Education Commons^™

Mentoring Undergraduate Research In Statistics: Reaping The Benefits And Overcoming The Barriers, Joseph R. Nolan, Kelly S. Mcconville, Vittorio Addona, Nathan L. Tintle, Dennis K. Pearl

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Undergraduate research experiences (UREs), whether within the context of a mentor-mentee experience or a classroom framework, represent an excellent opportunity to expose students to the independent scholarship model. The high impact of undergraduate research has received recent attention in the context of STEM disciplines. Reflecting a 2017 survey of statistics faculty, this article examines the perceived benefits of UREs, as well as barriers to the incorporation of UREs, specifically within the field of statistics. Viewpoints of students, faculty mentors, and institutions are investigated. Further, the article offers several strategies for leveraging characteristics unique to the field of statistics to overcome …

Student Gains In Conceptual Understanding In Introductory Statistics With And Without A Curriculum Focused On Simulation-Based Inference, Beth Chance, Stephanie Mendoza, Nathan L. Tintle

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Using “simulation-based inference” (SBI) such as randomization tests as the primary vehicle for introducing students to the logic and scope of statistical inference has been advocated with the potential of improving student understanding of statistical inference, as well as the statistical investigative process as a whole. Moving beyond the individual class activity, entirely revised introductory statistics curricula centering on these ideas have been developed and tested. In this presentation we will discuss three years of cross-institutional tertiary-level data in the United States comparing SBI-focused curricula and non-SBI curricula (roughly 15,000 students). We examine several pre/post measures of conceptual understanding in …

Development Of A Tool To Assess Students’ Conceptual Understanding In Introductory Statistics, Nathan L. Tintle, Jill Vander Stoep

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Few tools exist to assess students’ conceptual understanding in post-secondary, introductory statistics courses. The CAOS test is widely considered to be the gold standard, but was first published in 2007 and does not necessarily reflect some of the changes in student learning at the secondary level. Furthermore, it may not be sensitive enough to measure student conceptual understanding in modern post-secondary statistics courses (e.g., simulation-based inference). In this paper we will describe the process of developing a new instrument which uses some CAOS items, as well as additional new items to improve validity and reliability. We will share the validity …

Assessing The Association Between Quantitative Maturity And Student Performance In Simulation-Based And Non-Simulation Based Introductory Statistics, Nathan L. Tintle

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The recent simulation-based inference movement in algebra-based introductory statistics courses has provided preliminary evidence of improved student conceptual understanding and retention of key statistical concepts. However, little is known about whether these positive effects in courses using simulation-based inference are preferentially distributed across different types of students. Recent studies investigating predictors of student performance in traditional, algebra-based introductory statistics courses (Stat 101) have focused primarily on mathematical achievement or competencies in high school and early college. Little consideration has been given to how prior experience and competency with statistical thinking may be associated with student performance in college-level courses. In …

Effects Of Growth Mindset Training On Undergraduate Statistics Students, Valorie L. Zonnefeld

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Undergraduate introductory statistics courses have experienced numerous changes in the past century, for instance, increased enrollment and diversification of students required to take the courses. Promising research has been conducted on mathematical mindsets, however, no research is available for introductory statistics courses. This presentation addresses the effect of growth mindset training on students in mathematics.

Broadening The Impact And Effectiveness Of Simulation-Based Curricula For Introductory Statistics, Nathan L. Tintle, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, Jill Vanderstoep

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The demands for a statistically literate society are increasing, and the introductory statistics course “Stat 101” remains the primary venue for learning statistics for the majority of high school and undergraduate students. After three decades of very fruitful activity in the areas of pedagogy and assessment, but with comparatively little pressure for rethinking the content of this course, the statistics education community has recently turned its attention to focusing on simulation-based methods, including bootstrapping and permutation tests, to illustrate core concepts of statistical inference within the context of the overall statistical investigative process. This new focus presents an opportunity to …

Student Performance In Curricula Centered On Simulation-Based Inference: A Preliminary Report, Beth Chance, Jimmy Wong, Nathan L. Tintle

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"Simulation-based inference"(e.g., bootstrapping and randomization tests) has been advocated recently with the goal of improving student understanding of statistical inference, as well as the statistical investigative process as a whole. Preliminary assessment data have been largely positive. This article describes the analysis of the first year of data from a multi-institution assessment effort by instructors using such an approach in a college-level introductory statistics course, some for the first time. We examine several pre-/post-measures of student attitudes and conceptual understanding of several topics in the introductory course. We highlight some patterns in the data, focusing on student level and instructor …

Combating Anti-Statistical Thinking Using Simulation-Based Methods Throughout The Undergraduate Curriculum, Nathan L. Tintle, Beth Chance, George Cobb, Soma Roy, Todd Swanson, Jill Vanderstoep

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The use of simulation-based methods for introducing inference is growing in popularity for the Stat 101 course, due in part to increasing evidence of the methods ability to improve students’ statistical thinking. This impact comes from simulation-based methods (a) clearly presenting the overarching logic of inference, (b) strengthening ties between statistics and probability/mathematical concepts, (c) encouraging a focus on the entire research process, (d) facilitating student thinking about advanced statistical concepts, (e) allowing more time to explore, do, and talk about real research and messy data, and (f) acting as a firmer foundation on which to build statistical intuition. Thus, …

Mindsets, Attitudes, And Achievement In Undergraduate Statistics Courses, Valorie L. Zonnefeld

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The purpose of this study was to determine the effects of theories of intelligence and an intervention of incremental mindset training on students’ attitudes toward statistics and their mastery of content in an introductory statistics college course. The sample was 547 undergraduate students at a small, faith-based, liberal arts college in the Midwest.

A pretest-posttest design was used for the three instruments implemented. The Comprehensive Assessment of Outcomes in a first Statistics course (CAOS) assessed students’ statistical literacy. The Student Attitudes Towards Statistics – 36© (SATS©) assessed six components of students’ attitudes toward statistics including affect, cognitive competence, difficulty, effort, …

Students Learning From Atlanta Public Schools Cheating Scandal, Thomas M. Van Soelen

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http://exclusive.multibriefs.com/content/students-learning-from-atlanta-public-schools-cheating-scandal/education

Quantitative Evidence For The Use Of Simulation And Randomization In The Introductory Statistics Course, Nathan L. Tintle, Ally Rogers, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, Jill Vanderstoep

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The use of simulation and randomization in the introductory statistics course is gaining popularity, but what evidence is there that these approaches are improving students’ conceptual understanding and attitudes as we hope? In this talk I will discuss evidence from early full-length versions of such a curriculum, covering issues such as (a) items and scales showing improved conceptual performance compared to traditional curriculum, (b) transferability of findings to different institutions, (c) retention of conceptual understanding post-course and (d) student attitudes. Along the way I will discuss a few areas in which students in both simulation/randomization courses and the traditional course …

Challenging The State Of The Art In Post-Introductory Statistics: Preparation, Concepts, And Pedagogy, Nathan L. Tintle, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, Jill Vanderstoep

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The demands for a statistically literate society are increasing, and the introductory statistics course ("Stat 101") remains the primary venue for learning statistics for the majority of high school and undergraduate students. After three decades of very fruitful activity in the areas of pedagogy and assessment, but with comparatively little pressure for rethinking the content of this course, the statistics education community has recently turned its attention to use of randomization-based methods to illustrate core concepts of statistical inference. This new focus not only presents an opportunity to address documented shortcomings in the standard Stat 101 course (for example, improving …