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Education Research

The C-CoMP team is rounded out by education researchers who will conduct empirical research on the impacts of C-CoMP education and outreach activities. Their research will examine the impacts of both formal curriculum interventions and research education experiences. Given the aim to broaden participation among racial, socioeconomic, sexual, and gender groups, all educational research studies will examine the experiences and outcomes of sub-populations of individuals with attention to intersectionality (i.e., experiences of individuals with multiple marginalized identities). Educational research activities will be framed in terms of relevant learning, motivation, and career development theory, as well as the logical connections between the stated goals of each activity, the fidelity of its implementation, and its hypothesized outcomes.

Initial Research

We will follow the core principles of “improvement science” advocated by the Carnegie Foundation for the Advancement in Teaching. This approach guides ongoing development and modification of activities by focusing on what works, for whom, and under what conditions, leading to activities that are scalable to other locations and populations. When educational activities are optimized later in the funding period, more conventional research approaches will be used to examine the impact of activities on learner outcomes and their mechanisms of action.

Undergraduate education research

All undergraduate activities (CUREs, VIP Teams, Summer Research Internships) will be evaluated formatively and summatively to make year-to-year improvements and examine effectiveness in terms of developing student interest, motivation, and integration into the scientific community. Evaluation will address success in:

(1) Engaging all C-CoMP senior personnel in outreach and/or undergraduate education and training

(2) Providing experiences that promote learning and development

(3) Providing multiple entry points into research

(4) Scaling mentor: student ratios with the difficulty of research

(5) Integrating data science competencies at all program levels.