The AI Education Revolution is Coming – or is it? | Dr. Philippa Hardman | TEDxSantaBarbaraSalon

Summary

Phil, an Affiliated Scholar at Cambridge University, discusses the potential of edtech to revolutionize learning. Despite over 30 years of research in learning science, he notes a disconnect between theory and practice, with technology often reinforcing traditional teaching methods rather than innovating. He highlights the importance of active, personalized learning, and the need for educators to embrace AI to enhance, not replace, human learning. Phil also touches on the 'three teams' approach to AI in education: avoidance, detection, and embracing AI, advocating for the latter as the future of education.

Takeaways

• 🎓 Phil, an Affiliated scholar at Cambridge University, is a learning scientist with a passion for edtech and its potential to transform learning experiences.
• 🔍 Learning science, with over 30 years of research, remains largely inaccessible behind paywalls and Ivory Towers, creating a disconnect with practical learning design.
• 📚 Phil advocates for the application of learning science research to bridge the gap between theory and the design of effective learning experiences.
• 🕵️‍♂️ The optimal conditions for human learning, as researched by educational psychologist Benjamin Bloom, suggest a shift from traditional teaching methods to more active, problem-based learning approaches.
• 📈 Bloom's findings indicate that a change in instructional methods could significantly improve learning outcomes, especially for non-traditional or underrepresented learners.
• 🚀 Despite the potential, educational technology has often reinforced traditional teaching methods rather than innovating new, more effective systems.
• 🤖 AI in education has been used to automate and accelerate existing, sometimes ineffective, practices rather than to innovate pedagogy.
• 🔎 Phil questions why, with the knowledge of effective learning formulas, technology isn't used more effectively to achieve these scenarios and provide equal learning opportunities.
• 🌐 The discussion highlights the need for a discourse between education technology and the application of AI to truly innovate and improve learning outcomes.
• 🔄 The 'three teams' concept discusses the different approaches to AI in education: avoiding AI, detecting and banning it, and embracing it as a tool for enhancing learning experiences.

Q & A

What is Phil's official title and what does it imply?

Phil's official title is 'learning scientist', which implies that he is involved in the study of how humans learn, a field that has been researched for over 30 years but remains largely unknown to the general public.

Why does Phil believe there is a lack of intersection between learning science research and educational practices?

Phil believes there is a lack of intersection because the research in learning science, which has been conducted for over 30 years, remains locked behind paywalls and Ivory Towers, not influencing the way learning experiences are designed.

What was Benjamin Bloom's significant finding about optimal learning conditions?

Benjamin Bloom found that the optimal learning experience for humans involves active learning, problem-based approaches, and ideally one-to-one coaching support, which significantly improves learning outcomes, especially for non-traditional or underrepresented learners.

How has educational technology historically been used, according to Phil?

Phil states that educational technology has historically been used to reinforce the traditional 'sage on the stage' teaching model, making it more efficient rather than introducing new, more effective systems of learning.

What is the risk Phil identifies with the use of AI in education?

The risk Phil identifies with AI in education is that it could make us more efficient at ineffective practices, rather than innovating pedagogy and improving learning outcomes.

What does Phil think about the potential of AI to disrupt education?

Phil believes AI has the potential to disrupt education and deliver on Bloom's vision of optimal learning, but the real question is whether we will allow it to do so, as we have had the capability to do this for 30 years and have not yet fully embraced it.

What is Phil's perspective on the recent integration of AI into learning experiences by Khan Academy?

Phil sees the integration of AI by Khan Academy as a positive step towards realizing Bloom's recommendations from 1984, offering personalized, adaptive learning paths powered by AI.

What are the 'three teams' Phil mentions in the context of generative AI in education?

Phil mentions 'three teams': Team Avoid, which tries to circumvent AI; Team Bennett, which attempts to detect and ban AI-generated work; and Team Embrace, which seeks to integrate AI into the classroom positively.

Why does Phil think Team Embrace is the most promising approach to AI in education?

Phil believes Team Embrace is the most promising because it acknowledges the inevitability of AI in education and focuses on educating students about AI, its uses, weaknesses, and risks, rather than trying to avoid or ban it.

What does Phil suggest is the role of educators in an AI-powered future?

Phil suggests that educators in an AI-powered future should play a critical role in guiding students on how to use AI, understanding its capabilities and limitations, and navigating its ethical and practical implications.