Awesome GPT-4
Radi Cho,
GitHub,
2023/03/23
This is "curated list of prompts, tools, and resources regarding the GPT-4 language model," including open source examples and community demos, and product integrations. Related: Bryan Alexander shares a conversation with Ruben Puentedura to explore the implications of large language model artificial intelligence; he adds some other interesting items, including authoring a 300-page text in one day with chatGPT, Microsoft's introduction to Copilot, and the Socratic Tutor system. I also ran across a Marcus Aurelius AI, which is a neat concept. Finally, the usual suspects from the music industry form a coalition to make sure publishers' copyrights aren't violated (but be careful - if new rules are created that apply to computers, including limits to fair use, they will definitely be extended to humans - imagine being told you can't record because your voice sounds too similar to someone else's).
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Every Possible Wordle Solution Visualized
Shri Khalpada,
PerThirtySix,
2023/03/23
I like this interactive visualization because it shows the advantage of working with connected data rather than raw lists or quantified data. Wordle is a game where you guess a five-letter word; you get five guesses, and it tells you when you've found correct letters. It's a always a question: where do you start, when you have no information about the word? Where next, when you have one of two letters? Suggestions abound, usually based on how frequently a letter appears. A graph analysis enables a better suggestion. But playing with the graph, you come to see you don't want to select letters that leave too many possibilities (which is what you get if you're vowel-heavy) or too few (which is what you get is you select infrequently used consonants). Anyhow, have fun with it.
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Agency in Educational Technology: Interdisciplinary Perspectives and Implications for Learning Design
Garvin Brod, Natalia Kucirkova, Joshua Shepherd, Dietsje Jolles, Inge Molenaar,
Educational Psychology Review,
2023/03/23
The post that led me to this paper tended to repeat the same point over and over, offering a number of ways of saying we want a balance between too little agency and too much agency (which, we are told, might lead to suboptimal educational outcomes). The paper itself, to which I link here, is much better structured, but still seems to repeat that same point a lot. Still, there are good bits, including especially the identification of six different types of agency. Is this list exhaustive? Almost certainly not. But it's very useful to keep in mind that agency isn't some undifferentiated whole; epistemic agency, moral agency, and group agency (for example) are each very different.
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Learning with Digital Media: A Systematic Review of Students’Use in African Higher Education
Frank Senyo Loglo, Olaf Zawacki-Richter,
Journal of Learning for Development,
2023/03/23
"Over the past four decades, tertiary enrolment in Africa has increased, and the demand for higher education is expected to witness a further increase," write the authors. Not surprisingly, "While educational technologies provide opportunities for widening access, they may also accommodate a deep divide." This survey analyzes 64 papers from 2010 forward to examine this trend. The research is mostly still in the descriptive phase; "More than half of the included articles failed to incorporate any theory, framework, or model." That's not necessarily a bad thing; why would we expect the African experience to be framed by theories developed for the European or American experience? But a mostly uncritical use, write the authors, means that tools might not be as useful as they could be. They write, "to achieve beneficial outcomes for technology-enhanced learning in Africa, it is essential to pursue a deliberate and sustainable policy of developing the digital skills and competencies of students and teachers, in particular, for the effective use of digital media."
Web: [Direct Link] [This Post]
Learning Analytics and the Abolitionist Imagination
Shea Swauger, Remi Kalir,
Journal of Learning Analytics,
2023/03/23
The authors argue "The academic learning analytics (LA) community should contest prominent tool-based and data-centric conceptions of LA that frequently render this technology as a neutral object delimiting ethical implementations, critiques and potential harms such as surveillance and discrimination." They support this analysis with three speculative vignettes that "illustrate that LA technologies can be used by students in ways not intended by designers or not expected given institutional norms." I have no objection to looking at any technology with a critical eye, but that should be a part, not the whole, of any such consideration. Image: A data-centric view of the management framework, Couch.
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