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Yasemin Copur-Gencturk; Jingxian Li; Sebnem Atabas – American Educational Research Journal, 2024
Scalable and accessible professional development programs have the potential to address the opportunity gap many teachers experience. Yet many asynchronous online programs lack interaction with and timely feedback to teachers. We addressed this problem by developing a virtual, interactive program that uses intelligent tutoring systems to provide…
Descriptors: Artificial Intelligence, Faculty Development, Individualized Instruction, Interaction
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Fancsali, Stephen E.; Li, Hao; Sandbothe, Michael; Ritter, Steven – International Educational Data Mining Society, 2021
Recent work describes methods for systematic, data-driven improvement to instructional content and calls for diverse teams of learning engineers to implement and evaluate such improvements. Focusing on an approach called "design-loop adaptivity," we consider the problem of how developers might use data to target or prioritize particular…
Descriptors: Instructional Development, Instructional Improvement, Data Use, Educational Technology
Rose E. Wang; Ana T. Ribeiro; Carly D. Robinson; Susanna Loeb; Dorottya Demszky – Annenberg Institute for School Reform at Brown University, 2024
Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive, creating significant barriers to improving education…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Tutors, Elementary School Students