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Practical Classroom Strategies to Build/Support AI Literacy
Inspired by University of Toronto Libraries Framework for AI Literacy
Feel free to add more ideas to this spreadsheet!
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AI Literacy DimensionPedagogical StrategyPossible Context(s)Learning Outcome(s)Implementation NotesAI Usage RequirementNotes/Comments
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Technical Foundations / Understanding
AI “Demystification” Mini-Lectures with ReflectionIntro-level or survey courses across disciplinesStudents can explain in plain language how generative AI tools work, their training data, and major limitations.Faculty provide a short explainer on how LLMs work, followed by a reflective activity.
Faculty uses AI (to demo outputs/explain concepts)
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Technical Foundations / Understanding
Reverse-Engineering AI OutputsWriting, business, STEM courses using AI-generated contentStudents can identify patterns in AI output and link them to model training.Students compare multiple outputs for the same prompt, hypothesize model behavior, then debrief.Faculty + Students use AI
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Technical Foundations / Understanding
Short AI Concept QuizzesAny discipline; especially effective in large lecturesStudents demonstrate comprehension of basic AI terms (hallucination, bias, token, prompt).Low-stakes LMS or clicker quizzes after AI-related content.No AI use required
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Functional Use & ApplicationPrompt Comparison ExercisesWriting-intensive or applied coursesStudents craft and compare prompts and evaluate output usefulness.Provide a scenario, have students generate with different prompts and reflect.Students use AI
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Functional Use & ApplicationAI-Enhanced Drafting with Peer ReviewCourses with essays, reports, project proposalsStudents use AI to draft/brainstorm then apply peer feedback.Structured peer review where AI contributions are documented.Students use AI
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Functional Use & ApplicationApplied AI Tool ExplorationProfessional courses (engineering, health, business)Students demonstrate competence in applying a discipline-relevant AI tool.Low-stakes assignment: trial an AI tool, document steps, reflect on usability.Students use AI
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Critical / Evaluative SkillsAI Output Fact-CheckingResearch, social sciences, humanitiesStudents can verify accuracy of AI claims and citations.Summarize an article with AI, then fact-check against original.Students use AI
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Critical / Evaluative SkillsComparative Evaluation of AI ToolsCourses with diverse research or applied tasksStudents compare outputs across tools and evaluate against standards.Use two AI tools for same task, compare, and critique.Students use AI
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Critical / Evaluative SkillsAI Reliability RubricsMid- to upper-level coursesStudents apply a rubric to assess AI-generated text for credibility, logic, bias.Provide a rubric (accuracy, relevance, ethics, completeness), apply to outputs.
Faculty provides AI text; Students may use AI
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Ethical / Societal / Policy Awareness
AI Case Study DebatesAny discipline; seminarsStudents articulate ethical risks and societal implications of AI.Provide case studies, have students debate pros/cons.
No AI use required (optional faculty demo)
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Ethical / Societal / Policy Awareness
AI Policy Review AssignmentProfessional or policy-focused programsStudents summarize and critique institutional/disciplinary AI use policies.Compare YorkU principles with discipline-specific norms.No AI use required
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Ethical / Societal / Policy Awareness
AI and Equity Reflection JournalsGeneral education or capstone coursesStudents reflect on how AI may exacerbate/reduce inequities in their field.Weekly journal prompts (e.g., 'Whose voices are amplified/erased by AI?').No AI use required
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Creativity, Communication & Human-Centeredness
AI + Human Co-Creation ProjectsArts, design, communication, interdisciplinaryStudents integrate AI outputs into a project while maintaining originality.Create multimedia artifact with AI + human contributions documented.Students use AI
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Creativity, Communication & Human-Centeredness
Rhetorical AI AnalysisWriting or communication coursesStudents analyze rhetorical moves in AI outputs.Provide AI-generated texts; students analyze persuasion, bias, omissions.
Faculty provides AI text; Students analyze
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Creativity, Communication & Human-Centeredness
Human Voice Preservation AssignmentAdvanced writing or media coursesStudents practice editing AI drafts to preserve voice and nuance.Students input their work, compare AI rewrite, reflect on changes.Students use AI
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Adaptability & Lifelong LearningAI Tool Scavenger HuntIntroductory courses for non-specialistsStudents explore emerging AI tools and report functions/limits.Assign students to explore tools, present short summaries.Students use AI
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Adaptability & Lifelong Learning“Future-Proof” Project ReflectionCapstone or final-year coursesStudents articulate strategies for adapting to new AI tools in profession.Write reflection on expected future tools and preparation strategies.No AI use required
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Adaptability & Lifelong LearningAI Literacy Self-AssessmentAny course, early or late in programStudents assess their strengths/weaknesses in AI literacy.Pre/post surveys; students set AI literacy goals and reflect.No AI use required
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Disciplinary / Domain SensitivityAI-in-Discipline Case StudiesDiscipline-specific courses (health, law, engineering, humanities)Students analyze how AI is used in their field.Case study analysis from disciplinary sources.
No AI use required (optional faculty demo)
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Disciplinary / Domain SensitivityCustomized AI Ethics ScenariosUpper-level discipline coursesStudents articulate ethical concerns specific to their field.Role-play deciding whether/how to use AI in a case.No AI use required
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Disciplinary / Domain SensitivityDiscipline-Specific AI Tool CritiquesProfessional programsStudents evaluate a discipline-relevant AI tool.Test tool, critique limits, propose responsible practice.Students use AI
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