Data Science for Undergraduates: Opportunities and Options
As our economy, society, and daily life become increasingly dependent on data, work across nearly all fields is becoming more data driven, affecting both the jobs that are available and the skills that are required. At the request of the National Science Foundation, the National Academies of Sciences, Engineering, and Medicine were asked to set forth a vision for the emerging discipline of data science at the undergraduate level. The study committee considered the core principles and skills undergraduates should learn and discussed the pedagogical issues that must be addressed to build effective data science education programs. Data Science for Undergraduates: Opportunities and Options underscores the importance of preparing undergraduates for a data-enabled world and recommends that academic institutions and other stakeholders take steps to meet the evolving data science needs of students.
During this webinar, invited speakers discussed key components that should be included in data science curriculum, how to best teach students to make good judgments about data, and how data acumen can be evaluated.
During this webinar, invited speakers discussed how partnerships between industry and educational programs could be encouraged, whether a focus on real problems could attract a more diverse cadre of data science students, and how to help students gain access to real-world data sets.
During this webinar, invited speakers discussed what types of faculty training would be beneficial, how to encourage faculty development in data science, and how to build data science programs with the flexibility needed to respond to changes in the field and encourage diverse participation. Host: Nicholas Horton, Amherst College Michael Posner: Villanova University Robert Panoff, Shodor
During this webinar, invited speakers discussed how to foster communication and teamwork in data science programs and how multidisciplinary teams could serve as effective models for the real world. Host: Lee Rainie, Pew Research Madeleine Claire Elish, Data & Society Adam Hughes, Pew Research
During this webinar, invited speakers discussed best practices for fostering collaboration between departments, opportunities for new data science education initiatives, and how organizational structures could be restructured to encourage data science collaboration. Host: Tom Ewing, Virginia Tech Mark Embree, Virginia Tech Michael Franklin, University of Chicago
During this webinar, invited speakers will discuss how ethical considerations can best be incorporated throughout data science curricula and how students can be taught to make ethical decisions throughout the problem-solving process. Host: Lee Rainie, Pew Research Sorin Matei, Purdue University Brittany Fiore-Gartland, University of Washington
During this webinar, invited speakers discussed existing evaluation processes, best practices for assessing data science programs, and whether there are standard evaluation approaches that can be adopted across programs. Host: Louis Gross, University of Tennessee, Knoxville Pamela Bishop, University of Tennessee, Knoxville Kari Jordan, Data Carpentry
During this webinar, invited speakers discussed how to broaden participation, diversity, and inclusion in data science programs and strategies for recruiting and retaining diverse data science students. Host: Nicholas Horton, Amherst College Talithia Williams, Harvey Mudd College Allison Master, University of Washington
During this webinar, invited speakers discussed how to facilitate partnerships between 2-year and 4-year institutions and what aspects of data science are appropriate and feasible to develop at 2-year institutions. Host: Laura Haas, University of Massachusetts, Amherst Brian Kotz, Montgomery College Suzanne Smith, Johnson County Community College
On December 12-13, 2016, the study committee held a meeting to discuss plans for the study and upcoming workshops. Participants discussed the state of current undergraduate data science education and brainstormed ways to improve the data science education pipeline. Agenda and Presentations
On May 2-3, 2017, the study committee organized a workshop to discuss key themes relevant to envisioning the future of data science. Participantsdiscussed data science skills and knowledge, education delivery, and broad participation.