ABSTRACT

This project aims to serve the national interest by improving undergraduate teaching and learning of statistics and data science. It will do so by developing better ways to measure and improve student and faculty attitudes toward statistics and data science. Statistics is the science of collection, analysis, interpretation, and presentation of numerical data. Data science is ability to extract actionable insights from data of all types. Using these tools to use and manipulate data sets is a critical skill for today's STEM workforce, as well as for a data-savvy citizenry. However, engaging faculty to successfully teach and students to successfully learn these skills continues to be challenging. The proposed project expects to make progress toward better teaching and learning of statistics and data science by developing a deeper understanding about student and instructor attitudes toward these topics. This understanding, in turn, can help in developing effective ways to teach and learn statistics and data science and to identify what works best for educating skilled and motivated statisticians and data scientists.

Positive attitudes have been shown to be essential to student learning of all types. Currently, few instruments exist for assessing attitudes toward statistics and data science, and these have critical flaws. This project will collect data from a nationally representative sample of undergraduate students and their instructors to develop and statistically validate new instruments for these purposes. The final data set will be analyzed for trends that may indicate best practices in statistics and data science education and be made publicly available. A sustainable infrastructure will be created to facilitate ongoing data collection and dissemination of results. A diversity of student populations will be included in all phases to identify challenges, opportunities, and pedagogical practices that are particularly effective for specific groups of learners. The NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR) Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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