AI and Motivation for Learning
Here’s the follow up I promised in my last post about earners’ and teachers’ Agency and Gen AI. Motivation plays a crucial role in the learning process. As opposed to behaviorist theories of learning, learners are increasingly seen as active participants in learning leading to a focus on how learners make sense of and choose to engage with their learning environments (National Academies of Sciences, Engineering, and Medicine. 2018). Cognitive theories, for example, have focused on how learners set goals for learning and achievement and how they maintain and monitor their progress toward those goals. While earlier research focused largely […]
Teachers’ and Learners’ Agency and Generative AI
It is true that there is plenty being written about AI in education – almost to the extent that it is the only thing being written about education. But as usual – few people are talking about Vocational Education and Training. And the discourse appears to almostdefault to a techno-determinist standpoint – whether by intention or not. Thus while reams are written on how to prompt Large Language Models little is being said about the pedagogy of AI. All technology applications favour and facilitate or hinder and block pedagogies whether hidden or not (Attwell G and Hughes J. 2010) . […]
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AI and Ed: pitfalls but encouraging signs
Joahna Kuiper / Better Images of AI / Little […]
Who owns your data?
Arguments over what data should be allowed to be used for training Large Language Models rumble on. Ironically it is LinkedIn which hosts hundreds of discussion is AI which is the latest villain. The platform updated its policies to clarify data collection practices, but this led to user backlash and increased scrutiny over privacy violations. The lack of transparency regarding data usage and the automatic enrollment of users in AI training has resulted in a significant loss of trust. Users have expressed feeling blindsided by LinkedIn’s practices. In response to user concerns, LinkedIn has committed to updating its user agreements […]
AI and Ed: pitfalls but encouraging signs
In August I became hopeful that the hype around Generative AI was beginning to die down. Now I thought we might get a gap to do some serious research and thinking about the future role of AI in education. I was wrong! Come September and the outpourings on LinkedIn (though I can’ really understand how such a boring social media site became the focus for these debates) grew daily. In part this may be because there has now been time for researchers to publish the results of projects actually using Gen AI, in part because the ethical issues continue to […]
Pedagogical Approaches and Google NotebookLM
Some ten or so years ago myself and Jenny Hughes were commissioned by Lifelong Learning UK to produce a Literature review on Pedagogic approaches to using technology for learning. As Wikipedia explains, Lifelong Learning UK (LLUK) was one of the independent, Sector Skills Councils (SSCs) for UK employers in the lifelong learning sector. It was responsible for the professional development of all those working in community learning and development, further education, higher education, libraries, archives and information services, and work based learning across the UK. As has arisen in the recent debate over the new Labour Government’s establishment of SkillsUK, […]
The AI Assessment Scale
I don’t know quite how I have managed to miss this up to now. The AI Assessment Scale (AIAS) has been around for over a year. On the occasion of updating to the latest version – see illustration above, Leon Furze, a Consultant, author and PhD candidate and one of the authors, said in his blog: The original AIAS and its subsequent formal version (published in JUTLP) represents a moment in time where educational institutions across the world were reaching for something to help with the immediate problems of AI, such as the perceived threat to academic integrity. Jason Lodge […]