Error Discovery Learning

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Abstract

Error discovery learning (EDL) is a web-based active learning method that makes students’ mistakes their most powerful learning tool. It engages students to solve fast challenge problems through their own thinking, in their own words, and then to assess competing conceptual arguments and identify specific conceptual errors. In 7 years of studies using EDL both inside and outside of the classroom, it has greatly increased student engagement, exam scores, and course completion rates (e.g., for women in a computer science theory course). Notably, EDL produced its biggest improvements for the bottom half of enrolled students - apparently by way of big boosts in their engagement - reducing course outcome disparities. Moreover, EDL is designed to be easy for instructors and scalable to large classes, using a free, open-source web platform (Courselets.org). I briefly review these results, show how EDL works with clear examples, and focus on simple best practices that make EDL easy for any instructor to start. The following questions are covered: Where is the easiest place in your class to start using EDL? How exactly do you run an EDL exercise for maximum learning? What is the first place to “individualize” student learning using EDL? How can I apply EDL to graded homework? How do I write effective EDL problems?.

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APA

Lee, C. (2020). Error Discovery Learning. In Active Learning in College Science: The Case for Evidence-Based Practice (pp. 757–771). Springer International Publishing. https://doi.org/10.1007/978-3-030-33600-4_47

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