Rosella Gennari
Alessandra Melonio
ABSTRACT
Children are experiencing Artificial Intelligence (AI) devices in their daily lives. It is crucial to provide them with knowledge concerning how AI works, for enabling them to use AI responsibly and participate actively in their AI-driven future. To support motivation and engagement, playful tools are often used in technology education for K-12 children. This paper offers a systematic literature review of tools for teaching AI to K-12 learners in a playful manner. The most relevant articles are classified and analysed in terms of the nature of the tools they use, that is, whether tools are digital, partly physical and partly digital, or unplugged. Their analysis also considers the target age, the educational focus, and whether their impact is evaluated. According to the results of the review, there are tools for learners of all school grades, and digital tools are the most investigated. Moreover, several studies with tools tend to evaluate engagement and learning but in different manners. The paper concludes by discussing the evaluation aspect, general future work directions and limitations in relation to HCI and education for children.
- 2010. Head Up Games: combining the best of both worlds by merging traditional and digital play. Personal and Ubiquitous Computing 14, 5 (2010), 435–444. https://doi.org/10.1007/s00779-009-0265-0Google Scholar
Digital Library
- AIII and CSTA. 2020. AI4K12. https://ai4k12.org [Online, Last access April 2023].Google Scholar
- Safinah Ali, Daniella DiPaola, and Cynthia Breazeal. 2021. What are GANs?: introducing generative adversarial networks to middle school students. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 35. 15472–15479.Google ScholarCross Ref
- Ewelina Bakala, Anaclara Gerosa, Juan Hourcade, Gonzalo Tejera, Kerry Peterman, and Guillermo Trinidad Barnech. 2022. A Systematic Review of Technologies to Teach Control Structures in Preschool Education. Frontiers in Psychology 13 (09 2022), 911057. https://doi.org/10.3389/fpsyg.2022.911057Google ScholarCross Ref
- Matteo Baldoni, Cristina Baroglio, Monica Bucciarelli, Sara Capecchi, Elena Gandolfi, Cristina Gena, Francesco Iani, Elisa Marengo, Roberto Micalizio, Amon Rapp, 2021. Empowering AI competences in children: A training program based on simple playful activities, Vol. 3100. CEUR, Workshop Proceedings, 1–12.Google Scholar
- Matteo Baldoni, Cristina Baroglio, Monica Bucciarelli, Elena Gandolfi, Francesco Ianì, Elisa Marengo, and Ivan Nabil Ras. 2022. Empowering AI competences in children: the first turning point. In Methodologies and Intelligent Systems for Technology Enhanced Learning, Workshops, 12th International Conference. Springer, 171–181.Google Scholar
- Andrea Bonani, Andreas Bollin, and Rosella Gennari. 2021. Touch, See and Talk: Tangibles for Engaging Learners into Graph Algorithmic Thinking. In Human-Computer Interaction – INTERACT 2021, Carmelo Ardito, Rosa Lanzilotti, Alessio Malizia, Helen Petrie, Antonio Piccinno, Giuseppe Desolda, and Kori Inkpen (Eds.). Springer International Publishing, 630–651.Google ScholarDigital Library
- V. Braun and V. Clarke. 2006. Using thematic analysis in psychology. Qual. Res. Psychol. 3, 2 (2006), 77–101.Google ScholarCross Ref
- Brian Broll, Shuchi Grover, and Derek Babb. 2022. Beyond Black-Boxing: Building Intuitions of Complex Machine Learning Ideas Through Interactives and Levels of Abstraction. In Proceedings of the Conference on International Computing Education Research - Volume 2. ACM, 21–23. https://doi.org/10.1145/3501709.3544273Google ScholarDigital Library
- Brian Broll, Akos Lédeczi, Peter Volgyesi, Janos Sallai, Miklos Maroti, Alexia Carrillo, Stephanie L. Weeden-Wright, Chris Vanags, Joshua D. Swartz, and Melvin Lu. 2017. A Visual Programming Environment for Learning Distributed Programming. ACM, 81–86. https://doi.org/10.1145/3017680.3017741Google ScholarDigital Library
