Metrics for Evaluation of Student Models

PELÁNEK, Radek. Metrics for Evaluation of Student Models. Journal of Educational Data Mining. 2015, vol. 7, No 3, p. 1-19. ISSN 2157-2100.

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

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

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

---

Abstract

V originále

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).