extended-abstract

Learn to Machine Learn: Designing a Game Based Approach for Teaching Machine Learning to Primary and Secondary Education Students

Authors:

Elias Stouraitis,

Antonios Liapis,

Georgios YannakakisAuthors Info & Claims

IDC '21: Proceedings of the 20th Annual ACM Interaction Design and Children Conference

Pages 593 - 598

https://doi.org/10.1145/3459990.3465176

Published: 24 June 2021 Publication History

Abstract

With the ubiquitous role of Artificial Intelligence (AI) in everyday applications such as smartphones and social media, children need digital literacy skills to navigate the digital world, critically view, and reflect on the social and ethical implications of the design and architecture of AI systems. To address this increasing need for AI literacy skills, particularly for younger students, this paper presents the rationale of the LearnML project which aims to develop a framework and game-based educational material for promoting AI literacy among primary and secondary education students. We also describe the design and initial assessment of the game “ArtBot”, developed as part of the LearnML project. We review existing literature, discuss the educational game design and development of “ArtBot” and describe the initial feedback of students and teachers. Our goal is to provide insights and suggest guidelines for the implementation of game-based learning environments for supporting AI literacy skills of students.

References

[1]

Tilde Bekker, Saskia Bakker, Iris Douma, Janneke van der Poel, and Koen Scheltenaar. 2015. Teaching children digital literacy through design-based learning with digital toolkits in schools. International Journal of Child-Computer Interaction 5 (2015), 29–38. https://doi.org/10.1016/j.ijcci.2015.12.001

Digital Library

[2]

Karl-Emil Kjær Bilstrup, Magnus H. Kaspersen, and Marianne Graves Petersen. 2020. Staging Reflections on Ethical Dilemmas in Machine Learning: A Card-Based Design Workshop for High School Students. In Proceedings of the Designing Interactive Systems Conference. 1211–1222. https://doi.org/10.1145/3357236.3395558

Digital Library

[3]

Douglas Clark, Brian Nelson, Pratim Sengupta, and Cynthia D’Angelo. 2009. Rethinking Science Learning Through Digital Games and Simulations: Genres, Examples, and Evidence. In Learning science: Computer games, simulations, and education workshop.

[4]

Stefania Druga, Sarah T. Vu, Eesh Likhith, and Tammy Qiu. 2019. Inclusive AI Literacy for Kids around the World. In Proceedings of FabLearn. 104–111. https://doi.org/10.1145/3311890.3311904

Digital Library

[5]

Michail Giannakos, Iro Voulgari, Sofia Papavlasopoulou, Zacharoula Papamitsiou, and Georgios Yannakakis. 2020. Games for Artificial Intelligence and Machine Learning Education: Review and Perspectives. 117–133. https://doi.org/10.1007/978-981-15-6747-6_7

[6]

Ting-Chia Hsu, Shao-Chen Chang, and Yu-Ting Hung. 2018. How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education 126 (2018), 296–310. https://doi.org/10.1016/j.compedu.2018.07.004

[7]

Tibor Koltay. 2011. The media and the literacies: media literacy, information literacy, digital literacy. Media, Culture & Society 33, 2 (2011), 211–221. https://doi.org/10.1177/0163443710393382

[8]

MIT Media Lab. 2021. AI + Ethics Curriculum for Middle School Project.MIT Media Lab, Personal Robots group. https://www.media.mit.edu/projects/ai-ethics-for-middle-school/overview/Retrieved April 13, 2021.

[9]

MET Museum of Art. 2020. The MET Open Collection. The Metropolitan Museum of Art, New York. https://www.metmuseum.orgRetrieved November 12, 2020.

[10]

James Parker and Katrin Becker. 2014. ViPER : Game That Teaches Machine Learning Concepts - A Postmortem. In Proceedings of the IEEE Games and Entertainment Media Conference.

[11]

Stuart Russell, Daniel Dewey, and Max Tegmark. 2015. Research Priorities for Robust and Beneficial Artificial Intelligence. AI Magazine 36, 4 (2015), 105–114. https://doi.org/10.1609/aimag.v36i4.2577

Digital Library

[12]

Steven L. Salzberg. 1994. C4.5: Programs for Machine Learning by J. Ross Quinlan. Machine Learning 16, 3 (1994), 235–240. https://doi.org/10.1007/BF00993309

[13]

Nicole Sintov, Debarun Kar, Thanh Nguyen, Fei Fang, Kevin Hoffman, Arnaud Lyet, and Milind Tambe. 2016. From the Lab to the Classroom and beyond: Extending a Game-Based Research Platform for Teaching AI to Diverse Audiences. In Proceedings of the AAAI Conference on Artificial Intelligence. 4107–4112.

