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Posts Tagged ‘Adam Garry’

I have been thinking a lot about assistance lately. Who gets it, who does not, and why we suddenly get moralistic about it the moment the assistance comes from AI.

The spark for this post is Nick Potkalitsky’s Substack essay, “In Praise of Assistance.” It is one of those pieces that does not just add to the AI and writing conversation. It reframes it (Thanks to Adam Garry for pointing me towards it).

Nick starts from the now familiar worry about “cognitive offloading,” students delegating the thinking to a tool, and he agrees the concern is real. But then he names what often sits underneath the concern: not just pedagogy, but ideology.

He argues that the cognitive offloading critique rests on “a historical fiction: the autonomous learner.” Because if we are honest, most of us did not learn to write (or think, or revise) alone.

My own invisible advantage

In high school, I had a huge advantage: my dad was an English teacher, and he read every essay before I submitted it. Not just English essays. All of them, across every subject.

He did not write my essays. But he did what good teachers do. He asked questions I had not thought to ask. He pointed out where my logic sagged. He helped me tighten sentences. He coached me toward clarity.

That continued through university. And years later, when I became a newspaper columnist, he was still my first reader. Every column went to him before it went to my editor. He would call with suggestions, and I would decide what to keep and what to let go.

At the time, nobody called this cheating. We called it support. Nick puts it simply: “Students have always learned through assistance. From peers, from teachers, from resources…” 

We rarely worry students are “offloading” onto classmates in a discussion. We celebrate it. But when AI enters the picture, suddenly assistance becomes suspect.

That is the tension.

The question is not “help or no help”

When we talk about AI and writing, the debate often collapses into a binary: real writing (alone, unaided) versus fake writing (assisted, scaffolded).

But that binary does not match how writing actually works. It does not match how learning has actually  ever worked.

The better question is the one Nick keeps pointing us toward: what kind of assistance builds thinking, rather than replacing it?

That is where his essay becomes more than a defense of AI. It is a critique of an unspoken standard that has been unevenly distributed for a long time. The idea that “authentic struggle” is the price of admission to learning.

Nick names the class based reality bluntly: affluent students often have “small seminars, writing conferences, office hours, peer review sessions” while others are in systems where meaningful feedback barely exists. And then comes the sentence: “The outcome depends on whether we recognize assistance for what it is: not a threat to learning, but its precondition.”

What I have been writing toward

In October, I wrote “Modeling AI for Authentic Writing.”  If AI is here (it is), then our job is to model the kind of use that keeps the writer in control. In that post, I tried to move the conversation from “Don’t use AI” to “Show your decisions.”

Because the heart of authentic writing is not whether you had help. It is whether your thinking is present. What did you accept? What did you reject? Why? What did you learn in the revision?

I wrote then: “None of this replaces judgment. I accept or reject every change.”

For years, Tricia Buckley, and before her Sharon Pierce and Deb Podurgiel, have played a similar role here on this blog, reading every post before publication and offering feedback. The byline is still mine because the ideas, voice, and final choices are mine.

That is the point.

Assistance is not the enemy of learning. Abdication is.

What I want to add

There is a system design question underneath that I keep circling back to.

If we accept that all learning has always been assisted, what changes about how we run schools?

A few weeks ago I wrote about the tutoring revolution and found myself wrestling with a similar tension. For years, success in certain courses quietly required something extra: a tutor. Parents traded recommendations, students admitted they needed help, and the whole system ran on an unspoken understanding that school alone was not enough. At least not for everyone.

AI is changing that. But here is the part that worries me: the digital divide is no longer just about device access. It is about knowing how to use the tool well. A student with strong digital literacy might turn ChatGPT into a Socratic tutor. Another might never get past using it as a homework completion machine.

Nick writes about elite students who have always had access to “assistance made flesh.” The risk now is that we create a new version of the same divide. Some students learn to collaborate with AI in ways that deepen their thinking. Others use it to bypass thinking altogether. And if we are not intentional, digital confidence becomes the new proxy for privilege.

The question is not whether students will have AI assistance. They already do. The question is whether we will teach them to use it in ways that build capacity or let the gap widen on its own.

A Culture of Yes stance

A Culture of Yes does not mean saying yes to every tool or every shortcut.

It means saying yes to the conditions that help more people learn well.

So here is where I am landing, at least today.

Writing has always been assisted. The myth of the autonomous writer has always favoured students with the most support. AI can absolutely be used to bypass thinking. But it can also be used to invite thinking, especially where feedback is scarce.

Our job is to design and model practices where assistance makes thinking visible and growth possible.

Nick’s essay refuses the easy frame. It asks us to stop policing help and start building learning communities where help is normal, explicit, teachable, and more equitably available.

That feels like the kind of “yes” worth defending.

The image at the top of this post was generated through AI.  Various AI tools were used as feedback helpers (for our students this post would be a Yellow assignment – see link to explanation chart) as I edited and refined my thinking.

