Cognitive styles and web-based instruction: field dependent/independent vs. Holist/Serialist

Authors:
Natalie Clewley;Sherry Y. Chen;Xiaohui Liu
Affiliations:
Department of Information Systems, Mathematics and Computing, Brunel University, Uxbridge, UK;Department of Information Systems, Mathematics and Computing, Brunel University, Uxbridge, UK;Department of Information Systems, Mathematics and Computing, Brunel University, Uxbridge, UK
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

Citing 8
Cited 1

C4.5: programs for machine learning

C4.5: programs for machine learning
User interface design: a structured approach

User interface design: a structured approach
The CN2 Induction Algorithm

Machine Learning
A flexible interface design for Web directories to accommodate different cognitive styles: Research Articles

Journal of the American Society for Information Science and Technology
Optimization-based feature selection with adaptive instance sampling

Computers and Operations Research
Combined mining of Web server logs and web contents for classifying user navigation patterns and predicting users' future requests

Data & Knowledge Engineering
An Integrated Approach for Modeling Learning Patterns of Students in Web-Based Instruction: A Cognitive Style Perspective

ACM Transactions on Computer-Human Interaction (TOCHI)
Web-Based Learning through Educational Informatics: Information Science Meets Educational Computing

Web-Based Learning through Educational Informatics: Information Science Meets Educational Computing

Design of adaptive hypermedia learning systems: A cognitive style approach

Computers & Education

Quantified Score

Hi-index	0.00

Visualization

Abstract

Evolutionary multiobjective optimization (EMO) is an active research area in the field of evolutionary computation. EMO algorithms are designed to find a non-dominated solution set that approximates the entire Pareto front of a multiobjective optimization ...