PAPOUŠEK, Jan, Vít STANISLAV and Radek PELÁNEK. Evaluation of an Adaptive Practice System for Learning Geography Facts. Online. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge. Edinburgh, United Kingdom: ACM, 2016, p. 134-142. ISBN 978-1-4503-4190-5. Available from: https://dx.doi.org/10.1145/2883851.2883884.
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Basic information
Original name Evaluation of an Adaptive Practice System for Learning Geography Facts
Authors PAPOUŠEK, Jan (203 Czech Republic, belonging to the institution), Vít STANISLAV (203 Czech Republic, belonging to the institution) and Radek PELÁNEK (203 Czech Republic, guarantor, belonging to the institution).
Edition Edinburgh, United Kingdom, Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, p. 134-142, 9 pp. 2016.
Publisher ACM
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW URL
RIV identification code RIV/00216224:14330/16:00090423
Organization unit Faculty of Informatics
ISBN 978-1-4503-4190-5
Doi http://dx.doi.org/10.1145/2883851.2883884
UT WoS 000390844700017
Keywords in English attrition bias; computerized adaptive practice; engagement; evaluation; learning curve; survival analysis
Tags firank_B
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 13/5/2020 19:17.
Abstract
Computerized educational systems are increasingly provided as open online services which provide adaptive personalized learning experience. To fully exploit potential of such systems, it is necessary to thoroughly evaluate different design choices. However, both openness and adaptivity make proper evaluation difficult. We provide a detailed report on evaluation of an online system for adaptive practice of geography, and use this case study to highlight methodological issues with evaluation of open online learning systems, particularly attrition bias. To facilitate evaluation of learning, we propose to use randomized reference questions. We illustrate application of survival analysis and learning curves for declarative knowledge. The result provide an interesting insight into the impact of adaptivity on learner behaviour and learning.
Links
MUNI/A/0935/2015, interní kód MUName: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity (Acronym: SKOMU)
Investor: Masaryk University, Category A
MUNI/A/0945/2015, interní kód MUName: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace V.
Investor: Masaryk University, Category A
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