EFFENBERGER, Tomáš and Radek PELÁNEK. Interpretable Clustering of Students’ Solutions in Introductory Programming. Online. In Roll I., McNamara D., Sosnovsky S., Luckin R., Dimitrova V. Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science, vol 12748. Cham: Springer, 2021. p. 101-112. ISBN 978-3-030-78291-7. Available from: https://dx.doi.org/10.1007/978-3-030-78292-4_9. [citováno 2024-04-24]
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Basic information
Original name Interpretable Clustering of Students’ Solutions in Introductory Programming
Authors EFFENBERGER, Tomáš (203 Czech Republic, guarantor, belonging to the institution) and Radek PELÁNEK (203 Czech Republic, belonging to the institution)
Edition Cham, Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science, vol 12748, p. 101-112, 12 pp. 2021.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW URL
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/21:00121982
Organization unit Faculty of Informatics
ISBN 978-3-030-78291-7
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-030-78292-4_9
UT WoS 000885021300009
Keywords in English interpretable clustering; pattern mining; introductory programming; problem solving
Tags core_A, firank_A
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 16/8/2023 13:20.
Abstract
In introductory programming and other problem-solving activities, students can create many variants of a solution. For teachers, content developers, or applications in student modeling, it is useful to find structure in the set of all submitted solutions. We propose a generic, modular algorithm for the construction of interpretable clustering of students’ solutions in problem-solving activities. We describe a specific realization of the algorithm for introductory Python programming and report results of the evaluation on a diverse set of problems.
Links
MUNI/A/1549/2020, interní kód MUName: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 21 (Acronym: SKOMU)
Investor: Masaryk University
MUNI/A/1573/2020, interní kód MUName: Aplikovaný výzkum: vyhledávání, analýza a vizualizace rozsáhlých dat, zpracování přirozeného jazyka, umělá inteligence pro analýzu biomedicínských obrazů.
Investor: Masaryk University
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