AI Literacy for All is a practical AI literacy initiative designed to support both faculty and students in understanding, evaluating, teaching, and responsibly applying generative AI within educational contexts.
The project builds on ongoing work in ethical AI, digital learning, reflective instructional design, and classroom-based AI literacy initiatives. Rather than focusing solely on AI tools, the series emphasizes critical thinking, decision-making, transparency, and human judgment in the age of AI.
AI Literacy for All is designed as a dual-purpose framework:
- Faculty Learning Track: Supports educators in developing the knowledge, judgment, and practical strategies needed to navigate AI in teaching and learning.
- Faculty-to-Student Teaching Track: Provides adaptable resources, activities, and implementation strategies that faculty can use to support student AI literacy within their courses.
The initiative aims to:
- Support faculty through practical guidance, classroom resources, and adaptable teaching materials.
- Help students develop informed, responsible, and reflective approaches to AI use.
- Encourage critical evaluation, transparency, and intentional decision-making.
- Foster meaningful conversations about AI, learning, creativity, authorship, and professional practice.
- Support flexible adoption across disciplines and learning environments.
The Faculty Learning Track is organized around four dimensions:
→ Understand
Develop foundational knowledge of generative AI and its implications for learning.
→ Evaluate
Assess AI use in relation to learning outcomes, student development, and educational goals.
→ Teach
Support student AI literacy through guidance, reflection, transparency, and classroom dialogue.
→ Apply
Integrate AI literacy into existing courses through practical activities, resources, and implementation strategies.
A central goal of this work is helping educators and learners view AI not as a replacement for thinking, but as a tool that still requires active human judgment, reflection, creativity, and decision-making.
This work continues an evolving inquiry into ethical AI integration, student experience, AI literacy, reflective practice, and human-centred approaches to teaching and learning. It is also informed by classroom implementation, faculty development initiatives, and student reflections collected through practice-based AI literacy projects at George Brown Polytechnic.
