August 8, 2022
Shared interests between statistics and computer science education researchers have been underdeveloped by comparison to the scale of opportunity presented by the growth of interest in data sciences. Our objective is to introduce CAUSE Research to the SIGCSE and ICER community in order to build bridges among data science education researchers in CS education, statistics education, and related disciplines. The Consortium for the Advancement of Undergraduate Statistics Education (CAUSE; causeweb.org) is a U.S.-based organization with international reach whose mission is to support the advancement of undergraduate statistics and data science education. CAUSE Research is a subsidiary entity of CAUSE that seeks to promote and support the advancement of statistics and data science education research. While the broader CAUSE organization has been a vibrant and active community for approximately 20 years, CAUSE Research had fallen dormant until recently. After appointing two new co-Associate Directors for Research, CAUSE Research has jump-started a substantial reboot to better serve statistics and data science education researchers. We hope to generate both interest and ideas from the ICER community, to welcome your involvement with CAUSE Research, and to learn how we can better serve data science education research(ers) together.
Matthew D. Beckman and Laura Le. 2022. Connecting and supporting data science education researchers through the CAUSE Organization. In ICER ’22: ACM Conference on International Computing Education Research, August 07–11, 2022, Lugano, Switzerland. ACM, New York, NY, USA, 1 page.
August 8, 2022
With the growing popularity of introductory data science courses, there is a need for quality research assessment tools developed and validated for general use across institutions and programs in order to compare and contrast curriculum interventions, pedagogical innovations, etc. This project has set out to develop a research assessment to measure learning outcomes for introductory data science students before and after a first course. A team of statistics and data science education researchers examined syllabi and resources in use by experienced introductory data science instructors, and then drafted and revised an assessment tool aligned with the core knowledge, skills, and abilities. The team then conducted structured interviews with experienced data science instructors with expertise in statistics education, computer science education, and/or educational measurement. Interviews invite both holistic feedback (e.g., essential topics for a data science assessment) as well as a detailed critique of each item and its contribution. This lightning talk discusses current successes and challenges in the assessment development process, progress toward a larger scale pilot of the assessment tool, and invite both feedback and participation from colleagues in the ICER network.
Matthew D. Beckman, Mine Cetinkaya-Rundel, Mine Dogucu, Evan Dragich, Chelsey Legacy, Maria Tackett, and Andrew Zeiffler. 2022. Piloting a new assessment tool for data science education researchers. In ICER ’22: ACM Conference on International Computing Education Research, August 07–11, 2022, Lugano, Switzerland. ACM, New York, NY, USA.
Matthew Beckman
Department of Statistics
Penn State University
University Park, PA 16802
email: mdb268 [at] psu [dot] edu
website: https://mdbeckman.github.io/