Marie-Monique Schaper
Ole Sejer Iversen
ABSTRACT
Technologies based on AI/ML are playing an increasingly prominent role in teenagers’ everyday lives. Mirroring this trend is a concomitant interest in teaching young people about intelligent technologies. Whereas previous research in the field of Child–Computer Interaction has proposed curriculum and learning activities that describe what teenagers need to learn about AI/ML, there is still a shortage of studies which specifically address teenager-centered perspectives in the teaching of AI/ML. This paper presents a study of teenagers’ everyday understanding of AI/ML technologies. Using a thematic analysis of the teenagers’ own explanations during a series of workshops, we present a conceptual map of the teenagers’ understandings of these technologies. We go on to propose five general recommendations for the teaching of AI/ML to teenagers through the lens of Computational Empowerment. Taken together, these recommendations serve as a teenage-centered starting point for teaching young people about intelligent technologies, an approach that can be implemented in future research interventions with similar objectives.
- 2021. Digital Education Action Plan – Action 8 | European Education Area. https://education.ec.europa.eu/focus-topics/digital-education/action-plan/action-8Google Scholar
- Ashraf Abdul, Jo Vermeulen, Danding Wang, Brian Y Lim, and Mohan Kankanhalli. 2018. Trends and trajectories for explainable, accountable and intelligible systems: An hci research agenda. In Proceedings of the 2018 CHI conference on human factors in computing systems. 1–18.Google ScholarDigital Library
- Saira Anwar, Nicholas Alexander Bascou, Muhsin Menekse, and Asefeh Kardgar. 2019. A systematic review of studies on educational robotics. Journal of Pre-College Engineering Education Research (J-PEER) 9, 2 (2019), 2.Google ScholarCross Ref
- Stephanie Ballard, Karen M. Chappell, and Kristen Kennedy. 2019. Judgment Call the Game: Using Value Sensitive Design and Design Fiction to Surface Ethical Concerns Related to Technology. In Proceedings of the 2019 on Designing Interactive Systems Conference (San Diego, CA, USA) (DIS ’19). Association for Computing Machinery, New York, NY, USA, 421–433. https://doi.org/10.1145/3322276.3323697Google ScholarDigital Library
- Karl-Emil Kjær Bilstrup, Magnus Høholt Kaspersen, Mille Skovhus Lunding, Marie-Monique Schaper, Maarten van Mechelen, Mariana Aki Tamashiro, Rachel Charlotte Smith, Ole Sejer Iversen, Information Studies, and Digital Design. 2022. Supporting Critical Data Literacy in K-9 Education : Three Principles for Enriching Pupils ’ Relationship to Data. In Proceedings of the 2022 ACM Interaction Design and Children Conference. Association for Computing Machinery.Google ScholarDigital Library
- Karl-Emil Kjær Bilstrup, Magnus H. Kaspersen, and Marianne Graves Petersen. 2020. Staging Reflections on Ethical Dilemmas in Machine Learning. In Proceedings of the 2020 ACM Designing Interactive Systems Conference. ACM, New York, NY, USA, 1211–1222. https://doi.org/10.1145/3357236.3395558Google ScholarDigital Library
- Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative Research in Psychology 3, 2 (jan 2006), 77–101. https://doi.org/10.1191/1478088706qp063oaGoogle ScholarCross Ref
- Vicky Charisi, Laura Malinverni, Elisa Rubegni, and Marie-Monique Schaper. 2020. Empowering Children’s Critical Reflections on AI, Robotics and Other Intelligent Technologies. In Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society. ACM, New York, NY, USA, 1–4. https://doi.org/10.1145/3419249.3420090Google ScholarDigital Library
- Beverly Clarke. 2020. Exploring CS: Alternate AI Curriculum. Technical Report.Google Scholar
- Jan Cuny. 2012. Transforming High School Computing: A Call to Action. ACM Inroads 3, 2 (June 2012), 32–36. https://doi.org/10.1145/2189835.2189848Google ScholarDigital Library
- Daniella DiPaola, Blakeley H Payne, and Cynthia Breazeal. 2020. Decoding design agendas: an ethical design activity for middle school students. In Proceedings of the Interaction Design and Children Conference. 1–10.Google ScholarDigital Library
