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Direct linkDanielle S. McNamara; Tracy Arner; Reese Butterfuss; Debshila Basu Mallick; Andrew S. Lan; Rod D. Roscoe; Henry L. Roediger; Richard G. Baraniuk – Grantee Submission, 2022
The learning sciences inherently involve interdisciplinary research with an overarching objective of advancing theories of learning and to inform the design and implementation of effective instructional methods and learning technologies. In these endeavors, learning sciences encompass diverse constructs, measures, processes, and outcomes…
Descriptors: Artificial Intelligence, Learning Processes, Learning Motivation, Educational Research
Matthew E. Jacovina; Erica L. Snow; G. Tanner Jackson; Danielle S. McNamara – Grantee Submission, 2015
To optimize the benefits of game-based practice within Intelligent Tutoring Systems (ITSs), researchers examine how game features influence students' motivation and performance. The current study examined the influence of game features and individual differences (reading ability and learning intentions) on motivation and performance. Participants…
Descriptors: Game Based Learning, Intelligent Tutoring Systems, Learning Motivation, Performance
