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Learning Together

A preliminary exploration of Lo’s CARE approach for academic librarians: From search first to answer first with generative AI through the lens of Freirean pedagogy 

Caitlin McClurg, MLIS

Librarian, Libraries and Cultural Resources. University of Calgary

CAPAL Conference June 22-23, 2026

Lightning Talk

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Lightning Talk

Who are Paulo Freire and Leo Lo?

Considering AI literacy frameworks through the lens of Freirean pedagogy

Moving forward together

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Paulo Freire (1921-1997)

  • Brazilian educator/philosopher
    • Grew up in Great Depression and political unrest
    • Illiteracy barred Brazilians from voting
      • Freire developed a pedagogical approach for the oppressed to liberate learners by recognizing experience
    • He was deemed a radical, was imprisoned and subsequently exiled
  • Core philosophies:
    • Critical consciousness
      • one must understand their reality to participate in learning activities
    • Transformative action results in social change
    • Dialogical processes for learning
      • idea exchange through discussion, rooted in transformation and action processes
  • Banking model of education
    • Hierarchical process of depositing information
      • Expert and novice do not exchange ideas
    • Lived experience (personal/changing) disconnected from knowledge (facts/fixed information)
  • Problem-posing model
    • Critical questions are asked and considered through a process of reflection and action
    • Social reality is prioritized

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Leo Lo

  • Dean of Libraries, Advisor for AI Literacy: University of Virginia
  • Past President of the Association of College & Research Libraries (ACRL)
  • Established national (US) Task Force of AI Competencies for Library Workers
  • CLEAR framework (prompt engineering)
    • Concise, Logical, Explicit, Adaptive and Reflective
    • Lo, L. S. (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship, 49(4), 102720.
  • CARE approach for AI literacy
    • Care, Assess, Review, Enhance

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The Big Questions

  • Back to the Banking Model?
    • Does generative AI bring the collective back into the banking model of learning and education?
      • "Tokens" are the word for the unit/block of data processed by AI models
      • AI requires both digital information literacy and access to AI (free, or paid subscriptions)
      • Information exchange can be as simple as a deposit in and a return out
  • How is Critical Consciousness relevant to generative artificial intelligence?
    • Models trained on datasets (bias exist)
    • How is lived experience reflected (or not) in AI conversations and broader machine learning?
  • What about Problem-Posing instead?
    •  Open-ended questions to liberate learning conversations away from prescriptive one-way teaching approaches
    • While prompting models exist that tout specificity in their structure, the opportunity exists for flexibility and critical review is encouraged.

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Using Freirean Pedagogy within the CARE Approach

  • CARE moves the searching process from the traditional database orientation “search first” to “answer first” via machine learning
  • Freirean pedagogy is rooted in dialogical exchange, whereby co-creation of ideas emerges from storytelling, conversations and other modes of communication
    • This learning process is more complex than simple discussion, there is an emphasis on social justice and understanding of one's positionality and context
    • Listening to understand; responding to meaningfully contribute
    • Moving away from passive consumption of information

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Preliminary Mapping of the Frameworks

CARE Approach

Freirean Pedagogical Approaches

Classify: Are you asking the AI to produce facts, offer interpretation, format something, or be strategic in shaping a process or workflow?

Problem-posing: Gen AI users are encouraged to determine what they need at the outset. Learner is liberated to seek the answer first rather than being directed.

Assess: user interrogates the output for tonality, provided evidence/citations, bias or nuance

Interrogation of the banking model: the instant and authoritative nature of gen AI responses lulls the learner into a passive receptacle of information. Librarians can help people question and assess the resulting information.

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Review: Engage in traditional research processes to cross-check output against verifiable sources

Dialogical engagement: The learner/gen AI user reviews the results and engages in a critical process of discovery and verfication.

Enhance: Rework the prompt, or ask sophisticated follow up questions to further refine, avoiding the pitfall of the tool being the all-knowing entity in the exchange.

Praxis: The learner/gen AI user responds to the tool to redirect or request clarification. Learner transformation occurs when both reflection and action is actively engaged.

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Learning Together

  • CARE model:
    • The answer-first approach maps well to the pedalogical underpinnings that empower learners and users of this technology
  • Critical consciousness whereby individuals recognize:
    • Social, political and economic contradictions
    • Take action to combat oppressive forces
  • ​Prioritize the human
    • Center the human user through using AI to synthesize information
    • Pedagogy of hope

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References

Freire, P. (2000). Pedagogy of the oppressed (30th anniversary ed.). Continuum.

�Lo, L. S. (2026). The CARE approach for academic librarians: From search first to answer first with generative AI. The Journal of Academic Librarianship, 52(1), 103186.