As artificial intelligence drives profound change, it opens new possibilities for teaching and learning while shifting the focus toward essential student competencies. Teaching and assessment practices must evolve to meet the changing needs of young people, raising key questions: What learning experiences are most relevant? And how can we embrace new ways of educating students? During a national webinar hosted by the EdCan Network, education experts explored how to support educators in integrating AI into their practice while creating learning environments that foster the transferable skills students will need for the future.
Artificial intelligence is catalyzing profound change in education, shifting the focus from content delivery to the development of global competencies. Building on earlier conversations in this webinar series—on ethics and AI, and on AI and future skills—organized by the EdCan Network in partnership with Engaged Learning by École branchée and The Dais, this third and final webinar brought together education experts to examine how schools can adapt to this new reality. The discussion emphasized teacher empowerment, evolving assessment practices, and the enduring importance of the human element in the classroom.
The panelists:
Here are the key takeaways from the discussion. They will be explored and supported throughout this article.
To help students develop essential human skills such as critical thinking and adaptability, teachers must first be supported in developing these competencies themselves. Joelle Rodway suggests that the distinction between “teacher” and “student” is becoming increasingly blurred. As she notes, “Everybody is showing up as a student… the best way forward here is for teachers to recognize that they are also learners.” By modelling curiosity and a willingness to “fail forward” when engaging with new technologies, educators can better guide students in developing ethical practices.
However, this shift requires systemic support. Panelists emphasized the importance of fostering “permission-based cultures,” where teachers feel safe to innovate without fear of failure. Sarah Rankin underscores this need: “We need to empower our teachers to feel comfortable enough to explore AI… so they don’t see it as a taboo subject.”
AI’s ability to generate polished essays in seconds has exposed “weak spots” in traditional assessment. The consensus among panelists is a shift from evaluating the final “product” to evaluating the “process”. Sarah Rankin highlights that the “final product is not enough anymore. Especially if AI can do it all and it can build that product very easily, then what do we really need to measure? Is it the end product or is it how you got to that product?”. Measuring the process involves “triangulating” data through conversation, observation, and work habits—elements that are much harder for a student to “AI”.
Mohammed Estaiteyeh suggests moving toward “performance-based authentic assessments in the classrooms, tasks that are messy, open-ended, they are rooted in real contexts, which also bring me back to the interdisciplinary concept… if the teaching is interdisciplinary, the assessment has to address this interdisciplinarity”. Instead of simple recall, students should be asked to defend positions or critique AI-generated work. In some districts, AI is even being used to improve assessment.
Caroline Roberts described an AI agent called “CART” used at Foothills School Division to help teachers communicate student learning more consistently. “It’s connected to our curriculum and so it is a tool that we can use to grow the practice of communicating student learning and more effectively align that communication… that’s how we’re using AI and actually looking at it and aligning with curriculum implementation and our instructional design”.
While AI can automate technical instruction, panelists were adamant that it cannot replace the relational essence of education. Mohammed Estaiteyeh distinguishes between “instruction,” which is a technical act, and “education,” which is human. He notes, “AI tools can replace some of what the teachers do, but they wouldn’t replace what teachers are for their students”. He points to the pandemic as evidence: despite having technology and content, “engagement collapsed” because the “human infrastructure” was missing.
Caroline Roberts summarized this sentiment with a powerful divisional mantra: “Artificial intelligence can personalize learning; only human teachers can humanize it”. Ultimately, learning is a “social practice,” and as Joelle Rodway concluded, while AI is a powerful assisting tool, it remains a machine that lacks the mentorship and trust provided by a human educator. The future of the classroom lies not in replacing the teacher, but in leveraging AI to keep “teachers and students at the centre of learning”.
Click here to watch the webinar!
Below is a curated list of references shared in the chat, along with a selection of relevant Engaged Learning resources to help extend the conversation and deepen reflection.
Video shared: Pedagogical Debt: What We Owe Our Students in an AI World
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