Appendix A1.1 Study characteristics: Nunnery & ross 2007 (quasi-experimental design)
Characteristic | Description |
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Study citation | Nunnery, J. A., & Ross, S. M. (2007). The effects of the School Renaissance program on student achievement in reading and mathematics. Research in the Schools, 14(1), 40–59. |
Participants | The analysis sample included 992 students (482 treatment, 510 comparison) in the 2001/02 grade 8 cohort from four middle schools (two treatment and two comparison). Of the student sample, 21% qualified for free or reduced-price lunch (21% treatment, 20% comparison), 4% were limited English proficient (4% treatment, 4% comparison), 7% African-American (9% treatment, 6% comparison), 3% Asian (2% treatment, 3% comparison), 19% Hispanic (19% treatment, 20% comparison), 0% Native American (0% treatment, 0% comparison), and 70% were White (69% treatment, 71% comparison). Information about attrition was provided only at the level of assignment. Of the 11 elementary and middle schools originally selected as comparison schools, three schools did not provide appropriate grade-level test score data and were replaced (it is unknown whether any of these replaced schools were middle schools). Students in the analysis sample remained in the same school and had matched data available for three consecutive years (1999/2000–2001/02). |
Setting | The treatment group schools came from one suburban school district in Texas. Comparison schools came from other school districts in Texas with similar populations of students. |
Intervention | In 2000/01, schools in the treatment group implemented School Renaissance, a comprehensive school reform model that includes Accelerated Math. Accelerated Math is a progress-monitoring software program that tracks students’ daily activities, provides immediate feedback to students and teachers, alerts teachers to students struggling with certain assignments, and monitors achievement. Teachers can use the program with their existing math curriculum. Students in the treatment group experienced two years of the Accelerated Math program. |
Comparison | Schools in the comparison condition were from Texas school districts that had not implemented the full School Renaissance package. However, it is still possible that some elements of Accelerated Math were present in the comparison schools. |
Primary outcomes and measurement | The study used the Texas Learning Index (TLI) math scores (based on the Texas Assessment of Academic Skills); for the grade 8 cohort, program comparisons were based on average transformed scores for grades 7 and 8 from 2001 and 2002. The TLI has a common interpretation across grades: a score of 70 or above indicates performance at or above grade-level expectations. A student receiving the same score at consecutive grade levels made one year of academic progress. For a more detailed description of these outcome measures, see Appendix A2. |
Staff/teacher training |
A Renaissance coach conducts an initial training seminar and provides ongoing assistance to teachers. |
Appendix A1.2 study characteristics: ysseldyke & bolt, 2007 (randomized controlled trial with attrition)
Characteristic | Description |
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Study citation | Ysseldyke, J., & Bolt, D. M. (2007). Effect of technology-enhanced continuous progress monitoring on math achievement. School Psychology Review, 36(3), 453–467. |
Participants1 | The initial study sample included 3,309 students in grades 2–8 during the 2003/04 school year from 133 classrooms in nine schools, representing eight school districts in eight states. In the initial study sample 1% of the students were Asian, 28% African-American, 38% Hispanic, 0% Native American, 24% White, and 8% not specified. This review focuses on the middle school sample, which initially included 1,823 grade 6–8 students (1,010 treatment and 813 control) in 73 classrooms (41 treatment and 32 control). Demographic data on the middle school students could not be culled from the original study. Middle school classrooms dropped from the analysis include: 7 special education or enrichment treatment classrooms taught by teachers who had access to, but did not receive training in, Accelerated Math; 4 classrooms (2 treatment, 2 control) taught by two teachers who, according to the authors, arbitrarily chose which students to treat; and 22 classrooms (11 treatment, 11 controls) in a large, urban middle school district that, according to the authors, was unable to devote sufficient time and resources to Accelerated Math. The results here are drawn from the test-takers in the 40 middle school classrooms (21 treatment, 19 control) included in the analysis—792 students took the STAR Math test (418 treatment, 374 control) and 851 took the Terra Nova test (454 treatment, 397 control). Postattrition treatment and control groups were equivalent on pretests at baseline. Because these samples reflect attrition rates greater than 20%, the WWC rated this study as meeting evidence standards with reservations. |
Setting | The study took place in eight schools in seven districts in seven states: Alabama, Florida, Michigan, Mississippi, North Carolina, South Carolina, and two schools in Texas. The middle school sample analyzed here comprises three schools in Michigan, Mississippi, and North Carolina. |
Intervention | Students were taught by teachers using the Accelerated Math program during the 2003/04 school year. Accelerated Math is a progress-monitoring software program that teachers can use with their existing math curriculum. The program tracks students’ daily activities, provides immediate feedback to students and teachers, alerts teachers to students struggling with certain assignments, and monitors student achievement. Teachers assigned to the treatment group were asked to use Accelerated Math with their present math curriculum. In practice, the program was not implemented for approximately 40% of grade 2–8 students in the initial treatment group; the authors did not report the percentage of grade 6–8 students in the treatment group of the analysis sample that did not participate in Accelerated Math. |
Comparison | Students in the control group were taught using existing math curricula, without Accelerated Math. The existing curricula included: Scott Foresman Middle School Math, Consumer Math, Everyday Math, Transition Math (Prentice Hall), and Chicago Math in Michigan; Glencoe in Mississippi; and Glencoe, McGraw-Hill, and the state curriculum in North Carolina. Control students had the same teachers as the intervention group students. |
Primary outcomes and measurement | Participating students were pretested in October 2003 and posttested in May 2004 using two nationally normed, standardized tests (STAR Math and Terra Nova) for math achievement. Students in the treatment and control groups were compared using a linear regression analysis in which posttest scores were regressed on pretest scores and on dummy variables related to main effects for experimental condition and school. |
Staff/teacher training | Teachers in the intervention group were trained to use Accelerated Math. During the school year, teachers using Accelerated Math received three to five visits from a Renaissance Learning math consultant, who guided teachers on how to improve their use of the program. Teachers also had unlimited access to technical support. |
1The study authors provided the WWC with sample sizes for the middle schools. |
Appendix A1.3 study characteristics: ysseldyke & tardrew, 2007 (quasi-experimental design)
Characteristic | Description |
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Study citation | Ysseldyke, J., & Tardrew, S. (2007). Use of a progress monitoring system to enable teachers to differentiate mathematics instruction. Journal of Applied School Psychology, 24(1), 1–28. |
Participants1 | The initial study sample included 2,397 students (1,319 treatment and 1,078 comparison) in grades 3–10 during the 2001/02 school year from 125 classrooms (67 treatment and 58 comparison) in 47 schools in 24 states. The middle school analysis sample in this review included 475 grade 6–8 students (235 treatment, 240 comparison) in 25 classrooms (13 treatment, 12 comparison). Of the students, 43% were male (43% treatment, 43% comparison), and 49% female (48% treatment, 51% comparison). Of the total student gender, 7% were reported as unspecified (8% treatment, 6% comparison). Of the students, 0% were Asian (0% treatment, 0% comparison), 1% African-American (1% treatment, 0% comparison), 9% Hispanic (9% treatment, 9% comparison), 0% Native American (0% treatment, 0% comparison), 44% White (38% treatment, 49% comparison), and 46% were reported as unspecified (51% treatment, 42% comparison). |
Setting | The study was conducted in 47 schools in 24 states (Alabama, Arkansas, California, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Massachusetts, Michigan, Minnesota, Missouri, Montana, New Mexico, Ohio, Oklahoma, Oregon, Pennsylvania, Tennessee, Texas, Virginia, Washington, and Wisconsin). The authors did not report whether all schools and states were represented in the middle school (grades 6–8) sample. |
Intervention | Students were taught by teachers using Accelerated Math during the spring semester of the 2001/02 school year. A progress-monitoring software program, Accelerated Math can be used with teachers’ existing math curriculum. The program tracks students’ daily activities, provides immediate feedback to students and teachers, alerts teachers’ to students struggling with certain assignments, and monitors student achievement. Teachers assigned to the Accelerated Math treatment group were asked to use the program with their existing math curriculum. |
Comparison | Teachers assigned to the comparison group did not use Accelerated Math but continued their usual math curriculum and practices. |
Primary outcomes and measurement | Using a computer adaptive test of math achievement (STAR Math), students were pretested in January 2002 and posttested in May 2002. |
Staff/teacher training | Intervention teachers participated in a one-day training session conducted by Renaissance Learning. The training was designed to familiarize teachers with Accelerated Math and to guide them in integrating it into curriculum and instruction. Of 68 treatment group teachers in the full sample, 66 attended the training. |
1The study authors provided the WWC with the number of middle school classrooms by treatment status. |
Appendix A2 Outcome measures for the math achievement domain
Characteristic | Description |
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Texas Learning Index math scores (based on the Texas Assessment of Academic Skills) | The Texas Assessment of Academic Skills (TAAS) is a criterion-referenced standardized state test that measures problem-solving and critical-thinking skills. The Texas Learning Index (TLI) is an outcome metric, based on student performance on the TAAS, which allows for comparisons between administrations and between grades. The TLI has a common interpretation across grades: a score of 70 or above indicates the student performed at or above grade-level expectations. A student receiving the same score at consecutive grade levels made one year of academic progress. Analyses in the study were based on a transformation of the TLI that was conducted to induce normality. |
STAR Math assessment | STAR Math is a computer-adaptive math test that assesses math skills. It combines computation and numeration items with word problems, estimation, statistics, charts and graphs, geometry, measurement, and algebra. STAR scores can appear as scaled scores or normal curve equivalent values. |
Terra Nova mathematics subtest |
The Terra Nova subtest is a national norm-referenced test that assesses academic performance in math. |
Appendix A3 Summary of study findings included in the rating for the math achievement domain1
Authors' findings from the study | ||||||||
---|---|---|---|---|---|---|---|---|
Mean outcome (standard deviation)2 |
WWC calculations | |||||||
Outcome measure | Study sample | Sample size (clusters/ students) | Accelerated Math group | Comparison group | Mean difference3(Accelerated Math – comparison) | Effect size4 | Statistical significance5 |
Improvement index6 |
Nunnery & Ross, 2007 (quasi-experimental design)7 |
||||||||
2001 and 2002 transformed Texas Learning Index scores | Grade 8 cohort | 4/992 | 1.218 |
1.168 |
0.05 | 0.11 | ns | +4 |
Average for math achievement (Nunnery & Ross, 2007)9 | 0.35 | ns | +4 | |||||
Ysseldyke & Bolt, 2007 (randomized controlled trial with attrition)7 |
||||||||
2004 STAR Math normal curve equivalent scores | Grades 6–8 |
40/792 | 48.1110 |
44.4511 |
3.66 | 0.19 | ns | +7 |
2004 Terra Nova normal curve equivalent scores | Grades 6–8 |
40/851 | 46.8910 |
48.1711 |
–1.28 | –0.07 | ns | –3 |
Average for math achievement (Ysseldyke & Bolt, 2007)9 | 0.06 | ns | +2 | |||||
Ysseldyke & Tardrew, 2007, grade 6 cohort (quasi-experimental design)7 |
||||||||
2002 STAR Math scale scores |
Grade 6 | 17/326 | 773.4312 |
762.8013 |
10.63 | 0.10 | ns | +4 |
Average for math achievement (Ysseldyke & Tardrew, 2007 grade 6)9 | 0.10 | ns | +4 | |||||
Ysseldyke & Tardrew, 2007, grades 7 and 8 cohort (quasi-experimental design)7 |
||||||||
2002 STAR Math scale scores |
Grades 7 and 8 | 8/149 | 801.1412 |
786.4713 |
14.67 | 0.17 | ns | +7 |
Average for math achievement (Ysseldyke & Tardrew, 2007, grades 7 and 8)9 | 0.17 | ns | +7 | |||||
Domain average for math achievement across all studies9 | 0.11 | na | +4 | |||||
1This appendix reports findings considered for the effectiveness rating and the average improvement indices for the math achievement domain. |
Appendix A4 Accelerated Math rating for the math achievement domain
The WWC rates an intervention's effects for a given outcome domain as positive, potentially positive, mixed, no discernible effects, potentially negative, or negative.1
For the outcome domain of math achievement, the WWC rated Accelerated Math as no discernible effects. The remaining ratings (potentially negative effects and negative effects) were not considered, as Accelerated Math was assigned the highest applicable rating.
Rating received |
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No discernible effects: No affirmative evidence of effects.
|
Other ratings considered |
Positive effects: Strong evidence of a positive effect with no overriding contrary evidence.
|
Potentially positive effects: Strong evidence of a positive effect with no overriding contrary evidence.
|
Mixed effects: Evidence of inconsistent effects as demonstrated through EITHER of the following.
|
1 For rating purposes, the WWC considers the statistical significance of individual outcomes and the domain-level effect. The WWC also considers the size of the domain-level effect for ratings of potentially positive or potentially negative effects. For a complete description, see the WWC Intervention Rating Scheme. |
Appendix A5 Extent of evidence by domain
Sample size | ||||
---|---|---|---|---|
Outcome domain | Number of studies | Schools | Students | Extent of evidence1 |
Math achievement | 3 | >72 | ≥2,2593 | medium to large |
1A rating of “medium to large” requires at least two studies and two schools across studies in one domain and a total sample size across studies of at least 350 students or 14 classrooms. Otherwise,
the rating is “small.” |