Learning analytics challenges: trade-offs, methodology, scalability
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00118360" target="_blank" >RIV/00216224:14330/20:00118360 - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/doi/10.1145/3375462.3375463" target="_blank" >https://dl.acm.org/doi/10.1145/3375462.3375463</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3375462.3375463" target="_blank" >10.1145/3375462.3375463</a>
Alternative languages
Result language
angličtina
Original language name
Learning analytics challenges: trade-offs, methodology, scalability
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Tenth International Conference on Learning Analytics & Knowledge
ISBN
9781450377126
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
554-558
Publisher name
Association for Computing Machinery
Place of publication
New York, NY, United States
Event location
New York, NY, United States
Event date
Jan 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000558753800069