AN EXAMINATION OF FACTORS THAT RELATE TO SCHOOL COUNSELORS' KNOWLEDGE AND SKILLS IN MULTI-TIERED SYSTEMS OF SUPPORT.
Research indicates that students in schools where comprehensive school counseling programs are implemented benefit academically and behaviorally (Dimmitt & Wilkerson, 2012; Lapan, Gysbers, & Petroski, 2001; Wilkerson, Perusse, & Hughes, 2013). Furthermore, according to the American School Counselor Association (ASCA), "school counselors are stakeholders in the development and implementation of multi-tiered systems of support (MTSS)" and "align their work with MTSS through the implementation of a comprehensive school counseling program" (2014a, p. 38). Research that addresses school counselors' involvement in MTSS is lacking. Given that more than 23,000 schools nationwide implement MTSS (pbis.org, 2016) and school counselors are specifically called to align their programs with MTSS (ASCA, 2014a), research is needed to understand school counselors' knowledge and skills in MTSS.
MULTI-TIERED SYSTEMS OF SUPPORT AND COMPREHENSIVE SCHOOL COUNSELING
The multi-tiered systems of support (MTSS) framework is an effective and efficient approach to improving students' academic and behavioral experience in schools (Sugai, Simonsen, Bradshaw, Horner, & Lewis, 2014). An MTSS framework is a "coherent continuum of evidence-based, system-wide practices to support a rapid response to academic and behavioral needs" (Kansas State Department of Education, 2013, p. 3). Two of the most widely used and familiar versions of MTSS in schools are Response to Intervention (RtI) and Positive Behavioral Interventions and Supports (PBIS). Research shows that schools implementing MTSS had higher scores on academic accountability measures (Marin & Filce, 2013; McIntosh, Sadler, & Brown, 2012), significantly reduced office discipline referrals and suspension rates (Benner, Nelson, Sanders, & Ralston, 2012), and improved perceptions of school safety among school staff and students (Horner et al., 2009). MTSS implementation can also improve outcomes for students who may otherwise go underserved (Betters-Bubon, Brunner, & Kansteiner, 2016; McIntosh, Girvan, Horner, Smolkowski, & Sugai, 2014).
A review of the literature regarding comprehensive school counseling programs and MTSS indicates that the frameworks have shared goals and beneficial outcomes for all students. However, research is limited and relatively few publications directly address the alignment of comprehensive programs and MTSS or school counselors' role in MTSS implementation. With that said, the growing quantity of research and literature indicates that when school counselors align comprehensive school counseling programs with MTSS, students benefit in important ways (Betters-Bubon & Donohue, 2016; Campbell, Rodriguez, Anderson, & Barnes, 2013; Curtis, Van Horne, Robertson, & Karvonen, 2010; Smith, Evans-McCleon, Urbanski, & Justice, 2015). Furthermore, literature addressing comprehensive program and MTSS alignment shows practical implications for school counselors. Research demonstrates that when school counselors take leadership roles in MTSS implementation, their efforts contribute to improved MTSS implementation and increased use of student data to set school-wide goals (Cressey, Whitcomb, McGilvray-Rivet, Morrison, & Shander-Reynolds, 2014); reduced disproportionality (Cressey et al., 2014; Harrington, Griffith, Gray, & Greenspan, 2016); and improved systems for teaching, reinforcing, and monitoring expected student behavior (Goodman-Scott, 2014).
Obtaining MTSS knowledge and skills is challenging and has been widely explored in the MTSS literature (Bambara, Goh, Kern, & Caskie, 2012; Dulaney, Hallam, & Wall, 2013; Harlacher & Siler, 2011; Lohrmann, Martin, & Patil, 2013; Marrs & Little, 2014). However, aligning comprehensive school counseling programs and MTSS shows promise in expanding the reach of school counselors and improving student outcomes (Chitiyo & Wheeler, 2009; Cressey et al., 2014; Eagle, Dowd-Eagle, Snyder, & Holtzman, 2015). The current study examined how time spent on ASCA-aligned activities, the challenges to obtaining MTSS knowledge and skills, the school level, the school setting, and the extent of MTSS training relate to school counselors' MTSS knowledge and skills. Informed by extant literature on comprehensive programs and MTSS, the authors hypothesized that more time spent on ASCA-aligned activities would relate to more knowledge and skills in MTSS. Furthermore, the authors expected that having fewer challenges would relate to more MTSS knowledge and skills. In terms of school level, authors hypothesized that school counselors in elementary schools would have more MTSS knowledge and skills than counselors in secondary schools, and that school setting would have a direct relationship with MTSS knowledge and skills. With regard to MTSS training, the authors expected that more extensive training would relate to more knowledge and skills in MTSS. Finally, in an alternative model, the authors hypothesized that time spent on ASCA-aligned activities would mediate the relationship between school counselors' MTSS knowledge and skills and challenges, school level, school setting, and extent of MTSS training.
The researchers invited 15,106 practicing elementary, middle, secondary, or K-12 school counselors who were members of the American School Counselor Association (ASCA) to participate in the study. A total of 4,598 individuals responded to the survey, resulting in a response rate of 30%. Respondents (n = 532) who only completed a few items on the survey were excluded from all analyses, resulting in a total sample size of 4,066. Overall, demographic data indicated that the majority of participants were female (87%), and between the ages of 31 and 40 (33%) or 41 and 60 (41%). The majority of participants also self-identified their race as Caucasian (84%). Participants were predominately certified as a school counselor for 1 to 3 years (34%) or 4 to 8 years (25%), worked in schools with 500 to 1,000 students (40%), and reported student caseloads of 251 to 500 students (54%). Participants most frequently reported that 25% to 50% of students in their school were eligible for free or reduced-price lunch and a majority of participants considered their school to be racially or ethnically diverse (54%). Most participants reported working at the high school level (37%) and in suburban school settings (45%). Participants were from varying regions across the United States.
After receiving permission from the institutional review board, researchers used SurveyShare, an Internet-based survey system, to disseminate the survey and demographic questionnaire. They sent an initial email with an introductory letter explaining the purpose of the study and providing an online link for participation to all K-12th grade school counselors listed as professional members in the ASCA online directory. When participants clicked on the link, an informed consent form appeared immediately on the SurveyShare website. The form asked participants to enter an email address; a SurveyShare setting was used to disassociate the address from an individual's responses. To encourage participation, respondents who completed the online surveys were also entered into a random drawing using disassociated email addresses (Dillman, Smyth, & Christian, 2014). After viewing the informed consent form and agreeing to participate in the study, participants were directed to the survey and demographic questionnaire, which took approximately 10 to 15 minutes to complete. One week after sending the initial email, the researchers sent a follow-up email with the online link to the surveys to all recipients who did not complete the surveys. Researchers closed the link after 3 weeks and downloaded all data to the Statistical Package for Social Sciences (SPSS) software.
School Counseling Program Implementation Survey. Originally developed by Eisner and Carey (2005), the School Counseling Program Implementation Survey (SCPIS) was adapted by Clemens, Carey, & Harrington (2010b) to research ASCA National Model (2012a) implementation and assess school counseling programs. Clemens et al. (2010b) conducted an exploratory factor analysis of the SCPIS (Eisner & Carey, 2005) using the principal axis factor method and oblique rotation. The sample used for that analysis included 341 school counselors. The Kaiser-Meyer-Olkin measure of sampling adequacy was .89 and the Bartlett's test was significant at p < .001 (Clemens et al., 2010b). The exploratory factor analysis results led to the current version of the SCPIS, a 17-item, self-report survey using a four-point Likert scale to measure the extent to which a school counselor has implemented the ASCA National Model (2012) for comprehensive school counseling programs (Clemens, Carey, & Harrington, 2010a; Clemens et al., 2010b). Items of the SCPIS are divided into three subscales: (a) Programmatic Orientation (seven items; Cronbach's alpha reliability coefficient .79), (b) Use of Computer Software and Data (three items; Cronbach's alpha reliability coefficient .78), and (c) School Counseling Services (seven items; Cronbach's alpha reliability coefficient .81; Clemens et al., 2010b).
For each item, participants selected one of four responses to indicate the extent to which essential characteristics of the ASCA National Model (2012) are implemented in their school counseling program. Ratings were:
1 = Not Present, 2 = Development in Progress, 3 = Partly Implemented, and 4 = Fully Implemented. Because one purpose of the present study was to examine how time spent on ASCA-aligned activities influences school counselors' MTSS knowledge and skills, the language of the SCPIS ratings was adapted with the authors' permission to measure the frequency with which school counselors participate in ASCA-aligned activities. Adapted ratings to assess frequency of ASCA-aligned activities were: 1 = I never do this, 2 = I rarely do this, 3 = I occasionally do this, and 4 = I frequently do this.
School Counselor Knowledge and Skills Survey. In developing the Teacher Knowledge and Skills Survey (TKSS), Blum & Cheney (2009) included a small number of school counselors in their sample. However, the language in the TKSS was not designed specifically for school counselors; therefore, the authors of the present study adapted the TKSS in collaboration with its authors to develop the School Counselor Knowledge and Skills Survey for Multi-Tiered Systems of Support (SCKSS; Olsen, Blum, & Cheney, 2016).
The TKSS is a 33-item, self-report survey using a 5-point Likert scale to measure teachers' knowledge and skills related to Positive Behavior Supports. The items on the TKSS incorporate evidence-based knowledge, skills, and practices aligned with the multi-tiered Positive Behavior Support framework implemented in schools. Items on the TKSS are divided into five subscales: (a) Specialized Behavior Supports and Practices, (b) Targeted Intervention Supports and Practices, (c) School-wide PBS Practices, (d) Individualized Curriculum Supports and Practices, and (e) Positive Classroom Supports and Practices (Blum & Cheney, 2009).
Reliability coefficients for the five subscales that make up the TKSS are: .86 for the Specialized Behavior Supports and Practices subscale, .87 for the Targeted Intervention Supports and Practices subscale, .86 for the School-wide PBS Practices subscale, .84 for the Individualized Curriculum Supports and Practices subscale, and .82 for the Positive Classroom Supports and Practices subscale (Blum & Cheney, 2009). The total reliability coefficient for all items on the total test score is .96 (Blum & Cheney, 2009).
Adapting the SCKSS from the TKSS reflected updated terminology and enabled the researchers to use it more effectively with school counselors. The term Positive Behavior Supports (PBS) was changed to multi-tiered systems of support (MTSS) in the title, in the written directions, and for individual items. This adaptation reflects the recent use of the term multi-tiered systems of support (MTSS) in the literature to refer to all multi-tiered systems of academic and behavioral support, of which the Positive Behavior Supports (PBS) framework is one type (Sugai & Horner, 2009). The term teacher was changed to school counselor in the title and in the written directions to make the survey more relevant for school counselors who will be responding to the SCKSS. The final adaptation of the TKSS for the version of the SCKSS used for this study involves the adaptation of item 6 from "I know how to access and use our school's counseling programs" to "I know how to provide access and implement our school's counseling programs." The authors made this change because respondents to the SCKSS are school counselors and, therefore, would provide access to and implement the school's counseling programs instead of accessing and using the programs as a teacher would. No other adaptations of the TKSS were made to develop the version of the SCKSS used for this study.
