File Download

There are no files associated with this item.

Supplementary

Conference Paper: Leveraging Modern Psychometrics and Technology to Facilitate Instruction and Learning

TitleLeveraging Modern Psychometrics and Technology to Facilitate Instruction and Learning
Authors
Issue Date2020
Citation
The Hong Kong Examinations and Assessment Authority (HKEAA) 2nd Research Forum: Opportunities and Challenges in Assessment in the Digital Era, Hong Kong, 12 November 2020 How to Cite?
AbstractMany educational researchers and practitioners are interested in using educational assessment to improve student learning. However, as two distinct components, assessment and learning need to be integrated before the former can be used to inform the latter. In this presentation, I will discuss cognitive diagnosis modeling as a coherent framework for integrating assessment and learning.Specifically, I will introduce cognitive diagnosis models (CDMs), discuss their unique features, and highlight how they differ from traditional psychometric models. In addition to assessment,instructional materials based on the same framework are needed to facilitate learning. By leveraging technology, computerized adaptive testing and ancillary information can be used to further capitalize on the advantages of CDMs and make diagnostic testing more efficient. Similarly, technology can also be leveraged to determine the extent to which different instructional materials can be tailored to optimize learning. The presentation will conclude with a discussion of some of the challenges, recent developments, and possible future directions in the area.
DescriptionInvited presentation - Parallel Session 1 分題研討(一)Using Assessment Technology to Inform Learning
Organiser: Hong Kong Examinations and Assessment Authority (香港考試及評核局) ;Co-organiser: Education Bureau
Persistent Identifierhttp://hdl.handle.net/10722/312536

 

DC FieldValueLanguage
dc.contributor.authorde la Torre, J-
dc.date.accessioned2022-04-27T07:53:46Z-
dc.date.available2022-04-27T07:53:46Z-
dc.date.issued2020-
dc.identifier.citationThe Hong Kong Examinations and Assessment Authority (HKEAA) 2nd Research Forum: Opportunities and Challenges in Assessment in the Digital Era, Hong Kong, 12 November 2020-
dc.identifier.urihttp://hdl.handle.net/10722/312536-
dc.descriptionInvited presentation - Parallel Session 1 分題研討(一)Using Assessment Technology to Inform Learning-
dc.descriptionOrganiser: Hong Kong Examinations and Assessment Authority (香港考試及評核局) ;Co-organiser: Education Bureau-
dc.description.abstractMany educational researchers and practitioners are interested in using educational assessment to improve student learning. However, as two distinct components, assessment and learning need to be integrated before the former can be used to inform the latter. In this presentation, I will discuss cognitive diagnosis modeling as a coherent framework for integrating assessment and learning.Specifically, I will introduce cognitive diagnosis models (CDMs), discuss their unique features, and highlight how they differ from traditional psychometric models. In addition to assessment,instructional materials based on the same framework are needed to facilitate learning. By leveraging technology, computerized adaptive testing and ancillary information can be used to further capitalize on the advantages of CDMs and make diagnostic testing more efficient. Similarly, technology can also be leveraged to determine the extent to which different instructional materials can be tailored to optimize learning. The presentation will conclude with a discussion of some of the challenges, recent developments, and possible future directions in the area.-
dc.languageeng-
dc.relation.ispartofHong Kong Examination and Assessment Authority (HKEAA) Second Research Forum-
dc.titleLeveraging Modern Psychometrics and Technology to Facilitate Instruction and Learning-
dc.typeConference_Paper-
dc.identifier.emailde la Torre, J: j.delatorre@hku.hk-
dc.identifier.authorityde la Torre, J=rp02159-
dc.identifier.hkuros328206-
dc.publisher.placeHong Kong-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats