Teaching Introductory Statistics to Meet Undergraduate Students' Quantitative Literacy Requirements

2017 ◽  
Author(s):  
Robert A. Terry
Keyword(s):  
Undergraduate Students ◽  
Introductory Statistics ◽  
Quantitative Literacy

PAINT-BY-NUMBER OR PICASSO? A GROUNDED THEORY PHENOMENOGRAPHICAL STUDY OF STUDENTS’ CONCEPTIONS OF STATISTICS

2021 ◽  
Vol 19 (2) ◽  
pp. 76-102
Author(s):  
NICOLA JUSTICE ◽  
SAMANTHA MORRIS ◽  
VERONIQUE HENRY ◽  
ELIZABETH BRONDOS FRY
Keyword(s):  
Education Research ◽  
Grounded Theory ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Qualitative Approach ◽  
Introductory Statistics ◽  
Preliminary Results ◽  
Research Journal ◽  
Survey Responses

Statistics students’ conceptions of the work of statisticians and the discipline of statistics may play an important role in the topics to which they attend and their interest in pursuing further study. To learn about students’ conceptions, we collected open-ended survey responses from 44 undergraduate students who had completed introductory statistics courses. We used a grounded theory phenomenographical qualitative approach to identify several themes in students’ conceptions. In addition to the test-and-procedure conception, we offer several other themes, such as acknowledgement of variation and the role of ethical integrity. We use a metaphor of painting styles to compare to experts’ conceptions of statistics. By identifying “seeds” of what may be developed into expert conceptions, these preliminary results set possible foundations to explore trajectories that may help shape students’ conceptions of statistics. First published June 2020 at Statistics Education Research Journal Archives

INVESTIGATING STUDENTS’ REASONING ABOUT SAMPLING DISTRIBUTIONS THROUGH A RESOURCE PERSPECTIVE

2019 ◽  
Vol 18 (1) ◽  
pp. 26-45
Author(s):  
KELLY FINDLEY ◽  
ALEXANDER LYFORD
Keyword(s):  
Education Research ◽  
Grounded Theory ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Introductory Statistics ◽  
Research Journal ◽  
Sampling Distributions ◽  
Statistics Course ◽  
Resource Perspective ◽  
Problem Setting

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

TAKING PROJECT-BASED STATISTICS ABROAD: LEARNING EXPERIENCES AND OUTCOMES OF A PROJECT-BASED STATISTICS COURSE IN WEST AFRICA

2021 ◽  
Vol 19 (3) ◽  
Author(s):  
REBECCA AWUAH ◽  
KRISTEL M. GALLAGHER ◽  
LISA C. DIERKER
Keyword(s):  
West Africa ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Positive Impact ◽  
Learning Experiences ◽  
Introductory Statistics ◽  
Research Journal ◽  
Statistics Course ◽  
The Impact

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

STUDENTS’ PERCEPTIONS OF THE FUTURE RELEVANCE OF STATISTICS AFTER COMPLETING AN ONLINE INTRODUCTORY STATISTICS COURSE

2018 ◽  
Vol 17 (2) ◽  
pp. 120-140
Author(s):  
EMMANUEL SONGSORE ◽  
BETHANY J. G. WHITE
Keyword(s):  
Education Research ◽  
Undergraduate Students ◽  
Statistics Education ◽  
Thinking Skills ◽  
Introductory Statistics ◽  
First Year ◽  
Student Interest ◽  
Introductory Courses ◽  
Research Journal ◽  
Statistics Course

Statistics educators have long recognized the importance of empowering students with statistical thinking skills that could be applied beyond the classroom. However, there is a dearth of research on how students deem statistical topics as having practical future relevance after they complete introductory courses. Focusing on student interest in and perceived value of statistics, this study reports findings from a qualitative study that examined students’ written reflections to explore the nature and extent of the perceived future relevance of statistics among undergraduate students who completed a first-year introductory statistics course online. Findings show that students deemed statistics topics as important if they could be applied to their everyday lives or their academic- and career-related interests. We conclude with recommendations for instructors of introductory statistics courses that enroll students with diverse interests and goals. First published November 2018 at Statistics Education Research Journal Archives

An introductory statistics module improves both student performance and perceptions

