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Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00099575" target="_blank" >RIV/00216224:14330/17:00099575 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/s11257-017-9193-2" target="_blank" >http://dx.doi.org/10.1007/s11257-017-9193-2</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s11257-017-9193-2" target="_blank" >10.1007/s11257-017-9193-2</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • 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

    User Modeling and User-Adapted Interaction

  • ISSN

    0924-1868

  • e-ISSN

  • Volume of the periodical

    27

  • Issue of the periodical within the volume

    3-5

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    38

  • Pages from-to

    313-350

  • UT code for WoS article

    000414997500001

  • EID of the result in the Scopus database