Stephen Downes

Knowledge, Learning, Community

Stephen Downes works with the Digital Technologies Research Centre at the National Research Council of Canada specializing in new instructional media and personal learning technology. His degrees are in Philosophy, specializing in epistemology, philosophy of mind, and philosophy of science. He has taught for the University of Alberta, Athabasca University, Grand Prairie Regional College and Assiniboine Community College. His background includes expertise in journalism and media, both as a prominent blogger and as founder of the Moncton Free Press online news cooperative.  He is one of the originators of the first Massive Open Online Course, has published frequently about online and networked learning, has authored learning management and content syndication software, and is the author of the widely read e-learning newsletter OLDaily. Through a thirty-five year career Downes has contributed pioneering work in the fields of online learning games, learning objects and metadata, podcasting, and open educational resources. Recent projects include:gRSShopper, a personal learning environment; E-Learning 3.0, a course on new e-learning technologies; research and development in the use of distributed ledger technology in learning applications; and research on ethics, analytics and the duty of care. Downes is a member of NRC's Research Ethics Board. He is a popular keynote speaker and has spoken in three dozen countries on six continents.

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MAG replacement update: meet OpenAlex!

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Steve McCarty write to remind me that "Microsoft Academic is closing at the end of the year but OpenAlex plans to carry similar work on." Why is Microsoft Academic shutting down? The site explains, MAS was developed to address "inequality in accessing large datasets presented a significant obstacle" and now "this research project has achieved its objective." That's a matter of debate; what happens to access after the doors close? OpenAlex will step in, but it won't replicate everything MAS was doing, losing most abstracts and full coverage of DOI-unassigned works. Still, the objective of creating "a truly comprehensive map of the global scholarly conversation" is worthwhile and should be supported.

Today: 6 Total: 6 OpenAlex, 2021/09/20 [Direct Link]

Online learning, videoconferencing and energy consumption

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So here's the argument, from Renee Obringer: "A standard video conference uses 2.5 gigabytes per hour and has a carbon footprint of 157 g of CO2. If one individual has 15 one-hour meetings in a week, his monthly carbon footprint would be 9.4 kg." I see this sort of argument a lot. And I want to be clear that it has nothing to do with individual choices about videoconferencing. To illustrate that point, here's a chart of Ontario Electricity Production. As you can see, less than 3 percent of the electricity in Ontario is produced from fossil fuels. So we're not dumping carbon into the air when we videoconference. True, the situation is very different in other countries. But this is now a matter of national energy policy, not individual choices about videoconferencing (it does matter how you vote, however).

Today: 17 Total: 168 Tony Bates, Online learning and distance education resources, 2021/09/17 [Direct Link]

How does CORE substitute Microsoft Academic Graph?

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Microsoft Academic Graph (see next post) does a lot of what numerous education-led projects (including Jisc's CORE) intended to do. Where does this leave these projects? " CORE already fulfils a number of the solutions supplied by MAG, but critically CORE is not a direct replacement for MAG. In fact, there is no direct replacement for MAG. As OurResearch clearly says in their announcement – a “perfect” replacement is very hard to come by." In other words, this is a concession that Microsoft looked at what the sector was trying to do and did it better (it helps a lot I think that Microsoft didn't have a prior interest as a journal publisher). CORE there fore is now focused on more specific projects, such as "Methods for detecting citation intent and purpose embedded and applied on citation data" and "Full-scale near-duplicate detection to recognise different versions of manuscripts."

Today: 8 Total: 97 Melanie Heeley, JISC, 2021/09/17 [Direct Link]

Next Steps for Microsoft Academic – Expanding into New Horizons

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I missed this when it came out (one can't be everywhere) but I definitely want it entered into the record: " Microsoft Academic has been on a mission to explore new ways to empower researchers and research organizations to achieve more. The research project is characterized by two sets of technologies: one that reads all the Bing-indexed web pages and organizes the most up-to-date academic knowledge into a knowledge base called Microsoft Academic Graph (MAG), and the other that performs semantic reasoning and inference to serve that knowledge through the Microsoft Academic search website and API."

Today: 32 Total: 151 Microsoft Academic, 2021/09/17 [Direct Link]

Is “Teaching Loss” a Myth, Too?

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"Did teachers miss out on being able to have a fulfilling teaching experience?" asks Pav Wander. "So much happened that prevented us from truly being able to enjoy, or even be a part of, the full teaching experience. We were knocked off our foundations, we were just barely managing to keep learning meaningfully, and many of us, including myself, describe this past year as 'just trying to stay afloat.'" The article lists six facets of teaching loss, and is worth considering (you may need to convert it into a more readable font first, though). Via Doug Peterson. Image: EdCan network (found via Google image search, which credits it to Anthony Jess on Adobe Stock and gives this link to tell us "where this information came from").

Today: 16 Total: 110 Pav Wander, Chey & Pav, 2021/09/17 [Direct Link]

The Use and Misuse of Counterfactuals in Ethical Machine Learning

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This paper (9 page PDF) dives into the weeds a bit, but it's interesting and potentially very useful. When we use AI in learning, one of the criteria people ask for is for an explanation of decisions or recommendations. But for various reasons, which I mentioned here and will discuss in detail in the future, explanations will either be very difficult to get or not very useful. Instead, a lot of writers are recommending the use of counterfactuals; sometimes, what people need, rather than an explanation per se, is a statement of what could have been done instead to produce a different outcome. But counterfactuals introduce their own issues. How do you know that a counterfactual is true? This article looks at the semantics of counterfactuals and offers a table of the decisions we need to make in order to use them. And this gives us an interesting way to talk about the ethics of using AI in learning.

Today: 43 Total: 138 Atoosa Kasirzadeh, Andrew Smart, ACM Conference on Fairness, Accountability, and Transparency, 2021/09/17 [Direct Link]

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