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Introducing children to machine learning concepts through hands-on experience

Published: 19 June 2018 Publication History

Abstract

Machine Learning (ML) processes are integrated into devices and services that affect many aspects of daily life. As a result, basic understanding of ML concepts becomes essential for people of all ages, including children. We studied if 10--12 years old children can understand basic ML concepts through direct experience with a digital stick-like device, in a WoZ-based experiment. To assess children's understanding we applied an experimental design including a pretest, a gesture recognition training activity, and a posttest. The tests included validating children's understanding of the gesture training activity, other gesture detection processes, and application to ML processes in daily scenarios. Our findings suggest that children are able to understand basic ML concepts, and can even apply them to a new context. We conclude that ML learning activities should allow children to sample their own examples and evaluate them in an iterative way, and proper feedback should be designed to gradually scaffold understanding.

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cover image ACM Conferences
IDC '18: Proceedings of the 17th ACM Conference on Interaction Design and Children
June 2018
789 pages
ISBN:9781450351522
DOI:10.1145/3202185
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 19 June 2018

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Author Tags

  1. children
  2. machine learning
  3. physical experience

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IDC '18
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IDC '18: Interaction Design and Children
June 19 - 22, 2018
Trondheim, Norway

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IDC '18 Paper Acceptance Rate 28 of 96 submissions, 29%;
Overall Acceptance Rate 172 of 578 submissions, 30%

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IDC '25
Interaction Design and Children
June 23 - 26, 2025
Reykjavik , Iceland

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Cited By

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  • (2024)Revolutionizing PedagogyIntegrating Generative AI in Education to Achieve Sustainable Development Goals10.4018/979-8-3693-2440-0.ch014(264-281)Online publication date: 3-Jun-2024
  • (2024)Elective course on machine learning in high school: problems of sports programmingInformatics in school10.32517/2221-1993-2024-23-1-54-59(54-59)Online publication date: 18-Apr-2024
  • (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
  • (2024)Co-ML: Collaborative Machine Learning Model Building for Developing Dataset Design PracticesACM Transactions on Computing Education10.1145/364155224:2(1-37)Online publication date: 16-Apr-2024
  • (2024)Exploring AI Problem Formulation with Children via Teachable MachinesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642692(1-18)Online publication date: 11-May-2024
  • (2024)Testing, Socializing, Exploring: Characterizing Middle Schoolers’ Approaches to and Conceptions of ChatGPTProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642332(1-17)Online publication date: 11-May-2024
  • (2024)Work in Progress: Rubrics to Assess Learning Effectiveness of Artificial Intelligence Education for K-122024 IEEE World Engineering Education Conference (EDUNINE)10.1109/EDUNINE60625.2024.10500453(1-4)Online publication date: 10-Mar-2024
  • (2024)A systematic review of the evaluation in K-12 artificial intelligence education from 2013 to 2022Interactive Learning Environments10.1080/10494820.2024.2335499(1-29)Online publication date: 31-Mar-2024
  • (2024)The key artificial intelligence technologies in early childhood education: a reviewArtificial Intelligence Review10.1007/s10462-023-10637-757:1Online publication date: 8-Jan-2024
  • (2023)Teaching Machine Learning in K–12 Using RoboticsEducation Sciences10.3390/educsci1301006713:1(67)Online publication date: 10-Jan-2023
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