Chapter 4: Learning 4. Learning The Department’s long-standing edtech vision sees students as active learners; students participate in discussions that advance their understanding, use visualizations and simulations to explain concepts as they relate to the real world, and leverage helpful scaffolding and timely feedback as they learn. Constituents want technology to align to and build on these and other research-based understandings of how people learn. Educators can draw upon two books titled How People Learn and How People Learn II by the National Academies of Sciences, Engineering, and Medicine for a broad synthesis of what we know about learning. As we shape AIenhanced edtech around research-based principles, a key goal must be to strengthen and support learning for those who have experienced unfavorable circumstances for learning, such as caused by the COVID-19 pandemic or by broader inequities. And we must keep a firm eye toward the forms of learning that will most benefit learners in their future lives in communities and workplaces. Examples of AI supporting learning principles in this section include the following: AI-based tutoring for students as they solve math problems (based on cognitive learning theories), adapting to learners with special needs (based on the Universal Design for Learning framework and related theories), and AI support for effective student teamwork (based on theories in the field called “Computer Supported Collaborative Learning”). 4.1. Insight: AI Enables Adaptivity in Learning Adaptivity has been recognized as a key way in which technology can improve learning. AI can be a toolset for improving the adaptivity of edtech. AI may improve a technology’s ability to meet students where they are, build on their strengths, and grow their knowledge and skills. Because of P a g e | 30
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