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Adaptive Practice of Facts in Domains with Varied Prior Knowledge

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00076647" target="_blank" >RIV/00216224:14330/14:00076647 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Adaptive Practice of Facts in Domains with Varied Prior Knowledge

  • Original language description

    We propose a modular approach to development of a computerized adaptive practice system for learning of facts in areas with widely varying prior knowledge: decomposing the system into estimation of prior knowledge, estimation of current knowledge, and selection of questions. We describe specific realization of the system for geography learning and use data from the developed system for evaluation of different student models for knowledge estimation. We argue that variants of the Elo rating systems and Performance factor analysis are suitable for this kind of educational system, as they provide good accuracy and at the same time are easy to apply in an online system.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/LG13010" target="_blank" >LG13010: Czech Republic representation in the European Research Consortium for Informatics and Mathematics (ERCIM)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2014

  • 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 7th International Conference on Educational Data Mining (EDM 2014)

  • ISBN

    9780983952541

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    6-13

  • Publisher name

    International Educational Data Mining Society

  • Place of publication

    London, United Kingdom

  • Event location

    London, United Kingdom

  • Event date

    Jan 1, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article