- Stefania Druga, Fee Lia Christoph, and Amy J. Ko. 2022. Family as a Third Space for AI Literacies: How do children and parents learn about AI together?Conference on Human Factors in Computing Systems - Proceedings (2022). https://doi.org/10.1145/3491102.3502031Google ScholarDigital Library
- Stefania Druga, Sarah T Vu, Eesh Likhith, and Tammy Qiu. 2019. Inclusive AI literacy for kids around the world. In Proceedings of FabLearn 2019. 104–111.Google ScholarDigital Library
- Stefania Druga, Randi Williams, Cynthia Breazeal, and Mitchel Resnick. 2017. " Hey Google is it ok if I eat you?" Initial explorations in child-agent interaction. In Proceedings of the 2017 conference on interaction design and children. 595–600.Google ScholarDigital Library
- Stefania Druga, Randi Williams, Hae Won Park, and Cynthia Breazeal. 2018. How smart are the smart toys? Children and parents’ agent interaction and intelligence attribution. In Proceedings of the 17th ACM Conference on Interaction Design and Children. 231–240.Google ScholarDigital Library
- Ignacio Evangelista, German Blesio, and Emanuel Benatti. 2019. Why are we not teaching machine learning at high school? A proposal. 2018 World Engineering Education Forum - Global Engineering Deans Council, WEEF-GEDC 2018 (2019). https://doi.org/10.1109/WEEF-GEDC.2018.8629750Google Scholar
- Ignacio Evangelista, German Blesio, and Emanuel Benatti. 2019. Why are we not teaching machine learning at high school? A proposal. 2018 World Engineering Education Forum - Global Engineering Deans Council, WEEF-GEDC 2018 (2019). https://doi.org/10.1109/WEEF-GEDC.2018.8629750Google Scholar
- Barry J Fishman, William R. Penuel, Stephen Hegedus, and Jeremy Roschelle. 2011. What happens when the research ends? Factors related to the sustainability of a technology-infused mathematics curriculum. Journal of Computers in Mathematics and Science Teaching 30 (2011), 329–353.Google Scholar
- Christopher Frauenberger, Judith Good, Geraldine Fitzpatrick, and Ole Sejer Iversen. 2015. In pursuit of rigour and accountability in participatory design. International journal of human-computer studies 74 (2015), 93–106.Google Scholar
- Mafalda Gamboa. 2022. Living with Drones, Robots, and Young Children: Informing Research through Design with Autoethnography. ACM International Conference Proceeding Series (2022). https://doi.org/10.1145/3546155.3546658Google ScholarDigital Library
- Google. [n. d.]. Teachable Machine. https://teachablemachine.withgoogle.com/Google Scholar
- Oskar J Gstrein and Anne Beaulieu. 2022. How to protect privacy in a datafied society? A presentation of multiple legal and conceptual approaches. Philosophy & Technology 35, 1 (2022), 1–38.Google ScholarCross Ref
- Ole Sejer Iversen and Christian Dindler. 2014. Sustaining participatory design initiatives. CoDesign 10 (2014), 153–170. https://doi.org/10.1080/15710882.2014.963124Google ScholarCross Ref
- Ole Sejer Iversen, Rachel Charlotte Smith, and Christian Dindler. 2018. From computational thinking to computational empowerment. (2018), 1–11. https://doi.org/10.1145/3210586.3210592Google ScholarDigital Library
- Marguerita Lane and Anne Saint-Martin. 2021. The impact of Artificial Intelligence on the labour market: What do we know so far? (2021).Google Scholar
- Phoebe Lin and Jessica Van Brummelen. 2021. Engaging Teachers to Co-Design Integrated AI Curriculum for K-12 Classrooms. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–12.Google ScholarDigital Library
- 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
- Laura Malinverni, Cristina Valero, Marie Monique Schaper, and Isabel Garcia de la Cruz. 2021. Educational Robotics as a boundary object: Towards a research agenda. International Journal of Child-Computer Interaction 29 (2021), 100305.Google ScholarDigital Library
- Ha Nguyen. 2022. Examining Teenagers’ Perceptions of Conversational Agents in Learning Settings. Proceedings of Interaction Design and Children, IDC 2022 (2022), 374–381. https://doi.org/10.1145/3501712.3529740Google ScholarDigital Library
