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Knowledge-based design analytics for authoring courses with smart learning content

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dc.contributor.author Albó, Laia
dc.contributor.author Barria-Pineda, Jordan
dc.contributor.author Brusilovsky, Peter
dc.contributor.author Hernández Leo, Davinia
dc.date.accessioned 2021-05-26T07:26:21Z
dc.date.issued 2022
dc.identifier.citation Albó L, Barria-Pineda J, Brusilovsky P, Hernández-Leo D. Knowledge-based design analytics for authoring courses with smart learning content. Int J Artif Intell Educ. 2022;32(1):4-27. DOI: 10.1007/s40593-021-00253-3
dc.identifier.issn 1560-4292
dc.identifier.uri http://hdl.handle.net/10230/47654
dc.description.abstract Over the last 10 years, learning analytics have provided educators with both dashboards and tools to understand student behaviors within specific technological environments. However, there is a lack of work to support educators in making data-informed design decisions when designing a blended course and planning appropriate learning activities. In this paper, we introduce knowledge-based design analytics that uncover facets of the learning activities that are being created. A knowledge-based visualization is integrated into edCrumble, a (blended) learning design authoring tool. This new approach is explored in the context of a higher education programming course, where instructors design labs and home practice sessions with online smart learning content on a weekly basis. We performed a within-subjects user study to compare the use of the design tool both with and without visualization. We studied the differences in terms of cognitive load, controllability, confidence and ease of choice, design outcomes, and user actions within the system to compare both conditions with the objective of evaluating the impact of using design analytics during the decision-making phase of course design. Our results indicate that the use of a knowledge-based visualization allows the teachers to reduce the cognitive load (especially in terms of mental demand) and that it facilitates the choice of the most appropriate activities without affecting the overall design time. In conclusion, the use of knowledge-based design analytics improves the overall learning design quality and helps teachers avoid committing design errors.
dc.description.sponsorship This work is a result of a collaboration within a mobility grant for research funded by the SEBAP, Societat Econòmica Barcelonesa d’Amics del País. This work has also been partially funded by NSF DRL 1740775, “la Caixa Foundation” (CoT project, 100010434) and FEDER, the National Research Agency of the Spanish Ministry of Science, Innovations and Universities MDM-2015-0502, TIN2014-53199-C3-3-R, TIN2017-85179-C3-3-R. D. Hernández-Leo acknowledges the support by ICREA under the ICREA Academia programme.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer
dc.relation.ispartof International Journal of Artificial Intelligence in Education. 2022;32(1):4-27.
dc.rights © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/s40593-021-00253-3
dc.title Knowledge-based design analytics for authoring courses with smart learning content
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1007/s40593-021-00253-3
dc.subject.keyword Design Analytics
dc.subject.keyword Blended Learning
dc.subject.keyword Concept-level visualization
dc.subject.keyword Knowledge-based analytics
dc.subject.keyword Authoring tool
dc.subject.keyword Learning Design
dc.subject.keyword Smart Learning Content
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2014-53199-C3-3-R
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/TIN2017-85179-C3-3-R
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion


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