File Download
Supplementary

Conference Paper: Automated MOOC/SPOC Learning Design Verification based on Instructional Design Theories

TitleAutomated MOOC/SPOC Learning Design Verification based on Instructional Design Theories
Authors
KeywordsInstructional design
Verification
Visualization
MOOC
SPOC
Issue Date2019
PublisherSociety for Learning Analytics Research (SoLAR)
Citation
Companion Proceedings 9th International Conference on Learning Analytics & Knowledge (LAK19), Tempe, Arizona, USA, 4-8 March 2019, p. 656-665 How to Cite?
AbstractTeachers often work with course development teams to implement MOOCs and SPOCs. However, existing MOOC instructional quality analysis often requires manual effort and is not supported by instructional design theories. In this paper, we propose an automated MOOC/SPOC learning design verification mechanism based on instructional design theories. The mechanism can quickly visualize the courseware with faulty or at-risk designs that may cause obstacles for learners, which allows just-in-time revisions. The mechanism can facilitate the process of verifying the course design and assessing the quality of the course, and eventually minimize learning hurdles encountered by learners.
DescriptionLAK 19 Workshop - Extracting evidence in the context of MOOCs
Persistent Identifierhttp://hdl.handle.net/10722/276289

 

DC FieldValueLanguage
dc.contributor.authorLei, CU-
dc.contributor.authorHou, X-
dc.contributor.authorWang, J-
dc.contributor.authorGuo, Y-
dc.date.accessioned2019-09-10T02:59:54Z-
dc.date.available2019-09-10T02:59:54Z-
dc.date.issued2019-
dc.identifier.citationCompanion Proceedings 9th International Conference on Learning Analytics & Knowledge (LAK19), Tempe, Arizona, USA, 4-8 March 2019, p. 656-665-
dc.identifier.urihttp://hdl.handle.net/10722/276289-
dc.descriptionLAK 19 Workshop - Extracting evidence in the context of MOOCs-
dc.description.abstractTeachers often work with course development teams to implement MOOCs and SPOCs. However, existing MOOC instructional quality analysis often requires manual effort and is not supported by instructional design theories. In this paper, we propose an automated MOOC/SPOC learning design verification mechanism based on instructional design theories. The mechanism can quickly visualize the courseware with faulty or at-risk designs that may cause obstacles for learners, which allows just-in-time revisions. The mechanism can facilitate the process of verifying the course design and assessing the quality of the course, and eventually minimize learning hurdles encountered by learners.-
dc.languageeng-
dc.publisherSociety for Learning Analytics Research (SoLAR)-
dc.relation.ispartof9th International Conference on Learning Analytics & Knowledge (LAK19)-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectInstructional design-
dc.subjectVerification-
dc.subjectVisualization-
dc.subjectMOOC-
dc.subjectSPOC-
dc.titleAutomated MOOC/SPOC Learning Design Verification based on Instructional Design Theories-
dc.typeConference_Paper-
dc.identifier.emailLei, CU: culei@hku.hk-
dc.identifier.emailHou, X: hxiangyu@hku.hk-
dc.identifier.emailWang, J: wjq1015@hku.hk-
dc.identifier.emailGuo, Y: yxguo@hku.hk-
dc.identifier.authorityLei, CU=rp01908-
dc.description.naturepublished_or_final_version-
dc.identifier.hkuros303010-
dc.identifier.spage656-
dc.identifier.epage665-
dc.publisher.placeTempe, Arizona, USA-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats