ConGuess: a learning environment for configuration tasks.

Andreas Hofbauer, Alexander Felfernig

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

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.
Original languageEnglish
Title of host publication26th ACM International Systems and Software Product Line Conference, SPLC 2022 - Proceedings
EditorsAlexander 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
PublisherAssociation of Computing Machinery
Pages156-157
Number of pages2
VolumeB
ISBN (Electronic)978-1-4503-9206-8
DOIs
Publication statusPublished - 12 Sept 2022
Event26th ACM International Systems and Software Product Line Conference: ASPLC 2022 - Graz, Austria
Duration: 12 Sept 202216 Sept 2022
http://2022.splc.net/

Conference

Conference26th ACM International Systems and Software Product Line Conference
Abbreviated titleSPLC'22
Country/TerritoryAustria
CityGraz
Period12/09/2216/09/22
Internet address

Keywords

  • e-learning
  • gamification
  • knowledge-based configuration

ASJC Scopus subject areas

  • Software

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