Demographic questionnaire. The authors developed a 13-item, self-report demographic questionnaire to gather data on participants' gender, age, ethnicity, experience, size of school, size of student caseload, percentage of students in school eligible for free or reduced-price lunch, student diversity, and school regional location. Additional items assessed the independent variables of school level (i.e., elementary, middle/junior high, high school, K-8, K-12), school setting (i.e., rural, suburban, urban), extent of MTSS training (i.e., no training, low, medium, high), and challenges (i.e. training, administrative support, time, staff buy-in).
Design, Data Screening, and Analysis
The researchers used a nonexperimental survey research design to address the research question: How is time spent on ASCA-aligned activities related to level of MTSS knowledge and skills, and what are the impacts of challenges, school level, school setting, and extent of MTSS training? The researchers tested multiple conceptual models. The first model examined the direct relationship between MTSS knowledge and skills and all other variables. The second model examined the partial mediation effects of time spent on ASCA-aligned activities between MTSS knowledge and skills and all other variables. The final model tested the total mediation effects of time spent on ASCA-aligned activities between MTSS knowledge and skills and all other variables.
Prior to statistical analyses, the researchers screened the data using SPSS software to examine outliers, missing values, normality, and multicollinearity. They also addressed assumptions related to SEM. Missing data analyses suggested that 3% of respondents did not respond to the training question. Results of Little's missing completely at random test (MCAR: [chi square] = 108.47, df = 101, p=.29) suggested that the data could be treated as MCAR. Multiple imputation was used to estimate missing values.
An analysis of outlier data was conducted using box plots and Mahalanobis's distance. Results suggested all values were within acceptable ranges given the diversity of the population. Researchers assessed normality using kurtosis coefficients, skewness coefficients, and visual inspection of the data distributions, and results suggested univariate normality was tenable. To assess the data for multicollinearity, researchers examined bivariate correlations and variance inflation factors and found no evidence of multicollinearity.
To address the research question, the authors conducted structural equation modeling (SEM) analyses using maximum-likelihood estimation within MPLUS 7.11 (Muthen & Muthen, 2011). They performed the analyses in two phases, a measurement phase and a structural phase. In the measurement phase, they imposed a confirmatory factor analysis (CFA) model where all latent variables were allowed to covary. This allowed an examination of the potential misspecification of the measurement model before examining the structural relationships. For the measurement model, they allowed into the model only additions of residual covariances that made sense theoretically and were substantial enough that overfitting was not occurring (Byrne, 1994).
For the structural phase of the analyses, an initial model tested a direct relationship of all observe variables and the ASCA latent variable to the MTSS latent variable. Next, researchers tested a partial mediation model by allowing paths from the covarying observed variables (i.e., challenges and demographic variables) to the latent variable of ASCA, from observed variables to MTSS, and ASCA to MTSS. They used bootstrapping to estimate standard errors for the indirect effects and examined a full mediation model by fixing the direct paths between the observed variables and MTSS to 0.0.
To examine the goodness of fit of the model, the researchers used multiple fit indices. Comparative fit index (CFI; Bentler, 1990) assesses the theoretical model relative to a null model positing complete variable independence. CFI values close to .95 suggest satisfactory data model fit (Hu & Bentler, 1999). The second fit index used in this study was the standardized root-mean-squared residual (SRMR) and is an average of all standardized residual covariances. Hu and Bentler (1999) suggested SRMR values close to .08 were indicative of an acceptable fit. Steiger and Lind's (1980) root-mean-square error of approximation (RMSEA) reflects both the fit and parsimony of the model being tested. Hu and Bentler (1999) recommended values close to .06 for RMSEA. Due to the large sample in the present study, the authors expected the [chi square] values to be statistically significant in all analyses and are deemphasized in the discussion of results. The sample size was large enough to divide into two subsamples and cross-validate results. One subsample of the data was used to initially test the model (N = 2,033) and the second half of the data (N = 2,033) was used to verify the results.
The research question guiding this study examined the relationships among the observed variables of challenges (training, administrative support, time, staff buy-in), school level (elementary, middle/ high schools, and other organization structures such as K-8 and K-12), school setting (rural, urban, and suburban), and MTSS training (no training, low, medium, high). ASCA and MTSS were latent variables in the model. The original sample was divided in half, with the second half used to cross-validate the findings from the initial estimations.
The authors generated descriptive statistics to summarize the variables used in this study. Participants (N = 4,066) completed items on the School Counseling Program Implementation Survey (SCPIS) to determine time spent on ASCA-aligned activities. Table 1 presents the means and standard deviations for subscales on the SCPIS and the School Counselors Knowledge and Skills Survey (SCKSS). For the SCPIS subscales (i.e., Programmatic Orientation, Use of Computer Software and Data, and School Counseling Services), all means were above 3 (3 = occasionally and 4 = frequently), suggesting that most respondents are at least occasionally performing each of the functions. The percentage of respondents who reported at least occasionally performing each of the functions were (a) 60% for Program Orientation, (b) 78% for Use of Computer Software and Data, and (c) 84% for School Counseling Services.
Participants also completed items on the SCKSS, for which all means were above 3 (i.e., moderate) and below 4 (i.e., strong), suggesting that on average respondents rated their knowledge, skill level, or awareness at least moderate in all areas. The percentage of respondents who reported at least moderate knowledge, skills, or awareness for each subscale were (a) 83% for Specialized Behavior, (b) 84% for Targeted Intervention, (c) 84% for School-Wide, (d) 72% for Individualized Curriculum, and (e) 86% for Positive Classroom.
