Category: short reflections

Quote: I won’t ever really understand what it feels like to work here, because I know that I get to leave

It’s been a few difficult and long months – more on this soon –  but this week was the first time in I-can’t-remember-when that I was able to sit at a coffee shop with a book with no schedule, without a pressing sense to spend my time on more productive and pressing activities. I’ve missed it. At said coffee shop, a local chain called Serious Coffee,  I was reading Emily Guendelsberger’s On the Clock: What Low-Wage Work Did to Me and How It Drives America Insane in which she describes what it is like to work at a McDonalds, an Amazon warehouse, and a call centre.

I’ve always been drawn to ethnographies, stories from the inside, and such – please offer favourite books and articles in the comments – and this quote was a good reminder of the challenges we face in our efforts to understand other people’s experiences (p. 56-57):

I came to SDF8 [an Amazon fulfilment centre] to try to understand what it feels like to work in a fulfilment center. But the thing I really and truly understand now is that, regardless of how broke I may be, I’m the upper class. I always will be. I won’t ever really understand what it feels like to work here, because I know that I get to leave.


Tidying up this website

I’ve spent some time this morning updating a few of the static pages on my website, including

  • the consulting page (updated the list of clients to indicate work completed with institutions, governments, non-profit, and for-profit organizations)
  • the affiliations page (to indicate relationships beyond my employer)
  • the public scholarship page (to bring up-to-date my op-ed and public writing)
  • the grants page (to include recent grant received)

So very tired of predictions about AI in education…

By people who aren’t AIEd experts, education technology experts, education experts, and the like.

Case in point: “AI likely to spell end of traditional school classroom, leading [computer science] expert says.”

I appreciate cross disciplinary engagement as much as I love guacamole (which is to say, a lot), but I’d also appreciate that we stop wasting our time on these same unfulfilled prophecies year after year, decade after decade.

Will AI impact education? In some ways it will, and in others it won’t. Will education shape the ways AI comes to be used in classrooms? In some ways it will, and in others it won’t.

Truth be told, this negotiated relationship isn’t as appealing as DISRUPTION, AVALANCHE, MIND-READING ROBO-TUTOR IN THE SKY, etc, which are words that readers of the history of edtech will recognize.

Issues that hybrid, online, and blended modes of teaching and learning introduce to collective agreements and bargaining

A few weeks ago, I was invited to offer input to a committee at a Canadian university examining issues that hybrid, online, and blended modes of teaching and learning introduce to collective agreements and bargaining. I appreciated that the committee identified experts to speak with in order to gain an evidence-informed understanding of the issues they were facing rather than allow their deliberations be guided by assumptions and beliefs (which, to be honest, many of the conversations around modality default to!).

I thought the questions I was asked were relevant to many, and so I am sharing them below. The gist of my responses follows each question.

  • What is your sense of the future of online, hybrid, and blended course delivery in Canadian universities?
    • Necessary, valuable, and growing. Ignore them at your own peril.
  • How do you see the work, the workload, the rights, and the responsibilities of faculty changing within this shifting terrain?
    • Rising workloads at first, but shifting over time (similar to how workload is higher when assigned a new course; opportunity to learn & explore relationship between online/hybrid and pedagogy, which may transfer to other settings). Responsibilities around quality similar, if not higher (which is unfortunate given that conversations around quality are different in relation to in-person courses). Rights: an opportunity for expanding the conversation to encompass in-person practices: reflect on ownership and where the real value of faculty lies – it’s not content.
  • What would you suggest are the biggest advantages to these delivery modes, and what would you flag as the biggest challenges that institutions face in moving towards these modes?
    • advantages: rethinking pedagogy, flexibility, supporting justice and EDI, reaching and supporting different kinds of learners; challenges: institutional infrastructure to support online/hybrid learning quality at the same level as supporting in-person.
  • What kinds of supports—technological, training, in-class, infrastructural, workload-based, or other – do you see as necessary for faculty to successfully deliver course through online modes?
    • This is the right question to ask. It’s not just about individual skills, competencies, and perceptions – it’s about how the institutions will support these learning modalities at the system level. In addition to the ones mentioned in the question, my answer highlighted that online/hybrid learning is a team sport and noted the need for instructional design support.  
  • As part of our own deliberations, we are concerned with the process through which mode of delivery for particular courses is determined. Do you have any advice on how this best happens? Are there any lessons from experiences at other universities about this?
    • This is a difficult one, especially at a time of many circulating viruses. I emphasized the need for flexibility and a decision-making process that is based on mutual trust and cooperation, and that is informed by student input. Ideally one where decisions aren’t top-down and aren’t solely guided by individual preferences. Also: the proportion of courses that are online need not be uniform across departments.

