Validity and Reliability of Student Models for Problem-Solving
Activities

D 2021

Validity and Reliability of Student Models for Problem-Solving Activities

EFFENBERGER, Tomáš a Radek PELÁNEK

Základní údaje

Originální název

Validity and Reliability of Student Models for Problem-Solving Activities

Autoři

EFFENBERGER, Tomáš (203 Česká republika, garant, domácí) a Radek PELÁNEK (203 Česká republika, domácí)

Vydání

New York, NY, USA, Proceedings of the 11th International Conference on Learning Analytics and Knowledge, od s. 1-11, 11 s. 2021

Nakladatel

Association for Computing Machinery

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

URL

Kód RIV

RIV/00216224:14330/21:00121402

Organizační jednotka

Fakulta informatiky

ISBN

978-1-4503-8935-8

DOI

http://dx.doi.org/10.1145/3448139.3448140

UT WoS

000883342500001

Klíčová slova anglicky

student modeling; skills; difficulties; validity; reliability; performance measures; problem solving; introductory programming

Štítky

core_A, firank_A

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 16. 8. 2023 13:16, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Student models are typically evaluated through predicting the correctness of the next answer. This approach is insufficient in the problem-solving context, especially for student models that use performance data beyond binary correctness. We propose more comprehensive methods for validating student models and illustrate them in the context of introductory programming. We demonstrate the insufficiency of the next answer correctness prediction task, as it is neither able to reveal low validity of student models that use just binary correctness, nor does it show increased validity of models that use other performance data. The key message is that the prevalent usage of the next answer correctness for validating student models and binary correctness as the only input to the models is not always warranted and limits the progress in learning analytics.

Návaznosti

MUNI/A/1549/2020, interní kód MU

Název: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 21 (Akronym: SKOMU)

Investor: Masarykova univerzita, Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 21

Citovat

EFFENBERGER, Tomáš a Radek PELÁNEK. Validity and Reliability of Student Models for Problem-Solving Activities. Online. In Proceedings of the 11th International Conference on Learning Analytics and Knowledge. New York, NY, USA: Association for Computing Machinery, 2021, s. 1-11. ISBN 978-1-4503-8935-8. Dostupné z: https://dx.doi.org/10.1145/3448139.3448140.

@inproceedings{1759856,
   author = {Effenberger, Tomáš and Pelánek, Radek},
   address = {New York, NY, USA},
   booktitle = {Proceedings of the 11th International Conference on Learning Analytics and Knowledge},
   doi = {http://dx.doi.org/10.1145/3448139.3448140},
   keywords = {student modeling; skills; difficulties; validity; reliability; performance measures; problem solving; introductory programming},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {New York, NY, USA},
   isbn = {978-1-4503-8935-8},
   pages = {1-11},
   publisher = {Association for Computing Machinery},
   title = {Validity and Reliability of Student Models for Problem-Solving Activities},
   url = {https://dl.acm.org/doi/10.1145/3448139.3448140},
   year = {2021}
}

TY  - JOUR
ID  - 1759856
AU  - Effenberger, Tomáš - Pelánek, Radek
PY  - 2021
TI  - Validity and Reliability of Student Models for Problem-Solving Activities
PB  - Association for Computing Machinery
CY  - New York, NY, USA
SN  - 9781450389358
KW  - student modeling
KW  - skills
KW  - difficulties
KW  - validity
KW  - reliability
KW  - performance measures
KW  - problem solving
KW  - introductory programming
UR  - https://dl.acm.org/doi/10.1145/3448139.3448140
N2  - Student models are typically evaluated through predicting the correctness of the next answer. This approach is insufficient in the problem-solving context, especially for student models that use performance data beyond binary correctness. We propose more comprehensive methods for validating student models and illustrate them in the context of introductory programming. We demonstrate the insufficiency of the next answer correctness prediction task, as it is neither able to reveal low validity of student models that use just binary correctness, nor does it show increased validity of models that use other performance data. The key message is that the prevalent usage of the next answer correctness for validating student models and binary correctness as the only input to the models is not always warranted and limits the progress in learning analytics.
ER  -

EFFENBERGER, Tomáš a Radek PELÁNEK. Validity and Reliability of Student Models for Problem-Solving Activities. Online. In \textit{Proceedings of the 11th International Conference on Learning Analytics and Knowledge}. New York, NY, USA: Association for Computing Machinery, 2021, s.~1-11. ISBN~978-1-4503-8935-8. Dostupné z: https://dx.doi.org/10.1145/3448139.3448140.

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