Finally, on the demographic questionnaire, participants completed one item to measure challenges to obtaining the knowledge and skills needed to implement MTSS and one item to measure their extent of MTSS training. For challenges, all means were above 2 (i.e., need some more of) and below 3 (i.e., need a lot more of) suggesting that on average respondents reported needing at least some additional MTSS training, administrative support, time, and staff buy-in. For extent of MTSS training, the mean was above 2 (i.e., low training) and below 3 (medium training), suggesting that on average respondents reported having at least a low level of MTSS training.
Prior to testing the structural model, researchers tested the measurement model using confirmatory factor analysis (CFA). As described previously, the school counselors' knowledge and skills of MTSS construct had five measured indicators: Specialized Behavior Supports and Practice (SB), Targeted Intervention (TI), School-Wide Supports and Practices (SW), Individualized Curriculum (IC), and Positive Classroom (PC). The time on ASCA-aligned activities factor had as its indicators time spent on (a) Programmatic Orientation (PO), (b) Use of Computer Software and Data (CS), and (c) School Counseling Services (SER). The fit of the initial CFA model suggested that the measurement model was an acceptable fit, [chi square] = 162.650, df = 19, p < .001, CFI = .989, SRMR = .028, RMSEA = .059 (90% CI = .059, .067). All path coefficients were statistically significant at the .001 level. The verification sample results were almost identical to the initial data model fit indices results, [chi square] = 132.663, df = 19, p < .001, CFI = .991, SRMR = .021, RMSEA = .052 (90% CI = .044, .061). No modifications were used to improve the overall data model fit.
Model 1 (no mediation). The initial structural model tested specified that MTSS was influenced by ASCA-aligned activities and the observed variables of challenges, school level (elementary, middle/high schools, and other organization structures such as K-8 and K-12), school setting (rural, urban, and suburban), and MTSS training (no training, low, medium, high). The first theoretical model was tested and was determined to be a moderate fit to the data, [chi square] = 956.538, df = 19, p < .001, CFI = .935, SRMR = .073, RMSEA = .071 (90% CI = .067, .075). Several of the paths were not statistically significant, including CHAD (need more administration support) CHTI (need more time), CHBU (need more staff buy-in), OTHER (K-8 or K-12 compared to elementary school configuration), RURAL (rural location compared to suburban location). Both SECOND (middle/high schools compared to elementary schools) and URBAN (urban setting compared to suburban location) were statistically significant. For the verification sample, the model fit indices were similar to the initial results, which suggested a moderate fit to the data. The only difference was that URBAN was not statistically significant, where the initial estimates suggested statistical significance. These variables need to have a relationship with MTSS; therefore, they were excluded when testing for partial and total mediation.
Model 2 (partial mediation). The second theoretical model, which examined partial mediation, suggested a reasonable fit to the model, [chi square] = 484.711, df = 43, p < .001, CFI = .967, SRMR = .032, RM-SEA = .069 (90% CI = .063, .074). The results of the verification sample obtained similar fit indices as the initial estimates. For the initial model, all path coefficients were statistically significant, both direct and indirect paths, but the verification sample estimates suggested that the path coefficients between SECOND and ASCA were not statistically significant, suggesting that ASCA does not mediate the relationship between SECOND and MTSS.
Model 3 (total mediation). The total mediation model results, which included only indirect paths between the exogenous variables and MTSS with ASCA serving as the mediator, suggested that the model had a reasonable data model fit, [chi square] = 624.618, df = 47, p < .001, CFI = .957, SRMR = .060, RMSEA = .075 (90% CI = .070 to .081). The verification sample had similar fit indices values.
Recommended model. Because the partial mediation model was significantly better than the total mediation model, [[chi square].sub.diff] (4) = 139.905, p < .001, the suggested best model is shown in Figure 1. Table 2 shows standardized path coefficients and the sum of indirect effects (based on bootstrapping). The variance accounted for MTSS was .340 and for ASCA was .134.
The standardized path coefficient between MTSS and ASCA (.452) suggests time spent on ASCA-aligned activities has a strong, positive effect on MTSS knowledge and skills. The direct path between MTSS and TRAIN (.146) was also positive, indicating that increased MTSS training resulted in greater MTSS knowledge and skills. The direct paths between MTSS and CHTR (-.115) and SECOND (-.066) were negative, suggesting school counselors who reported needing more training and school counselors in secondary schools (compared to those in elementary schools) tended to have lower levels of MTSS knowledge and skills.
The indirect paths between ASCA and TRAIN (.299) and CHTR (-.105) had similar coefficient values as those reported with MTSS, but SECOND had a positive path coefficient (.071). School counselors with greater MTSS training tended to have greater time spent on ASCA-aligned activities, whereas school counselors who reported needing more MTSS training had less time spent on ASCA-aligned activities. Of particular interest, school counselors in secondary schools had greater time spent on ASCA-aligned activities, which suggests secondary school counselors spending more time on ASCA-aligned activities would have a positive impact on MTSS knowledge and skills.
Summary of Results
The results (see Table 2) demonstrate that time spent on ASCA-aligned activities can affect the relationship between MTSS knowledge and skills and challenges, school level, and MTSS training. Data showed moderate to strong relationships between MTSS knowledge and skills and (a) school counselors report of needing more MTSS training, (b) school level (secondary have less knowledge and skills of MTSS than elementary), and (c) extent of training in MTSS. When considering the time spent on ASCA-aligned activities, these relationships decreased (or were partially mediated). Time spent on ASCA-aligned activities can reduce some of the challenges to obtaining the knowledge and skill needed to implement MTSS.
The purpose of this study was to examine how time spent on ASCA-aligned activities, challenges, school level, school setting, and extent of MTSS training relate to school counselors' MTSS knowledge and skills. Results of the analysis show that time spent on ASCA-aligned activities is directly related to school counselors' knowledge and skills in MTSS. Specifically, more time spent on ASCA-aligned activities predicted more MTSS knowledge and skills. Researchers describing school counselors' involvement in MTSS implementation have reported that school counselors' time allocation does not change (Cressey et al., 2014). Researchers also propose that comprehensive school counseling programs and the MTSS framework align along key features (Ziomek-Daigle, Goodman-Scott, Cavin, & Donohue, 2016); and that comprehensive program and MTSS alignment can actually lead to more efficient use of school counselors' time (Goodman-Scott, 2014; Goodman-Scott, Betters-Bubon, & Donohue, 2016) and an increased capacity for leadership (Betters-Bubon & Donohue, 2016). The results of the current study confirm that a beneficial relationship exists between ASCA-aligned activities and MTSS. Furthermore, the results add to previous research highlighting the positive effects of school counselor participation in ASCA-aligned activities, including school counselor job satisfaction (Cervoni & DeLucia-Waack, 2011; Pyne, 2011) and promising student outcomes such as improved attendance, fewer suspensions, and fewer reports of bullying (Dimmitt & Wilkerson, 2012).
In terms of challenges, results indicate that school counselors who expressed needing more MTSS training had lower levels of MTSS knowledge and skills. This finding addresses previous research calling for a clearer understanding of the challenges school counselors face in obtaining MTSS knowledge and skills (Chitiyo & Wheeler, 2009; Cressey et al., 2014; Eagle et al., 2015). Results also indicate that school counselors who expressed needing more MTSS training spent less time on ASCA-aligned activities. Taken together, these findings highlight challenges school counselors face, as well as the impact of MTSS training on school counselors' knowledge and skills in MTSS.
The analysis points to interesting findings related to school level, particularly for secondary school counselors. Compared to elementary school counselors, secondary school counselors had lower levels of MTSS knowledge and skills. This finding makes sense in light of previous research showing that more schools at the elementary level implement MTSS compared to middle and high schools (Freeman et al., 2015). However, results also indicate that when time spent on ASCA-aligned activities was considered (i.e., as a mediating variable), secondary school counselors spent more time on ASCA-aligned activities and in turn had more MTSS knowledge and skills compared to elementary school counselors. In other words, secondary school counselors who spent more time on ASCA-aligned activities had increased knowledge and skills in MTSS. This finding suggests the benefits of following updated ASCA guidelines recommending school counselors at all levels spend approximately 80% or more of their time with direct and indirect services for students and the remaining time with program planning and school support (ASCA, 2012). This finding also contributes to recent research emphasizing the need for secondary school counselors to spend time on ASCA-aligned activities that address the increasing academic (Vega, Moore, & Miranda, 2015), social/emotional (Kann et al., 2014; McCotter & Cohen, 2013), and career development (National Center for Educational Statistics, 2013; Poynton, Lapan, & Marcotte, 2015) demands of today's secondary students. These continued efforts to spend more time on ASCA-aligned activities and less time on non-school counseling activities may also benefit secondary school counselors in terms of increased MTSS knowledge and skills. Similar to increased time on ASCA-aligned activities, increased knowledge and skills in MTSS are needed at the secondary level for school counselors to contribute to practices such as data-driven decision making, coordination of academic and behavioral interventions, and professional development aimed at meeting students' complex needs in secondary schools (Dulaney, 2013).
MTSS training was related to school counselors' MTSS knowledge and skills in that more training increased school counselors' knowledge and skills in MTSS. More MTSS training was also associated with more time spent on ASCA-aligned activities. These findings support previous research emphasizing the importance of ongoing training to provide school counselors and other educators with the knowledge and skills needed to effectively implement MTSS (Feuerborn & Tyre, 2012; Freeman et al., 2015), and the benefits of MTSS training on the development of school counselors' MTSS knowledge and skills (Cavanaugh & Swan, 2015; GoodmanScott et al., 2016). In addition, these findings are potentially significant considering previous research suggesting that MTSS training increases school counselors capacity to meet the needs of all students (Betters-Bubon & Donohue, 2016) and is critical to sustained MTSS implementation over time (Gravois & Rosenfield, 2005; Mathews, McIntosh, Frank, & May, 2014; Pinkelman, McIntosh, Rasplica, Berg, & Strickland-Cohen, 2015).
This study establishes an empirical foundation regarding school counselors' MTSS knowledge and skills and the factors that relate to school counselors' knowledge and skills in MTSS.
The survey responses used for this study were self-reported; therefore, participants may have responded in socially desirable ways. For example, participants may have responded to survey items measuring how they spend their time in ways they felt were most acceptable. Participants also may have responded to items measuring their MTSS knowledge and skill in ways that portray them as knowledgeable and skillful.
The generalizability of the results of this study is limited to ASCA members. ASCA members may be more likely participate in research and may respond to survey items differently than school counselors who are not ASCA members. Finally, the lack of participant diversity in terms of gender and race is a limitation. Participants in this study were primarily female and Caucasian. However, these numbers are reflective of the lack of diversity among school counselors in today's schools, given that 78% of school counselors are female and 77% identify as White (Bruce & Bridgeland, 2012).
Implications for Research and Improvement of Practice
Future research should expand the examination of school counselors' MTSS knowledge and skills to state- or district-level samples that include all school counselors regardless of ASCA membership status. In light of the results of this study, future research should also focus on developing strategies to overcome the challenges school counselors face in obtaining MTSS-related training. After strategies to overcome challenges are established, research could measure school counselors' knowledge and skills in MTSS to determine the most effective training strategies and the impact of training on school counselors' MTSS knowledge and skills. Finally, future research should assess the impact of comprehensive program and MTSS framework alignment to reveal components of that alignment that are particularly beneficial for all students or components of MTSS that particularly enhance comprehensive school counseling programs.
