A diverse and highly skilled engineering workforce plays a critical role in maintaining economic competitiveness and protecting national security. To achieve these aims, engineering programs in higher education must guarantee that curricula are both rigorous and equitable. As demand for engineering majors increases, so too do section sizes for foundational engineering courses. There is growing evidence that such courses represent significant barriers to student success and that the penalties associated with large classes can disproportionately affect women and underrepresented groups. Further, these educational environments make it challenging to implement evidence-based teaching practices known to be better for student learning. This project will build a learning organization ecosystem -- a grassroots effort involving engagement between faculty and departmental and institutional support structures to collaboratively identify problems and continuously, systematically improve the quality and equitability of the engineering curricula. During this project, sixteen instructors responsible for teaching approximately 4800 undergraduate engineering students in large foundational courses will be impacted. Beyond the instructors and the students directly impacted, research findings and project outcomes will be shared broadly so that other faculty and administrators might similarly improve their educational enterprise.
This project responds to national calls for undergraduate engineering to become more data-driven by exploring how existing, diverse data sources can be leveraged to enhance educational environments. Early efforts will focus on creating intelligent feedback loops, robust streams of existing institutional data (e.g., historical transcript data, student evaluations), existing instructor-level data (e.g., past exams), and newly collected data (e.g., surveys about how students spend time pre/post high-stakes tests). Such data sources will be triangulated and analyzed in a way that can be used by the instructors and the research team. Summer workshops will also be conducted to engage faculty and administrators in a participatory design process: (1) to build individual instructor action plans and (2) to construct an institutional change action plan collectively. Research efforts center at the intersection of learning analytics and faculty change to inform how others might productively leverage institutional data to improve the STEM undergraduate education system. The research team consists of educational researchers, engineering faculty, and administrative leaders from the college of engineering, institutional effectiveness, and learning sciences. Thus, the team is well-poised to not only lead this effort programmatically and from a research perspective, but also institutionalize project-developed strategies and outcomes.
