OLDaily

The Unreasonable Importance of Causal Reasoning
Hugo Bowne-Anderson, Mike Loukides, O'Reilly, 2022/03/24

We write about cause and effect a lot in the field of education and learning technology. After all, we're mostly writing about tools and outcomes, and tools that don't cause outcomes aren't especially useful. But what is causation? This article is a refreshing and detailed look at what we mean by causation in the 21st century, based on a progression from association through experimentation and finally to counterfactual reasoning, a journal that takes us through things like P-values, confounders,  colliders, and causal graphs. This article is accessible and yet doesn't really skimp on the important detail researchers and writers need. "As 'data science' became a buzzword, we got lazy: we thought that, if we could just gather enough data, correlation would be good enough..., and correlation still hasn't gotten us what we want: the ability to understand cause and effect. But as we've seen, it is possible to go further... causal graphs provide new tools and techniques for thinking about the relationships between possible causes."

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Growing together: What's the key to a successful learning community?
Alexandra Mihai, The Educationalist, 2022/03/24

I can't think of any academic environment I've been involved with that hasn't attempted some form of professional learning community. Alexandra Mihai writes, "They are based on the idea of creating a space for reflective practitioners to exchange and crowdsource ideas and support each other in their practice." We see them where I work in Slack forums, gcCollab discussions, seminars and workshops, and more (and these, I might add, have been a lot more active at NRC during the pandemic, and I hope we don't lose them). Minhai says successful professional learning communities depend on four factors: being a safe space, validation by peers, crowdsourcing ideas, and accountability. If I had to create my own list it would be: tools that work, practical value, timely response, and whole-of-enterprise (and beyond!) scope.

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Rhizo Narratology: Decentralized Processes
Keith Hamon, Learning Complexity, 2022/03/24

Beyond the title this article is all about complexity versus the great man theory, and barely mentions rhizo narratology at all. No matter. It's still a useful discussion of the role of the individual as a causal agent in a complex world, eventually landing on the position that a person like Steve Jobs is 'necessary but not sufficient' for the invention of the iPhone. I personally am not even sure he is necessary. We had smart phones before Jobs - just ask Blackberry - and a lot of which made the iPhone the phenomenon it was were the design and the marketing, both of which also existed independently of Jobs. Not that I am asserting some sort of historical necessity here - individual decisions do matter. But you need them from many interconnected people, not just one great man.

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Mozilla’s vision for the evolution of the Web
Mozilla, 2022/03/24

Sometimes when I read documents like this I wonder how they will be regarded in the far future, combining as they do elements of technology and philosophy. Here's Mozilla's technology philosophy: "Our vision starts with three basic values for the Web, rooted in the Mozilla Manifesto:

    Openness: Everyone can access the Web, and use it to reach others.
    Agency: Once individuals reach the Web, they are empowered to accomplish their goals effectively and on their own terms.
    Safety: The experience of using the Web must not put individuals in danger."

This link is to the full document; you can also read the executive summary in a separate document.

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DataViz Project
Ferdio, 2022/03/24

This is a set of common data visualization formats or templates, with an accompanying instruction page for each one. It would be quite useful for teaching about data visualizations. It's also interesting to me because it demonstrates clearly the phenomenon of recurring patterns or tropes in data visualization.

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Will Transformers Take Over Artificial Intelligence?
Stephen Ornes, Quanta Magazine, 2022/03/24

You will probably hear more about 'transformers' in artificial intelligence. This article describes them. To date, successful neural networks have worked through 'feature detection' - a convolutional neural network (CNN), for example, would focus on a small area and try to detect an edge (or a phrase, or a morpheme), gradually building a whole model out of parts. Transformers, by contrast, "runs processes so that every element in the input data connects, or pays attention, to every other element." This is called 'self-attention.' Transformers have performed quite well compared to more traditional neural network processes. And they're more 'universal' - the same approach used for image processing also works for natural language processing.

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10 Years of OERx
ALTC Blog, 2022/03/24

You can't really summarize ten years of a conference, but this short series (part one, part two) tries. The result is interesting because as it tracks the main themes of the successive conferences it also tracks the trends in the field of OER (or at least this one corner of it) as a whole, from the need for evidence and setting expectations to open badges and open educational practice to disruptive narratives, critical perspectives, and care. For me, OER has always been about access, but this community started from a more theoretical and more academic perspective and to my view drifted further and further away from that original intent. Not that the discussions haven't been useful, but I do think sometimes proponents of openness have lost the plot.

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Students must be taught to engage in academic writing, not to fear the Spanish Inquisition of plagiarism detection
Jan McArthur, WonkHe, 2022/03/24

I'm sympathetic with the gist of this article. "Too often our approaches to academic writing promote a sense that the most important thing a student can achieve is not to be accused of plagiarism." But "instilling a fear of being caught plagiarising undermines the centrality of academic work engaging with the minds of others." Sure, you shouldn't take credit for someone else's work. But maybe we should ask why we're evaluating students on the basis of stand-alone individually-written pieces of content. "Redesigning assessment for better learning is most often a win-win move. Students' learning is improved. Deliberate cheating is very difficult." Being integrated and working cooperatively with a community is something that's very difficult to fake, and much more rewarding for the student.

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