Results of this study establish an understanding of the factors that relate to school counselors' MTSS knowledge and skills. These findings have implications for school counselor training programs and counselor educators, and for practicing school counselors. Specifically, findings indicate that (a) MTSS training is related to increased MTSS knowledge and skills, and (b) school counselors who reported needing more MTSS training had lower levels of MTSS knowledge and skills. These results add to literature that shows MTSS training benefits school counselors in many ways (Betters-Bubon & Donohue, 2016; Cavanaugh & Swan, 2015). However, the extent to which MTSS training is integrated into school counselor training programs is unclear. Given that school counselors are introduced to comprehensive school counseling programs and the ASCA National Model (2012) during their training programs, it is logical for school counselors to also be introduced to the MTSS framework during training programs. Systematically integrating the principles and practices of MTSS into school counseling training programs would provide school counselors-in-training with a strong foundation of knowledge and skills to bring into the field, rather than waiting to begin developing MTSS competencies through professional development opportunities after graduation. School counselors-in-training would also be better equipped to work in today's K-12 schools and enter the field ready to collaborate with the many educators already implementing MTSS across the country. This implication is echoed by researchers in the field who call for MTSS training to be systematically integrated into school counseling training programs and offer concrete strategies for doing so (see Sink, 2016).
The results of this study also have implications for counselor educators. To incorporate MTSS principles and practices into school counselor training programs, counselor educators must have a proficient knowledge and skill base in MTSS. For counselor educators not experienced in MTSS, national, state, and local professional development opportunities are available. Collaboration among counselor educators and between counselor educators and professionals in other disciplines (e.g., special education, educational leadership, school psychology, teacher education) can be a way to share resources and teaching strategies, and develop research opportunities.
The results of this study also have implications for practicing school counselors. School counselors reported challenges related to obtaining MTSS training, and this challenge significantly affected knowledge and skills of MTSS. This finding indicates a need for assessing and targeting the MTSS training needs of school counselors to enable them to better develop knowledge and skills in MTSS. School counselors can assess the context-specific challenges related to MTSS training they face at the building, district, or state level to focus advocacy efforts and resources to reduce challenges. The results of this study may also inform district- and state-level professional development planning. To increase MTSS knowledge and skills, school counselors and leaders may seek out collaboration from experienced implementers and model school sites, and participate in ongoing training at the national, state, and local levels. The impact of training on knowledge and skill development, quality of comprehensive school counseling program and MTSS implementation, and relevant student outcomes can then be measured.
Students in today's schools have diverse academic and behavioral needs (Lopez & Bursztyn, 2013; Vincent et al., 2011), and comprehensive school counseling program and MTSS implementation play a critical role in meeting these needs (Lapan, 2012; Wilkerson et al., 2013). This study adds to the growing literature examining the alignment of comprehensive programs and MTSS and extends the knowledge base by providing an empirical examination of school counselors' MTSS knowledge and skills. Results of this study can guide counselor educators, school leaders, and practicing school counselors in assessing school counselors' MTSS knowledge and skills and determining action plans to improve knowledge and skills. The alignment of comprehensive school counseling programs and the ASCA National Model (2012) with MTSS can benefit school counselors and, most important, the students in K-12 schools.
Jacob Olsen, Ph.D., is an assistant professor in the Department of Advanced Studies in Education and Counseling at California State University Long Beach. E-mail: email@example.com Sejal Parikh-Foxx, Ph.D., is an associate professor with the Department of Counseling at the University of North Carolina at Charlotte. Claudia Flowers, Ph.D., and Bob Algozzine, Ph.D., are professors with the Department of Educational Leadership, also at the University of North Carolina at Charlotte.
American School Counselor Association. (2012). ASCA National Model: A framework for school counseling programs (3rd ed.). Alexandria, VA: Author.
American School Counselor Association. (2014a). The professional school counselor and multi-tiered systems of support (Position statement). Retrieved from http://www.schoolcounselor.org/ asca/media/asca/PositionStatements/ PositionStatements.pdf
American School Counselor Association. (2014b). The role of the professional school counselor. Alexandria, VA: Author. Retrieved from http://www. schoolcounselor.org/asca/media/asca/ home/RoleStatement.pdf
Bambara, L., Goh, A., Kern, L., & Caskie, G. (2012). Perceived barriers and enablers to implementing individualized positive behavior interventions and supports in school settings. Journal of Positive Behavior Interventions, 14, 228-240. doi:10.1177/10983000712437219
Belser, C. T., Shillingford, M. A., & Joe, J. R. (2016). The ASCA Model and a multi-tiered system of supports: A framework to support students of color with problem behavior. The Professional Counselor, 6(3), 251-262. doi:10.15241/cb.6.3.251
Benner, G. J., Kutash, K., Nelson, J. R., & Fisher, M. B. (2013). Closing the achievement gap of youth with emotional and behavioral disorders through multi-tiered systems of support. Education & Treatment of Children, 36(3), 15-29. doi:10.1353/etc.2013.0018
Benner, G. J., Nelson, J. R., Sanders, E. A., & Ralston, N. C. (2012). Behavior intervention for students with externalizing behavior problems: Primary-level standard protocol. Exceptional Children, 78, 181-198.
Bentler, P.M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246.
Betters-Bubon, J., Brunner, T., & Kansteiner, A. (2016). Success for all? The role of the school counselor in creating and sustaining culturally responsive positive behavior intervention and supports programs. The Professional Counselor, 6, 263-277. doi:10.15241/jbb.6.3.263
Betters-Bubon, J., & Donohue, P. (2016). Professional capacity building for school counselors through school-wide positive behavior interventions and supports implementation. Journal of School Counseling, 14(3). Retrieved from http://jsc.montana.edu/articles/ v14n3.pdf
Blum, C., & Cheney, D. (2009). The validity and reliability of the Teachers Knowledge and Skills Survey for positive behavior support. Teacher Education and Special Education, 32(3), 239-256. Retrieved from http://journals. sagepub.com/doi/ pdf/10.1177/0888406409340013
Bruce, M., & Bridgeland, J. (2012). 2012 National survey of school counselors--The true north: Charting the course to college and career readiness. Retrieved from https://secure-media.collegeboard. org/digitalServices/pdf/nosca/true-north.pdf
Byrne, B. M. (1994). Structural equation modeling with EQS and EQS/Windows. Thousand Oaks, CA: Sage Publications.