[14]

Tapani Toivonen, Ilkka Jormanainen, Juho Kahila, Matti Tedre, Teemu Valtonen, and Henriikka Vartiainen. 2020. Co-Designing Machine Learning Apps in K–12 With Primary School Children. In Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT). 308–310. https://doi.org/10.1109/ICALT49669.2020.00099

[15]

Tommaso Turchi, Daniela Fogli, and Alessio Malizia. 2019. Fostering computational thinking through collaborative game-based learning. Multimedia Tools and Applications 78, 10 (2019), 13649–13673. https://doi.org/10.1007/s11042-019-7229-9

Digital Library

[16]

Henriikka Vartiainen, Matti Tedre, and Teemu Valtonen. 2020. Learning machine learning with very young children: Who is teaching whom?International Journal of Child-Computer Interaction 25 (2020). https://doi.org/10.1016/j.ijcci.2020.100182

Digital Library

[17]

Henriikka Vartiainen, Tapani Toivonen, Ilkka Jormanainen, Juho Kahila, Matti Tedre, and Teemu Valtonen. 2021. Machine learning for middle schoolers: Learning through data-driven design. International Journal of Child-Computer Interaction 29 (2021). https://doi.org/10.1016/j.ijcci.2021.100281

Digital Library

[18]

Steve Vosloo. 2018. Guidelines for digital inclusion. United Nations Educational, Scientific and Cultural Organization, Paris. https://en.unesco.org/themes/literacy-all/pearson-initiative/guidelinesRetrieved 7 May 2021.

[19]

Christopher J. C. H. Watkins and Peter Dayan. 1992. Q-learning. Machine Learning 8, 3 (1992), 279–292. https://doi.org/10.1007/BF00992698

Digital Library

[20]

Mary E. Webb, Andrew Fluck, Johannes Magenheim, Joyce Malyn-Smith, Juliet Waters, Michelle Deschênes, and Jason Zagami. 2020. Machine learning for human learners: opportunities, issues, tensions and threats. Educational Technology Research and Development (2020). https://doi.org/10.1007/s11423-020-09858-2

[21]

Randi Williams, Hae Won Park, and Cynthia Breazeal. 2019. A is for Artificial Intelligence: The Impact of Artificial Intelligence Activities on Young Children’s Perceptions of Robots. In Proceedings of the CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3290605.3300677

Digital Library

[22]

Randi Williams, Hae Won Park, Lauren Oh, and Cynthia Breazeal. 2019. PopBots: Designing an Artificial Intelligence Curriculum for Early Childhood Education. In Proceedings of the AAAI Conference on Artificial Intelligence. 9729–9736. https://doi.org/10.1609/aaai.v33i01.33019729

Digital Library

[23]

Abigail Zimmermann-Niefield, Makenna Turner, Bridget Murphy, Shaun K. Kane, and R. Benjamin Shapiro. 2019. Youth Learning Machine Learning through Building Models of Athletic Moves. In Proceedings of the ACM International Conference on Interaction Design and Children. 121–132. https://doi.org/10.1145/3311927.3323139

Digital Library

Cited By

Kırksekiz AYıldız MKıyıcı MYıldız M(2024)Adaptation of Artificial Intelligence Literacy Scale: Latent Profile AnalysisSakarya University Journal of Education10.19126/suje.147929414:3(581-596)Online publication date: 30-Dec-2024
https://doi.org/10.19126/suje.1479294
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
Cho YNewman MPitt CYip JLee J(2024)You Are Tilted!: Leveraging Tabletop Gaming to Manage Tilt and Strengthen Team Dynamics in EsportsProceedings of the ACM on Human-Computer Interaction10.1145/36771168:CHI PLAY(1-29)Online publication date: 15-Oct-2024
https://dl.acm.org/doi/10.1145/3677116
Show More Cited By

