Innovation Insights: A Research Talk with Ben Motz

Casting a Wider Net: Generalizable Inferences from Embedded Experiments with ManyClasses and Terracotta

Date & Time

December 2, 2024, 12:00 PM - December 2, 2024, 1:00 PM

Location

Virtual

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Education research studies often encounter barriers due to limited scope and context-specific findings. In this presentation, Ben Motz advocates that transformative research must overcome these limitations, and introduces two innovations that are reshaping the terrain of education research: ManyClasses and Terracotta. ManyClasses is a research model that casts a very wide net – but to cast such a wide net, researchers need dedicated infrastructure. Motz will also discuss Terracotta, an LMS plugin that makes it easy to run experiments in classes, while maintaining ethical protections that are inherent to responsible research. Join this engaging research talk to explore the potential of these tools to advance our understanding of student learning at scale.

A Zoom link will be provided upon registration. We hope to see you there!
 

Innovation Insights

The Center for Academic Innovation brings together people who want to transform education, share knowledge, and increase learner success by hosting inspiring talks, collaborative problem-solving workshops, and discussions on the latest in educational research and practice. The Innovation Insights series features a diverse lineup of topics, delivered by leaders in academia and private industry, united by the common goals of delivering insights into how to further academic innovation and build the future of education.

 

About Ben Motz

Dr. Ben Motz (he rhymes with boats) is an Assistant Professor in Indiana University's Department of Psychological and Brain Sciences. He received his BS from Indiana University, MS from University of California San Diego, and his Ph.D. from Indiana University, all in Cognitive Science. His research is at the intersection of cognitive psychology and education, characterized by large-scale experiments and analyses on students from real education settings that test theoretical predictions from the psychological science of learning.