E
xperts across academia and industry discussed the next steps for AI in education, covering learning to research, policy and teacher capability.
Themes included cognitive offloading and
outsourcing, equity and inclusion, as well as a lack of policy and centralised guidance on AI use in education. There were calls too for a national ed tech strategy and more independent research on how AI tools impact various outcomes and teacher workload. The potential of 1-2-1 AI tutoring was explored
with some concern that students could miss out on a vital benefit teachers provide – getting young people motivated and interested. While many expressed the need to keep teachers at the heart of decision making when it comes to AI and ed tech in learning.
ON AI USE & MISUSE Daniel Wilson, Senior Product Manager, Data, AI, Skills and Social Responsibility, UK Impact, Amazon UK: AI is like a whetstone for our abilities. If it’s used well, it sharpens your skills, but if it’s used carelessly, it may dull your edge. And whilst access matters, worse than no AI skills might be bad AI habits, especially in the young, because they don’t have a pre-AI playbook to fall back on. So, a simple test that I like to challenge people with is: if AI disappeared tomorrow, would you be better off having used it? What have you gained that you can carry forward? As AI can handle more and more tasks – we need to make ‘effort’ cool. We need to call out the sloppy AI use. When we
showcase it to young people we need to engineer ways where humans are clearly aided by using the AI but we also need to showcase times where they’re clearly hindered by using it. We need to frame its outputs as opinions and not facts, and we need to encourage people to pick AI’s role to suit the task that they’ve got in front of them. Should you treat it as a tutor to teach you something? Should you treat it as a partner so it can challenge your assumptions? Or in some cases, but never all, to outsource your work to it? Some put off AI learning because they perceive it to
be too technical a thing to even get involved with, but with the right support I’ve seen for myself how people grow in confidence. The technical depth that we need to teach people around AI can be an obstacle to further engagement so the timing of it is really important. We also shouldn’t assume that more classically technical profiles of people will be the most proficient with generative AI – and that can help widen the pipeline for more technical talent in the future.
Prof Miles Berry, Computing Education, School of Education,
University of Roehampton:
On cognitive outsourcing the research is pretty well documented. We have a strong evidence base that the AIs are really very good and produce super work in all sorts of territory but they don’t necessarily help anyone to learn anything. The thing that you get good at is the thing you spend your time on, and that thing could be just prompting the AI, or it could be learning the subject.
9
GUIDE TO INTERNATIONAL EDUCATION & SCHOOLS AI IN EDUCATION
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48
