OLDaily

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

Each Facebook User is Monitored by Thousands of Companies – The Markup
Jon Keegan, The Markup, 2024/01/22

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I mean, we all knew it was bad. But this bad? "Each participant in the study had their data sent to Facebook by 2,230 companies. That number varied significantly, with some panelists' data listing over 7,000 companies providing their data." The surveillance extends far outside Facebook and Insta. "This type of tracking which occurs entirely outside of the user's view is just so far outside of what people expect when they use the internet... they don't expect Meta to know what stores they walk into or what news articles they're reading or every site they visit online." Even if you don't use Facebook, your data is being used to inform Facebook advertising. "Custom audiences allow advertisers to upload customer lists to Meta, often including identifiers like email addresses and mobile advertising IDs. These customers, and so-called 'lookalike audiences' made up of similar people, can then be targeted with ads on Meta's platforms."

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The Brains Blog
Luis H. Favela, Edouard Machery, The Brains Blog, 2024/01/22

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This is a great summary of the paper 'Investigating the concept of representation in the neural and psychological sciences' (13 page PDF) by the same authors. Readers will know I have been sceptical about the existence of mental representations, properly so-called, and this paper points to some of the reasons why. First, it identifies three types of representation in use in psychology and neuroscience: "intentional ("representation," being "about," "identifying"), causal ("responding," "processing"), and information theoretic ("carrying information") concepts." After examining the use of these types of representation, they argue that it is both unclear and confused. They suggest clarifying it would be unworkable (I agree). They also suggest that an eliminitivist approach would also be successful, because researchers will just keep using the terms anyways. Consequently, they encourage the adoption of an "epistemology of the imprecise". I'm fine with imprecision, but I would suggest that the confusion about representation stems from the fact that the concept is incoherent.

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Hologram lecturers thrill students at trailblazing UK university
Rachel Hall, The Guardian, 2024/01/22

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According to this article, AI is being used to animate holographic human figures for students. "Proto has the technology to project an image of Stephen Hawking, or anybody, and make it look like he's really there. We can hook it up to books, lectures, social media – anything he was attached to, any question, any interaction with him." We all want to be able to learn in a holodeck, I'm sure, but I'm less certain that Hawking-in-a-box would be appealing over the longer term.

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The Web Timelined Self
Alan Levine, CogDogBlog, 2024/01/22

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This is an interesting excursion into the ways we can keep track of ourselves through the things we post online. This post makes me think of Anil Dash's short commentary arguing that personal blogs are where tech news happens. I've always wondered what my timeline would look like if I were able to combine photos, blog posts, presentations, videos, maybe even some emails, etc., all in one comprehensive timeline. It would need to use something like an IFTTT gizmo, says Levine. I've been using IFTTT for many years now but have found it a bit glitchy, and it costs new users too much money. Levine posted today about Make; I have yet to try it but it looks like an interesting way to combine data from different services.

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Quality teaching and learning in a fully online large university class: a mixed methods study on students’ behavioral, emotional, and cognitive engagement
Nan Yang, Patrizia Ghislandi, Higher Education, 2024/01/22

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I was tempted to dismiss this paper (27 page PDF) out of hand when I read it was investigating "a new scenario: the fully online large university class." After all, we've been doing this for a few decades now. But I liked the oveall approach of the study involving, essentially, the study of student engagement rather than simple behavioural measures (like course grades) to evaluate course quality. Importantly, grades are not a measure of quality, and engagement is not a predictor of grades. "We suggest moving from the exclusive use of a prediction algorithm based only on behavioral data to the analysis of richer data sources that explore more types of engagement (behavioral but also emotional and cognitive)."

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A meta systematic review of artificial intelligence in higher education: a call for increased ethics, collaboration, and rigour
Melissa Bond, et al., International Journal of Educational Technology in Higher Education, 2024/01/22

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This is a tertiary review - that is, a review of systematic reviews - of studies of the use of AI in education, referencing Zawicki-Richter's typology (which of course is far too limited and doesn't include the many uses of generative AI; I of course am biased in favour of my own typology). Some obvious findings: "AI systems are adaptable and allow learning materials to be tailored to individual needs, thereby enhancing student autonomy, and enabling early interventions for disengaged students... Other significant benefits include the positive influence on learning outcomes, reduced administrative time for educators, and greater insight into student understanding." Notably, the paper calls for increased rigour in these systematic reviews. "A noticeable 65% of reviews are critically low to medium quality... The most concerning findings were that 31.8% of studies only searched in one or two databases."

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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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