Title: Level Up AI
Subtitle: Game-Based Learning for AI Literacy in a Complex World
Subject Classification:  Artificial Intelligence, Education, Technology  
BIC Classification: UYQ, JN, TB
BISAC Classification: COM004000, EDU039000, EDU029030
Binding: Hardback, eBook
Planned publication date: Oct 2026
ISBN (Hardback): 978-1-83711-577-8
ISBN (eBook): 978-1-83711-578-5

e-books available for libraries from   Proquest  and   EBSCO   with non-institutional availability from  GooglePlay

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Description

The central aim of Level Up AI is to provide a replicable, flexible model for AI literacy instruction that mirrors the interdisciplinary and uncertain nature of real-world AI systems. Rather than isolating AI education within computer science, the book invites learners to explore connections across astronomy, biology, literature, history, and the arts—fields where ambiguity, interpretation, and context deeply matter.

Game-based learning serves as a pedagogical approach to confront these complexities. By immersing students in interactive simulations and narrative-rich scenarios, games create safe environments to navigate uncertainty, make decisions with incomplete data, and reason through the ethical and civic dilemmas AI often presents. Students grapple with questions like: How should an algorithm rank applicants for public housing, and what trade-offs are fair? What might an AI misinterpret in a historical photograph, and how do biases enter the system? How do AI models classify galaxies—or generate visual art—and what happens when those classifications go wrong?

Biography

Author(s):  Zhichun Liu is an assistant professor at Hong Kong University, Hong Kong. Xiaoxue Du is an adjunct assistant professor at Teachers College, Columbia University.

Reviews

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