AERA-ICPSR PEERS Workshop

“Cutting-Edge Quantitative and Computational Methods for STEM Education Research”

February 25, 2021

Instructors

 
Kenneth Frank, Michigan State University

Guanglei Hong, University of Chicago

Stephen Raudenbush, University of Chicago

Yanyan Sheng, University of Chicago

Kaitlin Torphy, Michigan State University
 

About the Workshop

 
The overall goal of this webinar is to inform participants of a wide range of significant research questions, data structures, and advanced analytic techniques in the context of theory-driven and data-informed rigorous empirical investigations of STEM education, especially concerning under-represented groups. Cutting-edge methods are essential to study student and teacher experiences with STEM education programs developed, implemented, and evaluated in a complex environment that outstrips what can be rendered by conventional statistical techniques. To illustrate major methodological considerations, instructors will use a stylized case that evaluates the potentially differential impacts of curricular innovations representing the Next Generation Scientific Standards (NGSS) on instructional practices, student engagement, and science achievement. Key methodological issues will be discussed in six inter-related modules:

(1) Design: How to select the sample of schools and teachers and whether to adopt an experimental or a quasi-experimental design suitable for causal inference of the effects of the curricular innovation..

(2) Measurement: How to construct theoretically grounded instruments with strong psychometric properties to measure student engagement, student learning, teacher practices, etc.

(3) Social network analysis: How to represent and model teachers’ interactions with one another as they adapt and implement the new curriculum.

(4) Multilevel modeling: How to represent and model the student, teacher, and school level factors that affect the implementation and outcomes of the curriculum.

(5) Causal mediation analysis: How to examine instructional practices as a mediator of the effects of the curriculum on student outcomes.

(6) Computational methods: How to account for teachers’ and students’ engagement with one another and educational resources on-line.

Please find the slides for each module from the respective link above and stay tuned for the recording of the video presentation.

Scroll to Top