Multiple Measures Placement Using Data Analytics: An Implementation and Early Impacts Report
Barnett, Elisabeth A.; Bergman, Peter; Kopko, Elizabeth; Reddy, Vikash; Belfield, Clive R.; Roy, Susha (2018). Center for the Analysis of Postsecondary Readiness. Retrieved from: https://eric.ed.gov/?id=ED588752
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examining4,729Students, gradePS
Single Study Review
Review Details
Reviewed: August 2019
- Single Study Review (findings for Multiple measures placement using data analytics)
- Randomized Controlled Trial
- Meets WWC standards without reservations because it is a randomized controlled trial with low attrition.
This review may not reflect the full body of research evidence for this intervention.
Evidence Tier rating based solely on this study. This intervention may achieve a higher tier when combined with the full body of evidence.
Findings
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Outcome measure |
Comparison | Period | Sample |
Intervention mean |
Comparison mean |
Significant? |
Improvement index |
Evidence tier |
|---|---|---|---|---|---|---|---|---|
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Course pass rate |
Multiple measures placement using data analytics vs. Business as usual |
1 Semester |
Full sample;
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65.80 |
61.60 |
Yes |
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Outcome measure |
Comparison | Period | Sample |
Intervention mean |
Comparison mean |
Significant? |
Improvement index |
Evidence tier |
|---|---|---|---|---|---|---|---|---|
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College enrollment: First semester |
Multiple measures placement using data analytics vs. Business as usual |
0 Semesters |
Full sample;
|
81.60 |
80.70 |
Yes |
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|
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Outcome measure |
Comparison | Period | Sample |
Intervention mean |
Comparison mean |
Significant? |
Improvement index |
Evidence tier |
|---|---|---|---|---|---|---|---|---|
|
Credits earned |
Multiple measures placement using data analytics vs. Business as usual |
1 Semester |
Full sample;
|
5.77 |
5.17 |
Yes |
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Evidence Tier rating based solely on this study. This intervention may achieve a higher tier when combined with the full body of evidence.
Sample Characteristics
Characteristics of study sample as reported by study author.
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Female: 48%
Male: 52% -
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New York
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Race Asian 3% Black 18% Native American 1% White 43% -
Ethnicity Hispanic 22%
Study Details
Setting
The analytic sample includes 4,729 students who took a placement test at one of five State University of New York colleges at the time of fall 2016 entry. This is an interim report and there are seven colleges involved in the overall project (only five colleges were involved in the interim analyses). All students in the sample were at risk of being placed in either developmental English or math.
Study sample
Fifty-two percent of enrolled community college students in the sample were male. Forty-three percent of the sample were White, 18 percent were Black, and 22 percent were Hispanic. Forty-nine percent of all sample students enrolling in at least one course during the fall 2016 term received a federal Pell Grant for that term. The intervention sample demographics are as follows: 48 percent female, 19 percent Black, 44 percent White, 22 percent Hispanic. The comparison group demographics are: 48 percent female, 17 percent Black, 44 percent White, 22 percent Hispanic.
Intervention Group
The intervention entailed use of multiple measures to determine whether students should be placed into remedial math or English programs. That is, the use of the multiple measures system is conceptualized as the intervention. Students were placed into developmental or college-level courses using this system. The intervention involved applying a predictive algorithm based on alternative data (i.e., SAT scores and high school performance, college outcomes, placement tests) to predict students' eligibility for enrollment in college-level or developmental courses (in math and English).
Comparison Group
The status quo placement system uses an established cut score to place students.
Support for implementation
Implementation of the multiple measures placement system required a year of planning time with the research team to develop new procedures and processes. Participating colleges were initially required to help develop placement score algorithms using historical data, develop new plans for obtaining high school transcripts and other high school data, and enter these data into IT systems. Implementation efforts also required development of new placement reports and training testing staff.
An indicator of the effect of the intervention, the improvement index can be interpreted as the expected change in percentile rank for an average comparison group student if that student had received the intervention.
For more, please see the WWC Glossary entry for improvement index.
An outcome is the knowledge, skills, and attitudes that are attained as a result of an activity. An outcome measures is an instrument, device, or method that provides data on the outcome.
A finding that is included in the effectiveness rating. Excluded findings may include subgroups and subscales.
The sample on which the analysis was conducted.
The group to which the intervention group is compared, which may include a different intervention, business as usual, or no services.
The timing of the post-intervention outcome measure.
The number of students included in the analysis.
The mean score of students in the intervention group.
The mean score of students in the comparison group.
The WWC considers a finding to be statistically significant if the likelihood that the finding is due to chance alone, rather than a real difference, is less than five percent.
The WWC reviews studies for WWC products, Department of Education grant competitions, and IES performance measures.
The name and version of the document used to guide the review of the study.
The version of the WWC design standards used to guide the review of the study.
The result of the WWC assessment of the study. The rating is based on the strength of evidence of the effectiveness of the intervention. Studies are given a rating of Meets WWC Design Standards without Reservations, Meets WWC Design Standards with Reservations, or >Does Not Meet WWC Design Standards.
A related publication that was reviewed alongside the main study of interest.
Study findings for this report.
Based on the direction, magnitude, and statistical significance of the findings within a domain, the WWC characterizes the findings from a study as one of the following: statistically significant positive effects, substantively important positive effects, indeterminate effects, substantively important negative effects, and statistically significant negative effects. For more, please see the WWC Handbook.
The WWC may review studies for multiple purposes, including different reports and re-reviews using updated standards. Each WWC review of this study is listed in the dropdown. Details on any review may be accessed by making a selection from the drop down list.
Tier 1 Strong indicates strong evidence of effectiveness,
Tier 2 Moderate indicates moderate evidence of effectiveness, and
Tier 3 Promising indicates promising evidence of effectiveness,
as defined in the
non-regulatory guidance for ESSA
and the regulations for ED discretionary grants (EDGAR Part 77).