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brian crabtree, izzzzi, 2024/12/09

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I'm not sure whether this post will be here tomorrow so I'll quote it at some length: "izzzzi is an experiment which might be called "slow social media" where we are exploring a multitude of constraints imposed on the standard mechanism of people making posts:

• posts are collected into a digest once a day.
• posts from yesterday are deleted, forever, every day.
• posts are a draft and can be edited until the moment that yesterday is deleted and tomorrow becomes today.
• posts are only visible between people who "add" one another ("mutual follows").

it's become a sort of collaborative daily newspaper written by friends. on the surface the parameters feel antithetical: it's ephemeral, it only changes daily, hardly anyone sees it. this is precisely what makes it interesting." It's one of these things that may flare up for a bit and then disappear. Like its posts. Via Ed Summers.

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Dimensions of AI Literacies
Angela Gunder, Opened Culture, 2024/12/09

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This is a presentation of multiple AI literacies, influenced by Doug Belshaw's work, describing them as: cultural AI literacies, cognitive, constructive, communicative, confident, creative, critical, and civic AI literacies. Each of these describes a specific aspect of a person's skills or competencies, for example, 'constructive AI literacies describe "understanding what it means to construct, build, or make something within AI-enabled environments". Similarly, 'cognitive AI literacies' involve "developing the skills necessary to navigate various AI environments to build knowledge and understanding effectively'. It's a useful way to look at AI literacies and makes me rethink again my approach to literacies generally.

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Providing performance information of peers as a management tool?
Lisa Wolf, IDW, 2024/12/09

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It's not formative evaluation and it's not summative evaluation. We'll call it competitive evaluation. "More and more companies are gathering performance data on their employees and sharing that data among their staff. Their hope: that those employees who receive feedback that their own performance is lower than their colleagues' will be more motivated to change the way they work and are more motivated to explore." Here's the complete publication (20 page PDF). The authors found that the effect varies based on the data; learning about high-performing peers will encourage people to explore better ways to do their work, but learning about low-performers won't. Also, if the person receiving the data already has a high tendency to self-enhance, learning about high-performers won't help them at all; "Presumably, those with a high tendency to self-enhance did not increase their propensity to explore because they saw the information about their high-performing peer as a threat to their self-image and therefore, found ways to ignore or discount it."

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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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