being it > doing it
thoughts on competency in the age of AI
The fury of end-of-term marking is finally behind me, and I’m settling into that hazy period of debriefing what I’ve learned over the past year. Even after teaching the same course for so long, I still feel the need to challenge myself each time I step back into it.
Since 2020, being an educator has been one adventure after another or, depending on how you view it, one calamity after another.
The COVID-19 pandemic stretched teachers beyond our limits as we learned new ways to teach in remote spaces and worked to keep students’ spirits up in a world that felt unstable. For many teachers, the years from 2020 to 2023 blurred together. Just as we were beginning to find our footing, generative AI arrived on the heels of those changes, and for many educators, it’s felt like the last straw.
After all the work I’ve done in my dissertation, and the lessons I’ve learned along the way, one insight I keep returning to is that how I choose to view what lies ahead is one part of the situation I can control. I’ve been choosing to use the current tumult of the world as a kind of permission to look for new opportunities in my classroom.
With that in mind, last week I attended a campus conference that was all about assessment methods. Now, if you know me, you know that there are few things that get me more excited than assessment, so I went into the experience ready to soak up some new ideas to try next year. I was not disappointed.
Lately, I am finding that the more secure and confident I become in my educator identity, the more I am drawn to making my pedagogy and practices both simpler and more counter-intuitive to the “norm” of what is expected. One example that most of you will recognize from me is that, rather than embracing the “either/or” hierarchy that academia often imposes, I choose to advocate for a “both/and” approach.
I saw this same approach reflected in the keynote address for the conference, where I was struck by a shift in how the speaker, Susan Bens, framed her opening remarks. Dr. Bens is our campus’s Academic Integrity Specialist, and she spent most of her address showing that academic misconduct is only a small part of the broader practices of academic integrity.
What stood out most to me in Dr. Bens’ approach is that many of the conversations I have had around assessment in today’s classroom, especially in relation to AI, focus on reacting to academic misconduct, rather than on exploring more proactive ways to help students engage with their academic integrity and develop a sense of identity in their work.
Another line that stayed with me from Dr. Bens’ address was the simple truth that “There’s not a single cause to academic misconduct, which means there’s not a single solution to resolving it.” And yet, much of our response in academia remains fairly singular.
It does not matter how many blue-book, in-class essays we require our tech-reliant students to write — there needs to be more than fear + security measures if teachers are going to navigate the slop-filled waters of assignments today.
Even with that in mind, acknowledging the constraints of our educational context is not the same as putting up a white flag or accepting mediocre, generated work. After my past year of teaching technical communication, along with the ideas I gathered at last week’s conference, I can see real teaching opportunities ahead.
More than anything, I can see how this AI-fuelled moment has brought me back to a renewed confidence in the basics of what I am teaching.
That focus led me toward one of the workshop streams at the conference, which had to do with “Assessing Professional Competencies in Diverse Contexts.” It drew my attention right away.
I’ve said it before, but there’s nowhere else I’d rather be on campus than as a humanities person teaching in a technical context (the ultimate both/and). Staying in that space means keeping up with how best to support students in building competence in communication, which also means staying as informed as possible.
A defining feature of our College’s first-year Re:Engineered program is that it is designed around a competency-based assessment (CBA) model. Conventional assessment tends to capture a snapshot of performance at a single point in time, asking students to do the thing in a given moment. The emphasis is on product. Competency asks a different question: what do students need to be able to do, and can they do it again? Not just doing the thing, but becoming someone who can do the thing. The emphasis shifts to process.
And it’s in that shift, from valuing product to recognizing process, that I’m starting to see some hope and opportunity, despite the frustrations many teachers are facing in AI-influenced classrooms.
As I worked my way through the 70+ 15-page formal research reports that I received last month, I definitely encountered some that were clearly strung together by very mediocre LLMs and chatbots. I recognize that, just as I recognize that it is inevitable that some students will choose to offload the effort behind the process of putting together an engaging research report. That’s their choice.
But I also read many more research reports that were both unique and striking in their argument and approach. One student developed a convincing analysis of the colonial ideals embedded in the collegiate architecture on our USask campus, while another wrote about the potential “third space” community within Saskatoon’s hip hop scene. I had many students who, in the first month of class, described themselves as “bad writers” and dreaded receiving feedback, but who, by the end of the term, couldn’t wait to show what they’d learned through their process of research and writing.
Teaching has always been a hard gig, and lately it feels even harder. There are so many anxieties and unknowns around what generative AI will mean for higher education. But for me, this moment has clarified something rather than taken it away.
If anything, it has pushed me back toward the core of what I am trying to teach. Not just how to help a student produce a piece of writing, but how to support them in becoming someone who can do the thing. And that kind of learning is much harder to outsource.
Things that have brought me joy over the last few weeks:
My dissertation is officially PUBLISHED! I will be graduating! And my marks are submitted! Right now I don’t know what to do with myself without nursing a crushing load of guilt over the fact that I should be writing or marking something. (Don’t worry, dear Reader, I’m already working on a new side hustle.)
Speaking of which, my dissertation has won an award. There are five categories in which USask dissertations are judged, and mine received the Social Sciences B award! I am so thrilled to have my work recognized in this way, and I am also enjoying the irony of celebrating an award for a dissertation that critiques the performance-metric-driven system of success in academia.
There’s a sober drink store / alcohol-free store opening up in my neighbourhood!
Despite our unexpected end-of-April snow dump, Danny C. and I still made time for our annual crocus hunt:
Emma is back home from her first independent adult vacation! She went to Vancouver/Victoria with some good friends and told me it was “like Broadway, but times 100.” I agree, kiddo. Her spring class also started today.
I have new ink! That’s for a post to come — it’s my “happy finishing your PhD” tattoo, and of course, it’s symbolic.
Now that I’ve finished my PhD, I reached out to three of the theorists who meant so much to my research to tell them how grateful I was for their work. These scholars are all in their 80s and have long since retired from academia. I was able to get my letter through to all of them, and one of them even wrote back! But I’ll save that story for a future post.
Next week, I see a beach in my future.
Meme of the week:
There is a certain irony that Artificial Intelligence and Academic Integrity have the same initials.