Experimental Analysis of Mastery Learning Criteria
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00097866" target="_blank" >RIV/00216224:14330/17:00097866 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1145/3079628.3079667" target="_blank" >http://dx.doi.org/10.1145/3079628.3079667</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3079628.3079667" target="_blank" >10.1145/3079628.3079667</a>
Alternative languages
Result language
angličtina
Original language name
Experimental Analysis of Mastery Learning Criteria
Original language description
A common personalization approach in educational systems is mastery learning. A key step in this approach is a criterion that determines whether a learner has achieved mastery. We thoroughly analyze several mastery criteria for the basic case of a single well-specified knowledge component. For the analysis we use experiments with both simulated and real data. The results show that the choice of data sources used for mastery decision and setting of thresholds are more important than the choice of a learner modeling technique. We argue that a simple exponential moving average method is a suitable technique for mastery criterion and propose techniques for the choice of a mastery threshold.
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
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
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 25th Conference on User Modeling, Adaptation and Personalization
ISBN
9781450346351
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
156-163
Publisher name
ACM
Place of publication
New York, NY, USA
Event location
Bratislava, Slovakia
Event date
Jan 1, 2017
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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