scholarly journals TEACHING HIGHS AND LOWS: EXPLORING UNIVERSITY TEACHING ASSISTANTS’ EXPERIENCES

2010 ◽  
Vol 9 (2) ◽  
pp. 108-122
Author(s):  
JENNIFER L. GREEN

Recent reforms in statistics education have initiated the need to prepare graduate teaching assistants (TAs) for these changes. A focus group study explored the experiences and perceptions of University of Nebraska-Lincoln TAs. The results reinforced the idea that content, pedagogy, and technology are central aspects for teaching an introductory statistics course. The TAs addressed the need for clear, specific guidelines and examples, as well as collaboration between colleagues. The TAs also sought opportunities to enrich their teaching skills and, ultimately, their impact on students’ learning. These findings support previous research on graduate TAs and highlight the need for additional exploration of the role graduate statistics TAs play in introductory statistics education. First published November 2010 at Statistics Education Research Journal: Archives

2017 ◽  
Vol 16 (1) ◽  
pp. 294-319
Author(s):  
NICOLA JUSTICE ◽  
ANDREW ZIEFFLER ◽  
JOAN GARFIELD

Graduate teaching assistants (GTAs) are responsible for the instruction of many statistics courses offered at the university level, yet little is known about these students’ preparation for teaching, their beliefs about how introductory statistics should be taught, or the pedagogical practices of the courses they teach. An online survey to examine these characteristics was developed and administered as part of an NSF-funded project. The results, based on responses from 213 GTAs representing 38 Ph.D.–granting statistics departments in the United States, suggest that many GTAs have not experienced the types of professional development related to teaching supported in the literature. Evidence was also found to suggest that, in general, GTAs teach in ways that are not aligned with their own beliefs. Furthermore, their teaching practices are not aligned with professionally-endorsed recommendations for teaching and learning statistics. First published May 2017 at Statistics Education Research Journal Archives


2014 ◽  
Vol 13 (1) ◽  
pp. 53-65 ◽  
Author(s):  
ROBYN REABURN

This study aimed to gain knowledge of students’ beliefs and difficulties in understanding p-values, and to use this knowledge to develop improved teaching programs. This study took place over four consecutive teaching semesters of a one-semester tertiary statistics unit. The study was cyclical, in that the results of each semester were used to inform the instructional design for the following semester. Over the semesters, the following instructional techniques were introduced: computer simulation, the introduction of hypothetical probabilistic reasoning using a familiar context, and the use of alternative representations. The students were also encouraged to write about their work. As the interventions progressed, a higher proportion of students successfully defined and used p-values in Null Hypothesis Testing procedures. First published May 2014 at Statistics Education Research Journal Archives


2017 ◽  
Vol 16 (2) ◽  
pp. 487-510
Author(s):  
WARREN PAUL

We used the Survey of Attitudes Toward Statistics to (1) evaluate using pre-semester data the Students’ Attitudes Toward Statistics Model (SATS-M), and (2) test the effect on attitudes of an introductory statistics course redesigned according to the Guidelines for Assessment and Instruction in Statistics Education (GAISE) by examining the change in attitudes over the semester and, using supplementary data from an annual Student Feedback Survey, testing for a change in overall satisfaction following implementation of the redesigned course. We took an exploratory rather than confirmatory approach in both parts of this study using Bayesian networks and structural equation modelling. These results were triangulated with analysis of focus group discussions and the annual Student Feedback Survey. First published November 2017 at Statistics Education Research Journal Archives


2015 ◽  
Vol 14 (1) ◽  
pp. 36-59
Author(s):  
AUÐBJÖRG BJÖRNSDÓTTIR ◽  
JOAN GARFIELD ◽  
MICHELLE EVERSON

This study explored the use of two different types of collaborative tests in an online introductory statistics course. A study was designed and carried out to investigate three research questions: (1) What is the difference in students’ learning between using consensus and non-consensus collaborative tests in the online environment?, (2) What is the effect of using consensus and non-consensus collaborative tests on students’ attitudes towards statistics?, and (3) How does using a required consensus vs. a non-consensus approach on collaborative tests affect group discussions? Qualitative and quantitative methods were used for data analysis. While no significant difference was found between groups using the two collaborative testing formats, there was a noticeable increase in students’ attitudes across both formats towards learning statistics. This supports prior research on the benefits of using collaborative tests in face-to-face courses. First published May 2015 at Statistics Education Research Journal Archives


2017 ◽  
Vol 16 (2) ◽  
pp. 419-440
Author(s):  
MATTHEW D. BECKMAN ◽  
ROBERT C. DELMAS ◽  
JOAN GARFIELD

Cognitive transfer is the ability to apply learned skills and knowledge to new applications and contexts. This investigation evaluates cognitive transfer outcomes for a tertiary-level introductory statistics course using the CATALST curriculum, which exclusively used simulation-based methods to develop foundations of statistical inference. A common assessment instrument administered at the end of each course measured learning outcomes for students. CATALST students showed evidence of both near and far transfer outcomes while scoring as high, or higher than, on the assessed learning objectives when compared with peers enrolled in similar courses that emphasized parametric inferential methods (e.g., the t-test). First published November 2017 at Statistics Education Research Journal Archives


2012 ◽  
Vol 11 (1) ◽  
pp. 21-40 ◽  
Author(s):  
NATHAN TINTLE ◽  
KYLIE TOPLIFF ◽  
JILL VANDERSTOEP ◽  
VICKI-LYNN HOLMES ◽  
TODD SWANSON

Previous research suggests that a randomization-based introductory statistics course may improve student learning compared to the consensus curriculum. However, it is unclear whether these gains are retained by students post-course. We compared the conceptual understanding of a cohort of students who took a randomization-based curriculum (n = 76) to a cohort of students who used the consensus curriculum (n = 79). Overall, students taking the randomization-based curriculum showed higher conceptual retention in areas emphasized in the curriculum, with no significant decrease in conceptual retention in other areas. This study provides additional support for the use of randomization-methods in teaching introductory statistics courses. First published May 2012 at Statistics Education Research Journal: Archives


2019 ◽  
Vol 18 (1) ◽  
pp. 26-45
Author(s):  
KELLY FINDLEY ◽  
ALEXANDER LYFORD

Researchers have documented many misconceptions students hold about sampling variability. This study takes a different approach—instead of identifying shortcomings, we consider the productive reasoning pieces students construct as they reason about sampling distributions. We interviewed eight undergraduate students newly enrolled in an introductory statistics course. Taking a grounded theory style approach, we identified 10 resources that students used when reasoning about the sampling distribution for the average within two contexts: penny years and dice rolls. Students had varied success in their responses as they made choices about how to represent their resources in their constructions. Successful constructions exemplified careful blending of resources, while less  successful constructions reflected disjoint perceptions and tensions between seemingly conflicting resources. Our findings stress the importance of framing students as capable reasoning agents by describing student resources that were used while solving tasks related to sampling distributions. We also discuss the influence of context and problem setting in students’ reasoning and resource elicitation. First published May 2019 at Statistics Education Research Journal Archives


2021 ◽  
Vol 19 (3) ◽  
Author(s):  
REBECCA AWUAH ◽  
KRISTEL M. GALLAGHER ◽  
LISA C. DIERKER

To evaluate the impact of a multidisciplinary, project-based course in introductory statistics, this exploratory study examined learning experiences, feelings of confidence, and interest in future experiences with data for undergraduate students in Ghana, West Africa. Students completed a one-semester, introductory statistics course utilizing the Passion-driven Statistics curriculum. Results showed more than half of the students put more effort into the course and found the material more challenging compared to other courses, while nearly three-quarters reported interest in one or more follow-up courses. Importantly, students also reported increased confidence in a variety of applied statistical skills. These findings demonstrate the positive impact of a multidisciplinary, project-based curriculum on undergraduate students in Ghana, West Africa and demonstrate the potential for its global portability. First published December 2020 at Statistics Education Research Journal: Archives


2011 ◽  
Vol 10 (2) ◽  
pp. 48-74
Author(s):  
JENNIFER NOLL

Research investigating graduate teaching assistants’ (TAs’) knowledge of fundamental statistics concepts is sparse at best; yet at many universities, TAs play a substantial role in the teaching of undergraduate statistics courses. This paper provides a framework for characterizing TAs’ content knowledge in a sampling context and endeavors to raise new questions about TAs’ content knowledge and its potential impact on the teaching of undergraduate statistics. The participants in this study were sixty-eight TAs from 18 universities across the United States. These TAs demonstrated considerable knowledge of theoretical probability distributions. However, they experienced tensions when attempting to quantify expected statistical variability in an empirical sampling situation and had difficulty explaining conceptual ideas of variability. First published November 2011 at Statistics Education Research Journal: Archives


2018 ◽  
Vol 17 (2) ◽  
pp. 161-178
Author(s):  
LAURA ZIEGLER ◽  
JOAN GARFIELD

The purpose of this study was to develop the Basic Literacy In Statistics (BLIS) assessment for students in an introductory statistics course, at the postsecondary level, that includes, to some extent, simulation-based methods. The definition of statistical literacy used in the development of the assessment was the ability to read, understand, and communicate statistical information. Multiple instruments were available to assess students in introductory statistics courses; however, there were no assessments available that focused on statistical literacy. Evidence of reliability and validity were collected during the development of the assessment. Evidence of reliability and validity was high; however, more items with high difficulty levels could increase the precision in estimating ability estimates for higher achieving students. First published November 2018 at Statistics Education Research Journal Archives


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