The details matter: methodological nuances in the evaluation of student models

PELÁNEK, Radek. The details matter: methodological nuances in the evaluation of student models. User Modeling and User-Adapted Interaction. Springer, 2018, vol. 28, No 3, p. 207-235. ISSN 0924-1868. Available from: https://dx.doi.org/10.1007/s11257-018-9204-y.

Basic information

Original name

The details matter: methodological nuances in the evaluation of student models

Authors

PELÁNEK, Radek (203 Czech Republic, guarantor, belonging to the institution)

Edition

User Modeling and User-Adapted Interaction, Springer, 2018, 0924-1868

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Other information

Language

English

Type of outcome

Article in a journal

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

Germany

Confidentiality degree

is not subject to a state or trade secret

References:

URL

Impact factor

Impact factor: 3.400

RIV identification code

RIV/00216224:14330/18:00104013

Organization unit

Faculty of Informatics

DOI

http://dx.doi.org/10.1007/s11257-018-9204-y

UT WoS

000444730900001

Keywords in English

student modeling; evaluation; metrics; data; model comparison

Tags

International impact, Reviewed

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Abstract

V originále

The core of student modeling research is about capturing the complex learning processes into an abstract mathematical model. The student modeling research, however, also involves important methodological aspects. Some of these aspects may seem like technical details not worth significant attention. However, the details matter. We discuss three important methodological issues in student modeling: the impact of data collection, the splitting of data into a training set and a test set, and the details concerning averaging in the computation of predictive accuracy metrics. We explicitly identify decisions involved in these steps, illustrate how these decisions can influence results of experiments, and discuss consequences for future research in student modeling.