We are living through a transformation in how people learn — and the pace is only accelerating. New digital technologies are arriving faster than most institutions can absorb them, yet the opportunities they create for teaching and learning are too significant to ignore. This talk offers both the big picture and the practical detail. Starting with a description of the fundamental shift in how we define learning itself — from passive transmission to active construction — it maps the future skills today's students will need to thrive professionally. From there, it explores the frontier technologies reshaping education: playful learning, extended reality, and artificial intelligence, showing how each can be leveraged to spark genuine interest and drive meaningful outcomes. Read More >

What you'll take away: Read Less ^

• How our understanding of learning has evolved — and why that shift matters for how we design learning experiences
• A clear-eyed look at the most promising digital technologies reshaping education, including playful learning, XR, and AI
• Practical insights into how these technologies can be used to increase both student engagement and learning outcomes

AI isn't coming for education — it's already here. Yet most institutional responses have been reactive, focused on what students shouldn't do rather than what educators could do. This talk flips that script. Starting with a clear-eyed explanation of how large language models actually work, it makes the case for education institutions to stop playing defense and start leading. You'll explore concrete ways AI can be woven into teaching and learning to deepen understanding, sharpen critical thinking, and amplify human creativity — not replace it. The real question isn't whether AI belongs in education. It's whether institutions will actively shape that future or simply react to it. Read More >

What you'll take away: Read Less ^

• How large language models work — explained in plain language for educators and education leaders
• Practical strategies for integrating AI in ways that enhance rather than shortcut deeper learning
• A fresh lens for reconsidering your institution's pedagogical practices and value proposition in an AI-powered world

Personalized learning has long been called education's holy grail — and generative AI has sparked a wave of tools promising to finally deliver it. But are they? This talk cuts through the hype with a clear-eyed look at what today's adaptive systems are actually doing, and more importantly, what they're missing. Drawing on a taxonomy of adaptivity, you'll see why most current tools are only scratching the surface — personalizing on a narrow slice of variables while overlooking the cognitive, emotional, motivational, and cultural dimensions that make learners truly unique. The result is a richer, more demanding vision of what personalized learning could become — and a roadmap for getting there. Read More >

What you'll take away: Read Less ^

• A taxonomy of adaptivity that reveals the gap between current AI tools and genuine personalization
• The full range of variables — cognitive, affective, motivational, and socio-cultural — that future adaptive systems must incorporate
• A clearer picture of where generative AI can meaningfully advance personalization beyond chat-based interactions

Digital games are everywhere — and yet they remain one of the most misunderstood tools in the educator's toolkit. Heralded by some as agents of education reform and dismissed by others as distraction, games occupy a contested space in learning. This talk cuts through the noise with a research-grounded tour of what we actually know. Starting with a crisp distinction between gamification, game-based learning, and playful learning, it explores the cognitive, social, and emotional dimensions that determine whether games deliver real learning outcomes. You'll examine what the empirical evidence tells us, what design principles emerge from that research, and how evolving frameworks are being extended to make sense of games as serious learning environments. Read More >

What you'll take away: Read Less ^

• A clear distinction between gamification, game-based learning, and playful learning — and why the differences matter
• What the research actually shows about the cognitive, social, and emotional factors that make games effective for learning
• How contemporary learning theories, including Cognitive Load Theory, are being extended to explain and improve learning through games

For four decades, Cognitive Load Theory has shaped how we design classrooms and training programs worldwide — but the world of learning has changed. This talk brings CLT into the present, unpacking three bold updates that make the theory more powerful and practical than ever. You'll discover how we streamline cognitive load into two categories, why learner goals are now front and center, and how motivation and emotions have finally earned their place in the model. Whether you design simulations, games, or other digital learning experiences, this evolved framework gives you sharper tools to build environments where cognitive load is optimized and learners stay engaged. Read More >

What you'll take away: Read Less ^

• Why CLT needed to evolve — and the key debates that pushed it forward
• How the revised theory is able to guide the design of complex, real-world learning
• A practical framework for integrating cognitive load, learner motivation and emotion into your instructional strategy