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Researching the Effectiveness of School Counseling Programs - Article

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Researching the Effectiveness of School Counseling Programs - Article

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Abstract

Using the High School Longitudinal Study of 2009, we investigated school counselors' caseloads, how they spent their time, and the impact of those factors on schools' academic outcomes. Results showed that approximately 85% of the school counselors had a caseload of 455 or fewer students, with roughly one quarter reporting caseloads equal to or less than 250, and that school counselors spent more of their time on college, scheduling, and personal/social/academic/career development. We also found that how school counselors spent their time was predictive of ninth-grade retention rates, the percentage of students who enrolled in Advanced Placement (AP) courses, and the percentage of students who enrolled in 4-year universities. We provide discussion and implications for school counselors.

The passage of the Every Student Succeeds Act (ESSA) in 2015 ushered in an era of increased accountability for the school to educate the whole child. School-level indicators of academic success are becoming increasingly varied and expanding beyond academic performance ( Swaak, 2018). Regardless of the grade level, school counselors are an important part of the school leadership team and are positioned to address students' academic, career, and social/emotional well-being and development ( American School Counselor Association [ASCA], 2018). School counselors provide direct and indirect services that help students develop positive mind-sets and behaviors to promote academic achievement ( ASCA, 2016) and are charged to use evidence-based practice to ensure their work is supporting positive student outcomes ( Zyromski et al., 2018).

Dimmitt and colleagues (2007) proposed an evidence-based model for school counseling that integrated three aspects of school counselors' work: problem description, choosing interventions with evidence of efficacy, and program evaluation. In this study, we addressed the outcome aspect of this model by focusing on the impact of school counselor caseload and use of time on school-level academic outcomes.

Literature Review

School counselors have a long history of advocating for their role and how they can be successful. Decades of research have identified the ways that school counselors are too frequently tasked with duties unrelated to their job descriptions and shown that they are responsible for high numbers of students. For example, Borders and Drury (1992) articulated a model for a comprehensive school counseling program that defined the school counselor's role and how counselors should utilize their time to be most effective in promoting student success. Murray (1995) summarized how the role definition had become diffuse and provided a strategy for school counselors to define their role and facilitate communication with their administrators. Downs et al. (2002) presented at the ASCA 2002 Annual Meeting about high counselor caseloads in Southern California that ranged from 329 to 1,850 students, with an average caseload of 1,015 students. This brief literature review is not exclusively historical in nature, rather we aim to support the chronicity of the issues of high caseloads and the lack of definition of school counselors' roles and duties.

Despite the ASCA (2019b) recommendation for school counselors to have a student-to-school counselor ratio of 250:1, state and national reports indicate that counselors have caseloads higher than this recommendation. The National Association for College Admission Counseling (NACAC) and ASCA (n.d.) produced a combined report that detailed state and national average caseloads from the 2004-2005 to the 2014-2015 academic years. The national average school counseling caseload in 2015 was 482 students, and average state caseloads ranged from 924 in Arizona to 200 in Vermont. The school counselor caseload was below the recommended 250 in only three states ( NACAC & ASCA, n.d.).

ASCA (2019a) also recommends that school counselors spend 80% of their time providing direct and indirect services to students. This includes but is not limited to delivering school counseling curriculum, individual college and career planning, and responsive services to groups and individuals. However, school counselors also perform noncounseling duties that take away from their time in school counseling services. Foster et al. (2005) studied responses of 526 school counselors who reported how they used their time. For the most part, counselors were spending their time on tasks related to the three domains of the ASCA National Model ( ASCA, 2019a); however, authors concluded that further examination of time spent on noncounseling duties was warranted.

The purpose of this study is to add support for school counselors' appropriate caseloads and use of time on counseling duties by connecting these factors to school academic outcomes.

School Counselors' Caseload

Results from four states provided strong evidence suggesting that lower school counselor caseload is related to higher rate of student attendance and lower rate of discipline problems ( Carey & Dimmitt, 2012). As an identified stressor for school counselors, large caseloads can contribute to burnout ( McCarthy et al., 2010), and higher rates of staff burnout have been associated with increased reports of students' experiences of racial inequities ( Bottiani et al., 2014). In a recent study, Goodman-Scott and colleagues (2018) found that student-to-school counselor ratios were significantly associated with student grade point average and graduation from high school. In this study, we hypothesized that counselors' caseloads would also have an impact on school-level indicators of academic achievement.

