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Invited Paper Session Abstracts - Supporting Student Success in Introductory Statistics through Evidence-Based Practices

Please note: all sessions are listed in Mountain Daylight Time (MDT = UTC-6:00)

Saturday, August 7, 1:00 p.m. - 3:00 p.m.

Each academic year, over 600,000 students enroll in college introductory statistics courses, according to the 2015 CBMS survey. Enrollments have more than doubled since 2000. Although many of the new statistics students have sufficient mathematics fluency to succeed, many others struggle with algebra, numeric operations, and logic, leading to poor course outcomes.

In this session, speakers will present evidence-based results from projects about supporting students enrolled in introductory statistics courses. Projects include identifying students in need of extra assistance with mathematical fluency and/or statistical content, and then implementing one of several ways to provide that assistance, including instructor-led sessions, computer-based support, and undergraduate-led supplemental instruction. Session speakers work at a variety of institutions, small and large, public and private. Though the context for the presentations is Introductory Statistics, the innovations and pedagogical practices presented are adaptable to any introductory college level mathematics course and have broader implications for supporting student success in first-year college level mathematics and statistics.

Implementation and Continuation Issues for Supporting Underprepared Introductory Statistics Students Using an Assessment and Peer Tutoring Intervention Program

1:00 p.m. - 1:20 p.m.
M. Leigh Lunsford, Longwood University
Phillip L. Poplin, Longwood University
Leah N. Shilling-Stouffer, Longwood University


Based on results from a previously published study (Lunsford and Poplin 2011), we used an assessment tool to identify underprepared students in our introductory statistics course and subsequently required those students to attend peer tutoring, early in the semester, as an intervention. While we saw a significant increase in student success for all students compared with the previous study, the underprepared students who completed the required tutoring had a significantly higher increase (Lunsford, Poplin, and Pederson 2018). Despite these successes, continuation of the assessment and peer tutoring program has been a challenge. Unfortunately COVID-19 interrupted our planned intervention using our new Quantitative Reasoning Center for the Spring 2020 semester and this academic year. In this talk we will provide background information from our previous studies, discuss logistical and institutional hurdles, and share what we have learned (despite the COVID interruption) as well as our future plans.

Lunsford, M. L. and Poplin, P. (2011) "From Research to Practice: Basic Mathematics Skills and Success in Introductory Statistics," Journal of Statistics Education, 19(1). Available online:

Lunsford, M. L., Poplin, P. L., Pederson, J. G, (2018) “From Research to Practice: Using Assessment and Early Intervention to Improve Student Success in Introductory Statistics,” Journal of Statistics Education, 26(2). Available online:


Computer-based Learning plus Tutoring in Essentials of Statistics

1:30 p.m. - 1:50 p.m.
Jayne Ann Harder, Oral Roberts University


Oral Roberts University offers a 1-hour co-requisite course for elementary statistics, designed to support required mathematical skills and provide opportunities for students to receive more personal support. Students participate in a web-based diagnostic and learning tool called ALEKS that uses artificial intelligence to direct students through ready-to-learn modules based upon an initial assessment. Modules include the broad categories of numbers, algebraic expressions, linear equations, lines in the coordinate plane, descriptive statistics, and counting and probability. The ALEKS system provides targeted review of topics, without having to spend time on areas students have already mastered. Students are also required to log 120-minutes per week in a web-based attendance system. Minutes can be earned by attending classroom discussion sections run by a faculty member or by attending peer tutoring opportunities with trained undergraduate tutors. This talk will present results on the effectiveness of this approach, based on two years of implementation.


Large Scale Peer-Assisted Tutoring, Corequisites, and Other Math Support for Introductory Statistics

2:00 p.m. - 2:20 p.m.
Adam Molnar, Oklahoma State University


Non-calculus, non-business introductory statistics is a large and growing course at Oklahoma State University, with about 1550 enrollments in calendar year 2019. Many students know mathematics well, but many others struggle to recall arithmetic and algebra needed in the course. Additionally, a statewide initiative has encouraged reductions in prerequisite requirements. Over the past two years, the department has introduced a number of support initiatives, including corequisite sections with extra instructional time, a start-of-semester mathematics diagnostic to identify weaker areas in all students, and undergraduate-led supplemental peer instruction. In this talk, I will present results from about 400 students in calendar year 2019 who consented to external publication, showing which initiatives showed promise and which did less well.


Corequisite Statistics Courses for Equitable Support of All Students

2:30 p.m. - 2:50 p.m.
Alana Unfried, California State University, Monterey Bay


In 2018, CSUMB began offering corequisite courses alongside general education mathematics and statistics courses, in place of students beginning in mathematics remediation courses. This change has broadened student access to introductory statistics since the barrier of remediation is removed, but it has also created a more academically diverse introductory statistics course. This talk will discuss the design of corequisite courses for supporting introductory statistics students, and provide results from the first two years of implementation, showing that this course structure has allowed all students, including those who were not adequately prepared through prior experiences, to be successful in introductory statistics.