- Leire Ozaeta, Manuel Graña, Maya Dimitrova, and Alexander Krastev. 2018. Child oriented storytelling with NAO robot in hospital environment: preliminary application results. Problems of Engineering Cybernetics and Robotics 69 (2018), 21–29.Google Scholar
- Blakeley H Payne. 2019. An ethics of artificial intelligence curriculum for middle school students. MIT Media Lab Personal Robots Group. Retrieved Oct 10 (2019), 2019.Google Scholar
- Juan David Rodríguez-García, Jesús Moreno-León, Marcos Román-González, and Gregorio Robles. 2020. Introducing Artificial Intelligence Fundamentals with LearningML. In Eighth International Conference on Technological Ecosystems for Enhancing Multiculturality. ACM, New York, NY, USA, 18–20. https://doi.org/10.1145/3434780.3436705Google ScholarDigital Library
- Elisa Rubegni, Laura Malinverni, and Jason Yip. 2022. "Don’t let the robots walk our dogs, but it’s ok for them to do our homework": children’s perceptions, fears, and hopes in social robots.Proceedings of Interaction Design and Children, IDC 2022 (2022), 352–361. https://doi.org/10.1145/3501712.3529726Google ScholarDigital Library
- Ismaila Temitayo Sanusi and Solomon Sunday Oyelere. 2020. Pedagogies of Machine Learning in K-12 Context. Proceedings - Frontiers in Education Conference, FIE 2020-Octob (2020). https://doi.org/10.1109/FIE44824.2020.9274129Google ScholarDigital Library
- Marie-Monique Schaper, Laura Malinverni, and Cristina Valero. 2020. Robot Presidents: Who should rule the world? Teaching Critical Thinking in AI through Reflections upon Food Traditions. In Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society. https://doi.org/doi.org/10.1145/3419249.3420085Google ScholarDigital Library
- Marie-Monique Schaper, Rachel Charlotte Smith, Mariana Aki Tamashiro, Maarten Van Mechelen, Mille Skovhus Lunding, Karl-Emil Kjæer Bilstrup, Magnus Høholt Kaspersen, Kasper Løvborg Jensen, Marianne Graves Petersen, and Ole Sejer Iversen. 2022. Computational empowerment in practice: Scaffolding teenagers’ learning about emerging technologies and their ethical and societal impact. International Journal of Child-Computer Interaction (2022), 100537.Google ScholarDigital Library
- Laura Scheepmaker, Kay Kender, Christopher Frauenberger, and Geraldine Fitzpatrick. 2021. Leaving the field: Designing a socio-material toolkit for teachers to continue to design technology with children. Conference on Human Factors in Computing Systems - Proceedings (2021). https://doi.org/10.1145/3411764.3445462Google ScholarDigital Library
- Rachel Charlotte Smith and Ole Sejer Iversen. 2018. Participatory design for sustainable social change. Design Studies 59 (nov 2018), 9–36. https://doi.org/10.1016/j.destud.2018.05.005Google Scholar
- Ahuva Sperling and Dorit Lickerman. 2012. Integrating AI and machine learning in software engineering course for high school students. Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE (2012), 244–249. https://doi.org/10.1145/2325296.2325354Google ScholarDigital Library
- Shashank Srikant and Varun Aggarwal. 2017. Introducing data science to school kids. In Proceedings of the 2017 ACM SIGCSE technical symposium on computer science education. 561–566.Google ScholarDigital Library
- Mariana A Tamashiro, Maarten Van Mechelen, Marie-Monique Schaper, and Ole Sejer Iversen. 2021. Introducing Teenagers to Machine Learning through Design Fiction: An Exploratory Case Study. In Proceedings of the 20th ACM Conference on Interaction Design and Children (IDC 2021). ACM, New York, NY, USA.Google ScholarDigital Library
- Matti Tedre, Tapani Toivonen, Juho Kahila, Henriikka Vartiainen, Teemu Valtonen, Ilkka Jormanainen, and Arnold Pears. 2021. Teaching machine learning in K-12 Classroom: Pedagogical and technological trajectories for artificial intelligence education. IEEE Access 9, July (2021), 110558–110572. https://doi.org/10.1109/ACCESS.2021.3097962Google ScholarCross Ref
- David Touretzky, Christina Gardner-McCune, Fred Martin, and Deborah Seehorn. 2019. Envisioning AI for K-12: What should every child know about AI?. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 33. 9795–9799.Google ScholarDigital Library
