Mak Ahmad

Mak Ahmad is a researcher at the intersection of artificial intelligence and STEM education, investigating how AI tools can be integrated into learning environments without undermining the foundational skills students need to develop. His work spans data visualization, API design, and large-scale biology education, examining how different disciplines require different approaches to AI integration. A central theme across his research is the critical distinction between learning to use AI and using AI to learn — two objectives that are often conflated but demand fundamentally different pedagogical strategies. His findings consistently show that simple metacognitive scaffolding can outperform sophisticated AI feedback, suggesting that how students reflect on their learning may matter more than how advanced the technology supporting them is.