Recommendations

What is AI Literacy? Competencies and Design Considerations
CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Artificial intelligence (AI) is becoming increasingly integrated in user-facing technology, but public understanding of these technologies is often limited. There is a need for additional HCI research investigating a) what competencies users need in ...
Fostering Secondary School Students’ AI Literacy through Making AI-Driven Recycling Bins
Abstract
Artificial intelligence (AI) education has gained popularity, and educators are developing activities to enhance students' AI literacy and promote collaboration in problem-solving. While current approaches using simulations and games can improve ...
Augmenting the learning experience in primary and secondary school education: a systematic review of recent trends in augmented reality game-based learning
Abstract
There is a significant body of research relating to augmented reality (AR) uses for learning in the primary and the secondary education sectors across the globe. However, there is not such a substantial amount of work exploring the combination ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

IDC '21: Proceedings of the 20th Annual ACM Interaction Design and Children Conference

June 2021

697 pages

ISBN:9781450384520

DOI:10.1145/3459990

General Chairs:
Maria Roussou,
Suleman Shahid,
Program Chairs:
Jerry Alan Fails,
Monica Landoni

Copyright © 2021 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 June 2021

Check for updates

Author Tags

Qualifiers

Extended-abstract
Research
Refereed limited

Funding Sources

ERASMUS+ Strategic Partnership

Conference

IDC '21

Sponsor:

SIGCHI

IDC '21: Interaction Design and Children

June 24 - 30, 2021

Athens, Greece

Acceptance Rates

Overall Acceptance Rate 172 of 578 submissions, 30%

Upcoming Conference

IDC '25

Sponsor:
sigchi

Interaction Design and Children

June 23 - 26, 2025

Reykjavik , Iceland

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

31
Total Citations
View Citations
944
Total Downloads

Downloads (Last 12 months)248
Downloads (Last 6 weeks)41

Reflects downloads up to 08 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Kırksekiz AYıldız MKıyıcı MYıldız M(2024)Adaptation of Artificial Intelligence Literacy Scale: Latent Profile AnalysisSakarya University Journal of Education10.19126/suje.147929414:3(581-596)Online publication date: 30-Dec-2024
https://doi.org/10.19126/suje.1479294
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
Cho YNewman MPitt CYip JLee J(2024)You Are Tilted!: Leveraging Tabletop Gaming to Manage Tilt and Strengthen Team Dynamics in EsportsProceedings of the ACM on Human-Computer Interaction10.1145/36771168:CHI PLAY(1-29)Online publication date: 15-Oct-2024
https://dl.acm.org/doi/10.1145/3677116
Sebastian PSharma SIivari NKinnula MMonga CVerma DAbbas M(2024)Emerging Technologies in Global South Classrooms: Teachers Imagining Future of EducationProceedings of the Participatory Design Conference 2024: Full Papers - Volume 110.1145/3666094.3666109(234-247)Online publication date: 11-Aug-2024
https://dl.acm.org/doi/10.1145/3666094.3666109
Darabipourshiraz HAmbani DLong D(2024)DataBites: An embodied and co-creative museum exhibit to foster children's understanding of supervised machine learningProceedings of the 16th Conference on Creativity & Cognition10.1145/3635636.3664247(550-555)Online publication date: 23-Jun-2024
https://dl.acm.org/doi/10.1145/3635636.3664247
Morales-Navarro LKafai YKonda VMetaxa D(2024)Youth as Peer Auditors: Engaging Teenagers with Algorithm Auditing of Machine Learning ApplicationsProceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3655752(560-573)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3628516.3655752
Morales-Navarro LShah MKafai YStephenson BStone JBattestilli LRebelsky SShoop L(2024)Not Just Training, Also Testing: High School Youths' Perspective-Taking through Peer Testing Machine Learning-Powered ApplicationsProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630899(881-887)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3626252.3630899
Ng DXinyu CLeung JChu S(2024) Fostering students' AI literacy development through educational games: AI knowledge, affective and cognitive engagement Journal of Computer Assisted Learning10.1111/jcal.13009Online publication date: 16-May-2024
https://doi.org/10.1111/jcal.13009
Akoth Ongoro CFanJiang YHung CLin BGuo J(2024)TARES: A Game-Based Tangible Augmented Reality English Spelling Mastery System With Minimal Cognitive LoadIEEE Access10.1109/ACCESS.2024.339348612(61163-61184)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3393486
Yim I(2024)Artificial Intelligence Literacy in Primary Education: An Arts-Based Approach to Overcoming Age and Gender BarriersComputers and Education: Artificial Intelligence10.1016/j.caeai.2024.100321(100321)Online publication date: Oct-2024
https://doi.org/10.1016/j.caeai.2024.100321
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Table of Conten