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Founded in 2017 by a group of learning scientists at UCLA and Cal State LA with a shared interest in understanding and improving how students learn things that are hard to learn. The initial focus is on the teaching and learning of introductory statistics and data science. But the longer-term agenda is to make research on teaching and learning more relevant and more effective for improving important learning outcomes for all students. Though much research on teaching and learning is conducted in labs over short periods of time, the development of transferable knowledge in complex domains such as mathematics, science, and statistics takes place over long periods of time – weeks, months, or even years – and in complex cultural contexts. Theories and findings from lab-based research often don't apply in the complex contexts in which students learn. Their introductory online textbook, Statistics and Data Science: A Modeling Approach, has been used at over 50 institutions worldwide, and adoption is growing. As the number of students grows, so do opportunities for research. So far, more than 1,000 incremental improvements have been made in the textbook and in supplemental materials.

Program Coordinator, Ji Yun Son

Website: coursekata.orgThis link will take you to an external website in a new tab.