Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/9446
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dc.contributor.authorDr. LI Wang On, Alexen_US
dc.contributor.authorSpinks, John A.en_US
dc.date.accessioned2024-04-15T08:09:09Z-
dc.date.available2024-04-15T08:09:09Z-
dc.date.issued2004-
dc.identifier.citationInternational Journal of Psychology, 2004, vol. 39(5-6), pp. 249.en_US
dc.identifier.issn1464-066X-
dc.identifier.issn0020-7594-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/9446-
dc.description.abstractKnowledge structure represents understanding of the world; studying it constitutes grounds for understanding learning. Multidimensional scaling has been used in previous research studies on revealing the characteristics of knowledge structure. This study examined how multidimensional scaling and property vector fitting can be used to reveal longitudinal qualitative changes in knowledge structures. Learners' knowledge structures appear to converge to a common structure as their learning experience grows. This study provides methods for statistically describing qualitative information about the evolution of knowledge structures during learning - something that has been elusive in previous research.en_US
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Psychologyen_US
dc.titleThe statistical assessment of learning outcome: Knowledge structureen_US
dc.typePeer Reviewed Journal Articleen_US
dc.identifier.doihttps://doi.org/10.1080/00207594.2004.20040811-
item.fulltextNo Fulltext-
crisitem.author.deptUniversity Management-
Appears in Collections:Counselling and Psychology - Publication
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