Do Effects of Quantway Persist in the Following Year? - A Multilevel Propensity Score Approach to Assessing Student College Mathematics Achievement

Oct 15, 2026

Uploaded by Margaret

This report evaluates whether Quantway 1 (QW1) effects persist into the following year, using a multilevel propensity score matching framework. Quantway 1 is a single-term accelerated developmental math course focused on quantitative reasoning and designed to improve access to college-credit mathematics. Building on prior results, the study tracks subsequent college math enrollment and outcomes over one year, finding higher enrollment in credit-bearing courses and generally comparable GPAs across diverse sex, race/ethnicity, classroom, and college contexts. Future directions are addressed.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Abstract

Method

Propensity Score Matching

Analytic Sample

Study Design

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Do Effects of Quantway Persist in the Following Year?
A Multilevel Propensity Score Approach to Assessing Student College Mathematics Achievement
March 2017 Hiroyuki Yamada
Carnegie Foundation for the Advancement of Teaching Stanford, CA | CARNEGIE MATH PATHWAYS TECHNICAL REPORT | Abstract This report analyzes evidence from a new study assessing the effectiveness of Quantway 1 (QW1), a single-term accelerated developmental math course with a focus on quantitative reasoning. Quantway􀂓 is one of the Pathways courses (along with Statway􀂓 ) developed by a network of faculty and content experts convened by the Carnegie Foundation to accelerate the progress of college students through developmental mathematics with the aim of increasing success rates in earning college credit in mathematics. This report is the sequel to an earlier study1 of the effectiveness of QW1, both of which applied a multilevel propensity score matching approach. The first study provided robust evidence that QW1 increases student success in fulfilling developmental math requirements and advances equity in student outcomes. The present study tracked student college math achievement through the year after QW1 enrollment. Results in this most recent analysis revealed that QW1 students were significantly more likely to enroll in credit-bearing college math courses within a year than their counterparts who followed traditional developmental math sequences were, and that while increasing subsequent math course taking, QW1 students demonstrated a comparable GPA. Significantly, QW1 effects were positive across all sex and race/ethnicity subgroups, as well as in nearly all classrooms and colleges. The current study provided additional empirical evidence of the persistence of QW1’s effectiveness for diverse student populations across varied classroom and institutional contexts. Directions for future work are discussed. As indicated in the prior study, additional questions still need to be answered: Do the effects of QW1 persist in the following year? More specifically, we are interested in whether or not QW1 students are (a) more likely than matched comparison students to enroll in creditbearing college math courses, and (b) perform comparably to or better than matched comparison students in college math courses. Because QW1 is designed not only to get students through their developmental math sequences but to help them meet their collegelevel math requirements, these questions will be particularly important to answer in determining QW1’s effectiveness. Therefore, the objective of the current study is to assess the persistence of effects of QW1 by tracking student college math achievement one year after QW1 participation. Method Propensity Score Matching Propensity score matching is a statistical technique applied to observational data to reduce possible selection bias—where certain kinds of students may have been more likely to enroll in QW1, leading to more positive outcomes than there otherwise would have been—and, accordingly, increase the validity of causal inference (Rosenbaum & Rubin, 1983) . There are two main steps involved in this procedure: (a) obtain a propensity score per student, which represents the likelihood of a student enrolling in QW1, and (b) identify as matches students whose propensity scores are similar to each other. Typically, a logistic regression approach is 1 See Yamada, H., Bohannon, A., & Grunow, A. (2016) used with a set of factors or covariates hypothesized to influence student enrollment in QW1 . To obtain propensity scores in the earlier study (Yamada et al., 2016), we selected a total of 37 student-level covariates including student background characteristics and prior course taking and success patterns during the two years prior to the Quantway 1 term based on prior research findings and advice from institutional researchers in the participating colleges and rana hierarchical line

FAQs

What is the main objective of this report?

To assess whether the effects of Quantway 1 persist in the year following student participation by tracking college math achievement one year after enrollment.

How does the report address selection bias?

It uses propensity score matching on observational data to reduce possible selection bias, matching students with similar propensity scores for enrolling in Quantway 1.

What outcomes are analyzed in the subsequent year?

The study examines whether students enroll in college-level mathematics courses in the subsequent calendar year (including summer where applicable) and compares their corresponding GPA outcomes.

Oct 15, 2026

Uploaded by Margaret