School Counselors' Use of Time

Delivering a comprehensive school counseling program includes individual planning, responding to student needs, and teaching classroom lessons ( ASCA, 2018). ASCA recommends that the majority of school counselors' time be spent providing direct services in person to students, with a small amount on indirect or supportive services to the system ( ASCA, 2018). Research has found discrepancies between ASCA-defined school counselor roles and principals' perceptions and endorsement of appropriate activities ( Amatea & Clark, 2005), and researchers have suggested how to change principals' perceptions of school counselors' roles and time use ( Leuwerke et al., 2009).

Empirical evidence demonstrates that time spent on college counseling positively affects students' college access. For example, Dimmitt et al. (2007) reported that student apathy, the antithesis of engagement in learning, could be counteracted by providing students with more information about graduation requirements and career options. Furthermore, McDonough (2005) concluded that not only increasing the number of school counselors but also increasing the amount of time they spend on college advisement, including support for parents, would increase college enrollment.

School-Level Academic Achievement

Access to and enrollment in academically rigorous courses help to boost college and career readiness and engage students more effectively in learning ( College Board, 2017). Students in AP courses have personal traits associated with success in a rigorous academic curriculum, including work habits, sustained focus, high goal setting, motivation, and perseverance ( Shaunessy-Dedrick et al., 2015). Scott and colleagues (2010) found that when controlling for student ethnicity, gender, class rank, and SAT score, students who had earned college credits through the AP program earned higher grade point averages in their first semester of college when compared to students who did not have AP credit. Therefore, this study uses AP course enrollment as an indicator of academic achievement at the school level; this is aligned with previous research ( Klopfenstein & Thomas, 2009; Warne, 2017).

Jimerson (2001) conducted a meta-analysis of 20 studies conducted between 1990 and 1999 on retained students. He concluded that retention at any point in school is the strongest predictor of dropout. Transition from middle to high school is a normal developmental change and comes with significant challenges for adjustment ( Pharris-Ciurej et al., 2012). Pharris-Ciurej et al. (2012) found that ninth-grade failure was a significant predictor of students subsequently dropping out of high school. Bornsheuer and colleagues (2011) reported that students who were retained in ninth grade were 6 times more likely to delay graduation. Therefore, a higher percentage of students retained in ninth grade is an undesirable school-level academic outcome.

The continuum of options for students who obtain a diploma varies, and the school counselor's role is to contribute to preparing youth for a successful transition to career and life after high school. In the spectrum of options of postsecondary schooling, enrolling in an institution that grants a bachelor's degree may be viewed as the most rigorous. In previous research, school effects, such as high school infrastructure and college-going climate, were significant in predicting enrollment in a 4-year institution when controlling for student demographic characteristics ( Engberg & Wolniak, 2010; Roderick et al., 2011). Aspects of the school environment that support students' college readiness include high standards for academic performance, giving students a greater chance to gain access to a 4-year college, and completion of necessary coursework to gain admission ( Roderick et al., 2009). School counselors are responsible for creating and supporting a rigorous academic plan of study so that students have the most competitive options available for their postsecondary education ( Roderick et al., 2011).

Continuing to examine the relationship between school counselors' caseload and use of time in relation to academic outcomes is valuable in order to advocate for school counselors doing appropriate duties and to promote academic outcomes. Specifically, this study aims to answer the following three research questions: (1) What are school counselors' average caseloads? (2) How do school counselors spend their time? and (3) After controlling for school demographic variables, how do school counselors' caseloads and the ways they use their time relate to schools' academic outcomes?

Method

Data Source

This study used the High School Longitudinal Study of 2009 (HSLS:09) restricted-use school data. The HSLS:09 is an ongoing longitudinal study conducted by the National Center for Education Statistics ( NCES, 2014). In 2009, NCES employed a two-stage, stratified, random sampling design, first randomly sampling schools and then randomly sampling students within those schools. In this study, we examined only school-level data, resulting in a total of 944 high schools (including regular public schools, public charter schools, and private schools in all 50 states and DC) participating in the study. A lead school counselor or someone identified by the school as the most knowledgeable about the entering ninth-grade class completed the school counselor questionnaire. A knowledgeable staff person and the principal completed the administrator questionnaire.

Participants

From 944 schools that were included in the HSLS:09 data, a total of 852 school counselors participated in the data collection. Demographic information about the schools is presented in Table 1. We treated missing data in this study using multiple imputation (MI) method in SPSS. With MI, each missing value is replaced by several different values, consequently generating several different completed data sets ( Li et al., 2015) for which SPSS provides pooled results. This study provides pooled regression results.

