Relationship between brain-based learning styles and behavioural learning patterns in web-based educational systems

Mohammed Ahmed Ghazal, Nor Azan Mat Zin, Zurina Muda

Research output: Contribution to journalArticle

Abstract

Web-Based Educational Systems (WBESs) deliver the same design features such as learning content and user interface to all learners. However, learners have different preferences according to their brain structures. The brain dominance determines how learners prefer to learn, communicate, collaborate and solve problems effectively. Tracking learners’ behaviours within the WBES is an essential approach to predict the learners’ Learning Styles. Therefore, the relationship between learners’ behavioural interactions in WBES and Learning Styles should be examined. This study investigated the learning patterns of 69 respondents within WBES with respect to Herrmann Whole Brain Model (HWBM) Learning Style. Results showed that there is a significant correlation between some learning patterns and HWBM Learning Styles. The most preferred features for designing WBES according to Learning Style model were also identified. The results can be used for developing an adaptive learner model.

Original languageEnglish
Pages (from-to)262-277
Number of pages16
JournalJournal of Theoretical and Applied Information Technology
Volume78
Issue number2
Publication statusPublished - 20 Aug 2015

Fingerprint

Brain models
Learning Styles
Web-based
Brain
User interfaces
Model
User Interface
Relationships
Learning
Education
Predict
Interaction

Keywords

  • Behavioural learning patterns
  • Design features of web-based educational system (WBES)
  • Herrmann whole brain model learning style (HWBM LS)
  • Learner modelling
  • Systematic observation study

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

@article{04fdeee6965149fb8cd8b706c37b6e5f,
title = "Relationship between brain-based learning styles and behavioural learning patterns in web-based educational systems",
abstract = "Web-Based Educational Systems (WBESs) deliver the same design features such as learning content and user interface to all learners. However, learners have different preferences according to their brain structures. The brain dominance determines how learners prefer to learn, communicate, collaborate and solve problems effectively. Tracking learners’ behaviours within the WBES is an essential approach to predict the learners’ Learning Styles. Therefore, the relationship between learners’ behavioural interactions in WBES and Learning Styles should be examined. This study investigated the learning patterns of 69 respondents within WBES with respect to Herrmann Whole Brain Model (HWBM) Learning Style. Results showed that there is a significant correlation between some learning patterns and HWBM Learning Styles. The most preferred features for designing WBES according to Learning Style model were also identified. The results can be used for developing an adaptive learner model.",
keywords = "Behavioural learning patterns, Design features of web-based educational system (WBES), Herrmann whole brain model learning style (HWBM LS), Learner modelling, Systematic observation study",
author = "Ghazal, {Mohammed Ahmed} and {Mat Zin}, {Nor Azan} and Zurina Muda",
year = "2015",
month = "8",
day = "20",
language = "English",
volume = "78",
pages = "262--277",
journal = "Journal of Theoretical and Applied Information Technology",
issn = "1992-8645",
publisher = "Asian Research Publishing Network (ARPN)",
number = "2",

}

TY - JOUR

T1 - Relationship between brain-based learning styles and behavioural learning patterns in web-based educational systems

AU - Ghazal, Mohammed Ahmed

AU - Mat Zin, Nor Azan

AU - Muda, Zurina

PY - 2015/8/20

Y1 - 2015/8/20

N2 - Web-Based Educational Systems (WBESs) deliver the same design features such as learning content and user interface to all learners. However, learners have different preferences according to their brain structures. The brain dominance determines how learners prefer to learn, communicate, collaborate and solve problems effectively. Tracking learners’ behaviours within the WBES is an essential approach to predict the learners’ Learning Styles. Therefore, the relationship between learners’ behavioural interactions in WBES and Learning Styles should be examined. This study investigated the learning patterns of 69 respondents within WBES with respect to Herrmann Whole Brain Model (HWBM) Learning Style. Results showed that there is a significant correlation between some learning patterns and HWBM Learning Styles. The most preferred features for designing WBES according to Learning Style model were also identified. The results can be used for developing an adaptive learner model.

AB - Web-Based Educational Systems (WBESs) deliver the same design features such as learning content and user interface to all learners. However, learners have different preferences according to their brain structures. The brain dominance determines how learners prefer to learn, communicate, collaborate and solve problems effectively. Tracking learners’ behaviours within the WBES is an essential approach to predict the learners’ Learning Styles. Therefore, the relationship between learners’ behavioural interactions in WBES and Learning Styles should be examined. This study investigated the learning patterns of 69 respondents within WBES with respect to Herrmann Whole Brain Model (HWBM) Learning Style. Results showed that there is a significant correlation between some learning patterns and HWBM Learning Styles. The most preferred features for designing WBES according to Learning Style model were also identified. The results can be used for developing an adaptive learner model.

KW - Behavioural learning patterns

KW - Design features of web-based educational system (WBES)

KW - Herrmann whole brain model learning style (HWBM LS)

KW - Learner modelling

KW - Systematic observation study

UR - http://www.scopus.com/inward/record.url?scp=84939552951&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84939552951&partnerID=8YFLogxK

M3 - Article

VL - 78

SP - 262

EP - 277

JO - Journal of Theoretical and Applied Information Technology

JF - Journal of Theoretical and Applied Information Technology

SN - 1992-8645

IS - 2

ER -