Elo-based Learner Modeling for the Adaptive Practice of Facts

J 2017

Elo-based Learner Modeling for the Adaptive Practice of Facts

PELÁNEK, Radek, Jan PAPOUŠEK, Jiří ŘIHÁK, Vít STANISLAV, Juraj NIŽNAN et. al.

Basic information

Original name

Elo-based Learner Modeling for the Adaptive Practice of Facts

Authors

PELÁNEK, Radek (203 Czech Republic, guarantor, belonging to the institution), Jan PAPOUŠEK (203 Czech Republic, belonging to the institution), Jiří ŘIHÁK (203 Czech Republic, belonging to the institution), Vít STANISLAV (203 Czech Republic, belonging to the institution) and Juraj NIŽNAN (703 Slovakia, belonging to the institution)

Edition

User Modeling and User-Adapted Interaction, Springer Netherlands, 2017, 0924-1868

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 2.808

RIV identification code

RIV/00216224:14330/17:00095908

Organization unit

Faculty of Informatics

DOI

http://dx.doi.org/10.1007/s11257-016-9185-7

UT WoS

000395032400004

Keywords in English

Learner modeling;Computerized adaptive practice;Elo rating system;Model evaluation;Factual knowledge

Abstract

V originále

We investigate applications of learner modeling in a computerized adaptive system for practicing factual knowledge. We focus on areas where learners have widely varying prior knowledge. We propose a modular approach to the development of such adaptive practice systems: decomposing the system design into estimation of prior knowledge, estimation of current knowledge, and construction of questions. We provide a detailed discussion of learner models for both estimation steps, including a novel use of the Elo rating system for learner modeling. We implemented the proposed approach in a system for practice of geography facts; the system is widely used and allows us to perform evaluation of all three modules. We compare predictive accuracy of different learner models, discuss insights gained from learner modeling, and also impact of different variants of the system on learners engagement and learning.

Links

MUNI/A/0897/2016, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VI.

Investor: Masaryk University, Category A

MUNI/A/0945/2015, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace V.

Investor: Masaryk University, Category A

MUNI/A/0992/2016, interní kód MU

Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity (Acronym: SKOMU)

Investor: Masaryk University, Category A

Citovat

PELÁNEK, Radek, Jan PAPOUŠEK, Jiří ŘIHÁK, Vít STANISLAV and Juraj NIŽNAN. Elo-based Learner Modeling for the Adaptive Practice of Facts. User Modeling and User-Adapted Interaction. Springer Netherlands, 2017, vol. 26, No 1, p. 89-118. ISSN 0924-1868. Available from: https://dx.doi.org/10.1007/s11257-016-9185-7.

@article{1359654,
   author = {Pelánek, Radek and Papoušek, Jan and Řihák, Jiří and Stanislav, Vít and Nižnan, Juraj},
   article_number = {1},
   doi = {http://dx.doi.org/10.1007/s11257-016-9185-7},
   keywords = {Learner modeling;Computerized adaptive practice;Elo rating system;Model evaluation;Factual knowledge},
   language = {eng},
   issn = {0924-1868},
   journal = {User Modeling and User-Adapted Interaction},
   title = {Elo-based Learner Modeling for the Adaptive Practice of Facts},
   url = {http://dx.doi.org/10.1007/s11257-016-9185-7},
   volume = {26},
   year = {2017}
}

TY  - JOUR
ID  - 1359654
AU  - Pelánek, Radek - Papoušek, Jan - Řihák, Jiří - Stanislav, Vít - Nižnan, Juraj
PY  - 2017
TI  - Elo-based Learner Modeling for the Adaptive Practice of Facts
JF  - User Modeling and User-Adapted Interaction
VL  - 26
IS  - 1
SP  - 89-118
EP  - 89-118
PB  - Springer Netherlands
SN  - 09241868
KW  - Learner modeling;Computerized adaptive practice;Elo rating system;Model evaluation;Factual knowledge
UR  - http://dx.doi.org/10.1007/s11257-016-9185-7
N2  - We investigate applications of learner modeling in a computerized adaptive system for practicing factual knowledge. We focus on areas where learners have widely varying prior knowledge. We propose a modular approach to the development of such adaptive practice systems: decomposing the system design into estimation of prior knowledge, estimation of current knowledge, and construction of questions. We provide a detailed discussion of learner models for both estimation steps, including a novel use of the Elo rating system for learner modeling. We implemented the proposed approach in a system for practice of geography facts; the system is widely used and allows us to perform evaluation of all three modules. We compare predictive accuracy of different learner models, discuss insights gained from learner modeling, and also impact of different variants of the system on learners engagement and learning.
ER  -

PELÁNEK, Radek, Jan PAPOUŠEK, Jiří ŘIHÁK, Vít STANISLAV and Juraj NIŽNAN. Elo-based Learner Modeling for the Adaptive Practice of Facts. \textit{User Modeling and User-Adapted Interaction}. Springer Netherlands, 2017, vol.~26, No~1, p.~89-118. ISSN~0924-1868. Available from: https://dx.doi.org/10.1007/s11257-016-9185-7.

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