AI Literacy for Higher Education Faculty
A research-based 4-workshop series for university faculty on AI-resilient assessment redesign. Moves beyond surveillance-based detection toward intentional pedagogical transformation, grounded in Conceptual Change Theory, Social Constructivism, and Metacognitive Scaffolding.
Executive Summary
This project addresses the challenge of cognitive offloading and academic integrity in higher education as Generative AI becomes a primary tool for student productivity. Designed for university faculty, the initiative moves beyond traditional surveillance-based detection to focus on intentional assessment redesign.
The core of the intervention is a four-phase curriculum built on a tri-lens theoretical framework:
- →Conceptual Change Theory: Using cognitive dissonance through live AI failure demonstrations (forced hallucinations) to dismantle outdated mental models and create a felt need for new pedagogical strategies.
- →Social Constructivism: Facilitating collaborative sense-making via gallery walks and peer-to-peer policy drafting, allowing faculty to co-construct institutional norms.
- →Metacognitive Scaffolding: Implementing structured journal reflections and synthesis worksheets that force faculty to isolate high-order human cognitive processes, such as judgment and contextual evaluation, that AI cannot reliably replicate.
The project delivered a full institutional plug-and-play suite, including a Strategic Rationale Report, Facilitator Field Guides with scripted talk-tracks for handling faculty skepticism, and Interactive Participant Worksets. The result is not just a technology tutorial but a research-grounded blueprint for sustainable institutional transformation.
01. The Challenge: Bridging the Intuition Gap
Why AI Literacy for Professors?
Higher education faculty often enter the AI conversation with strong but conflicting intuitions, ranging from high anxiety to over-optimism. The core problem identified in this project was not just learning how to use tools, but re-evaluating what "academic integrity" means when cognitive offloading becomes effortless.
The Goal: Move faculty from a mindset of detection and prevention to one of intentional assessment redesign.
02. The Solution: A Four-Phase Arc
From Awareness to Institutional Transformation
I architected a modular, four-workshop series designed to lead faculty through a psychological and pedagogical shift:
- Workshop 1: Foundations & Reflections: Surfacing mental models and confronting the hallucination risks of LLMs through live demonstrations.
- Workshop 2: Assessment Redesign: Moving from "AI-vulnerable" to "AI-resilient" tasks.
- Workshop 3: Policy & Communication: Developing transparent classroom frameworks (Green/Yellow/Red zones) for AI use.
- Workshop 4: Equity & Transformation: Addressing the digital divide and ensuring AI does not widen existing educational inequalities.
03. Design Strategy: Inducing Cognitive Dissonance
Turning Research into Experience
To engage a skeptical academic audience, the design utilised Conceptual Change Theory. Rather than telling faculty that AI is unreliable, I designed experiences where they could see it fail in real time.
- →The "Dolphin" Experiment: A live demo where AI is prompted to explain why dolphins are fish, exposing how confidently LLMs produce false claims.
- →The "Coffee" Hallucination: Forcing the AI to generate fake peer-reviewed citations proving coffee cures anxiety, demonstrating fabrication at the source level.
- →The "Human-in-the-Loop" Worksheet: A structured reflection tool that forces participants to identify which cognitive processes, such as evaluation, judgment, and contextual application, AI cannot replace.
04. Comprehensive Artifact Suite
This project provides a plug-and-play solution for university departments, featuring a full library of implementation materials. Each artifact is designed so that a department head with no prior AI background can run the full workshop series with high fidelity.
- →The Strategic Rationale (Report): A deep dive into the learning science and situational analysis behind the curriculum, grounding the intervention in peer-reviewed theory.
- →Facilitator Field Guide: A sample comprehensive guide for Workshop 1 that empowers any department head or facilitator to lead sessions with high fidelity, including scripted talk-tracks for handling faculty pushback and skepticism.
- →Visual Narrative (PPT): A sample deck for Workshop 1 facilitators featuring 2024 citations on LLM reasoning collapse and truth-verification struggles.
- →Participant Reflection Worksheet: A sample worksheet for Workshop 1 and the "Active Learning" engine of the workshop, facilitating small-group sense-making and assessment redesign.
05. Key Insights & Professional Takeaways
- →Assessment as the Anchor: AI is not a threat to education; it is a threat to outdated assessment. By anchoring the workshop in assessment redesign, we transform faculty anxiety into creative agency.
- →Psychological Safety: Workshop 1 focuses heavily on surfacing intuitions. Before faculty can learn new technology, they must feel that their fears about academic integrity are heard and normalised.
- →Scalability via Documentation: The Facilitator Guide ensures the intervention can be scaled across an entire university without losing the nuances of the pedagogical research.
