OLDaily

A Proposed Ethics Code for Online Learning During Crisis
Reham Salhab, Shireen Hashaykeh, Eman Najjar, Dua'a Wahbeh, Saida Affouneh, Zuheir Khlaif, International Journal of Emerging Technologies in Learning, 2021/10/26

Ethical codes abound; you can't go very far through professional literature without encountering one. The context of this one is unique, though, as it looks to the need for a code of ethics in Palestinian online learning as it is made more urgent by the ongoing pandemic. The study (17 page PDF) relied on focus groups and a survey of teachers in the public schools system. The result: "researchers propose four online learning ethical principles: respect and protect digital dignity, commitment to the profession, commitment to the distance educational system, teachers' and students' rights and responsibilities within an online learning environment."

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Fragment: Generative Plagiarism and Technologically Enhanced Cheating?
Tony Hirst, OUseful Info, 2021/10/26

In a nutshell: "With tools such as Github CoPilot on the verge of offering automated code generation from natural language text, and GPT-3 capable of generating natural language texts that follow on from a starting phrase or paragraph, I wonder if a natural evolution for essay mills is not that they places where people will write your essay for you, but machines will (or perhaps they already are?)." This raises anew questions about what counts as cheating and not cheating, and what counts as permissible support and what does not.

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Introduction to Causation With A Human Face
James Woodward, The Brains Blog, 2021/10/26

The goal of science is to find underlying causes and natural laws. But what if there are no underlying causes? That's the question philosophy has been wrestling with for 300 years. This article suggests that "causal reasoning should be understood in 'functional' terms– that is in terms of the role that it plays in human life and the human goals and purposes that it serves." It's the sort of principle in light of David Hume's characterization of causation as a 'useful fiction' we create to explain things to each other. And it's distinct from what might be called an 'interventionist' account of causation, where it's a principle we appeal to in the name of 'making things happen'.

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Why “Uber for education” metaphors are flawed (and just rubbish)
Martin Weller, The Ed Techie, 2021/10/26

When I was in charge of the LPSS program I received a lot of training on management principles, business cases and plans, and related subjects. One message in this training was to emphasize the utility of phrases like "the Netflix of learning" in plans. This was because senior executive needed to be able to comprehend the idea quickly, and such metaphors were the surest shortest path to accomplish this. Now to be sure, there are weaknesses in this approach, which are made very clear in this post from Martin Weller. He dissects the problem with metaphors like "the Uber of such-and-such". I would say, though, that almost any metaphor will fail under close scrutiny. What makes a metaphor work is salience - the one feature of the example that shines through clearly. In the Uber case, for example, you should ignore most of the business model and focus on the fact that, unlike a taxi, you don't need an expensive taxi plate to drive an Uber (the one thing Weller actually misses in his dissection).

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Keep Badges Weird...
Laura Hilliger, We Are Open, 2021/10/26

Back in August Doug Belshaw called on people to "Act now to prevent the hijacking of the Open Badges standard by an IMS faction!" I was busy being on hiatus and didn't really follow up on this. But I take this opportunity to look at it again on the occasion of the Keep Badges Weird social learning approach being officially launched at the 2021 Badge Summit.

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Adapt Learning Path by Recommending Problems to Struggling Learners
Youssef Jdidou, Souhaib Aammou, Mohamed Khaldi, International Journal of Emerging Technologies in Learning, 2021/10/26

I would classify this as a relatively basic approach to content recommendation, though it is of course useful to select problems of appropriate difficulty for people who are struggling in a course. And it's pretty clear and offers an instance of the idea applied in EdX. This paper (16 page PDF) describes a collaborative recommendation mechanism based on people in the same class (or type of class) who are the 'nearest neighbour' based on a test of similarity. the idea is that 'people who like me struggled with this type of content were successful with this class of problems'.

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Neuron Bursts Can Mimic Famous AI Learning Strategy
Allison Whitten, Quanta, 2021/10/26

This article describes work showing how back propagation might work in a human brain. In back propagation, a neural network learns (that is, a neural network adjusts connection weights) after processing some input as a result of signals sent back against the flow of processing. In a human this seemed impractical because it would require the senses to shut down. The work describes here shows that neuron 'bursts' could perform the back propagation function. "Naud and Richards’ team proposed that neurons have separate compartments at their top and bottom that process the neural code in completely different ways." One would interpret a burst as a corrective signal, while the other would interpret it as a normal signal.

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Making Barriers to Learning in MOOCs Visible. A Factor Analytical Approach
Maartje Henderikx, Karel Kreijns, Kate M. Xu, Marco Kalz, Open Praxis, 2021/10/26

This study reports on a survey with 540 responses from students at Delft University taking courses on the EdX platform in English. A list of 44 potential barriers, identified in a previous literature review, was used. The results were presented in a dashboard (pictured). The big issues were 'lack of time' along with motivational factors. Unsurprisingly, university students preferred to learn in person and (to my observation) lacked the skill and inclination to manage their own learning.

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