Jane Hart from the Centre for Learning & Performance Technologies has published the seventeenth in her annual survey of the Top 100 Tools for Learning. There were 2,022 votes in the survey drawn from both the education sector and industry. There was little change or surprise in the top three" YouTube, Google Search and Microsoft Teams. And perhaps there should be no surprise in the fourth top tool with ChatGPT leaping in from nowhere the year before. Other big winners in this years survey were Netflix, Grammarly and Tiktok. Jane explained that this year there were more votes from the education sector than last year, leading to many of the educational tools have regaining lost ground over more productivity and workflow tools on this year’s list.
For those of us who have been working on AI in Education it is a bit of a strange time. On the one hand it is not difficult any longer to interest policy makers, managers or teachers and trainers in AI. But on the other hand, at the moment AI seems to be conflated with the hype around Chat GPT. As one senior policy person said to me yesterday: "I hadn't even heard of Generative AI models until two weeks ago."
And of course there's a loge more things happening or about to happen on not just the AI side but in general developments and innovation with technology that is likely to impact on education. So much in fact that it is hard to keep up. But I think it is important to keep up and not just leave the developing technology to the tech researchers. And that is why I am ultra impressed with the new publication from the Netherlands SURF network - 'Tech Trends 2023'.
In the introduction they say
This trend report aims to help us understand the technological developments that are going on around us, to make sense of our observations, and to inspire. We have chosen the technology perspective to provide an overview of signals and trends, and to show some examples of how the technology is evolving.
Surf scanned multiple trend reports and market intelligence services to identify the big technology themes. They continue:
We identified some major themes: Extended Realities, Quantum, Artificial intelligence, Edge, Network, and advanced computing. We believe these themes cover the major technological developments that are relevant to research and education in the coming years.
But what I particularly like is for each trend the link to to public values and the readiness level as well. The values are taken from the diagram above. As SURF say "public values are key to efficient education and research."
We do far too few book reviews on this site and I am afraid this isn’t going to be one either. Instead we are plugging an eagerly awaited (and very timely) book be ed-tech journalist Audrey Watters which was published…
This is quite a good introduction to machine learning. If you don't know what it is and would like a quick no-nonsense introduction, this is it. Machine learning is depicted "as the science of getting computers to learn automatically." It's a type of artificial intelligence, which means essentially that they are software systems that "operate in an intentional, intelligent, and adaptive manner." The third point is the most important, because it means they can change their programming based on experience and changing circumstances. The article talks about some types of machine learning systems and outlines some application in the field. It's FutureLearn, so at the end it recommends some course tracks for people interested in making this a career, and just to dangle a carrot, the web page lets you know the median base salary and number of job opening for the program in question.
This is quite a good introduction to machine learning. If you don’t know what it is and would like a quick no-nonsense introduction, this is it. Machine learning is depicted “as the science of getting computers to learn automatically.” It’s a type of artificial intelligence, which means essentially that they are software systems that “operate in an intentional, intelligent, and adaptive manner.” The third point is the most important, because it means they can change their programming based on experience and changing circumstances. The article talks about some types of machine learning systems and outlines some application in the field. It’s FutureLearn, so at the end it recommends some course tracks for people interested in making this a career, and just to dangle a carrot, the web page lets you know the median base salary and number of job opening for the program in question.
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