Added April 20, 2018
Executive Summary
This study sought to answer the following research questions:
1. After controlling for demographic differences between students, is RAMP status associated with (a) student attendance, (b) student disciplinary referrals, and (c) end of year course grades?
2. In what ways do RAMP and non-RAMP school counseling programs address student attendance, disciplinary referrals, and grades?
The research was conducted in Greenville County School District, a large school district located in the northwestern corner of South Carolina. The district has 52 elementary schools and, at the time of the study, four were RAMP. Data were collected at four elementary schools, two that had RAMP school counseling programs and two that did not. The district provided assistance in identifying comparison schools that would closely match the RAMP schools; the student demographic breakdown was comparable across all schools, and each was classified as a large, suburban school. Student-level data were collected for all students in the participating schools for whom complete data were available at the end of the 2016-17 academic year (see below). From the participating schools, four principals, four instructional coaches, four school counselors, and ten teachers were interviewed.
| Student Characteristic | Number | Percent |
| Grade 2 | 497 | 24 |
| Grade 3 | 549 | 27 |
| Grade 4 | 536 | 26 |
| Grade 5 | 485 | 24 |
| White | 1,488 | 72 |
| Hispanic | 318 | 15 |
| Black | 261 | 13 |
| Male | 1,067 | 52 |
| Female | 1,000 | 48 |
| Special Education | 337 | 16 |
| Limited English Proficiency | 227 | 11 |
| Attending RAMP School | 1,069 | 52 |
Research Question 1
De-identified student-level data was obtained from the district for all students in grades 2-5 who were in attendance for the entire 2016-17 school year. Dependent variables included number of days absent, number of disciplinary referrals, and end of year course grades for Language Arts, Math, Reading, and Social Studies (recorded as an average percentage grade across all four courses). The independent variables were ethnicity, Limited English Proficiency (LEP) status, gender, special education status, grade level, and school name (to identify RAMP status).
Hierarchical multiple linear regression was used to examine the first research question. Separate analyses were conducted for each student outcome (attendance, discipline, and grades). Assumptions related to normality, linearity, homoscedasticity, and multicollinearity were all met, and the dependent variables were normally distributed (absences M = 6.03, SD = 5.70; disciplinary referrals M = 0.29, SD = 1.28; grades M = 88.65, SD = 8.25).
Using a stepwise approach, for each separate analysis the demographic variables (gender, LEP status, special education status, grade level, and ethnicity) were entered in step 1; grade level and ethnicity were dummy coded. RAMP status (RAMP or non-RAMP) was entered in step 2. Overall, the combination of all variables significantly predicted absences, referrals, and grades at p < .05, but RAMP status offered little or no unique contribution to the overall variance.
Specifically, the linear combination of demographic variables and RAMP status was significantly related to absences, F (9, 2,057) = 9.46, p < .001, R2 = .04. However, adding RAMP status in step 2 did not change the overall variance accounted for by the model (see Table 1). RAMP status also was not a significant predictor (t = .91, p = .36) of absences. For disciplinary referrals, the combination of demographic variables and RAMP status was significantly related to the number of referrals, F (9, 2,057) = 18.54, p < .001, R2 = .08. This time, the effect of adding RAMP status in step 2 was small, explaining an additional 1% of the variance (see Table 2). Additionally, RAMP status was a significant predictor (t = 4.75, p = .00) of disciplinary referrals. Finally, the linear combination of demographic variables and RAMP status was significantly related to end of course grades, F (9, 2,057) = 67.92, p < .001, R2 = .23). In step 2, although adding RAMP status as a predictor did not change the overall amount variance explained above and beyond the demographic variables, it was a significant predictor (t = -2.16, p = .03) of course grades.
Research Question 2
Qualitative data were collected via semi-structured interviews individually with the school counselors, principals, and instructional coaches at each school as well as via small groups of teachers. Interviews were audio recorded and transcribed. The interview and focus group data were analyzed by following steps to thematic analysis outlined by Braun and Clark: (a) familiarizing oneself with the data, including transcribing interviews, reading transcripts, and making initial notes, (b) generating initial codes, (c) searching for themes, (d) reviewing themes, and (e) defining and naming themes. Four themes emerged from the qualitative analysis.
(1) Direct services: The Direct Services theme represents how school counselors addressed attendance, behavior, and grades through interventions they provided directly to students. All the counselors described using classroom instruction as well as individual and small group counseling to address those target areas. The frequency of those interventions and the topics covered varied, as they were informed by student needs as well as school and counseling program goals.
(2) Accountability: The Accountability theme includes content that explains how the school counselors used data in their efforts to address attendance, behavior, and grades. On a systemic level, and through their roles on school administrative or leadership teams, the counselors played a role in reviewing school data and targeting goals set by the administration. Also, the district director of school counseling required that each counselor develop program goals related to student attendance, behavior, and grades. Additionally, the counselors gathered and reviewed data from various sources to inform their work. For example, some counselors described reviewing school and program data from the previous year and using needs assessments. The RAMP counselors embraced data and communicated with their colleagues about how data informed their work. Doing so led to increased awareness and positive perceptions of their programs.
(3) Collaboration: Collaboration reflects the ways that the counselors were involved in a systemic approach to address attendance, behavior, and grades. School counselors were valued for their expertise, and many participants consulted with them because they could offer a unique perspective. Teachers also appreciated the resources and recommendations the counselors offered them through consultation. The counselors also were able to share their expertise with teachers through presentations at faculty meetings. Instructional coaches also commented on the important role school counselors played in relation to professional development.
(4) Student-centered: The Student-Centered theme captures school counselors approaching students holistically, considering students’ unique needs beyond academics. This holistic concept extended beyond the child, to assisting the child’s family as well. Furthermore, the relationships and connections school counselors build with students and families enabled them to get at the root of attendance, behavioral, or academic concerns. Some participants believed in addition to helping students feel safe to share their concerns, the relationship served as motivation for students to improve their academics, behavior, or attendance.
Discussion
Results from this study suggest RAMP status had little to no relationship with student absences, disciplinary referrals, or end of course grades. Numerous reasons could exist for these results, one being that schools can potentially implement comparable comprehensive school counseling programs without pursuing the RAMP designation (i.e., RAMP is voluntary). In the school district where data were collected, all schools are expected to implement comprehensive school counseling programs that adhere in part to the ASCA National Model. Additionally, the counselors all had access to the same district level school counseling resources, supports, and professional development opportunities. As such, potentially the only differences among the RAMP and non-RAMP schools could be counselor desire and/or level of administrative support to seek RAMP recognition.
To that end, the qualitative data provide some insight into how counselors in the participating schools implemented their comprehensive programs. First, it appears school counselors in the RAMP and non-RAMP schools were similar in attempting to spend 80% of their time in direct services, implementing preventative curriculum in classrooms, and providing responsive services via group and individual counseling. They also took a holistic approach to addressing student concerns, recognizing the overlap among academic, behavioral, and social concerns. The counselors engaged in similar types of indirect services, including sharing their unique perspectives and expertise with their colleagues, initiating collaborative relationships with families and community agencies, and serving as leaders in their schools.
The aspect of school counseling program implementation that seemed different between the RAMP and non-RAMP schools was accountability. All of the counselors used data to inform their work, and they worked collaboratively with their administrators to review schoolwide data (e.g., test scores, disciplinary records) to identify goals and targeted interventions. The counselors at the RAMP schools, however, seemed to more fully embrace data. That is, they talked about using data to monitor student progress and they shared results with stakeholders, which appeared to help increase teacher and administrator understanding of the school counseling program and its effectiveness. Perhaps it is this more comprehensive use of data that resulted in the slightly stronger relationship between RAMP status and disciplinary referrals in this study. School counselors who use data to monitor the effectiveness of their interventions might be more likely to make relevant adjustments midyear, as opposed to missing opportunities by only reviewing end of year data.
Implications for School Counseling
First, given the subtle differences noted regarding accountability practices between the RAMP and non-RAMP counselors, continued attention to preparing school counselors for accountability seems important. Perhaps if more school counselors felt prepared to engage in accountability practices required for RAMP, more would pursue RAMP (or at minimum would spend more time monitoring their effectiveness and using data more comprehensively). Given the importance of accountability to the RAMP process (and to the implementation of a comprehensive school counseling program in general), training opportunities that can help ensure greater consistency in accountability practices among school counselors seem important.
Further, district level personnel can play an important role in promoting and facilitating ongoing training for school counselors not only in accountability, but also relevant to the implementation of comprehensive school counseling programs and the RAMP process in particular. Similar to the district where this research was conducted, other districts could develop RAMP mentoring groups and offer informational workshops about the RAMP process. Also, district-level requirements can help shape school counseling program implementation. For example, by requiring all district school counselors submit annual agreements, action plans, and results reports, a district can help ensure some level of consistency throughout the district in school counseling practices that are aligned with the ASCA National Model, even if schools do not seek RAMP recognition.
Finally, many school districts and counselors question what the real incentive is to pursue RAMP. Using an approach similar to this study, individual districts could examine the impact of RAMP locally, integrating other variables relevant to their schools and population. For example, large school districts considering whether or not to promote and support RAMP could experiment by identifying a number of comparable schools that have similar baseline data, using one as a control while the other implements RAMP. Further, rather than focusing only on one year, a longitudinal approach could be used to monitor if RAMP schools outperform non-RAMP schools on various student outcome measures. Data gathered from these types of initiatives could help administrators justify programmatic decisions relevant to school counseling
Amy Milsom, Ed.D., and Claudia Salazar, Clemson University
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