Open University Learning Analytics dataset
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F17%3A00315919" target="_blank" >RIV/68407700:21730/17:00315919 - isvavai.cz</a>
Result on the web
<a href="https://www.nature.com/articles/sdata2017171" target="_blank" >https://www.nature.com/articles/sdata2017171</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/sdata.2017.171" target="_blank" >10.1038/sdata.2017.171</a>
Alternative languages
Result language
angličtina
Original language name
Open University Learning Analytics dataset
Original language description
Learning Analytics focuses on the collection and analysis of learners’ data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students’ interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Scientific Data
ISSN
2052-4463
e-ISSN
2052-4463
Volume of the periodical
4
Issue of the periodical within the volume
November
Country of publishing house
GB - UNITED KINGDOM
Number of pages
8
Pages from-to
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UT code for WoS article
000416400600001
EID of the result in the Scopus database
2-s2.0-85036530553