2021 ◽  
Author(s):  
Tim Downing ◽  
Emma K. Finlay
Keyword(s):  
Computational Biology ◽  
Student Performance ◽  
Undergraduate Students ◽  
Introductory Statistics ◽  
Continuous Assessment ◽  
Prior Learning ◽  
Improved Outcomes ◽  
Improved Performance

Improving learning in statistics is increasingly important for science undergraduate students to enable them to achieve a deeper understanding of computational biology. An introductory 1st year statistics module was added to a biology degree to improve learning in a 2nd year statistics module. This 2nd year module was taught for two years before the 1st year module’s addition, and for three subsequent years, including students from another degree who had no 1st year module throughout these years. The prior learning of students who completed the 1st year module was correlated with improved outcomes in the 2nd year one across both exam and continuous assessment. Completing the 1st year module was associated with improved attitudes towards the importance of statistics and interest in this topic. Improved performance and attitudes highlighted the importance of vertical module alignment to improve familiarity, confidence and learning.

Statistical Literacy in the Classroom: Should Introductory Statistics Courses Rethink their Goals?

2016 ◽  
Vol 7 (1-2) ◽  
Author(s):  
Cynthia McLauchlan ◽  
Matthias Schonlau
Keyword(s):  
Undergraduate Students ◽  
Online Survey ◽  
Learning Outcome ◽  
Simple Random Sample ◽  
Introductory Statistics ◽  
Statistical Literacy ◽  
Margin Of Error ◽  
Statistics Course ◽  
Statistics Courses ◽  
The University

AbstractMany undergraduate degrees require the completion of an introductory statistics course, but it is unclear to what extent taking a statistics course improves statistical literacy. We conducted an online survey with a simple random sample of undergraduate students at the University of Waterloo, Canada. We then compared students who have completed at least one statistics course to those who have completed none and found that taking a statistics course did not improve statistical literacy on the questions asked (causation versus correlation, margin of error, and others). Introductory statistics courses may want to address statistical literacy as a learning outcome more explicitly for a better understanding of public policies.

scholarly journals An analysis of student reflections of semester projects in introductory statistics courses

2020 ◽  
Vol 18 (3) ◽  
pp. 42-57
Author(s):  
Richard Spindler
Keyword(s):  
Student Perceptions ◽  
Undergraduate Students ◽  
Teaching And Learning ◽  
Quantitative Methods ◽  
Learning Activity ◽  
Introductory Statistics ◽  
Qualitative And Quantitative Methods ◽  
Project Data ◽  
Personal Reflections ◽  
Student Reflections

Projects in an introductory statistics course have been implemented for many years as an authentic assessment and learning activity. This article examines student perceptions toward semester projects and the relationship of those perceptions to outcomes. Student semester project data including personal reflections and assessment scores from 254 undergraduate students in six semesters of introductory statistics were analysed using qualitative and quantitative methods, relying heavily on content analysis. The projects comprehensively assessed introductory statistics content, and student reflections were based on three prompts. High levels of learning and interest were reported by the students. Workload issues were not expressed by students to an appreciable degree. Finally, this study illustrates the value of using qualitative methods with case studies to inform teaching and learning.

scholarly journals Assessing Student Ability to Interpret Regression Diagnostic Plots

2019 ◽  
Vol 23 (1) ◽  
pp. 18-34
Author(s):  
◽  
Mark Berenson ◽  
Haiyan Su
Keyword(s):  
Undergraduate Students ◽  
Traditional Approach ◽  
Linear Regression Analysis ◽  
Introductory Statistics ◽  
Introductory Courses ◽  
Modeling And Analysis ◽  
Institutional Review ◽  
Statistics Courses ◽  
Regression Diagnostic ◽  
Residual Plots

Simple linear regression analysis is an important component of introductory statistics courses, and testing the validity of its assumptions is an important part of regression modeling and analysis. The traditional approach in introductory statistics courses is to use residual plots to assess possible departures from the key assumptions. Confirmatory statistics are typically not used. But do undergraduate students in these introductory courses have the ability to assess residual plots correctly? This paper presents the results of an Institutional Review Board (IRB) approved study to address this question. The results are interesting and have implications for the teaching of regression in introductory courses as well as for textbook authors who cater to these courses.

Sign in / Sign up

Export Citation Format

Share Document