AI in education is a huge topic. It has this in common with most of the topics Rick Huckstep and I talk about on the BTLT podcast. This subject in particular is sensitive in how it's subjectively perceived. There appears to be as many negative as positive anecdotal examples of how it might be abused or embraced. For the record, I'm optimistic about what it can do, and pessimistic about how it will be used. I hope my pessimism is proved wrong in time.

Here are my notes for episode 34 of Big Tech Little Tech. As usual, I didn't get to explore all of them in the show itself, but my co-host and I got to many of them. Have you heard the episode yet? If you have, what did we miss out that we can discuss in a future episode? Your feedback is always appreciated.

A quick reminder: There's more content in our video version. If you're a Patreon subscriber, you can spend £2 a month to get extended video versions and transcripts.

How is AI currently being used in teaching?

• Personalised learning: AI platforms can analyse student data to better understand each student's attitudes and needs. From this, AI tools can design personalised training pathways. This might help teachers that have large classrooms, too.
• Streamlined admin: AI can help with grading or note-taking, so teachers could focus more on personalised instruction and student engagement.
• School management: AI is being used to manage entire schools, powering student records systems, transportation, IT, maintenance, scheduling, budgeting etc.
• Intelligent tutoring: AI-powered tutoring helps us learn better and faster when paired with high-quality learning materials.
• Providing immediate feedback: AI can provide meaningful and immediate feedback to students, allowing them to feel comfortable making mistakes.
  
  

What are the advantages of AI in teaching?

• Save time.
• Provide real-time feedback.
• Save manual labour.
• Understand individual student needs.
• Help with lesson plans.

What are the limitations of AI in teaching, and how could they be addressed?

• Is there enough reliable data for AI systems to process? Collaboration between researchers, educators and policymakers could help ensure the availability of high-quality data for AI systems in education.
• AI can be expensive, especially in how often they require updates. Open source alternatives.
• AI systems require some technical expertise to get the best out of them. Training teachers is expensive, too. Provide necessary training.
• Student and teacher data privacy concerns, algorithmic bias and lack of human empathy. Establish clear guidelines and regulations.
  
  

Ted Chiang for The New Yorker

Having students write essays isn’t merely a way to test their grasp of the material; it gives them experience in articulating their thoughts. If students never have to write essays that we have all read before, they will never gain the skills needed to write something that we have never read.

What do future developments in AI look like, and how might they impact teaching?

• AI could help inspire teachers to create more engaging learning experiences.
• AI could go further in reducing administrative strain linked to overcrowded classrooms and overworked teachers.
• Access to more varied educational resources. AI is better than Google!
  
  

Who’s leading the way in EdTech?

• The US is considered the leading nation in terms of EdTech development, being home to 43% of the world's EdTech companies. It's also invested huge amounts of money.
• China is doing well, as is India. Covid was a driver.
• Sweden is where the highest proportion of EdTech companies secure funding.
• The UK is home to some of the top tech and engineering programs in the world: Cambridge, Oxford, Imperial College London and the University of Manchester.