ConGuess: a learning environment for configuration tasks.

Andreas Hofbauer; Alexander Felfernig

doi:10.1145/3503229.3547042

ConGuess: a learning environment for configuration tasks.

Andreas Hofbauer, Alexander Felfernig

Institut für Softwaretechnologie (7160)

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Abstract

Learning the concepts of constraint solving and configuration is often a effortful task since it requires the development of a basic understanding of configuration rule semantics. Also, students engaged in topic-related courses have to tackle the challenge of understanding formal configuration knowledge representations. In this paper we introduce a gamification-based environment (ConGuess) that can help to learn configuration rule semantics. This environment is based on the idea of presenting configuration knowledge to game players (learners) and let players figure out correct solutions.

Originalsprache	englisch
Titel	26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings
Redakteure/-innen	Alexander Felfernig, Lidia Fuentes, Jane Cleland-Huang, Wesley K.G. Assuncao, Wesley K.G. Assuncao, Clement Quinton, Jianmei Guo, Klaus Schmid, Marianne Huchard, Inmaculada Ayala, Jose Miguel Rojas, Viet-Man Le, Jose Miguel Horcas
Herausgeber (Verlag)	Association of Computing Machinery
Seiten	156-157
Seitenumfang	2
Band	B
ISBN (elektronisch)	978-1-4503-9206-8
DOIs	https://doi.org/10.1145/3503229.3547042
Publikationsstatus	Veröffentlicht - 12 Sept. 2022
Veranstaltung	26th ACM International Systems and Software Product Line Conference: SPLC 2022 - Graz, Österreich Dauer: 12 Sept. 2022 → 16 Sept. 2022 http://2022.splc.net/

Konferenz

Konferenz	26th ACM International Systems and Software Product Line Conference
Kurztitel	SPLC'22
Land/Gebiet	Österreich
Ort	Graz
Zeitraum	12/09/22 → 16/09/22
Internetadresse	http://2022.splc.net/

ASJC Scopus subject areas

Software

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10.1145/3503229.3547042Lizenz: CC BY 4.0

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Hofbauer, A., & Felfernig, A. (2022). ConGuess: a learning environment for configuration tasks. in A. Felfernig, L. Fuentes, J. Cleland-Huang, W. K. G. Assuncao, W. K. G. Assuncao, C. Quinton, J. Guo, K. Schmid, M. Huchard, I. Ayala, J. M. Rojas, V-M. Le, & J. M. Horcas (Hrsg.), 26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings (Band B, S. 156-157). Association of Computing Machinery. https://doi.org/10.1145/3503229.3547042

ConGuess: a learning environment for configuration tasks. / Hofbauer, Andreas; Felfernig, Alexander.
26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings. Hrsg. / Alexander Felfernig; Lidia Fuentes; Jane Cleland-Huang; Wesley K.G. Assuncao; Wesley K.G. Assuncao; Clement Quinton; Jianmei Guo; Klaus Schmid; Marianne Huchard; Inmaculada Ayala; Jose Miguel Rojas; Viet-Man Le; Jose Miguel Horcas. Band B Association of Computing Machinery, 2022. S. 156-157.

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Hofbauer, A & Felfernig, A 2022, ConGuess: a learning environment for configuration tasks. in A Felfernig, L Fuentes, J Cleland-Huang, WKG Assuncao, WKG Assuncao, C Quinton, J Guo, K Schmid, M Huchard, I Ayala, JM Rojas, V-M Le & JM Horcas (Hrsg.), 26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings. Bd. B, Association of Computing Machinery, S. 156-157, 26th ACM International Systems and Software Product Line Conference, Graz, Österreich, 12/09/22. https://doi.org/10.1145/3503229.3547042

Hofbauer A, Felfernig A. ConGuess: a learning environment for configuration tasks. in Felfernig A, Fuentes L, Cleland-Huang J, Assuncao WKG, Assuncao WKG, Quinton C, Guo J, Schmid K, Huchard M, Ayala I, Rojas JM, Le V-M, Horcas JM, Hrsg., 26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings. Band B. Association of Computing Machinery. 2022. S. 156-157 doi: 10.1145/3503229.3547042

Hofbauer, Andreas ; Felfernig, Alexander. / ConGuess: a learning environment for configuration tasks. 26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings. Hrsg. / Alexander Felfernig ; Lidia Fuentes ; Jane Cleland-Huang ; Wesley K.G. Assuncao ; Wesley K.G. Assuncao ; Clement Quinton ; Jianmei Guo ; Klaus Schmid ; Marianne Huchard ; Inmaculada Ayala ; Jose Miguel Rojas ; Viet-Man Le ; Jose Miguel Horcas. Band B Association of Computing Machinery, 2022. S. 156-157

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AB - Learning the concepts of constraint solving and configuration is often a effortful task since it requires the development of a basic understanding of configuration rule semantics. Also, students engaged in topic-related courses have to tackle the challenge of understanding formal configuration knowledge representations. In this paper we introduce a gamification-based environment (ConGuess) that can help to learn configuration rule semantics. This environment is based on the idea of presenting configuration knowledge to game players (learners) and let players figure out correct solutions.

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A2 - Felfernig, Alexander

A2 - Fuentes, Lidia

A2 - Cleland-Huang, Jane

A2 - Assuncao, Wesley K.G.

A2 - Quinton, Clement

A2 - Guo, Jianmei

A2 - Schmid, Klaus

A2 - Huchard, Marianne

A2 - Ayala, Inmaculada

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ConGuess: a learning environment for configuration tasks.

Abstract

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ASJC Scopus subject areas

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