Stephen Downes

According to this article, " instead of only asking whether employees have the right skills for the tasks on hand, leaders should ponder how fast - and how well - they can acquire the skills they will need next." These skills - here called 'meta-skills' (but also known as 'soft skills' or 'durable skills') break down into two major categories: critical thinking skills, and social skills (I'm sure there's an interesting story to be found detailing how critical thinking and social skills lead to better learning). According to the article, meta-skills can be assessed via three major indicators: "people with strong meta-skills acquire new skills faster"; they "show up when people apply principles learned in one context to structurally similar but unfamiliar problems": and "meta-skills are visible in how people work." And people can learn them. "Higher order thinking, metacognitive regulation, analogical reasoning and social coordination all improve with structured practice, feedback and reasonably demanding environments."

This article raises some interesting questions about early language learning (ELL) and AI. Specifically, it makes the point that while AI is already quite good for some things (such as speech to word transcription) it needs specialized training for others, such as  low-stakes oral reading fluency, and absolutely flounders at others, such as phoneme-level assessment. The model needs "a separate step that compares the recording with the expected sounds." And "Improvements on this narrower task also may not translate into better general transcription." So what does this tell us about phonics as a thing that is learned? Maybe (and I'm speculating here) we learn how words are pronounced first, and parts of words later. The pronunciation of 'cat' and transcription to the letters c-a-t happen as a single step, and are not composed of separate steps (pronunciation of 'k', pronunciation of 'at', transcription to correct letters). Something to think about.

This article describes a Triadic Learning Ecosystem (TLE) that "offers an architecture of that near future, connecting teachers, students, and AI-enabled tools in a collaborative model of learning." The three elements are students (as peer groups), the teacher (as conductor), and pedagogical AI assistant (PAIA) (as scaled support). "Teachers are elevated from content-communicator to classroom conductor. They encourage, challenge, intervene, motivate, and lead." Interesting word choice, 'elevated'. "The students are not passive recipients of information but active builders of it. In small peer groups, they produce, debate, and explain to one another." There's a five phase model that describes class sequencing: co-design, student exploration and creation, PAIA simulation, real-time feedback loop, reflection and synthesis. There's also a (very simple) technology mapping to the framework. There's some good thinking here, but I think it's far too rigid a structure.

A professional can, as Tim Klapdor says, pick up their tools, find a new chair, and keep going. "The skill is his. The relationship with his clients is his. The craft he's spent years developing is entirely portable." Why isn't that the same with university professors? Klapdor explains this by saying each university is a unique machine, but I don't think that's it. True, "the academic, at their best, owns a body of work and the reputation that comes with it." But they don't own their own client list (and don't have the marketing reach to generate one), and they don't own the credential that they, uniquely, can confer.

There's so much talk about in-person for the sake of in-person, and then our actual in-person interactions (whether online or in-person) are so badly managed. This article seeks to correct that by focusing on designed meetings, where the purpose, roles, flows and outcomes are determined (so far as possible) to maximize and respect people's time. I appreciate that. Now this article is focused on leadership in a corporate mode, but of course if we elide the business elements (i.e., expenses, value, leverage, etc.) we get a good model for in-person interactions in general, which can inform what we're doing when we collaborate and learn together. Via Ben Werdmuller.

This open access book (116 page PDF) is a collection of essays that asks of digital education "what kinds of futures are being imagined and enacted for education, whose interests these futures serve, what assumptions underpin the current drive towards digitalisation, and what remains unexamined or quietly displaced in its wake?" The focus is less on the stated (Utopian) intentions and more on what is actually being put into practice. "A central concern running through the volume is the place of the human in digitally mediated education," write the editors. But this is a moving target; "the chapters attend to the ways in which human agency, judgement, and relationships are being reshaped under conditions of digitalisation." The volume considers tensions such as those between scale and care, efficiency and responsibility, and access and meaningful participation. A deeper current is what Melinda dela Peña Bandalaria calls "the erosion of shared frameworks through which universities justify their actions, define value, and make their commitments intelligible." Some characterize this as "chasing technology", some focus on emerging social values, and some characterize it as a recharacterization of our own humanity.