- UNICEF. 2019. Workshop Towards Global Guidance on AI and Child Rights. Technical Report June.Google Scholar
- Marie E. Vachovsky, Grace Wu, Sorathan Chaturapruek, Olga Russakovsky, Richard Sommer, and Li Fei-Fei. 2016. Towards more gender diversity in CS through an artificial intelligence summer program for high school girls. SIGCSE 2016 - Proceedings of the 47th ACM Technical Symposium on Computing Science Education (2016), 303–308. https://doi.org/10.1145/2839509.2844620Google ScholarDigital Library
- 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. Proceedings of Interaction Design and Children, IDC 2021February (2021), 305–313. https://doi.org/10.1145/3459990.3460730 arxiv:2102.01367Google ScholarDigital Library
- Maarten Van Mechelen, Rachel Charlotte Smith, Marie-Monique Schaper, Mariana Aki Tamashiro, Karl-Emil Kjær Bilstrup, Mille Skovhus Lunding, Marianne Graves Petersen, and Ole Sejer Iversen. 2022. Emerging technologies in K–12 education: A future HCI research agenda. ACM Transactions on Computer-Human Interaction (2022).Google Scholar
- Henriikka Vartiainen, Tapani Toivonen, Ilkka Jormanainen, Juho Kahila, Matti Tedre, and Teemu Valtonen. 2020. Machine learning for middle-schoolers: Children as designers of machine-learning apps. In 2020 IEEE Frontiers in Education Conference (FIE). IEEE, 1–9. https://doi.org/10.1109/FIE44824.2020.9273981Google ScholarDigital Library
- Xiaoyu Wan, Xiaofei Zhou, Zaiqiao Ye, Chase K. Mortensen, and Zhen Bai. 2020. SmileyCluster. In Proceedings of the Interaction Design and Children Conference. ACM, New York, NY, USA, 23–35. https://doi.org/10.1145/3392063.3394440Google ScholarDigital Library
- Randi Williams and Cynthia Breazeal. 2020. How to train your robot: A middle school AI and ethics curriculum. IJCAI.Google Scholar
- 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 2019 CHI Conference on Human Factors in Computing Systems. 1–11.Google ScholarDigital Library
- Sarah Woods. 2006. Exploring the design space of robots: Children’s perspectives. Interacting with Computers 18, 6 (dec 2006), 1390–1418. https://doi.org/10.1016/j.intcom.2006.05.001Google ScholarDigital Library
- Julia Woodward, Zari McFadden, Nicole Shiver, Amir Ben-hayon, Jason C Yip, and Lisa Anthony. 2018. Using co-design to examine how children conceptualize intelligent interfaces. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. 1–14.Google ScholarDigital Library
- Junnan Yu, Janet Ruppert, Ricarose Roque, and Ben Kirshner. 2020. Youth civic engagement through computing: cases and implications. ACM Inroads 11, 4 (2020), 42–51. https://doi.org/10.1145/3432727Google ScholarDigital Library
Index Terms
- Five Design Recommendations for Teaching Teenagers’ about Artificial Intelligence and Machine Learning
Recommendations
Exploring Why Underrepresented Students Are Less Likely to Study Machine Learning and Artificial Intelligence
ITiCSE '21: Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1There is little research on why underrepresented minorities are less likely to specifically study Machine Learning and Artificial Intelligence (ML/AI). We surveyed 159 undergraduate students about their interest in, exposure to, and personal views on ML/...
Teenagers' personal accounts of experiences with digital intimate partner violence and abuse
Abstract BackgroundWhile in-person intimate partner violence and abuse (IPVA) among teenagers has been widely studied in the past two decades, knowledge about the role digital media plays in IPVA is limited.
...Highlights- Teenage intimate partner violence and abuse is affected by the inclusion of digital media.
A research agenda for computational empowerment for emerging technology education
AbstractThe article proposes a research agenda for computational empowerment for emerging technologies in the field of child–computer interaction (CCI) – in artificial intelligence (AI), machine learning (ML), the internet of things (IoT), augmented ...
Comments