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Conference Paper: Leveraging Modern Psychometrics and Technology to Facilitate Instruction and Learning
Title | Leveraging Modern Psychometrics and Technology to Facilitate Instruction and Learning |
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Authors | |
Issue Date | 2020 |
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? |
Abstract | Many 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. |
Description | Invited 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 Identifier | http://hdl.handle.net/10722/312536 |
DC Field | Value | Language |
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dc.contributor.author | de la Torre, J | - |
dc.date.accessioned | 2022-04-27T07:53:46Z | - |
dc.date.available | 2022-04-27T07:53:46Z | - |
dc.date.issued | 2020 | - |
dc.identifier.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 | - |
dc.identifier.uri | http://hdl.handle.net/10722/312536 | - |
dc.description | Invited presentation - Parallel Session 1 分題研討(一)Using Assessment Technology to Inform Learning | - |
dc.description | Organiser: Hong Kong Examinations and Assessment Authority (香港考試及評核局) ;Co-organiser: Education Bureau | - |
dc.description.abstract | Many 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.language | eng | - |
dc.relation.ispartof | Hong Kong Examination and Assessment Authority (HKEAA) Second Research Forum | - |
dc.title | Leveraging Modern Psychometrics and Technology to Facilitate Instruction and Learning | - |
dc.type | Conference_Paper | - |
dc.identifier.email | de la Torre, J: j.delatorre@hku.hk | - |
dc.identifier.authority | de la Torre, J=rp02159 | - |
dc.identifier.hkuros | 328206 | - |
dc.publisher.place | Hong Kong | - |