- Harald Burgsteiner, Martin Kandlhofer, and Gerald Steinbauer. 2016. IRobot: Teaching the Basics of Artificial Intelligence in High Schools. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence. AAAI Press, 4126–4127.Google ScholarCross Ref
- Winslow S. Burleson, Danielle B. Harlow, Katherine J. Nilsen, Ken Perlin, Natalie Freed, Camilla Nørgaard Jensen, Byron Lahey, Patrick Lu, and Kasia Muldner. 2018. Active Learning Environments with Robotic Tangibles: Children’s Physical and Virtual Spatial Programming Experiences. IEEE Transactions on Learning Technologies 11, 1 (2018), 96–106. https://doi.org/10.1109/TLT.2017.2724031Google ScholarCross Ref
- Heloisa Candello, Mauro Carlos Pichiliani, and Claudio Santos Pinhanez. 2021. Teaching Conversational Robots in a Museum Exhibition with Interactive Surfaces. In Interactive Surfaces and Spaces. 41–45.Google Scholar
- Sebastian Deterding, Dan Dixon, Rilla Khaled, and Lennart Nacke. 2011. From Game Design Elements to Gamefulness: Defining Gamification. Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, MindTrek 11, 9–15. https://doi.org/10.1145/2181037.2181040Google ScholarDigital Library
- Utkarsh Dwivedi. 2021. Introducing children to machine learning through machine teaching. In Interaction design and children. 641–643.Google Scholar
- Rosella Gennari, Alessandra Melonio, and Mehdi Rizvi. 2019. Turn taking with turn-talk in group. Multimedia Tools and Applications 78, 10 (2019), 13461–13487. https://doi.org/10.1007/s11042-018-7090-2Google ScholarDigital Library
- Xiaofei Han, Junwei Zou, Wei Ren, and Yan Sun. 2020. A Game Battle Platform based on Web-API for Artificial Intelligence Education. In 2020 International Wireless Communications and Mobile Computing (IWCMC). 1789–1793. https://doi.org/10.1109/IWCMC48107.2020.9148114Google ScholarCross Ref
- Julie Henry, Alyson Hernalesteen, and Anne-Sophie Collard. 2021. Teaching Artificial Intelligence to K-12 Through a Role-Playing Game Questioning the Intelligence Concept. KI-Künstliche Intelligenz 35, 2 (2021), 171–179.Google ScholarCross Ref
- Juan Pablo Hourcade. 2022. Child-Computer Interaction. CreateSpace Independent Publishing Platform.Google Scholar
- Ting-Chia Hsu, Hal Abelson, Natalie Lao, Yu-Han Tseng, and Yi-Ting Lin. 2021. Behavioral-pattern exploration and development of an instructional tool for young children to learn AI. Computers and Education: Artificial Intelligence 2 (2021), 100012.Google ScholarCross Ref
- Brian Jordan, Nisha Devasia, Jenna Hong, Randi Williams, and Cynthia Breazeal. 2021. PoseBlocks: A toolkit for creating (and dancing) with AI. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 35. 15551–15559.Google ScholarCross Ref
- Duri Long and Brian Magerko. 2020. What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems. 1–16.Google ScholarDigital Library
- Duri Long, Anthony Teachey, and Brian Magerko. 2022. Family Learning Talk in AI Literacy Learning Activities. In Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM. https://doi.org/10.1145/3491102.3502091Google ScholarDigital Library
- Jingsi Ma, Yi Zhang, Hesiqi Bin, Kang Wang, Jinfang Liu, and Hanrui Gao. 2022. The Development of Students’ Computational Thinking Practices in AI Course Using the Game-Based Learning: A Case Study. In International Symposium on Educational Technology (ISET). IEEE, 273–277.Google ScholarCross Ref
- Emily McReynolds, Sarah Hubbard, Timothy Lau, Aditya Saraf, Maya Cakmak, and Franziska Roesner. 2017. Toys That Listen: A Study of Parents, Children, and Internet-Connected Toys. In Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM, 5197–5207. https://doi.org/10.1145/3025453.3025735Google ScholarDigital Library
- Viktoriya Olari, Kostadin Cvejoski, and Øyvind Eide. 2021. Introduction to machine learning with robots and playful learning. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 35. 15630–15639.Google ScholarCross Ref