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This is not my last post of the year, but as we move through the middle December I wanted to pull together various threads and posts from this year on AI, and a few thoughts about what comes next. I find myself reflecting on what has been a transformative year for me as an educator, leader, and writer. Few technologies in my career have reshaped the way I think, work, and innovate as rapidly as AI has over the past twelve months.

This year, I have explored the opportunities and challenges of AI in education in a series of blog posts. It has been a journey of enthusiasm, curiosity, and learning, punctuated by moments of skepticism and concern. Now, as we approach 2025, I sense that we may be entering what the Gartner Hype Cycle calls the Trough of Disillusionment. And yet, I believe this is where the real work begins.

Here is my best effort at pulling together various posts I have written, presentations I have participated in and other learnings from this year:

Blog Posts

Gen AI – Governments, Districts, and Schools (May) Examining how British Columbia’s education system addresses generative AI, detailing the roles of the provincial government in providing guidance and resources, and individual school districts in implementing specific tools and fostering community engagement.

Leveraging Generative AI for Elementary Learners at Home (Sept) Offering parents practical advice on integrating generative AI into their children’s home learning, suggesting activities like using AI for writing assistance, personalized learning paths, and creative projects, while emphasizing the importance of safety and balance.

Exploring the Role of Generative AI in Supporting Governance (Sept) Exploring how generative AI can enhance school district governance by aiding in communication, professional development, policy drafting, strategic planning, and scenario analysis, advocating for a learning mindset among leaders.

Gen AI and the High School Sports Coach (Oct) This piece discusses the potential of generative AI to support high school sports coaches in areas such as creating training plans, simulating game strategies, preventing injuries, providing performance feedback, and developing skills, while acknowledging the importance of human judgment.

The Stages of Gen AI Adoption in Schools (Oct) Outlining a three-stage process for integrating generative AI in education: personal use by staff, professional use for tasks like lesson planning, and direct application with students, emphasizing gradual adoption to build confidence.

Leading the AI Charge:  Strategies for Forward Thinking Districts (Oct) Sharing strategies for school districts to effectively integrate AI, including designating leadership roles, forming cross-functional teams, creating clear guidelines, focusing on key applications, engaging the community, modeling AI use, consulting external experts, and participating in networks.

When AI Meets Education:  The Power of Diffusion Over Replication (Nov) A reflection  on the organic adoption of AI in education, advocating for trust in educators to adapt AI tools to their unique contexts, and promoting the diffusion of innovation through professional dialogue and shared experiences.

Video Presentations

The West Vancouver Story (Sept) – Cari Wilson, Megan Roughley and I share perspectives from our different vantage points on the use of AI in West Vancouver.  

AI Unlocked (Oct) – Presentation specifically for support staff in West Vancouver with an overview of AI and ways it could be incorporated into work that support staff do.  

Generative AI in K-12 (Oct) – Cari Wilson and I along with grade 12 student Jadyn Mithani shared our current work in AI and advice as part of a UBC speakers series.

Alec Couros Presentation (Oct) – West Vancouver has worked with Alec Couros from the University of Regina as we grow AI understanding in our community.  This video is a presentation he did for parents in the community.

Where I am Learning

On social media, I am finding LinkedIn to be my go to place for AI learning.  If I identified a couple people to add to your network they would be Adam Garry and Leon Furze.  Adam works with school districts across North American, including West Vancouver, as we look to thoughtfully plan for AI use in our systems and Leon is out of Australia and digs deep into both practical and ethical considerations around AI.

I also find podcasts super helpful.  There are lots of good ones, but the one I listen to every week is the TED AI Show with Bilawal Sidhu.

Of course, much of AI is just about playing.  I find myself going to AI first before Google, and regularly thinking if AI could add value – either efficiency or quality to the work I am doing.  


Reflections on the Year

As I look back, I’m struck by how much my thinking has evolved. At the start of the year, AI felt like an exciting frontier—a tool to experiment with and explore. By mid-year, it became clear that AI is no longer optional for educators. It’s a fundamental shift that requires us to rethink everything from pedagogy to policy.

Now, I see the cracks emerging—the Trough of Disillusionment. Educators are grappling with questions about bias, misinformation, and the ethical use of AI. Some are even questioning whether the promises of AI can be fulfilled. These doubts are natural. They are a sign that we’re moving beyond the initial hype and beginning to confront the complexities and possible outcomes.

Moving Forward with Hope

What gives me hope is that education has always been about people, not technology. AI is a powerful agent—but it’s our creativity, empathy, and leadership that will determine its impact. As we move into 2025, I am committed to continuing to push this dialogue and think about the impact of AI on our system today and into the future.

I am so appreciative of my network –  thank you for engaging with these ideas this year.  As I have regularly noted, it is the power of the network that is crucial in our AI work. Whether you’ve agreed, challenged, or simply reflected, widespread engagement has made the conversation richer and is crucial as we look ahead.

My “Top 3” Post will come next week, but for all wrapping up in schools this week before the break – Happy Holidays!

Ironically, I did not use a lot of AI in this week’s post.  The image at the top is generated in Magic School AI.

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