Thesis Format
Integrated Article
Degree
Doctor of Philosophy
Program
Education
Supervisor
Gadanidis, George
Abstract
As artificial intelligence (AI) increasingly permeates various sectors of society, it becomes crucial to develop educational approaches that prepare students for the concepts, applications, consequences and ethical considerations of AI. This dissertation investigates how current AI education strategies can be enhanced to better prepare K-12 students for the challenges associated with understanding and navigating AI’s impact on society. Specifically, it examines the potential of Design Fiction Pedagogy (DFP) in advancing AI education for addressing a gap in existing pedagogical methods.
The research employs both theoretical studies and an empirical case study. The theoretical component develops a model of DFP, which integrates speculative design with narrative learning principles. The empirical investigation involves a case study of two separate week-long AI camps conducted in Ontario, Canada, where DFP was applied to engage students in exploring possible AI futures.
Key findings reveal that design fiction, as a pedagogical method, may offer benefits for AI education. The DFP model has the potential to enhance AI education through its flexible adaptation in various settings. By integrating speculative design and narrative techniques, DFP makes abstract AI concepts and applications more accessible and relevant, fostering a deeper understanding among students. Additionally, it encourages students to consider the ethical implications and future impacts of AI technologies, promoting both ethical reflection and critical thinking. This approach may improve AI educational outcomes and equip students with the mindset and skills needed to navigate the applications and consequences of AI with a future-oriented perspective.
By highlighting the potential of design fiction to bridge theoretical and practical aspects of AI, this research offers insights for educators and researchers aiming to prepare students for the challenges of a technology-driven future. DFP’s integration into AI education represents a step towards more engaging and effective teaching strategies. Further exploration and refinement of DFP is needed, to better understand its role in shaping educational practices and enhancing students’ readiness for an increasingly complex technological landscape.
Summary for Lay Audience
As artificial intelligence (AI) becomes more integrated into our daily lives, it is important for schools to teach students about this technology in ways that are engaging and insightful. This dissertation explores how a new teaching method, Design Fiction Pedagogy (DFP), may help improve how we teach about AI concepts, applications, consequences and ethics to K-12 students.
The study addresses a key question: How may DFP—a method that combines creative design with storytelling—help to better prepare students for the challenges of AI?
To answer this, the research includes both theoretical work and an empirical case study. The theoretical part of the study develops a model for DFP that blends speculative design (imagining possible futures) with narrative learning (using stories to teach). The practical part involves a case study of two separate week-long AI camps in Ontario, Canada, where DFP was used to engage students in exploring possible AI futures.
The key findings show that DFP has the potential to be a powerful tool for teaching about AI. It helps students grasp AI concepts and application more easily and makes the learning experience more relevant. By using creative scenarios and storytelling, DFP encourages students to think about the ethical implications and future impacts of AI technologies. This method may improve how students learn and prepare them to tackle the challenges of a tech-driven world.
Overall, this study highlights that by using speculative and narrative techniques, DFP has the potential to make learning about AI more accessible, engaging, and reflective. The insights from this research are valuable for educators and researchers to better prepare students for a future shaped by technology.
Recommended Citation
Li, Li, "AI Education and Design Fiction" (2025). Electronic Thesis and Dissertation Repository. 10687.
https://ir.lib.uwo.ca/etd/10687
Included in
Curriculum and Instruction Commons, Educational Methods Commons, Educational Technology Commons, Elementary Education Commons, Science and Mathematics Education Commons
