2024 ASEE Annual Conference & Exposition

This NSF Improving Undergraduate STEM Education (IUSE: EHR) Institutional and Community Transformation (ICT) capacity-building project is designed to support faculty to collaboratively explore questions on student learning and success in introductory and gateway undergraduate STEM courses, such as early engineering courses as well as prerequisite math and science courses. The project motivates faculty to consider evidence-based teaching strategies by including them as co-designers of learning analytics tools and storytellers inspired by data and their reflections. Learning analytics uses data about learners and learning to draw inferences to inform actions and changes to achieve a goal, which for this project is improving student success and retention in early STEM courses. Learning analytics is an emerging approach to motivating STEM faculty to implement evidence-based teaching practices.

The project also builds and strengthens faculty communities and develops a culture of inquiry and conversations that are evidence-based and data-informed – all to build readiness for transformation. We are exploring how a change framework for intentional capacity building by creating faculty communities with similar interests across disciplines and course-level data dashboards can establish the foundation for implementing change in their instructional practices and curriculum, with faculty members becoming change agents.

While most transformation projects and use of learning analytics have been conducted at large research institutions, the findings from this project will contribute to the knowledge of engineering education change in the context of a public, regional, primarily undergraduate institution in the Midwest. This paper describes the grounding, planning, and implementation of these activities to build capacity for change and shares the challenges encountered and strategies used.