Need: Most of the highest paying, in-demand jobs now require skills in data analysis, making data analysis and interpretation skills arguably as important as reading or writing. Yet developing analytic skills is often viewed as an obstacle rather than an opportunity to pursue your interests and to answer questions that you feel passionately about. Our goal is to increase the number and diversity of students exposed to meaningful and empowering data analysis experiences and to inspire the pursuit of advanced data-driven experiences and opportunities for everyone! Guiding Questions: Does the curriculum result in positive student outcomes? Does the curriculum increase exposure to data analysis skills for women, under-represented students, and students with learning disabilities? Is the model of educator training and professional development effective in fostering knowledge and confidence in its delivery? To what extent do participating educators apply and sustain the project-based model within their programs and classrooms? At the institutional level, what format and fiscal model of support provides greatest sustainability for the data-driven curriculum? Outcomes: The project-based course enrolled higher numbers of URM students compared to a traditional introductory statistics course (Dierker et al., 2015). Higher rates of female, URM and a wider range of mathematical aptitude as measured by their Math SAT scores enroll in the project-based course compared to both a general introductory programming course and an introductory course representing a gateway to the computer science major (Cooper & Dierker, 2017). Students enrolled in the project-based course had more positive course experiences than those enrolled in the traditional course including being able to better understand the information presented through one-on-one support, engaging in greater preparation for class sessions, finding the course more useful and gauging its reward and feelings of accomplishment more highly (Dierker et al., 2018). It has been found to be associated with increases in confidence and interest in pursuing additional coursework in data analysis and statistics (Dierker et al., 2018). Similar findings with the project-based curriculum on undergraduate students in Ghana, West Africa, demonstrate the potential for its global portability (Awuah et al., 2020). Youth as young as 12 have successfully engaged with a shortened version of which all students reported they would or probably would recommend the course to other students (Rose & Dierker, 2019). Recent findings suggest the course may contribute to the decision for students to enroll in future courses in statistics and data analysis, when compared to the psychology and mathematics department courses (Nazzaro et al., 2020). Broader Impact: By making data science education more accessible, the project aims to increase the recruitment and retention of women and other underrepresented students, into careers requiring data analysis skills. In this way, it can help to create a larger, more diverse population with the data analysis skills needed across industry sectors, disciplines, and audiences, thus contributing to the nation’s competitiveness in the global economy. By conducting evaluative research that includes the areas of educator training, program sustainability, and student outcomes, the project will contribute new knowledge about teaching and learning data analytics.
Lisa Dierker, Wesleyan University, Middletown, CT; Jennifer Rose, Wesleyan University, Middletown, CT