
Author(s):  
Laura S. Testerman ◽  
Nichole C. Hardy ◽  
Matthew T. Tatum ◽  
Holly M. Irwin-Chase ◽  
Jim Johnson
Keyword(s):  
Learning Style ◽  
Course Satisfaction

Reliability and Validity of the VARK: A Learning Style Assessment

2006 ◽  
Author(s):  
Matthew T. Tatum ◽  
Nichole C. Hardy ◽  
Laura S. Testerman ◽  
Holly M. Irwin-Chase ◽  
John T. Wu
Keyword(s):  
Learning Style ◽  
Reliability And Validity

Maybe they’re born with it, or maybe it’s experience: Toward a deeper understanding of the learning style myth.

2020 ◽  
Vol 112 (2) ◽  
pp. 221-235 ◽  
Author(s):  
Shaylene E. Nancekivell ◽  
Priti Shah ◽  
Susan A. Gelman
Keyword(s):  
Learning Style
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