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AUTOMATON: A Gamification Machine Learning Project
University of Gothenburg, Sweden.
Insert Coin, Sweden.
Linnaeus University, School of Business and Economics, Department of Marketing and Tourism Studies (MTS).ORCID iD: 0000-0003-2924-2874
2023 (English)In: Encyclopedia of Data Science and Machine Learning / [ed] John Wang, IGI Global, 2023, p. 3090-3101Chapter in book (Refereed)
Abstract [en]

This article displays a design ethnographic case study on an ongoing machine learning project at a Scandinavian gamification start-up company. From late 2020 until early 2021, the project produced a machine learning proof of concept, later implemented in the gamification start-up´s application programming interface to offer smart gamification. The initial results show promise in using prediction models to automate the cluster model selection affording more functional, autonomous, and scalable user segments that are faster to implement. The finding provides opportunities for gamification (e.g., in learning analytics and health informatics). An identified challenge was performance; the neural networks required hyperparameter fine-tuning, which is time-consuming and limits scalability. Interesting further investigations should consider the neural network fine-tuning process, but also attempt to verify the effectiveness of the cluster models selection compared with a control group.

Place, publisher, year, edition, pages
IGI Global, 2023. p. 3090-3101
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:lnu:diva-119634DOI: 10.4018/978-1-7998-9220-5.ch185Scopus ID: 2-s2.0-85188105044ISBN: 9781799892205 (print)ISBN: 1799892204 (print)ISBN: 9781799892212 (electronic)OAI: oai:DiVA.org:lnu-119634DiVA, id: diva2:1741080
Note

Bidrag till encyklopedi

Available from: 2023-03-03 Created: 2023-03-03 Last updated: 2024-04-04Bibliographically approved

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Helmefalk, Miralem

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf