Logue, A. W., Watanabe-Rose, M., & Douglas, D. (2016). Educational Evaluation and Policy Analysis
Reviewed: March 2018
This review may not reflect the full body of research evidence for this intervention.
|
Outcome measure |
Comparison | Period | Sample |
Intervention mean |
Comparison mean |
Significant? |
Improvement index |
||
|---|---|---|---|---|---|---|---|---|---|
|
Passed course |
Mainstreaming vs. Business as usual |
0 Days |
Full sample: STAT-WS v. EA-WS;
|
0.48 |
0.36 |
Yes |
|
||
| More Outcomes | |||||||||
| Show Supplemental Findings | |||||||||
|
Passed course |
Mainstreaming vs. Business as usual |
0 Days |
Full sample: STAT-WS v. EA;
|
0.48 |
0.31 |
Yes |
|
||
|
Number of Non-STEM Courses Passed |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: STAT-WS v. EA-WS;
|
2.19 |
1.67 |
No |
|
||
|
Passed course |
Mainstreaming vs. Business as usual |
0 Days |
Full sample: EA-WS v. EA;
|
0.36 |
0.31 |
No |
-- | ||
|
Number of STEM Courses Passed |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: STAT-WS v. EA-WS;
|
0.4 |
0.33 |
No |
-- | ||
|
Number of Non-STEM Courses Passed |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: STAT-WS v. EA;
|
2.19 |
2 |
No |
-- | ||
|
Number of STEM Courses Passed |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: STAT-WS v. EA;
|
0.4 |
0.44 |
No |
-- | ||
|
Number of STEM Courses Passed |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: EA-WS v. EA;
|
0.33 |
0.44 |
No |
-- | ||
|
Number of Non-STEM Courses Passed |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: EA-WS v. EA;
|
1.67 |
2 |
No |
-- | ||
|
Outcome measure |
Comparison | Period | Sample |
Intervention mean |
Comparison mean |
Significant? |
Improvement index |
||
|---|---|---|---|---|---|---|---|---|---|
|
Total credits |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: Stat-WS v. EA-WS;
|
20.04 |
14.66 |
Yes |
|
||
| More Outcomes | |||||||||
|
Fall-to-Fall Enrollment Persistence |
Mainstreaming vs. Business as usual |
9 Months |
Full sample: STAT-WS v. EA-WS;
|
0.60 |
0.51 |
Yes |
|
||
| Show Supplemental Findings | |||||||||
|
Total credits |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: STAT-WS v. EA;
|
19.93 |
15.53 |
Yes |
|
||
|
Total Number of College Credits Earned, Excluding Statistics |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: STAT-WS v. EA-WS;
|
18.54 |
14.66 |
Yes |
|
||
|
Total Number of College Credits Earned, Excluding Statistics |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: STAT-WS v. EA;
|
18.4 |
15.53 |
Yes |
|
||
|
Fall-to-Fall Enrollment Persistence |
Mainstreaming vs. Business as usual |
9 Months |
Full sample: STAT-WS v. EA;
|
0.60 |
0.55 |
No |
-- | ||
|
Total credits |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: EA-WS v. EA;
|
14.66 |
15.53 |
No |
-- | ||
|
Total Number of College Credits Earned, Excluding Statistics |
Mainstreaming vs. Business as usual |
1 Year |
Full sample: EA-WS v. EA;
|
14.66 |
15.53 |
No |
-- | ||
|
Fall-to-Fall Enrollment Persistence |
Mainstreaming vs. Business as usual |
9 Months |
Full sample: EA-WS v. EA;
|
0.51 |
0.55 |
No |
-- | ||
Characteristics of study sample as reported by study author.
The study was conducted at three City University of New York (CUNY) community colleges, one in each of three NYC boroughs: the Bronx, Queens and Manhattan.
Across all three groups, 55% of students were female (55% in Stat-WS, 58% in EA-WS, and 51% in EA), and 86% of students were underrepresented minorities (84% in Stat-WS, 88% in EA-WS, and 87% in EA). In each of the three groups, the majority of students (56%) reported that their first language was English. The average age of study participants was 21 years old.
The intervention (Stat-WS) was a mainstream, credit-bearing, college-level introductory statistics course (Stat-WS), delivered in the fall of 2013. Course topics included probability, binomial probability distributions, normal distributions, confidence intervals, and hypothesis testing. The course was held over one semester and lasted between 3 and 6 hours per week, depending on the college. The course required students to attend a two-hour workshop every week for supplemental instruction on statistical concepts and problems. The workshops had three components: (1) 10-15 minutes of reflection on concepts learned so far and what was difficult; (2) about 100 minutes of individual and group work on difficult topics and problems, and (3) a final five minutes of reflection on whether the difficult issues were addressed or not. The 24 class sections that included workshops were taught by 21 workshop leaders, who were either advanced undergraduates or recent graduates of CUNY.
The primary comparison group was a traditional non-credit-bearing remedial algebra course that included supplemental weekly workshops (EA-WS). The course covered topics such as linear equations, exponents, polynomials, and quadratic equations. Students in both comparison groups took the mandatory CUNY-wide elementary final and received their grade based on a CUNY-wide elementary algebra-grading rubric. The weekly workshops delivered to the EA-WS group followed the same three-component structure implemented for the workshops in the intervention group.
Instructors attended a six-hour orientation workshop, met monthly with researchers, and met weekly with the workshop leaders assigned to their two sections (Stat-WS and EA-WS). The study’s 21 workshop leaders completed 10 hours of training focused on the details of the study as well as methods for conducting the workshops. Workshop leaders also met monthly with the researchers to discuss concerns and other issues as needed.
In the case of multiple manuscripts that report on one study, the WWC selects one manuscript as the primary citation and lists other manuscripts that describe the study as additional sources.
Logue, A. W., Watanabe-Rose, M., & Douglas, D. (2015, April). Elementary algebra or statistics: A randomized controlled trial with students assessed as needing remedial mathematics. Paper presented at the meeting of the American Educational Research Association, Chicago, IL.
An indicator of the size of the effect from using the intervention. It is the expected change in percentile rank for an average comparison group student if the student had received the intervention, ranging from -50 to +50. At the study level, the improvement index is only shown if the findings are characterized as statistically significant or substantively important (greater than +10 or less than -10); dashes are displayed for an indeterminate effect.
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.
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