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Cited by 89Teaching and Learning ProgrammingInteractive and Immersive DisplaysStatistics Education and Methodologies

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

The Machine Learning Machine: A Tangible User Interface for Teaching Machine Learning

Open access
Kaspersen, Magnus Høholt, Bilstrup, Karl-Emil Kjær, Petersen, Marianne Graves·2021·Proceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction
DOI 10.1145/3430524.3440638
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Abstract

Machine Learning (ML) is often used invisibly in everyday applications with little opportunity for consumers to investigate how it works. In this paper, we expand recent efforts to unfold what students should know about ML and how to design tools and activities allowing them to engage with ML. To do so, we explore how to make processes and aspects of ML tangible through the design of the Machine Learning Machine (MLM); a tangible user interface which enables students to create their own data-sets using pen and paper and to iteratively build and test ML models using this data. Based on insights from the design process and a preliminary pilot study with the MLM, we discuss how a tangible approach to engaging with ML can spur curiosity in students and how the iterative process of improving ML models can encourage students to reflect on the relation between data, model and predictions.

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Crossref · 10.1145/3430524.3440638

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Cited by

Metadata

Authors
Kaspersen, M. H., Bilstrup, K.-E. K., & Petersen, M. G.
Affiliations
Aarhus University (DK)
ORCID
Venue
Proceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction
Publisher
ACM
Published
2021-02-14
Pages
1-12
DOI
10.1145/3430524.3440638
OpenAlex
W3132204078
Cited by
89
References
5
Citations by year
2026: 4 · 2025: 9 · 2024: 53 · 2023: 8 · 2022: 14 · 2021: 1
FWCI
22.18
Type
conference paper
Language
en
Open access
Licence
Locations
  • International Conference on Tangible, Embedded, and Embodied Interaction (TEI) (publishedVersion)
  • Scopus (Elsevier) (submittedVersion, other-oa)
Funders
Villum Fonden (28831)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
  • Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
  • Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
Keywords
machine learning education, tangible user interfaces, student curiosity

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.