License to evaluate: Preparing learning analytics dashboards for educational practice

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Abstract

Learning analytics can bridge the gap between learning sciences and data analytics, leveraging the expertise of both fields in exploring the vast amount of data generated in online learning environments. A typical learning analytics intervention is the learning dashboard, a visualisation tool built with the purpose of empowering teachers and learners to make informed decisions about the learning process. Related work has investigated learning dashboards, yet none have explored the theoretical foundation that should inform the design and evaluation of such interventions. In this systematic literature review, we analyse the extent to which theories and models from learning sciences have been integrated into the development of learning dashboards aimed at learners. Our analysis revealed that very few dashboard evaluations take into account the educational concepts that were used as a theoretical foundation for their design. Furthermore, we report findings suggesting that comparison with peers, a common reference frame for contextualising information on learning analytics dashboards, was not perceived positively by all learners. We summarise the insights gathered through our literature review in a set of recommendations for the design and evaluation of learning analytics dashboards for learners.
Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Learning Analytics and Knowledge
Subtitle of host publication(LAK '18)
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages32-40
ISBN (Print)978-1-4503-6400-3
DOIs
Publication statusPublished - 1 Mar 2018
EventInternational Conference on Learning Analytics and Knowledge - Sydney, Australia
Duration: 7 Mar 20189 Mar 2018
https://latte-analytics.sydney.edu.au/

Conference

ConferenceInternational Conference on Learning Analytics and Knowledge
CountryAustralia
CitySydney
Period7/03/189/03/18
Internet address

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Keywords

  • learning dashboards
  • learning theory
  • learning analytics
  • systematic review
  • learning science
  • social comparison
  • evaluation

Cite this

Jivet, I., Scheffel, M., Specht, M., & Drachsler, H. (2018). License to evaluate: Preparing learning analytics dashboards for educational practice. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge : (LAK '18) (pp. 32-40). New York: Association for Computing Machinery (ACM). https://doi.org/10.1145/3170358.3170421
Jivet, Ioana ; Scheffel, Maren ; Specht, Marcus ; Drachsler, Hendrik. / License to evaluate: Preparing learning analytics dashboards for educational practice. Proceedings of the 8th International Conference on Learning Analytics and Knowledge : (LAK '18). New York : Association for Computing Machinery (ACM), 2018. pp. 32-40
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Jivet, I, Scheffel, M, Specht, M & Drachsler, H 2018, License to evaluate: Preparing learning analytics dashboards for educational practice. in Proceedings of the 8th International Conference on Learning Analytics and Knowledge : (LAK '18). Association for Computing Machinery (ACM), New York, pp. 32-40, International Conference on Learning Analytics and Knowledge, Sydney, Australia, 7/03/18. https://doi.org/10.1145/3170358.3170421

License to evaluate: Preparing learning analytics dashboards for educational practice. / Jivet, Ioana; Scheffel, Maren; Specht, Marcus; Drachsler, Hendrik.

Proceedings of the 8th International Conference on Learning Analytics and Knowledge : (LAK '18). New York : Association for Computing Machinery (ACM), 2018. p. 32-40.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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Jivet I, Scheffel M, Specht M, Drachsler H. License to evaluate: Preparing learning analytics dashboards for educational practice. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge : (LAK '18). New York: Association for Computing Machinery (ACM). 2018. p. 32-40 https://doi.org/10.1145/3170358.3170421