PELÁNEK, Radek. Learning analytics challenges: trade-offs, methodology, scalability. Online. In Christoph Rensing, Hendrik Drachsler. Proceedings of the Tenth International Conference on Learning Analytics & Knowledge. New York, NY, United States: Association for Computing Machinery, 2020, p. 554-558. ISBN 978-1-4503-7712-6. Available from: https://dx.doi.org/10.1145/3375462.3375463.
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Basic information
Original name Learning analytics challenges: trade-offs, methodology, scalability
Authors PELÁNEK, Radek (203 Czech Republic, guarantor, belonging to the institution).
Edition New York, NY, United States, Proceedings of the Tenth International Conference on Learning Analytics & Knowledge, p. 554-558, 5 pp. 2020.
Publisher Association for Computing Machinery
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW URL
RIV identification code RIV/00216224:14330/20:00118360
Organization unit Faculty of Informatics
ISBN 978-1-4503-7712-6
Doi http://dx.doi.org/10.1145/3375462.3375463
UT WoS 000558753800069
Keywords in English trade-offs; scalability; methodology
Tags firank_B
Tags International impact, Reviewed
Changed by Changed by: doc. Mgr. Radek Pelánek, Ph.D., učo 4297. Changed: 10/9/2021 07:56.
Abstract
Ryan Baker presented in a LAK 2019 keynote a list of six grand challenges for learning analytics research. The challenges are specified as problems with clearly defined success criteria. Education is, however, a domain full of ill-defined problems. I argue that learning analytics research should reflect this nature of the education domain and focus on less clearly defined, but practically essential issues. As an illustration, I discuss three important challenges of this type: addressing inherent trade-offs in learning environments, the clarification of methodological issues, and the scalability of system development.
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