Title
Changing Paradigms: Faculty Moving to Data Science from Other Disciplines
Document Type
Poster Presentation
Publication Date
5-17-2019
Abstract
Student demand for data science has increased in many schools. However, in many institutions hiring new data science faculty has proven difficult. Assisting existing faculty from a variety of traditional disciplines in making a change to data sciences approaches - particularly by moving away from more parametric approaches to more resampling-based approaches using R - can help meet the need for faculty. This qualitative study explores the transitions made by two faculty at a small liberal arts college from other disciplines (political science and computer science) to data science, both from the perspective of the faculty members making the transition and from the perspective of faculty who had already made the transition. Although both faculty members had some background in statistics, the transition to data science required professional development, mentoring, and a deep commitment on the part of the faculty and the program. From these experiences, insight into the transition process have been gained; these insights may be useful to programs at other institutions.
Publication Information
Ricca, Bernard P.; Blaine, Bruce Evan; Donovan, Kathleen; and Geraci, Anne, "Changing Paradigms: Faculty Moving to Data Science from Other Disciplines" (2019). Mathematical and Computing Sciences Faculty/Staff Publications. Paper 20.
https://fisherpub.sjf.edu/math_facpub/20
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Comments
Poster presented at the United States Conference on Teaching Statistics in State College, Pennsylvania on May 17, 2019.