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There are many initiatives that teach Artificial Intelligence (AI) literacy to K-12 students. Most downsize college-level instructional materials to grade-level appropriate formats, overlooking students' unique perspectives in the design of curricula. To investigate the use of educational games as a vehicle for uncovering youth's understanding of AI instruction, we co-designed games with 39 Black, Hispanic, and Asian high school girls and non-binary youth to create engaging learning materials for their peers. We conducted qualitative analyses on the designed game artifacts, student discourse, and their feedback on the efficacy of learning activities. This study highlights the benefits of co-design and learning games to uncover students' understanding and ability to apply AI concepts in game-based learning, their emergent perspectives of AI, and the prior knowledge that informs their game design choices. Our research uncovers students' AI misconceptions and informs the design of educational games and grade-level appropriate AI instruction.
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This content will become publicly available on June 29, 2027
Translating Game-Based AI Literacy Activities Across Age Groups: A Pilot Study in Undergraduate Computer Science
As advancements in AI increasingly shape professional and societal practice, the landscape of teaching crucial AI concepts is shifting rapidly. At the undergraduate level, it is critical for computer science students to develop not only technical proficiency but also foundational AI literacy that supports reasoning about how AI-driven systems work and where they may succeed or fail. This paper reports on a pilot study that investigates the adaptation of three game-based learning activities, originally created for informal middle grades educational settings, into an upper-level undergraduate AI course. The activities are grounded in the AI4K12 Five Big Ideas in AI and focus on a range of concepts, including search and reinforcement learning. Findings indicate strong student engagement and suggest that the activities can serve as effective entry points for discussing higher-level AI concepts, while also revealing gaps in students’ mental models of AI systems. The results highlight both the promise and the limits of reusing youth-oriented game-based learning activities in undergraduate contexts and point to design considerations for scaling AI literacy experiences across educational levels.
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- Award ID(s):
- 2148680
- PAR ID:
- 10679498
- Publisher / Repository:
- Springer
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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