EdTech, magic mushrooms, and magic bullets

In my inbox, an email says:

Alberta’s new regulations on psychedelics to treat mental health issues come into effect today, making it the first province to regulate the use of hallucinogens in therapy.

Today in The Conversation Canada, Erika Dyck of the University of Saskatchewan walks readers through the new regulations, as well as the history, potential and pitfalls of hallucinogens both inside and outside clinical settings.

Psychedelics — from magic mushrooms and ayahuasca to LSD — are having a moment in the spotlight, with celebrity endorsements and a new generation of research on potential clinical uses. There is certainly a need for therapeutics to treat mental health issues, the growing prevalence of which could place a strain on the health-care system.

“Psychedelics are being held up as a potential solution,” Dyck writes. “But, magic mushrooms are not magic bullets.

That last line captures so much of what is happening in our field, and education more broadly, that it is worth repeating.

  • AI is being held up as a potential solution, but it is not a magic bullet.
  • A return to in-person learning is being held up as a potential solution, but it is not a magic bullet.
  • Online learning is being held up as a potential solution, but it is not a magic bullet.
  • Microcredentials are being held up as a potential solution, but they are not a magic bullet.
  • … and so on

These things – and others – can be solutions to some problems, but they consider them to be part of a Swiss army knife, part of a toolkit. And while sometimes your Swiss army knife will work, this isn’t always going to be the case, especially when we’re considering some of the most major challenges facing higher ed, the kinds of things that we’re not talking about (e.g., precarious employment and and external regulations that encourage and foster conservatism, etc).

And perhaps, that’s the crux of the issue: That these solutions are used to respond to the symptoms of larger problems, of the things we’re not talking about, rather than the root causes of them.

Image credit: Wall-e output in response to the prompt “a magic bullet in the style of salvador dali”

AI use in class policy

Ryan Baker shares his class policy on foundation models, and asks for input:

Within this class, you are welcome to use foundation models (ChatGPT, GPT, DALL-E, Stable Diffusion, Midjourney, GitHub Copilot, and anything after) in a totally unrestricted fashion, for any purpose, at no penalty. However, you should note that all large language models still have a tendency to make up incorrect facts and fake citations, code generation models have a tendency to produce inaccurate outputs, and image generation models can occasionally come up with highly offensive products. You will be responsible for any inaccurate, biased, offensive, or otherwise unethical content you submit regardless of whether it originally comes from you or a foundation model. If you use a foundation model, its contribution must be acknowledged in the handin; you will be penalized for using a foundation model without acknowledgement. Having said all these disclaimers, the use of foundation models is encouraged, as it may make it possible for you to submit assignments with higher quality, in less time. The university’s policy on plagiarism still applies to any uncited or improperly cited use of work by other human beings, or submission of work by other human beings as your own.

As far as policies go, I like what Ryan created because

  • It functions as a policy as well as a pedagogical tool (“you should know that these models do X”) that draws students’ attention to specific issues that are important (e.g., ethics and equity).
  • It encourages use of foundation models. It recognizes that they are available and they can have benefits, unlike head in the sand efforts that ban their use
  • It invites students to engage with the output of foundation models in meaningful ways

In the LinkedIn thread, Jason D. Baker has a great comment that speaks to this, when he asks whether students solely need to state whether they used a model or whether they will need to explain in detail how they used model outputs. What would an explanation accompanying a submission look like? I’m not quite sure, but here’s an example of an article demonstrating the ways the human was involved and the ways the AI contributed to an article.

Time *with* people, online learning, and feeling ridiculous

I really enjoyed the quote below from John Warner, who is writing about graduate programs in writing and pursuing writing as a career. It strikes me that it also seems to capture some aspects of online learning which takes place in community with people vis-a-vis the independent, self-paced, and autodidactic approaches. Group dynamics and being in community are powerful, but even then, does being in community necessarily mean feeling not ridiculous? Perhaps the emphasis is on the “not so.”

Spending so much time immersed in a group of people that are interested in the same things you are, and want the same things you do can be incredibly nourishing. Being alone, and believing you want to write can honestly feel like a kind of madness. For sure there’s some writers who have a kind of self-belief and inner fortitude that buoys them, but the rest of us are like any other human being walking around wondering if what you think, what you believe, what you want, is ridiculous, and you are therefore a ridiculous person.

Basically, being surrounded by others who are similarly oriented makes you feel not so ridiculous. (emphasis mine)

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