research-article

SmileyCluster: supporting accessible machine learning in K-12 scientific discovery

Authors:

Chase K. Mortensen,

Zhen BaiAuthors Info & Claims

IDC '20: Proceedings of the Interaction Design and Children Conference

Pages 23 - 35

https://doi.org/10.1145/3392063.3394440

Published: 21 June 2020 Publication History

Abstract

There is an increasing need to prepare young learners to be Artificial Intelligence (AI) capable for the future workforce and everyday life. Machine Learning (ML), as an integral subfield of AI, has become the new engine that revolutionizes practices of knowledge discovery. Making ML experience accessible to young learners, however, remains challenging due to its high demand for mathematical and computational skills. This research focuses on designing novel learning environments that help demystify ML technologies for K-12 students, and also investigating new opportunities for maximizing ML accessibility through integration with scientific discovery in STEM education. We developed SmileyCluster - a hands-on and collaborative learning environment that utilizes glyph-based data visualization and superposition comparative visualization to assist learning an entry-level ML technology, namely k-means clustering. Findings from an initial case study with high school students in a pre-college summer program show that SmileyCluster leads to positive change in learning ML concepts, methods and sense-making of patterns. Findings of this study also shed light on understanding ML as a data-enabled approach to support evidence-based scientific discovery in K-12 STEM education.

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Cited By

Cheah YKim J(2025)STEM teachers' perceptions, familiarity, and support needs for integrating generative artificial intelligence in K‐12 educationSchool Science and Mathematics10.1111/ssm.18334Online publication date: 28-Jan-2025
https://doi.org/10.1111/ssm.18334
Yue MJong MDai YLau W(2025)Students as AI literate designers: a pedagogical framework for learning and teaching AI literacy in elementary educationJournal of Research on Technology in Education10.1080/15391523.2025.2449942(1-22)Online publication date: 21-Jan-2025
https://doi.org/10.1080/15391523.2025.2449942
Morales-Navarro LKafai Y(2024)Unpacking Approaches to Learning and Teaching Machine Learning in K-12 Education: Transparency, Ethics, and Design ActivitiesProceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research10.1145/3677619.3678117(1-10)Online publication date: 16-Sep-2024
https://dl.acm.org/doi/10.1145/3677619.3678117
Show More Cited By

Index Terms

SmileyCluster: supporting accessible machine learning in K-12 scientific discovery
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User studies

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cover image ACM Conferences

IDC '20: Proceedings of the Interaction Design and Children Conference

June 2020

642 pages

ISBN:9781450379816

DOI:10.1145/3392063

General Chairs:
Elisa Rubegni
University of Lancaster, UK
,
Asimina Vasalou
University College London, UK
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Program Chairs:
Narcís Parés
Universitat Pompeu Fabra, Spain
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Nitin Sawhney
Aalto University, Finland

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Published: 21 June 2020

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Cited By

Cheah YKim J(2025)STEM teachers' perceptions, familiarity, and support needs for integrating generative artificial intelligence in K‐12 educationSchool Science and Mathematics10.1111/ssm.18334Online publication date: 28-Jan-2025
https://doi.org/10.1111/ssm.18334
Yue MJong MDai YLau W(2025)Students as AI literate designers: a pedagogical framework for learning and teaching AI literacy in elementary educationJournal of Research on Technology in Education10.1080/15391523.2025.2449942(1-22)Online publication date: 21-Jan-2025
https://doi.org/10.1080/15391523.2025.2449942
Morales-Navarro LKafai Y(2024)Unpacking Approaches to Learning and Teaching Machine Learning in K-12 Education: Transparency, Ethics, and Design ActivitiesProceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research10.1145/3677619.3678117(1-10)Online publication date: 16-Sep-2024
https://dl.acm.org/doi/10.1145/3677619.3678117
Olari VRomeike R(2024)Data-related practices for creating Artificial Intelligence systems in K-12Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research10.1145/3677619.3678115(1-10)Online publication date: 16-Sep-2024
https://dl.acm.org/doi/10.1145/3677619.3678115
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Zhou XTang JLyu HLiu XZhang ZQin LAu FSarkar ABai Z(2024)Creating an authoring tool for K-12 teachers to design ML-supported scientific inquiry learningExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650762(1-7)Online publication date: 11-May-2024
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