Elo-based Learner Modeling for the Adaptive Practice of Facts

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, vol. 26, No 1, p. 89-118. ISSN 0924-1868. doi:10.1007/s11257-016-9185-7. 2017.

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

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Netherlands
• Confidentiality degree: is not subject to a state or trade secret
• WWW: 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
• Tags: International impact, Reviewed

Abstract

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