Impact of Methodological Choices on the Evaluation of Student Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00116669" target="_blank" >RIV/00216224:14330/20:00116669 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-52237-7_13" target="_blank" >https://doi.org/10.1007/978-3-030-52237-7_13</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-52237-7_13" target="_blank" >10.1007/978-3-030-52237-7_13</a>
Alternative languages
Result language
angličtina
Original language name
Impact of Methodological Choices on the Evaluation of Student Models
Original language description
The evaluation of student models involves many methodological decisions, e.g., the choice of performance metric, data filtering, and cross-validation setting. Such issues may seem like technical details, and they do not get much attention in published research. Nevertheless, their impact on experiments can be significant. We report experiments with six models for predicting problem-solving times in four introductory programming exercises. Our focus is not on these models per se but rather on the methodological choices necessary for performing these experiments. The results show, particularly, the importance of the choice of performance metric, including details of its computation and presentation.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science, vol 12163.
ISBN
9783030522360
ISSN
0302-9743
e-ISSN
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Number of pages
12
Pages from-to
153-164
Publisher name
Springer
Place of publication
Cham
Event location
Ifrane, Morocco
Event date
Jan 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000885049000013