Transforming Learning Experiences with Teachable AI

Overview

Teachable AI refers to artificial intelligence systems that can be trained or improved by non-experts, by providing their own data or preferences. This allows users to directly shape how the AI responds in real-world situations. By making AI more accessible, adaptable, and intuitive, teachable AI is transforming education. It lowers barriers to adoption and empowers both teachers and learners to actively shape and enhance their learning experiences. This new paradigm is opening up exciting possibilities for classrooms everywhere.

In this presentation, Professor Hu will highlight several recent studies—from K-12 to higher education—on integrating teachable AI with learning analytics to support both teachers and students across diverse subjects. These studies span topics such as introducing machine learning in secondary school AI education, leveraging generative AI and learning analytics for language and creative learning, and deploying adaptive, interactive AI-powered tools in university general education courses.

Empirical evidence demonstrates that teachable AI offers remarkable flexibility when applied in educational settings. While its potential is vast, there are clear challenges—both in ensuring technological accuracy and in designing systems that are truly human-centered and education-focused. Addressing these challenges requires close collaboration among educators, policymakers, and researchers. By working together, we can harness the full benefits of teachable AI to transform teaching and learning for all.