Education Commons^™

Instructional Decision Making In A Gateway Quantitative Reasoning Course, Deependra Budhathoki, Gregory D. Foley, Stephen Shadik

Numeracy

Many educators and professional organizations recommend Quantitative Reasoning as the best entry-level postsecondary mathematics course for non-STEM majors. However, novice and veteran instructors who have no prior experience in teaching a QR course often express their ignorance of the content to choose for this course, the instruction to offer students, and the assessments to measure student learning. We conducted a case study to investigate the initial implementation of an entry-level university quantitative reasoning course during fall semester, 2018. The participants were the course instructor and students. We examined the instructor’s motives and actions and the students’ responses to the course. …

Threshold Concepts In Quantitative Reasoning, Judith Canner, Jennifer E. Clinkenbeard

Numeracy

The idea of “threshold concepts” has been used to identify discipline-based concepts that are critical to that academic area. Threshold concepts are often difficult for students to assimilate in a meaningful way but, once done, can be powerful for the learner. In general, threshold concepts are 1) transformative to learner thinking; 2) bounded by the discipline; 3) integrative with other concepts; and 4) irreversible once understood (Meyer and Land 2003). This paper presents five threshold concepts in quantitative reasoning (QR) developed by transdisciplinary faculty workgroups that may be applicable for non-mathematics disciplines as well. They are as follows: 1) QR …

Focused On Pedagogy: Qr Grading Rubrics For Written Arguments, Ruby Daniels, Kathryn Appenzeller Knowles, Emily Naasz, Amanda Lindner

Numeracy

Institutional assessments of quantitative literacy/reasoning (QL/QR) have been extensively tested and reported in the literature. While appropriate for measuring student learning at the programmatic or institutional level, such instruments were not designed for classroom grading. After modifying a widely accepted institutional rubric designed to assess QR in written arguments, the current mixed method study tested the reliability of two QR analytic grading rubrics for written arguments and explored students’ reactions to the grading tools. Undergraduate students enrolled in a business course (N = 59) participated. A total of 415 QR artifacts from 40 students were assessed; an additional 19 …

Investigating Alignment In A Quantitative Literacy Course For Social Sciences Students, Vera Frith, Pam Lloyd

Numeracy

The Numeracy Centre at the University of Cape Town has taught a one-semester quantitative literacy course for social sciences students since 1999. This study aims to provide an example for how the design of such a course can be assessed for alignment with quantitative reasoning goals. We propose a framework of learning outcomes for the course and use that framework to analyse the assessments and student performance on them. We find that just under half of the overall mark for the course was devoted to the interpretation and communication of quantitative information (our “main” outcomes), and about a quarter was …

Are We At A Watershed Moment For The Quantitative Literacy Movement?: Review Of Shifting Context, Stable Core: Advancing Quantitative Literacy In Higher Education, By Luke Tunstall, Gizem Karaali, And Victor Piercey, Eds., Maura Mast

Numeracy

Luke Tunstall, Gizem Karaali, and Victor Piercey, eds. 2019. Shifting Concepts, Stable Core: Advancing Quantitative Literacy in Higher Education. Math Notes 88. (Mathematics Association of America, MAA Press). Print ISBN 978-0-88385-198-2. Electronic ISBN 978-1-61444-324-7.

The thematic approach of the edited MAA Notes volume Shifting Contexts, Stable Core: Advancing Quantitative Literacy in Higher Education is that the “construct” of quantitative literacy is now fairly stable, but the contexts in which quantitative literacy is taught (and practiced) continue to change. Several chapters give the reader much to consider regarding what constitutes the foundation of this stable core and, relatedly, how quantitative …

Alignment Between Learning Objectives And Assessments In A Quantitative Literacy Course, Younggon Bae, Samuel L. Tunstall, Kathryn S. Knowles, Rebecca L. Matz

Numeracy

In this analysis, we examine how course assessment items were aligned with learning objectives in a quantitative literacy course at Michigan State University. The alignment analysis consisted of mapping assessment items to a list of operationalized learning objectives from the course. Our analysis shows how often the learning objectives are represented in assessment items, how often they are paired with other learning objectives, and how influential they are in contributing to a student’s course grade. In addition, through comparisons across four assessment types (e.g., exams and homework), we show how each learning objective was assessed differently within each assessment type. …

Preliminary Evaluation Of The Psychometric Quality Of HeightenTm Quantitative Literacy, Katrina C. Roohr, Hyesun Lee, Jun Xu, Ou Lydia Liu, Zhen Wang

Numeracy

Quantitative literacy has been identified as an important student learning outcome (SLO) by both the higher education and workforce communities. This paper aims to provide preliminary evidence of the psychometric quality of the pilot forms for HEIghten quantitative literacy, a next-generation SLO assessment for students in higher education. We evaluated the psychometric quality of the test items (e.g., item analyses), individual- and group-level reliability, the relationship with student performance and related variables (e.g., grade point average) as well as student perceptions, and differences across college-related and demographic subgroups. Our study used data from a pilot test administered to over 1,500 …

The Quantitative Reasoning For College Science (Quarcs) Assessment 2: Demographic, Academic And Attitudinal Variables As Predictors Of Quantitative Ability, Katherine Follette, Sanlyn Buxner, Erin Dokter, Donald Mccarthy, Beau Vezino, Laci Brock, Edward Prather

Numeracy

In this article, we explore the ability of demographic and attitudinal variables to predict student scores on the Quantitative Reasoning for College Science (QuaRCS) Assessment. Variables measured by the assessment include: students' academic choices and plans, attitudes and perceptions regarding mathematics, self-reported effort level, and basic demographics such as age, race/ethnicity, gender and disability status. As in previously published numeracy studies, we find significant score deviations according to gender, race/ethnicity, and disability status; however, the effect size of these correlations pale in comparison to the effect size of affective/attitudinal variables on QuaRCS score. A large number of variables with …