Statistics graduate teaching assistants' beliefs, practices and preparation for teaching introductory statistics

Graduate teaching assistants (GTAs) are responsible for the instruction of approximately 15% of introductory courses in U.S. statistics departments (Blair, Kirkman & Maxwell, 2013). Little is known about graduate teaching assistants’ beliefs and practices regarding the teaching of introductory statistics. As part of an NSF-funded project (eATLAS, DUE 1044812 & 1043141), an online survey was developed to explore the beliefs and practices of statistics GTAs, including course content priorities, teaching methods, use of technology and assessment strategies. The data collected from the survey were based on responses from 213 GTAs across over 35 Ph.D. granting institutions in the United States. The results can inform future programs for GTA development. OVERVIEW Institutions rely on graduate teaching assistants (GTAs) to teach a substantial share of statistics course offerings. According to Blair, Kirkman and Maxwell (2013), GTAs teach approximately 15% of introductory statistics courses taught in statistics departments, and nearly 30% of introductory statistics courses offered in mathematics departments. Despite the large role GTAs play in undergraduate statistics education, research particular to GTAs of statistics is relatively sparse; two main studies have been published in the literature. Noll (2011) investigated the statistical knowledge necessary for GTAs to teach the introductory course; and Green (2010) explored the experiences and perceptions of GTAs of statistics. Still, little is known about national trends in GTAs' development as teachers, teaching practices, or beliefs about teaching introductory statistics. In particular, little is known about whether GTAs' teaching beliefs and practices align with recommendations outlined in the Guidelines for Assessment and Instruction in Statistics Education (GAISE; ASA, 2005). In response, we developed and administered an online survey to investigate the beliefs, practices, and teaching development experiences of GTAs in statistics departments across the United States. The data were analyzed in response to four questions: 1) What professional development experiences have GTAs had? 2) To what extent are statistics GTAs’ pedagogical practices aligned with the GAISE recommendations? 3) What are GTAs’ beliefs about the teaching of introductory statistics? 4) To what extent are GTAs' pedagogical beliefs and practices aligned? THE GRADUATE STUDENT STATISTICS TEACHING INVENTORY The Graduate Student Statistics Teaching Inventory (GSSTI) was developed to explore GTAs' beliefs, practices and development experiences in teaching statistics. The instrument was developed as part of a NSF-funded project (eATLAS, DUE 1044812 & 1043141). Many items on the GSSTI were adopted or modified from the latest version of the Statistics Teaching Inventory, an instrument originally developed by Zieffler, Park, Garfield, delMas, and Bjornsdottir (2012). Questions underwent several rounds of revision in order to properly apply to graduate students and to fit within the web-based program, Survey Monkey. The online survey was then piloted with three GTAs who were teaching introductory statistics. Based on data from this piloting, the instrument was again revised. In its final form, the GSSTI consisted of eight items related to GTAs’ teaching responsibilities, seven items related their teaching practices, 12 items related to their beliefs about the introductory course (i.e. content, pedagogies, and assessment strategies), and 17 items related to GTAs’ development experiences in teaching. Two additional open-ended items appeared in the survey; responses to these are addressed in this analysis. The survey was sent to faculty contacts in statistics departments ranked in the 2013 US News and World Report. These contacts were asked to forward the survey to their GTAs and solicit participation. Additional participants were contacted via a blog posting on Statistical Modeling, Causal Inference, and Social Science (Gelman, 2013). Prior to analysis, respondents from