Recently, I was invited to give a keynote speech at the LGFL conference, where I had the opportunity to explore the hotly debated topic of AI in education. My talk centred around the question, “AI: should we lean into it or block it?” and the impacts it could potentially have. As I prepared for the presentation, I realised that there are still more questions than answers when it comes to AI in education, given that we’re just at the cusp of its capabilities.
While there are many experts and guides available on the topic, I wanted to share some of the crucial questions I have about AI in education and the current research available in this blog post. This is not a call for a complete ban on AI in the classroom, but rather a word of caution and reflection before diving headfirst into this exciting new era of technology.
As this topic is a complex and important one, I have broken it down into five separate blog posts. In each post, I will delve deeper into one of the key themes surrounding AI in education. The first post will focus on pupils using AI in the classroom and the many brilliant tools available to enhance their learning experience. The second post will explore the potential benefits and risks of pupils using AI at home. The third post will look at how teachers can use AI to improve their teaching methods and student engagement. The fourth post will examine the use of AI in assessments. Finally, the fifth post will explore the integration of AI into the curriculum and how it can enhance the learning outcomes for students across a range of subjects. I hope you find these upcoming posts helpful and informative, and I encourage you to stick around for all 5 to get a comprehensive understanding of these issues for AI in education.
Before delving into our first topic, it’s important to have a clear understanding of what AI, machine learning, and deep learning actually mean. AI stands for artificial intelligence and refers to the ability of machines to simulate human intelligence and perform tasks that normally require human intervention, such as decision-making, problem-solving, and learning. Machine learning is a subset of AI that involves using algorithms to analyse and learn from data, without being explicitly programmed to do so. Deep learning is an even more advanced subset of machine learning, where the algorithms are capable of learning from large amounts of unstructured data, such as images and sounds.
With Chat GPT hitting the headlines earlier this year AI may seem like a new technology, but the truth is that many teachers are already using some form of AI in their classrooms, such as automatic grading systems or educational games that adapt to a student’s performance. In fact AI is becoming increasingly integrated into our everyday lives, from personal assistants like Siri and Alexa that use natural language processing to understand and respond to our requests, to the recommendations we receive on Netflix and Amazon based on our previous viewing and purchase history. Even our smartphones use AI algorithms to improve the quality of our photos and provide real-time translations of foreign languages.
However, it’s important to recognize that AI is much more than just chatbots like GPT-3. AI has the potential to revolutionise the way we teach and learn, but it also brings with it a set of challenges and considerations that must be carefully evaluated before implementing it in the classroom.
Part 1: AI in Education: Pupils How can we safely integrate AI into our classrooms to enhance pupils’ learning?
Part 2: AI in Education: Homework How can we ensure responsible use of AI by pupils at home for learning purposes?
Part 3: AI in Education: Teachers How can we utilise AI to enhance lesson quality and reduce workload while complying with laws and legislation?
Part 4. AI in Education: Curriculum How can we design an AI-ready curriculum for students?
Rachel Arthur writes 