This project team is building on the results of a TUES Type 1 award that created new learning materials for a project-based course that provides greater access to introductory statistics for large numbers of students primarily not in STEM-intensive majors. The approach features training in flexible application of knowledge, opportunities to analyze data in real world contexts, and education about statistical concepts through computing. In this Type 2 effort the principal investigators (PIs) are adapting and fine-tuning the current materials to add flexibility and seamlessness so that they are usable across a wide array of institutional settings and easily modified to meet the needs of students with different levels of preparation, learning styles, and interest.
The intellectual merit of the project lies in its focus on the need of students outside of traditional STEM disciplines to have conceptual and analytical tools at their disposal to grapple with "big data" applications in their fields of inquiry. Moreover, the initial course materials have been piloted by nine different instructors and 350 students. Short-term and long-term learning gains for students are also being assessed at both the transition to college and post-graduation levels.
The PIs are pursuing the broader impact of their efforts along two dimensions: first, by implementing and assessing their project-based model for learning in five partner institutions including universities, community colleges, and in a small number of cases, secondary school settings; and second, by conducting summer workshops for new faculty from varied disciplinary backgrounds to become prepared to teach using this project-based model.
