Using Big Data to Understand Factors that Affect Student Success in STEM
Understanding both the barriers as well as the pathways to student success is critical to support all students to learn and achieve in STEM. In this talk, I will describe a research project that brings together an interdisciplinary team of learning scientists to understand the factors that affect student success in STEM disciplines. We are particularly concerned with questions about for whom educational innovations are effective, and their longitudinal outcomes. I will describe the overarching project and how we bring together different types of data and expertise to answer these questions. I will then describe one strand of the project that has focused on understanding underrepresentation of women in physics. As a first step, we have begun to examine student motivational and performance patterns across multiple large introductory physics courses. The findings have implications for the development and implementation of pedagogies to help all students learn.