| NSF Org: |
DUE Division Of Undergraduate Education |
| Recipient: |
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| Initial Amendment Date: | July 31, 2015 |
| Latest Amendment Date: | August 28, 2019 |
| Award Number: | 1544254 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Sandra Richardson
srichard@nsf.gov (703)292-4657 DUE Division Of Undergraduate Education EDU Directorate for STEM Education |
| Start Date: | October 1, 2015 |
| End Date: | September 30, 2020 (Estimated) |
| Total Intended Award Amount: | $299,753.00 |
| Total Awarded Amount to Date: | $299,753.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
3720 S FLOWER ST FL 3 LOS ANGELES CA US 90033 (213)740-7762 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
3470 Trousdale Parkway Los Angeles CA US 90089-4037 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | IUSE |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.076 |
ABSTRACT
Using High School Transcript Data and Diagnostic Information to Fine-Tune Placement Policy and Tailor Instruction in Developmental Math
Mathematical ability is critical for students' continued success in school, access to postsecondary education, and preparation for future employment. People who succeed in mathematics in high school and college have better employment prospects than others and can expect to earn more. Clearly, mathematical literacy is a growing need in our increasingly technological society. However, many students come to college unprepared for success; depending on the college, up to 40 percent of these students are placed in developmental courses their freshman year. Developmental mathematics is a college course, generally aimed to remediate areas missed in high school mathematics and prepare students for higher-level college mathematics. Unfortunately, many students do not complete or pass their developmental courses; college completion rates within six years are less than 60 percent at many colleges. In addition, even if they do succeed in these courses, they are not necessarily prepared to succeed in more advanced courses. Research that contributes to improving this situation is greatly needed. This Early Concept Grant for Exploratory Research (EAGER) will use diagnostic testing and high school performance data to improve the process of determining which mathematics courses students start with as they begin their college careers. They will also conduct research to investigate the effects of accurately placing students in mathematics courses on student retention in college and in STEM fields, graduation rates, and time to graduation.
The project will combine information from assessments and high school and college performance data to improve the accuracy of students' placement in mathematics courses upon entering college. They will use the Mathematics Diagnostic Testing Project (MDTP) assessment to obtain a detailed view of students' mathematical skills and areas in need of remediation. They will collect high school transcript data from Mathematics and English courses, standardized test scores, and GPA, as well as demographic data. They will also collect college level performance data including placement and other assessment results and data on courses taken including grades, withdrawals, and number of course attempts. They will combine these data to achieve two primary goals. Using quantitative methods, they will develop a model to improve placement accuracy. Using qualitative methods, they will identify ways to personalize instruction in college mathematics. They will work with students and instructors at two large urban community colleges in the Los Angeles Community District (LACCD).
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The goals of this project were to explore how using high school transcript data in the assessment and placement process at community colleges could improve student outcomes in developmental math. We first created a longitudinal dataset that tracks high school students from a large urban school district in California as they transitioned to local community colleges. We used the longitudinal student data to study how high school information may be relevant for college math course placement.
These data have resulted in six scholarly papers published in top peer-reviewed journals in the field of education: Educational Researcher, Educational Evaluation and Policy Analysis, The Journal of Higher Education, Research in Higher Education, Community College Review (forthcoming), and Urban Education. We also have another paper in the last stages of revision. A major contribution of this collection of works is the notion of inter-sector math misalignment (ISMM) – a naming device that can help to measure alignment and misalignment between high school and college-level math standards (Melguizo & Ngo, 2020). ISMM is the extent to which students who graduate high school meeting college-readiness benchmarks end up placed in developmental courses in high school. The results confirm that ISMM was prevalent and substantial with respect to high school grades, moderate to substantial based on different measures of math course-taking, and minor to moderate based on standardized test results.
In addition to identifying ISMM, we explore the implications of it with respect to student persistence and attainment in community colleges. We find a substantial equity cost of ISMM, with Black students the most negatively affected by the lack of alignment between high school and community college standards in math (Ngo & Melguizo, 2020; Ngo & Velasquez, 2020). We also explored the notion of inter-sector English misalignment (ISEM) for native English speakers as well as English Language Learners who have been re-classified in high school as proficient in English. The results also illustrate that the cost of misalignment was higher for students who were re-classified as English proficient in high school as compared to English only students.
The data also allowed us to explore the relationship between math misalignment, developmental math placement, and STEM pathways between high school and community college. We found that STEM-aspiring students who experienced math misalignment were less likely to attempt and complete STEM courses than STEM-aspiring students who were directly placed in transfer-level math (Park, Ngo, & Melguizo, 2020). We also found that that lower math placement was a deterrent to both math progression and STEM participation, especially for those at the margin of placement in transfer-level math (Park & Ngo, 2020). We translated the main findings into three policy briefs. This is valuable for leaders, practitioners, and faculty to understand the implications of the findings for their own work.
Finally, the project also allowed us to conduct qualitative research on math faculty beliefs and attitudes about high school data. We conducted surveys and interviews aimed at understanding community college math faculty perceptions of placement testing processes and the usefulness of student academic background data, which became particularly relevant as the California Community College system implemented a mandate (Assembly Bill 705) to move away from reliance on placement testing and towards the use of measures of high school preparation for placement. This resulted in one scholarly publication in Community College Review. We found that while faculty acknowledged the rich opportunity to use high school data to personalize instruction, the majority expressed what appeared to be satisfaction with the status quo of placement testing, and a hesitation to part with it. Underlying beliefs related to college-readiness, the trustworthiness of high school data, and deficit-orientations informed their views of the data. These research activities became the basis for our expanded inquiry into a broader policy implementation study funded by the Spencer Foundation. We are also in the process of preparing an application to NSF: IUSE Level 1. The goal is to explore whether Guided Math Pathways which is a move towards encouraging non-STEM aspiring students to enroll in college-level statistics courses instead of the traditional math courses (e.g., Calculus), might be de-tracking students from pursuing certificates, Associate Degrees, and eventually transfer to a four-year college to pursue a B.A. in a STEM field.
Last Modified: 11/09/2020
Modified by: Federick Ngo
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