PELÁNEK, Radek. Metrics for Evaluation of Student Models. Journal of Educational Data Mining. 2015, vol. 7, No 3, p. 1-19. ISSN 2157-2100.
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Basic information
Original name Metrics for Evaluation of Student Models
Authors PELÁNEK, Radek (203 Czech Republic, guarantor, belonging to the institution).
Edition Journal of Educational Data Mining, 2015, 2157-2100.
Other information
Original language English
Type of outcome Article in a journal
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
WWW URL
RIV identification code RIV/00216224:14330/15:00086954
Organization unit Faculty of Informatics
Keywords in English student modeling; evaluation; metrics
Tags International impact, Reviewed
Changed by Changed by: doc. Mgr. Radek Pelánek, Ph.D., učo 4297. Changed: 2/9/2020 08:56.
Abstract
Researchers use many different metrics for evaluation of performance of student models. The aim of this paper is to provide an overview of commonly used metrics, to discuss properties, advantages, and disadvantages of different metrics, to summarize current practice in educational data mining, and to provide guidance for evaluation of student models. In the discussion we mention the relation of metrics to parameter fitting, the impact of student models on student practice (over-practice, under-practice), and point out connections to related work on evaluation of probability forecasters in other domains. We also provide an empirical comparison of metrics. One of the conclusion of the paper is that some commonly used metrics should not be used (MAE) or should be used more critically (AUC).
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