Explanatory and Predictive Modeling Within Improvement Science Projects

Title: Explanatory and Predictive Modeling Within Improvement Science Projects
Abstract/Description: This paper explores the role of explanatory and predictive modeling within a large-scale, networked improvement community called the Carnegie Math Pathways. Drawing on multiple data sources from across multiple years, we demonstrate how both explanatory and predictive models helped in understanding what it means to be a successful student and learner in the Pathways.
Author/creator: Krumm, Andrew E.; Yeager, David Scott; Yamada, Hiroyuki
Date: 2019
At conference: AERA Annual Meeting
Resource type: en Research/Scholarly Media
Resource status/form: en Presentation/Poster
Scholarship genre: en Empirical
Language: en
Open access/full-text available: en No
Peer reviewed: en No
URL: Official Event Webpage (AERA)
Citation: Krumm, A. E., Yeager, D. S., & Yamada, H. (2019). Explanatory and Predictive Modeling Within Improvement Science Projects. AERA Annual Meeting, Toronto, ON. http://tinyurl.com/yaxj9my4
Place: Toronto, ON

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