Collaborative Research: Investigating Inclusive Data Science Tools to Overcome Statistics Anxiety

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The objective of this collaborative project is to design, create, and evaluate the Relatable Online Accessible Data Science (ROADS) platform. ROADS is designed to make online data science easier to understand by undergraduate and graduate students, with a focus on overcoming statistics anxiety. Reasons for statistical anxiety include limited math and computing background, self-esteem, gender, ethnicity, and disability, in addition to the design of statistics platforms. Data science literacy is integral for success in post-secondary science, technology, engineering, and math (STEM) fields, as well as for developing critical, industry-relevant, computational thinking skills. In collaboration with partner organizations, which span higher education, accessibility, and data science, the project will evaluate ROADS to lower barriers for successful participation. ROADS will be iteratively and inclusively designed, using both formative and summative empirical evaluations, at all stages of development, to inform the end user experience.This project will investigate a new platform that uses relatable data science language, is readily available online through the web, and is accessible through visual, auditory, and touch feedback to students with disabilities. It brings together investigators in Computer Science, Mechanical Engineering, Education, and Cognitive Neuroscience to investigate three critical areas: (1) clarity and human comprehension of data science representations; (2) anxiety reduction; and (3) accessibility to people with disabilities. For evaluation, a series of studies is planned, involving 180 undergraduate students without disabilities and 120 with disabilities. Further, the researchers plan to study the outputs of data science tools, in conjunction with anxiety, involving approximately 1,000 undergraduate or graduate students, with and without disabilities. The project will incorporate regular feedback from an engaged advisory board, including a data science governance group (ACM Data Science Task Force), the Association on Higher Education and Disability, and disabilities services offices at four institutions. Project outcomes will include the development of design implications for inclusive design of data science tools and pedagogy at the undergraduate and graduate level, with a specific focus on reducing anxiety associated with data science.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.