^{Themes: Lesson planning, Teaching Strategies
Audience & Subject: General (All Grades)}

Introduction

Over the past decade, artificial intelligence (AI) has developed rapidly, fundamentally altering how people live and work. Globally, educational jurisdictions are incorporating AI education into their curricula throughout grades K-12 and subject areas, focusing on AI applications, societal ramifications, and ethics (Gadanidis et al., 2024). According to the UNESCO (2022) report, eleven Member States (i.e., Armenia, Austria, Belgium, China, India, Republic of Korea, Kuwait, Portugal, Qatar, Serbia, and the United Arab Emirates) “have developed, endorsed and implemented” a national AI curriculum, and many more are developing a curriculum of their own (p. 19). Most other countries, including the United States, Canada, the United Kingdom, and Finland, have integrated AI knowledge into existing subjects, such as science and technology, fostering a STEAM approach in primary and secondary schools (Li, 2022). In Ontario, new curricula were developed between 2020 and 2023, specifically mentioning AI in grades 7-8 within the Science & Technology curriculum, Grade 9 science curriculum, and Grade 10 Computer Studies curriculum. These curricula emphasize the impact of AI on everyday life. (Gadanidis et al., 2024). However, given AI’s rapid evolution and the introduction of novel and uncertain impacts, a futures studies approach emerges as particularly well-suited to AI education. Within this context, this presentation explores the potential of employing design fiction as a pedagogical approach in AI education. It further discusses the development of a Design Fiction Pedagogy (DFP) model tailored for practical implementation in educational settings.

General Guidelines

Design fiction—originating in the design industry—is closely intertwined with futures studies and integrates design, science, and fiction to enable creators to envision solutions and scenarios beyond the present (Li, 2023). The practice serves as a thought-provoking medium within future studies, providing a platform for envisioning and analyzing potential future worlds (Li, 2023). Through components such as speculative designs, fictional narratives, and critical reflections, Design Fiction Pedagogy (DFP) immerses students in exploring AI concepts and their ramifications, making it a viable teaching approach in AI education.

Activity: Implement DFP in AI Education

Overview

This activity provides a practical pedagogical model comprising seven steps to implement DFP in AI education effectively. The purpose is to equip students with hands-on experiences with AI concepts and their societal implications and foster critical thinking, creativity, and ethical awareness. Below is an overview of the steps and corresponding activities:

1. Identifying and Researching a Problem: AI Problem Scavenger Hunt. AI problem scavenger hunt provides students with a list of real-world AI-related challenges and asks them to research and identify potential problems that AI applications may solve.
2. Designing a Prototype to Address the Problem: AI Prototype Development. Have students brainstorm AI-driven solutions to the problems they have identified. Provide students with tools and resources to develop their AI prototypes. Depending on the complexity of your class, this could involve using visual programming platforms like Scratch, Tinkercad, CoSpaces or hands-on maker tools.
3. Designing a Future Context: Future Scenario Creation. Introduce students to the concept of design fiction. Ask them to create future scenarios where their AI prototypes are integratable into an imagined context.
4. Building a Narrative in the Context: Narrative Building. Help students construct rich story worlds around their AI prototypes. Focus on the interaction between their characters and the prototyped AI product. Students can use digital storytelling tools such as Generative AI to enhance their narratives.
5. Sharing and Collaborative Learning: AI Story Showcase and Peer Feedback. Organize an AI story showcase where students present their prototypes and narratives to their peers. Encourage feedback and discussions, allowing students to refine their narratives further.
6. Reflecting on Impact and Ethical Considerations: Ethical Dilemma Discussions. Engage students in discussions (or AI Ethics Debate) on ethical dilemmas related to AI, considering the impact on society and individuals. Encourage them to reflect on the ethical considerations of their prototypes and narratives.
7. Evaluating Viability and Potential Redesign of the Prototype: Prototype Evaluation and Regulation. Guide students in evaluating the viability of their prototypes, considering legal and ethical regulations. Encourage them to think about how their designs can be responsibly innovative or refined to address potential challenges.

Key Benefits

Design fiction activities provide students with an engaging opportunity to explore creative solutions to real-world problems while considering the ethical implications of AI through hands-on experience. They foster curiosity, collaboration, and critical thinking, empowering students to become active agents in learning and shaping the future of technology and society.

Possible Challenges

Technical complexity, such as using digital tools and coding, may present difficulties in designing and implementing students’ ideas. Time management may also pose difficulties in meeting project deadlines.

Resources

• AI Education: Funded by Western University, the Leading AI Education Project team has developed AI education resources. Examples include:
  • AI, Fiction, & Possible Futures: Task prompts for classroom activities or term projects spanning various school subjects such as science, technology, math, and language arts.
  • Roots and Fruits of AI: An infographic that provides a comprehensive overview of AI’s development, applications, and impacts, making it a starting point to address curriculum expectations in AI education.
  • The Bots & The Bees and Talking to Whales are dynamic graphic stories for exploring diverse AI applications.
  • From Simple Machines to Machines that Think offers insights into the historical progression of simple machines and their relation to AI concepts.
  • Munchable Matrices assist students in grasping the mathematical algorithms underlying neural networks’ forward propagation.
  • Should I Stay or Should I Switch is a helpful resource for learning AI concepts and connecting them to the math curriculum, especially Conditional Probability.

References

Gadanidis, G., Li, L., & Tan, J. (2024). Mathematics & artificial intelligence: Intersections and educational implications. Journal of Digital Life and Learning, 4(1), 1-24. https://doi.org/10.51357/jdll.v4i1.249

Li, L. (2022). A literature review of AI education for K-12. Canadian Journal for New Scholars in Education/Revue canadienne des jeunes chercheures et chercheurs en éducation, 13(3). https://journalhosting.ucalgary.ca/index.php/cjnse/article/view/76563

Li, L. (2023). Diegetic prototypes in the design fiction film Her: A posthumanist interpretation. Journal of Futures Studies, 27(3). https://doi.org/10.6531/JFS.202303_27(3).0004

UNESCO. (2022). K-12 AI curricula—A mapping of government-endorsed AI curricula. https://unesdoc.unesco.org/ark:/48223/pf0000380602

About the author

name: Li Li

Li Li is a PhD candidate at Western University, specializing in AI education. With a focus on integrating innovative pedagogical approaches, Li Li’s research explores the intersection of design fiction and AI education. Their expertise lies in developing practical resources and activities to enhance interdisciplinary learning across various age groups. Li Li is committed to advancing AI education through research, collaboration, and knowledge dissemination.