Domain ontology and Hermann Brain Dominance Instrument model for personalized e-learning hypermedia system
Abstract
A number of adaptive e-learning hypermedia systems (AEHS) have been developed to support learning styles as a source for adaptation. However, these systems suffer from several problems, namely: lack of maintenance adaptation to learning style, less attention was paid to thinking styles and the insertion of specific teaching strategies into learning content. This paper proposes an AEHS model based on thinking styles and domain ontology. The experiment was completed in three phases for both experimental and control groups. In the first phase all the students were informed that they will participate in an experimental process. The students received a short introduction on how to use the system and to create a user account for login purposes into the system. Then, information about thinking styles categories were given to the experimental group and were asked to complete the questionnaire. In the second phase, the students followed regularly the lessons until the completion of the course; meanwhile taking a quiz at the end of each lesson. In the third phase, learners followed a link to do the post-test.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
An initial assessment of user preferences can serve as a ground for content adaptation.
“For example, an initial assessment of user preferences can serve as a ground for content adaptation [165,181].”
From Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis (2024) · cites this paper as [165]
Cites
W2 - Adaptive and Intelligent Web-Based Education Systems
Peylo, C. (2000) · Lecture notes in computer science · doi:10.1007/3-540-45108-0_86 · Cited by 627 · see citing works
Shute, V. J., & Towle, B. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3802_5 · Cited by 267 · see citing works
Herrmann, N. (1996) · Medical Entomology and Zoology · Cited by 259 · see citing works
Cano, F., & Hughes, E. C. H. (2000) · Educational Psychology · doi:10.1080/713663755 · Cited by 241 · see citing works
Adaptive Hypermedia: From Intelligent Tutoring Systems to Web-Based Education
Brusilovsky, P. L. (2000) · Lecture notes in computer science · doi:10.1007/3-540-45108-0_1 · Cited by 158 · see citing works
Mustafa, Y. E. A., & Sharif, S. M. (2011) · INTERNATIONAL JOURNAL OF LIBRARY AND INFORMATION SCIENCE · doi:10.5897/ijlis.9000009 · Cited by 118 · see citing works
Harrison, A. F. (1987) · Cited by 114 · see citing works
Student modelling in adaptive e-learning systems
Esichaikul, V., Lamnoi, S., & Bechter, C. (2011) · Knowledge Management & E-Learning An International Journal · doi:10.34105/j.kmel.2011.03.025 · Cited by 107 · see citing works
Adaptive E-learning Content Design and Delivery Based on Learning Styles and Knowledge Level
Vassileva, D. (2012) · Serdica Journal of Computing · doi:10.55630/sjc.2012.6.207-252 · Cited by 33 · see citing works
E-learning: Current State of Art and Future Prospects
Goyal, M., Yadav, D., & Choubey, A. (2012) · Cited by 28 · see citing works
JORDANIAN STUDENTS' THINKING STYLES BASED ON HERRMANN WHOLE BRAIN MODEL
Bawaneh, A. K. A., Abdullah, A. G. K., Saleh, S., et al. (2011) · Cited by 23 · see citing works
Bawaneh, A. K. A., Zain, A. N. M., & Saleh, S. (2011) · European Journal Of Physics Education · doi:10.20308/ejpe.62987 · Cited by 17 · see citing works
Thinking About Thinking: Problem Solving Style In The Engineering Classroom
Jablokow, K. (2020) · doi:10.18260/1-2--8773 · Cited by 16 · see citing works
An Adaptive Hypermedia System Integrating Thinking Style (AHS-TS) Model and Experiment
Lamia, M., Laskri, M. T., & Trigano, P. (2012) · HAL · doi:10.14257/ijhit.2012.5.1.02 · Cited by 16 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Halkiopoulos, C., & Gkintoni, E. (2024) · Electronics · doi:10.3390/electronics13183762 · Cited by 328 · see citing works
“Lamia and Laskri (2012) [165] - Propose an AEHS model based on thinking styles and domain ontology.”
- Authors
- Lamia, M., & Tayeb, L. M.
- Affiliations
- Badji Mokhtar-Annaba University (DZ)
- LRI Laboratory, University of Badji Moktar, Annaba, Algeria
- ORCID
- Lamia, Mahnane
- Venue
- International Journal of Web-Based Learning and Teaching Technologies
- Publisher
- IGI Global Scientific Publishing
- Published
- 2012-10-01
- Volume
- 7
- Issue
- 4
- Pages
- 1-12
- ISSN
- 1548-1093 (ISSN-L)
- 1548-1107
- OpenAlex
- W2056734582
- Cited by
- 3
- References
- 14
- Citations by year
- 2024: 1 · 2016: 1 · 2015: 1
- FWCI
- 0.64
- Type
- journal article
- Language
- ng
- Open access
- closed
- Locations
- International Journal of Web-Based Learning and Teaching Technologies (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Learning Styles and Cognitive Differences
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Information Systems › Educational Technology and Assessment
- Keywords
- thinking styles, domain ontology, personalized learning, learning styles, adaptive hypermedia, teaching methods
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
