Student Skill Models in Adaptive Testing

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F16%3A00468589" target="_blank" >RIV/67985556:_____/16:00468589 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Student Skill Models in Adaptive Testing
Original language description
This paper provides a common framework, a generic model, for Computerized Adaptive Testing (CAT) for different model types. We present question selection methods for CAT for this generic model. We use three different types of models, Item Response Theory, Bayesian Networks, and Neural Networks, that instantiate the generic model. We illustrate the usefulness of a special model condition – the monotonicity – and discuss its inclusion in these model types. With Bayesian networks we use specific type of learning using generalized linear models to ensure the monotonicity. We conducted simulated CAT tests on empirical data. Behavior of individual models was assessed based on these tests. The best performing model was the BN model constructed by a domain expert; its parameters were learned from data under the monotonicity condition.
Czech name
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Czech description
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Project
<a href="/en/project/GA16-12010S" target="_blank" >GA16-12010S: Conditional independence structures: combinatorial and optimization methods</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the Eighth International Conference on Probabilistic Graphical Models
ISBN
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ISSN
1938-7228
e-ISSN
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Number of pages
12
Pages from-to
403-414
Publisher name
Microtome Publishing
Place of publication
Brookline
Event location
Lugano
Event date
Sep 6, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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