Demographic Information of the Participating Schools in High School Longitudinal Study of 2009.

Measurements

The HSLS:09 includes a variable that asked the lead school counselor to provide the average caseload in their schools. This is a continuous variable.

A series of nine variables in the HSLS:09 asked the lead school counselor to report on the percentage of school counselors' time spent on the following activities: (a) high school course choice/scheduling, (b) college readiness/selection/application, (c) career planning, (d) personal/social/academic/career development, (e) job placement/job skill development, (f) school/personal problems, (g) academic testing, (h) noncounseling activities, and (i) other counseling activities. These variables are measured on a 5-point scale: 1 = 5% or less, 2 = 6%-10%, 3 = 11%-20%, 4 = 21%-50%, and 5 = more than 50%.

Because factors that contribute to diversity in schools are known to affect school academic outcomes, in this study, we controlled for schools' demographic characteristics such as region (e.g., South, Midwest), location (e.g., urban, suburban, rural), percentage of students in free and reduced meal (FARM) programs, and school type (e.g., public, private, religious).

We used three continuous variables from the HSLS:09 to measure schools' academic outcomes: (a) percentage of ninth graders repeating ninth grade; (b) percentage of student body enrolled in AP courses; and (c) percentage of 2008-2009 seniors who were enrolled in a 4-year bachelor's-granting institution.

Data Analysis Procedure

We obtained the license for restricted-use HSLS:09 data in 2014. All data were analyzed using SPSS v24. First, we conducted descriptive statistics and frequency analyses to get the basic information about the school demographic information and to answer the first two research questions. Then, to answer the third research question, we analyzed three hierarchical multiple regression models to examine the relationship between caseload, use of time, and school academic outcomes.

Three regression models were created with the three different school academic outcomes as dependent variables: ninth-grade retention, percentage of students enrolled in AP courses, and percentage of seniors who went to a 4-year college. In all three models, we entered schools' demographic variables at Stage 1 to control for the influence of schools' demographic characteristics on school academic outcomes. At Stage 2, we entered a set of variables related to school counselors' caseload and use of time, with the aforementioned demographic variables. This way of conducting regression analysis allows for gauging indirect effects in the models ( Trusty & Niles, 2003). That is, demographic variables likely have effects on school counselors' caseload and the way they spend their time, factors that, in turn, have effects on school academic outcomes.

When conducting the multiple regression analysis, we used a weight variable. NCES (2014) recommended using school-level weights when doing analysis with school-level data. Therefore, this study used W1SCHOOL, which is a school-level base-year weight variable available in the HSLS:09 data.

Results

Descriptive statistics results showed that the mean of caseloads for high school counselors was 268.62 with a standard deviation of 830.44. Approximately one quarter of the lead high school counselors reported their caseload to be equal to or less than 250, which is the student-to-school counselor ratio recommended by ASCA (2019b). Around 85% of high schools had a ratio equal to or less than 455:1, which is the national average reported by ASCA (2019b).

As shown in Table 2, the school counseling activities that took up the most time were (a) college counseling, (b) scheduling, and (c) personal/social/academic/career development, with each taking 11-20% of school counselors' time. Four activities each took 6-10% of school counselors' time: (a) school/personal problems, (b) career planning, (c) testing, and (d) other counseling activities. Less than 5% of school counselors' time was spent on (a) job placement/job skill development and (b) noncounseling activities.

Descriptive Statistics Results for School Counselors' Use of Time.

We analyzed three 2-stage regression models to answer this research question. Model 1 included "ninth-grade retention" as the dependent variable, Model 2 included "percentage of students enrolled in AP courses" as the dependent variable, and Model 3 included "percentage of seniors who went to a 4-year, bachelor's-granting institution" as the dependent variable. Results from the regression analyses are presented in Table 3.

Summary of Hierarchical Regression Analysis for Variables Predicting School Academic Outcomes.

In Model 1, the hierarchical regression analysis revealed that in Stage 1, the percentage of students in FARM, region, and location contributed significantly to the regression model, F(4, 636) = 44.92, p < .001, and accounted for 22% of the variance in ninth-grade retention. Introducing school counselors' caseload and use of time explained an additional 5.4% of the variances in ninth-grade retention. This change in R ² was statistically significant, F(10, 626) = 4.64, p < .001. After controlling for schools' demographic characteristics, the percentage of time counselors spent on other counseling activities and scheduling were both significantly positively predictive of ninth-grade retention, meaning that the more time school counselors spent on nontargeted counseling activities and scheduling, the higher the percentage of retained ninth graders in the school.

In Model 2, the hierarchical regression analysis revealed that in Stage 1, the percentage of students in FARM, location, region, and school type (public, catholic or other private) contributed significantly to the regression model, F(4, 641) = 42.27, p < .001, and accounted for 20.5% of the variance in the percentage of the student body enrolled in AP courses. Introducing the Stage 2 predictors of school counselors' caseload and use of time explained an additional 10.3% of the variances in the dependent variable. This change in R ² was statistically significant, F(10, 627) = 10.51, p < .001. After controlling for schools' demographic characteristics, three variables were positively significantly predictive of the percentage of students enrolled in AP courses: school counselors' caseload, percentage of hours counselors spent on college readiness/selection/application, and percentage of hours on school/personal problems. We found that the percentage of hours school counselors spent on career planning, job placement/job skill development, noncounseling activities, and course choice/scheduling were all negatively predictive of the dependent variable, meaning that in schools where counselors spent more time on these activities, fewer students were enrolled in AP courses.

In Model 3, the hierarchical regression analysis revealed that in Stage 1, the percentage of students in FARM and location contributed significantly to the regression model, F(4, 547) = 31.98, p < .001, and accounted for 18.5% of the variances in the percentage of seniors who were enrolled in 4-year universities. Introducing Stage 2 predictors explained an additional 25.5% of the variances in the dependent variable, and this change in R ² was significant, F(10, 533) = 25.75, p < .001. After controlling for schools' demographic characteristics, we found that the variables of counselors' caseload and amount of time spent on college readiness/selection/application were significantly positively predictive of the number of seniors going to 4-year universities. Counselors' time spent on course choice/scheduling, school/personal problems, noncounseling activities, and other counseling activities were found to be negatively predictive of the dependent variable. Therefore, the more time counselors spent on these activities, the smaller the number of seniors who were likely to go to 4-year universities.

Discussion

Contextualized within an evidence-based school counseling model, we focused on school-level academic outcomes and examined how school counselors' caseloads and use of time impacted school academic outcomes ( Dimmitt et al., 2007). We first explored the average of school counselors' caseloads in this large sample of 882 school counselors across the United States. We found that approximately 85% of the school counselors had a caseload of 455 or fewer students, with roughly one quarter of the school counselors reporting caseloads equal to or less than 250. These are slightly lower than the NACAC and ASCA (n.d.) report in which the average caseload was 482 and New Hampshire, Vermont, and Wyoming were the only states with caseloads at or below 250.

This is the first investigation that we know of that studied a national sample of school counselors to explore how school counselors use their time. In exploring the second research question, we found that school counselors reported spending the highest percentage of their time on counseling duties such as college counseling, academic advisement (scheduling), and personal/social/career development. This is encouraging and consistent with Foster et al. (2005). However, counselors reported still spending time on testing, which is not an appropriate duty, according to ASCA (n.d.). Chandler et al. (2018) argued that role confusion among school counselors themselves about counseling and noncounseling duties could be contributing to the continuation of school counselors' use of time on these tasks.

Our third research question explored how counselors' caseload and use of time related to school academic outcomes. In our first regression model, we explored how school counselor caseload and use of time was related to ninth-grade retention and found that in schools where counselors spent more time on scheduling and other counseling duties, students were more likely to be retained in ninth grade. These findings suggest that spending more time providing targeted direct and indirect counseling services is important for school counselors in schools where students are at higher risk to repeat ninth grade. Students who begin high school with greater risk of retention should be provided early identification and services ( Davoudzadeh et al., 2015) because of the multiple negative outcomes of grade retention ( Vandecandelaere et al., 2016).

These findings suggest that spending more time providing targeted direct and indirect counseling services is important for school counselors in schools where students are at higher risk to repeat ninth grade.

