Keywords: data science, introductory statistics, pedagogy, GAISE, GAISE College Report
Most members of the Mathematics Department at my two-year college teach our algebra-based introductory statistics course in the “traditional manner.” By which I mean, there is heavy emphasis on the student performing the various computations with the assistance of a calculator as well as the use of distribution tables. Given the use of the antiquated technology, there is not as much time to allow for the concrete recommendations that can be found in the ASA’s GAISE College Report of 2016 (e.g., statistics as an investigative process and experience with multivariable thinking). While there are some members of the Department who teach our introductory statistics courses in line with contemporary statistical pedagogy, we have met with resistance in our attempts to make this the norm. However, there are two main pressures, both from data science, that have lead to the possibility of the modernization of the pedagogical approach to statistics in our department. They are: 1. We are in the process of creating a Data Science Career Technical Education (CTE) program at our college, which was born out of myself and another member of our Department attending the ASA’s TYCDSS in Washington, DC in May of 2018 2. Some of the departments at my college whose students need an introductory statistics class for their major (e.g., psychology and sociology) are not satisfied with the statistics their students are learning in the Math Department’s course and wish to create their own course. In this presentation, I will first discuss these two pressures in detail. Secondly, I will recount some of the pragmatic considerations one has to take in account in order to have data science lead to the pedagogical reform of a two-year college’s introductory statistics course.