- Matthew J Page, Joanne E McKenzie, Patrick M Bossuyt, Isabelle Boutron, Tammy C Hoffmann, Cynthia D Mulrow, Larissa Shamseer, Jennifer M Tetzlaff, Elie A Akl, Sue E Brennan, Roger Chou, Julie Glanville, Jeremy M Grimshaw, Asbjørn Hróbjartsson, Manoj M Lalu, Tianjing Li, Elizabeth W Loder, Evan Mayo-Wilson, Steve McDonald, Luke A McGuinness, Lesley A Stewart, James Thomas, Andrea C Tricco, Vivian A Welch, Penny Whiting, and David Moher. 2021. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372 (2021). https://doi.org/10.1136/bmj.n71Google ScholarCross Ref
- Seymour Papert, Cynthia Solomon, E Soloway, and JC Spohrer. 1971. Twenty things to do with a computer. Studying the novice programmer (1971), 3–28.Google Scholar
- Kyungjin Park, Bradford Mott, Seung Lee, Anisha Gupta, Katie Jantaraweragul, Krista Glazewski, J. Adam Scribner, Anne Ottenbreit-Leftwich, Cindy E. Hmelo-Silver, and James Lester. 2022. Investigating a visual interface for elementary students to formulate AI planning tasks. Journal of Computer Languages 73 (2022), 101157. https://doi.org/10.1016/j.cola.2022.101157Google ScholarCross Ref
- Bawornsak Sakulkueakulsuk, Siyada Witoon, Potiwat Ngarmkajornwiwat, Pornpen Pataranutaporn, Werasak Surareungchai, Pat Pataranutaporn, and Pakpoom Subsoontorn. 2018. Kids making AI: Integrating Machine Learning, Gamification, and Social Context in STEM Education. In IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE). 1005–1010. https://doi.org/10.1109/TALE.2018.8615249Google ScholarCross Ref
- Alexander Scheidt and Tim Pulver. 2019. Any-Cubes: A Children’s Toy for Learning AI: Enhanced Play with Deep Learning and MQTT. In Proceedings of Mensch Und Computer. ACM, 893–895. https://doi.org/10.1145/3340764.3345375Google ScholarDigital Library
- Jaemarie Solyst, Jennifer Kim, Amy Ogan, and Jessica Hammer. 2022. Data Detectives: A Tabletop Card Game about Training Data. In Proceedings of the 27th Conference on Innovation and Technology in Computer Science Education Vol. 2. ACM, 632. https://doi.org/10.1145/3502717.3532128Google ScholarDigital Library
- David Touretzky, Christina Gardner-McCune, Fred Martin, and Deborah Seehorn. 2019. Envisioning AI for K-12: What Should Every Child Know about AI?Proceedings of the AAAI Conference on Artificial Intelligence 33, 01 (2019), 9795–9799. https://doi.org/10.1609/aaai.v33i01.33019795Google ScholarDigital Library
- Yu-Ling Tsai and Chin-Chung Tsai. 2020. A meta-analysis of research on digital game-based science learning. Journal of Computer Assisted Learning 36, 3 (2020), 280–294.Google ScholarCross Ref
- tuart Russell and Peter Norvig. 2022. Artificial Intelligence: a Modern Approach. Pearson.Google Scholar
- Jessica Van Brummelen, Viktoriya Tabunshchyk, and Tommy Heng. 2021. “Alexa, Can I Program You?”: Student Perceptions of Conversational Artificial Intelligence Before and After Programming Alexa. In Interaction Design and Children. ACM, 305–313. https://doi.org/10.1145/3459990.3460730Google ScholarDigital Library
- Anu Vazhayil, Radhika Shetty, Rao R. Bhavani, and Nagarajan Akshay. 2019. Focusing on Teacher Education to Introduce AI in Schools: Perspectives and Illustrative Findings. In IEEE Tenth International Conference on Technology for Education (T4E). 71–77. https://doi.org/10.1109/T4E.2019.00021Google ScholarCross Ref
- Patrick Virtue. 2021. GANs Unplugged.. In Proceedings of the AAAI conference on artificial intelligence. 15664–15668.Google ScholarCross Ref
- Ning Wang, Eric Greenwald, Ryan Montgomery, and Maxyn Leitner. 2022. ARIN-561: An Educational Game for Learning Artificial Intelligence for High-School Students. In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium. Springer, 528–531.Google Scholar
- Marvin Zammit, Iro Voulgari, Antonios Liapis, and Georgios N Yannakakis. 2022. Learn to machine learn via games in the classroom. (2022).Google Scholar
Index Terms
- How to Playfully Teach AI to Young Learners: a Systematic Literature Review
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