Ethical AI & Digital Learning

Artificial intelligence is reshaping teaching and learning, yet many educators are still navigating how to respond. This session reframes AI as a course design issue rather than a technical problem, focusing on how clarity, transparency, and intentional decisions can support ethical AI use.

Drawing on practice-based work with faculty, it highlights simple, adaptable strategies such as clear AI guidance, reflection-based assessment, and approaches that move beyond all-or-nothing thinking. The focus is on creating learning environments that support engagement, trust, and student responsibility.

The QM Learning Path is a structured digital resource designed to support faculty in creating high-quality, accessible, and engaging online and blended courses. Grounded in the Quality Matters Higher Education Rubric, it offers practical tools, checklists, and interactive modules to guide course design and improvement.

Developed as a flexible, self-paced resource, the Learning Path helps educators translate quality standards into actionable design decisions, with a focus on alignment, learner engagement, accessibility, and assessment.

This session demonstrates how UDL principles can be applied through interactive and multimedia design in higher education. Using practical examples such as scenario-based activities, escape rooms, and multimodal content, it highlights strategies for creating more accessible, flexible, and engaging learning experiences.

This session explores how educators can engage with AI in ways that are ethical, inclusive, and aligned with their teaching goals. Rather than focusing on tools, it reframes AI literacy as pedagogical decision-making, especially around when AI should not be used.

A practical framework and supporting resources are provided to help educators make intentional, transparent decisions about AI in their courses.

AI Literacy for All is a practical AI literacy resource series designed to support both faculty and students in understanding, evaluating, and responsibly applying generative AI in educational contexts.

The project builds on my ongoing work in ethical AI, digital learning, and reflective instructional design. Rather than focusing only on tools, the series emphasizes critical thinking, decision-making, and human judgment in the age of AI.

The initiative is designed to:

• support faculty with adaptable teaching resources and downloadable materials
• help students develop practical and responsible AI literacy skills
• encourage reflection, evaluation, and intentional AI use across disciplines

The series is organized around three core dimensions of AI literacy:

→ Understand

→ Evaluate

→ Use AI responsibly

A central goal of this work is helping learners see AI not as a replacement for thinking, but as a tool that still requires active human judgment, reflection, and decision-making.

This work continues my evolving inquiry into ethical AI integration, student experience, AI literacy, and human-centred approaches to teaching and learning.

Simple Ways to Set Clear AI Expectations in Your Course

This faculty development workshop introduces practical, low-overload approaches to communicating clear AI expectations in courses. The session focuses on supporting transparency, student reflection, and responsible AI use.

Designed and facilitated by Evelyn Chan, the workshop engages participants with ready-to-use resources, including AI guidance templates, reflection prompts, and reusable H5P materials for Brightspace.

The approach is informed by ongoing implementation and iteration in courses at George Brown Polytechnic.

George Brown TLX Day (Wintersession)

This session introduced the TLX Course Quality Checklist as a practical, research-informed tool aimed at enhancing AI literacy, digital learning, and course clarity across various teaching modalities. The poster-style format encouraged informal dialogue and low-overload engagement, while also offering optional follow-up support for faculty in leveraging educational technology.

Role
Evelyn Chan
Educational Technology & Digital Content Specialist (TLX), George Brown Polytechnic