Campbell, A., Rodriguez, B. J., Anderson, C., & Barnes, A. (2013). Effects of a tier 2 intervention on classroom disruptive behavior and academic engagement. Journal of Curriculum & Instruction, 7(1), 32-54. doi:10.3776/joci.2013.v7n1p32-54
Cavanaugh, B., & Swan, M. (2015). Building SWPBIS capacity in rural schools through building-based coaching: Early findings from a district-based model. Rural Special Education Quarterly, 34(4), 29-39. doi:10.1177/875687051503400404
Cervoni, A., & DeLucia-Waack, J. (2011). Role conflict and ambiguity as predictors of job satisfaction in high school counselors. Journal of School Counseling, 9(1). Retrieved from http:// files.eric.ed.gov/fulltext/EJ914271.pdf
Chitiyo, M., & Wheeler, J. (2009). Challenges faced by school teachers in implementing positive behavior support in their school systems. Remedial and Special Education, 30(1), 58-63. doi:10.1177/0741932508315049
Clemens, E. V., Carey, J. C., & Harrington, K. M. (2010a). The school counseling program implementation survey. Unpublished assessment instrument.
Clemens, E. V., Carey, J. C., & Harrington, K. M. (2010b). The school counseling program implementation survey: Initial instrument development and exploratory factor analysis. Professional School Counseling, 14, 125-134. doi:10.5330/prsc.14.2.k811174041n40l11
Cressey, J. M., Whitcomb, S. A., McGilvray-Rivet, S. J., Morrison, R. J., & Shander-Reynolds, K. J. (2014). Handling PBIS with care: Scaling up to school-wide implementation. Professional School Counseling, 18, 90-99. doi:10.5330/prsc.18.1.g1307kql2457q668
Curtis, R., Van Horne, J. W., Robertson, P., & Karvonen, M. (2010). Outcomes of a school-wide positive behavioral support program. Professional School Counseling, 13, 159-164. doi:10.5330/PSC.n.2010-13.159
Dillman, D.A., Smyth, J. D., & Christian, L. M. (2014.) Internet, phone, mail, and mixed-mode surveys: The tailored design method. Hoboken, NJ: John Wiley & Sons.
Dimmitt, C., & Wilkerson, B. (2012). Comprehensive school counseling in Rhode Island: Access to services and student outcomes. Professional School Counseling, 16, 125-135. doi:10.5330/PSC.n.2012-16.125
Dulaney, S. K. (2013). A middle school's response-to-intervention journey: Building systematic processes of facilitation, collaboration, and implementation. NAASP Bulletin, 97(1), 53-77. doi:10.1177/0192636512469289
Dulaney, S. K., Hallam, P. R., & Wall, G. (2013). Superintendent perceptions of multi-tiered systems of support (MTSS): Obstacles and opportunities for school system reform. AASA Journal of Scholarship & Practice, 10(2), 30-45.
Eagle, J. W., Dowd-Eagle, S. E., Snyder, A., & Holtzman, E. G. (2015). Implementing a multi-tiered system of support (MTSS): Collaboration between school psychologists and administrators to promote systems-level change. Journal of Educational & Psychological Consultation, 25, 160-177. doi:10.1080/10474412.2014.929960
Eisner, D., & Carey, J. (2005). School counseling program implementation survey. Unpublished assessment instrument.
Feuerborn, L. L., & Tyre, A. D. (2012). Establishing positive discipline policies in an urban elementary school. Contemporary School Psychology, 16(1), 47-58. doi:10.1007/BF03340975
Freeman, J., Simonsen, B., McCoach, D. B., Sugai, G., Lombardi, A., & Horner, R. (2015). Relationship between schoolwide positive behavior interventions and supports and academic, attendance, and behavior outcomes in high schools. Journal of Positive Behavior Interventions, 18(1), 1-11. doi:10.1177/1098300715580992
Goodman-Scott, E. (2014). Maximizing school counselors' efforts by implementing school-wide positive behavioral interventions and supports: A case study from the field. Professional School Counseling 17, 111-119. doi:10.5330/prsc.17.1.518021r2x6821660
Goodman-Scott, E., Betters-Bubon, J., & Donohue, P. (2016). Aligning comprehensive school counseling programs and positive behavioral interventions and supports to maximize school counselors' efforts. Professional School Counseling, 19, 57-67. doi:10.5330/1096-2409-19.1.57
Gravois, L., & Rosenfield, S. A. (2005). A multi-dimensional framework for evaluation of instructional consultative teams. Journal of Applied School Psychology, 19, 5-29.
Harlacher, J. E., & Siler, C. E. (2011). Factors related to successful RtI implementation. Communique, 39(6), 20-22.
Harrington, K., Griffith, C., Gray, K., & Greenspan, S. (2016). A grant project to initiate school counselors' development of a multi-tiered system of supports based on social-emotional data. The Professional Counselor, 6, 278-294. doi:10.15241/kh.6.3.278
Horner, R., Sugai, G., Smolkowski, K., Eber, L., Nakasato, J., Todd, A., & Esperanza, J., (2009). A randomized, wait-list controlled effectiveness trial assessing school-wide positive behavior support in elementary schools. Journal of Positive Behavior Interventions, 11, 133-145. doi:10.1177/1098300709332067
House, R., & Hayes, R. (2002). School counselors: Becoming key players in school reform. Professional School Counseling, 5, 249-256. doi:10.5330/PSC.n.2002-5.249.
