S.P.O.T: A Game-Based Application for Fostering Critical Machine Learning Literacy Among Children
Open accessAbstract
This paper describes S.P.O.T., a game-based application for promoting children's practical understanding of ML concepts and applications. Current tools for teaching ML in K-12 engage students in playful exploration of ML mechanisms and teach ML from a cognitive perspective. However, in S.P.O.T, learners interact with ML within real-life sociopolitical contexts and examine how ML predictions impact their daily lives and communities. Through the immersion of stories that mirror children's lived experiences, S.P.O.T. provides elementary school aged children with opportunities to learn how machine learning applications function and develop children's abilities to critically examine, question, and reimagine the consequences of ML decisions in the real world.
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In HCI, there is a substantial body of research exploring how to design technologies to promote children's and families' AI literacy.
“In HCI, there is a substantial body of research exploring how to design technologies to promote children's and families' AI literacy [1, 28, 61].”
From "When He Feels Cold, He Goes to the Seahorse"—Blending Generative AI into Multimaterial Storymaking for Family Expressive Arts Therapy (2024) · cites this paper as [1]
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Cites
The Scratch Programming Language and Environment
Maloney, J. H., Resnick, M., Rusk, N., Silverman, B., & Eastmond, E. (2010) · ACM Transactions on Computing Education · doi:10.1145/1868358.1868363 · Cited by 1,423 · see citing works
Learning by Design: Good Video Games as Learning Machines
Gee, J. P. (2005) · E-Learning and Digital Media · doi:10.2304/elea.2005.2.1.5 · Cited by 845 · see citing works
Learning with serious games: Is fun playing the game a predictor of learning success?
Iten, N., & Petko, D. (2016) · British Journal of Educational Technology · doi:10.1111/bjet.12226 · Cited by 294 · see citing works
Critical Counter-Narrative as Transformative Methodology for Educational Equity
Miller, R., Liu, K. Y., & Ball, A. F. (2020) · Review of Research in Education · doi:10.3102/0091732x20908501 · Cited by 256 · see citing works
Learning machine learning with very young children: Who is teaching whom?
Vartiainen, H., Tedre, M., & Valtonen, T. (2020) · International Journal of Child-Computer Interaction · doi:10.1016/j.ijcci.2020.100182 · Cited by 221 · see citing works
Interactive digital storytelling: bringing cultural heritage in a classroom
Rizvić, S., Bošković, D., Okanović, V., Šljivo, S., & Zukić, M. (2019) · Journal of Computers in Education · doi:10.1007/s40692-018-0128-7 · Cited by 87 · see citing works
The effect of educational game design process on students’ creativity
Bulut, D., Samur, Y., & Cömert, Z. (2022) · Smart Learning Environments · doi:10.1186/s40561-022-00188-9 · Cited by 76 · see citing works
Teaching machine learning in elementary school
Shamir, G., & Levin, I. (2021) · International Journal of Child-Computer Interaction · doi:10.1016/j.ijcci.2021.100415 · Cited by 68 · see citing works
From Theory Bias to Theory Dialogue
Kafai, Y. B., Proctor, C. P., & Lui, D. (2019) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3291279.3339400 · Cited by 58 · see citing works
Irgens, G. A., Vega, H., Adisa, I. O., & Bailey, C. S. (2022) · International Journal of Child-Computer Interaction · doi:10.1016/j.ijcci.2022.100541 · Cited by 35 · see citing works
Self-citationInteractive storytelling for children: a survey
Garzotto, F. (2014) · International Journal of Arts and Technology · doi:10.1504/ijart.2014.058940 · Cited by 34 · see citing works
Principles for educational game development for young children
Miller, J., & Kocurek, C. A. (2017) · Journal of Children and Media · doi:10.1080/17482798.2017.1308398 · Cited by 31 · see citing works
Williams, R. (2021) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3408877.3439690 · Cited by 25 · see citing works
Characterizing the research-practice gap in children’s interactive storytelling systems
Loustau, T., & Chu, S. L. (2022) · International Journal of Child-Computer Interaction · doi:10.1016/j.ijcci.2022.100544 · Cited by 5 · see citing works
The Studies on Educational Digital Games Regarding Children: A New Word Analysis Approach.
Çiftçi, S. (2018) · The turkish online journal of educational technology · Cited by 3 · see citing works
Flagged first, then by citations
Research works printed but not linked: 7
- Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism (1 edition). NYU Press.
- Cathy O'Neil. 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (1 edition). Crown.
- Paulo Freire. 1971. Pedagogy of the oppressed. Herder and Herder, New York.
- Evan W Patton, Michael Tissenbaum, and Farzeen Harunani. 2019. MIT app inventor: Objectives, design, and development. Computational thinking education (2019), 31–49.
- Matheus V Valenza, Isabela Gasparini, and Marcelo da S. Hounsell. 2019. Serious game design for children. Journal of Educational Technology & Society 22, 3 (2019), 19–31.
- Kout Yacine. 2017. "Counter narratives of war in video games." International Critical Media Literacy Conference. 13. (February 2017) https://digitalcommons.georgiasouthern.edu/criticalmedialiteracy/2017/2017/13
- Lappe and Dwyer. 2022. Using Interactive Storytelling to Teach Key Vocabulary Terms. (March 2022). https://www.edutopia.org/article/using-interactive-storytelling-teach-key-vocabulary-terms/
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Liu, D., Zhou, H., & An, P. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642852 · Cited by 38 · see citing works
- Authors
- Adisa, I. O., Thompson, I., Famaye, T., Sistla, D., Bailey, C. S., Mulholland, K., Fecher, A., Lancaster, C. M., & Arastoopour Irgens, G.
- Affiliations
- Clemson University (US)
- Learning Sciences, Clemson University, United States
- ORCID
- Venue
- Proceedings of the 22nd Annual ACM Interaction Design and Children Conference
- Publisher
- ACM
- Published
- 2023-06-19
- Pages
- 507-511
- OpenAlex
- W4380668146
- Cited by
- 18
- References
- 15
- Citations by year
- 2026: 7 · 2025: 4 · 2024: 6 · 2023: 1
- FWCI
- 19.19
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM International Conference on Interaction Design and Children (IDC) (publishedVersion)
- Funders
- National Science Foundation (2031175, 2024965)
- Clemson University
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Keywords
- game-based learning, children, primary education, K-12 education, critical thinking, storytelling, computational thinking
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