In our investigation of the relationship among caseload, use of time, and enrollment in AP courses, we found that the more time school counselors spent with students on career planning, job placement and skill development, and noncounseling activities, the less likely students were to enroll in AP courses. In contrast, the more time spent on college readiness/application and school/personal problems, the more likely students were to enroll in AP courses. This is not surprising because AP preparation is directly linked with college preparation. If school counselors spend more of their time on college-related activities and help enhance students' social/emotional wellness, their schools might have more students who are college-oriented. However, we encourage school counselors to consider other factors that could reduce barriers-for students and school counselors-to high academic outcomes. For example, in studying a sample of Latina/o students, Vela et al. (2013) found that students' expectations and their perceptions of support from their school counselors were predictive of AP enrollment.

The more time school counselors spent with students on career planning, job placement and skill development, and noncounseling activities, the less likely students were to enroll in AP courses. In contrast, the more time spent on college readiness/application and school/personal problems, the more likely students were to enroll in AP courses.

In the third regression model, we explored how school counselors' caseload and use of time related to the percentage of seniors who enrolled in a 4-year university. Counselors' caseload and time spent on the college application process were both positively predictive of students enrolling in a 4-year institution. Likewise, in schools where counselors spent more time on noncounseling activities, scheduling, and other counseling duties, students were less likely to enroll in 4-year universities. This demonstrates the positive effect on schools' college-going climate when school counselors use their time on college counseling. Although we anticipated that lower caseloads would be predictive of enrollment in 4-year colleges, the results from this study showed that counselors are still able to support students' college enrollment in spite of their large caseloads.

Limitations

This study has several limitations. First, in the HSLS:09 data set, head school counselors reported on behalf of entire school counseling departments, but much variability among counselors can exist within one school. The time use reported in this study is the head school counselors' estimation of how much time in general the school counselors in that school spend on the activities listed in the questionnaire. Second, this study did not control for whether or not the schools offer AP courses. Finally, AP enrollment alone is limited as a measure of academic achievement because enrollment does not necessarily mean performing well enough to get college credits or doing well on college admission tests ( Scott et al., 2010; Warne et al., 2015).

Conclusion

This study investigated school counselors' caseload, use of time, and how these factors related to school-level academic outcomes such as ninth-grade retention, AP enrollment, and 4-year college-going rates. The results showed that school counselors reported a much higher average caseload than ASCA recommends and that the ways school counselors spend their time has a significant impact on school-level academic outcomes. We recommend that school counselors be mindful of their time use and be strong advocates for themselves when they need to protect their time in order to best serve their students and support related academic outcomes.

Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

American School Counselor Association . (n.d.). Appropriate and inappropriate activities for school counselors. https://www.schoolcounselor.org/asca/media/asca/home/appropriate-activities-of-school-counselors.pdf
Google Scholar

American School Counselor Association . (2019a). ASCA National Model: A framework for school counseling programs (4th ed.). Author.
Google Scholar

Dimmitt, C., Carey, J. C., Hatch, T. (2007). Evidence-based school counseling: Making a difference with data-driven practices. Corwin Press.
Google Scholar

Roderick, M., Nagaoka, J., Coca, V. (2009). College readiness for all: The challenge for urban high schools. Future of Children, 19, 185-201. |
Google Scholar Crossref | Medline

Zyromski, B., Dimmitt, C., Mariani, M., Griffith, C. (2018). Evidence-based school counseling: Models for integrated practice and school counselor education. Professional School Counseling, 21. https://doi.org/10.1177/2156759X18801847
Google Scholar

Author Biographies

Qi Shi, PhD, is an associate professor with the School of Education at Loyola University Maryland in Timonium, MD. Email: [email protected]edu

Margaux H. Brown, PhD, is an assistant professor with the College of Education at Augusta University in Augusta, GA.

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School Counselors' Impact on School-Level Academic Outcomes: Caseload and Use of Time - Qi Shi, Margaux H. Brown, 2020

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Abstract Using the High School Longitudinal Study of 2009, we investigated school counselors' caseloads, how they spent their time, and the impact of those factors on schools' academic outcomes.

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Researching the Effectiveness of School Counseling Programs - Reflection

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Researching the Effectiveness of School Counseling Programs - Reflection

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Assess-peer reviewed article reflection (1)

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Use uploaded PowerPoint for reference

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Race IAT
Sexuality IAT

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Part 2: Implicit Bias Test Results Reflection

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Part 2: Implicit Bias Test Results Reflection

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School Counselor Competency Assessment - Reflection

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School Counselor Competency Assessment - Reflection

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Manage - School Counselor Competency Assessment

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Personal Philosophy of School Counseling

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Personal Philosophy of School Counseling

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Define - Personal Philosophy of School Counseling

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For students about microaggressions