OLDaily

Welcome to Online Learning Daily, your best source for news and commentary about learning technology, new media, and related topics.

Student motivation and online learning
Tony Bates, Online learning and distance education resources, 2023/02/24

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I quite like this take from Tony Bates: "The false assumption is that students who have opted for an online course need motivating to learn. At least where students have freely chosen to take an online course, they usually come highly motivated to learn... If as an instructor you find your online students are not engaged – they do not do assignments; they've dropped behind; they don't participate in discussions – don't blame them. You have unintentionally done something wrong in your online teaching to de-motivate them." Of course this does not apply in cases where remote learning has been mandated.

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The Future of Service Mesh Is Networking
Bill Mulligan, InfoQ, 2023/02/24

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This is another really interesting and deeply technological article from InfoQ. Here's the story in a relatively nontechnical nutshell: when it just runs on one machine, an application integrates a variety of services (for example, audio input, database access, etc.) but when it runs in a cloud environment, the program may access these services from across the network. But this is complex to manage, and ideally, should be hidden from programmers and users, just as the mechanics of TCP/IP are hidden today. So large enterprises like Cloudflare, Google and Facebook are adopting extended Berkeley Packet Filtering (eBPF) to do this. "From increasing packet throughput to DDoS mitigation and continuous profiling, eBPF allowed them to add the functionality needed to kernel networking in almost real time" with the result that "connecting service mesh to networking will allow us to have full context and control across all networking layers, improving setup, operations, and troubleshooting."

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How learning analytics can finally deliver on its promise
James Hodgkin, JISC, 2023/02/24

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The first question I had when I looked that article was: what exactly is the promise of learning analytics? It seems to be something like this: "Learning analytics means using student lifecycle data to understand student engagement. Through this, HEIs can potentially trigger interventions early enough to help improve their performance." This promise may or may not be achieved through (traditional) learning analytics; I think the jury is still out. But James Hodgkin seems to find another purpose for it: "understanding data is more than a dashboard: it can improve data governance across higher education." It's a bit chicken-and-egg: better data governance can improve learning analytics, while an emphasis on learning analytics can improve data governance. But it all somehow leaves me wanting more.

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Towards Transformative Socioemotional Learning | Dr. Ian O'Byrne
Ian O'Byrne, Carlos Lavin, 2023/02/24

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This is a set of presentation materials for a session titled Teaching in a Post-TruthSociety: Empowering students as they negotiate digital literacy, identity, and socioemotional learning. Some of the stuff goes over very familiar ground (TPACK, SAML) while there were some things that interested me. Slide 16, for example, has a set of South Carolina graduate competency statements (which I think would read better as first person statements, for example, "I read critically", "I express ideas", etc). Also, there's the comparison of the melting post model of American society with what we have always used to depict Canadian society, the salad bowl. The next slide says, "If we continue teaching SEL through a melting pot ideal, we continue replicating the same inequities

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Cleaning sample data in standardized way
Crystal Lewis, 2023/02/24

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This is the third in a set of informative articles on data cleaning: part 1 Data cleaning for data sharing; part 2 Creating a data cleaning workflow; part 3 Cleaning sample data in standardized way. Data cleaning is an important step in the development of artificial intelligence applications, and how you do it can impact the quality of the models that result. Via Data Science Weekly.

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The 2023 MAD (Machine Learning, Artificial Intelligence & Data) Landscape
Matt Turck, 2023/02/24

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Found listed in an extra-good issue of Data Science Weekly, this website makes it clear just how large and complex the landscape has become. "The last few months saw the unmistakable, exponential acceleration of Generative AI, with arguably the formation of a new mini-bubble. Beyond technological progress, it feels that AI has gone mainstream, with a broad group of non-technical people around the world now getting to experience its power firsthand." Be sure to click through to the comprehensive landscape visualization.

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We publish six to eight or so short posts every weekday linking to the best, most interesting and most important pieces of content in the field. Read more about what we cover. We also list papers and articles by Stephen Downes and his presentations from around the world.

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