Stephen Downes

I think this post raises a good point. YouTube is releasing a new feature for creators allowing them to create different versions of their videos to see which one performs best (which in YouTube's world means gains the most and longest views, the essential conditions for monetization). This is known in the business as 'an A/B test'. But this, writes Jim Nielsen, raises questions: how do viewers know they're in an A/B test? Which versions do the comments refer to? If I share it, will other people see the same video I did? Marques Brownlee, writes Nielsen, has released a video essay asking YouTube not to do this. "There's this sort of unspoken rule of community on YouTube, that like we're all having this same experience together." Nielsen echoes Brownlee's concerns. And I have to say, I am sympathetic with the argument.

Miguel Guhlin began by vibe-coding a learning management system his school could host on its own servers. Not a bad project. Then he asked, "What else would make this useful?" Turns out, he says, quite a bit. SapiqoLMS now goes beyond importing courses. This article lists a number of things hes done, including organizing learning around your people, giving learners something to do, and giving achievement a lasting record. Short post, most useful for stretching your imagination a bit. "The roadmap still calls for stronger recovery, accessible navigation, assignments, rubrics, and institutional pilots."

Julian Stodd describes three fundamental 'Logics' of adaptation to AI. They are (quoted):  'Structural Adaptation', and it includes Agentic deployment;  'Relational AI', which is AI held within human social structures as dialogic partner; and 'Contextual Shift', and it describes an emergent condition where social context itself has moved. What's important to understand, writes Stodd, is that these do not occur sequentially. They're all happening at the same time (that's why they're 'dimensions' and not 'stages'). "The Leadership question here is not kinetic: not the top down requirement to drive adoption of one or other Logic, but rather to consider how we lead when all three Logics are present and simultaneously true."

This is a two part article (part one, part two) asking some of the contributors to the Scholarly Kitchen (a.k.a. 'the chefs') what they would have done differently about open access had they been able to see the world as it has become today. There are basically two trends in the seven responses: continue to oppose open access, or try for something better than article processing charges (APC) or transformative deals (mostly involving disaggregation and multiple pricing and funding models). There's no suggestion that commercial publishers should be excluded from the system outright, which would have been my stance. 

"As an industry, we have spent a great deal of time talking about whether organizations can provide learning fast enough.," writes Elizabeth Loutfi-Hipchen. "I think we may be asking the wrong question. The issue increasingly isn't access to learning. It is whether people and organizations have the capacity to absorb what we are asking them to learn and turn it into performance." I think this is a good point. It may force a shift in how we think about learning from 'just in case' to 'just in time' (I know, this has been said before, but few have taken it seriously). Loufti-Hipchen expresses it this way: "This changes the goal of personalization. We are no longer trying to create an elaborate individual curriculum for every employee. We are trying to find the shortest credible path between current capability and required performance." This is a good discussion of the need with steps toward a response.

This article describes the way schools are experimenting with AI but expresses concern about the lack of policy, guidance or research. I want to complain that they are being overly fretful - after all, people experiment with every new technology; that's how we discover what the policy, guidance and research should be. But the article as a whole comes out in cautious favour of experimentation. "If we really close off AI experimentation, if we prevent kids from learning about AI, learning how to use it really well, thinking about how teaching could be transformed, we will set our kids back from being able to navigate a world that is changing outside of schools faster than we can possibly imagine." My thinking is: who better to learn first hand about the effects of AI on learning than teachers? That said, there is an argument for making sure organizations don't go overboard and do real harm.