| PELÁNEK, Radek. Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques. User Modeling and User-Adapted Interaction. 2017, roč. 27, 3-5, s. 313-350. ISSN 0924-1868. Dostupné z: https://dx.doi.org/10.1007/s11257-017-9193-2. |
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@article{1404956,
author = {Pelánek, Radek},
article_number = {3-5},
doi = {http://dx.doi.org/10.1007/s11257-017-9193-2},
keywords = {learner modeling; evaluation; adaptive learning},
language = {eng},
issn = {0924-1868},
journal = {User Modeling and User-Adapted Interaction},
title = {Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques},
url = {https://link.springer.com/article/10.1007/s11257-017-9193-2},
volume = {27},
year = {2017}
}
TY - JOUR
ID - 1404956
AU - Pelánek, Radek
PY - 2017
TI - Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques
JF - User Modeling and User-Adapted Interaction
VL - 27
IS - 3-5
SP - 313-350
EP - 313-350
SN - 09241868
KW - learner modeling
KW - evaluation
KW - adaptive learning
UR - https://link.springer.com/article/10.1007/s11257-017-9193-2
L2 - https://link.springer.com/article/10.1007/s11257-017-9193-2
N2 - Learner modeling is a basis of personalized, adaptive learning. The research literature provides a wide range of modeling approaches, but it does not provide guidance for choosing a model suitable for a particular situation. We provide a systematic and up-to-date overview of current approaches to tracing learners' knowledge and skill across interaction with multiple items, focusing in particular on the widely used Bayesian knowledge tracing and logistic models. We discuss factors that influence the choice of a model and highlight the importance of the learner modeling context: models are used for different purposes and deal with different types of learning processes. We also consider methodological issues in the evaluation of learner models and their relation to the modeling context. Overall, the overview provides basic guidelines for both researchers and practitioners and identifies areas that require further clarification in future research.
ER -
PELÁNEK, Radek. Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques. \textit{User Modeling and User-Adapted Interaction}. 2017, roč.~27, 3-5, s.~313-350. ISSN~0924-1868. Dostupné z: https://dx.doi.org/10.1007/s11257-017-9193-2.
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