When one of our learning support teachers asked me if there were any AI tools that would take notes for students, I could think of several solutions…but decided to create one myself and use this as an opportunity to test whether open-source resources (which help solve issues of privacy and cost) would be performant enough to be fit for purpose.
AI enhancements are often geared towards older students, but Microsoft's new Reading Coach promises to engage younger learners and help increase reading fluency by allowing them to co-create stories, adjusting reading levels, providing scaffoldings, personalizing practice, celebrating their achievements - and providing useful data to educators. There is a number of ways Reading Coach could be further improved, but it is free and safe to try.
ChatGPT can explain and illustrate concepts such as Theory of Mind. However, this does not mean that it truly understands human psychology. Indeed, it cannot use this “knowledge” to solve real-life problems in novel contexts. But it is possible to teach it how to do so - with prompt engineering.
A report by McKinsey&Co highlights 4 imperatives for successful AI integration in K-12 schools, including where to gain in efficiency through automation, and where to reallocate the time saved for greater effectiveness and improved student learning.
Research makes it clear that frequent, high-quality feedback is essential to professional growth. However, school leaders rarely have the bandwidth to get back to teachers timely and meaningfully after class observations. Here is how AI can help. A great example of the next stage in AI integration: workflow automation.
Teachers love creating custom chatbots for their own purposes. However, effective, specific ones still require complex prompts on POE, and GPTs have limited accessibility. Child and data safety, as well as academic integrity, also remain problematic. This is where Mizou, SchoolAI, and Sherpa come in. All 3 are probably in my Top 10 favorite EduAI tools at the moment. Really worth a try.
As educators grapple with the potential and limitations of AI integration in a school context, scientific research can give us some much needed perspective and an objective measure of the effectiveness of these technologies.
The most important issue surrounding the use of AI for teaching and learning purposes is arguably the least talked about: equity.
The growing powers and pervasiveness of AI technologies will either help students develop fundamental skills, or prevent them from doing so. Or rather, unless we guide and scaffold their use, the risk is high that they will worsen, rather than enhance, their thinking, information literacy, and other critical competencies. This gallery based on the International Baccalaureate "ATL Skills" framework includes examples of tools and prompts that can help students make the best of the opportunities provided by AI to superpower their learning.
The “AI Assessment Scale” is a five-point scale created by Leon Furze to help educators clarify the appropriate level of generative AI (GenAI) use in their assessments. Its author breaks it down as follows:
No AI - Brainstorming and Ideas - Outlining and Notes - Feedback and Editing - Full AI
While it has many benefits and was an important contribution to our collective reflection on the most effective ways to help teachers and students integrate GenAI effectively and appropriately in an educational context, it also has limitations that ultimately call for a new Revised AI Assessment Scale. Here, I propose two: an “Intensity” scale and a “Competency scale”.