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55.
Johnson, J., Rochkind, J., & Ott, A. (2010). Why guidance counseling needs to change. Educational Leadership, 67(7), 74-79.
Kann, L., Kinchen, S., Shanklin, S. L., Flint, K. H., Hawkins, J., Harris, W. A. ... Zaza, S. (2014). Youth risk behavior surveillance--United States 2013 (Report Vol. 63, No. 4). Altlanta, GA: Centers for Disease Control and Prevention. Retrieved from http://www. cdc.gov/mmwr/pdf/ss/ss6304.pdf
Kansas State Department of Education. (2013). Kansas multi-tier system of supports: Structuring guide module 1 leadership. Topeka, KS: Kansas MTSS Project, Kansas Technical Assistance System Network. Retrieved from http:// www.kansasmtss.org/pdf/ StructuringGuides/Structuring-Module-1-Guide.pdf
Lapan, R. T. (2012). Comprehensive school counseling programs: In some schools for some but not in all schools for all students. Professional School Counseling, 16, 84-88. doi:10.5330/PSC.n.2012-16.84
Lapan, R. T., Gysbers, N. C., & Petroski, G. F. (2001). Helping seventh graders be safe and successful: A statewide study of the impact of comprehensive guidance and counseling programs. Journal of Counseling & Development, 79, 320-330. doi:10.1002/j.1556-6676.2001.tb01977.x
Lohrmann, S., Martin, S., & Patil, S. (2013). External and internal coaches' perspectives about overcoming barriers to universal interventions. Journal of Positive Behavior Interventions, 15, 26-38. doi:10.1177/1098300712459078
Lopez, E. C., & Bursztyn, A. M. (2013). Future challenges and opportunities: Toward culturally responsive training in school psychology. Psychology in the Schools, 50(3), 212-228. doi:10.1002/pits.21674
Marin, A. M., & Filce, H. G. (2013). The relationship between implementation of school-wide positive behavior intervention and supports and performance on state accountability measures. Sage Open, 3, 1-10. doi:10.1177/2158244013503831
Marrs, H., & Little, S. (2014). Perceptions of school psychologists regarding barriers to response to intervention (RTI) implementation. Contemporary School Psychology, 18, 24-34. doi:10.1007/s40688-013-0001-7
Mathews, S., Mcintosh, K., Frank, J. L., & May, S. L. (2014). Critical features predicting sustained implementation of school-wide positive behavioral interventions and supports. Journal of Positive Behavior Interventions, 16(3), 168-178. doi:10.1177/1098300713484065
McCotter, S., & Cohen, S. (2013). Are middle school counseling programs meeting early adolescent needs? A survey of principals and counselors. The Journal of Counselor Preparation and Supervision 5(1), 6-27. doi:10.7729/51.0015
McIntosh, K., Girvan, E. J., Horner, R. H., Smolkowski, K., & Sugai, G. (2014). Recommendations for addressing disproportionality in education. OSEP Technical Assistance Center on Positive Behavioral Interventions and Supports. Retrieved from https://www.pbis.org/ Common/Cms/files/pbisresources/ RecommendationsForAddressing DisciplineDisproportionality.pdf
McIntosh, K., Sadler, C., & Brown, J. (2012). Kindergarten reading skill level and change as risk factors for chronic problem behavior. Journal of Positive Behavior Interventions, 14, 17-28. doi:10.1177/1098300711403153
Mitcham, M., Greenidge, W., BradhamCousar, M., Figliozzi, J., & Thompson, M. A. (2012). Increasing career self-efficacy through group work with culturally and linguistically diverse students. Journal of School Counseling, 10, 1-26. Retrieved from http://files.eric.ed.gov/fulltext/EJ981203. pdf
Muthen, L. K., & Muthen, B. O. (2011). Mplus User's Guide (6th ed.). Los Angeles, CA: Muthen & Muthen.
National Center for Education Statistics. (2013). Statistics in brief: First-year undergraduate remedial coursetaking: 1999-2000, 2003-04, 2007-08. Retrieved from https://nces.ed.gov/ pubs2013/2013013.pdf
National Center for Education Statistics. (2014). The condition of education 2014. Washington, DC: U.S. Department of Education. Retrieved from http://nces. ed.gov/pubs2014/2014083.pdf
Olsen, J. A., Blum, C., & Cheney, D. (2016). School counselor knowledge and skills survey. Unpublished survey, Department of Counseling, University of North Carolina at Charlotte, Charlotte, North Carolina.
PBIS.org. (2016). Number of schools implementing PBIS. Retrieved from http://www.pbis.org/
Pinkelman, S. E., McIntosh, K., Rasplica, C. K., Berg, T., & Strickland-Cohen, M. K. (2015). Perceived enablers and barriers related to sustainability of school-wide positive behavioral interventions and supports. Behavioral Disorders, 40(3), 171-183. doi:10.17988/0198-7429-40.3.171
Poynton, T. A., Lapan, R. T., & Marcotte, A. M. (2015). Financial planning strategies of high school seniors: Removing barriers to career success. The Career Development Quarterly, 63(1), 57-73. doi:10.1002/j.2161-0045.2015.00095.x
Pyne, J. R. (2011). Comprehensive school counseling programs, job satisfaction, and the ASCA National Model. Professional School Counseling, 15, 88-97. doi:10.5330/PSC.n.2011-15.88
Sink, C. A. (2016). Incorporating a multi-tiered system of supports into school counselor preparation. The Professional Counselor, 6, 203-219. doi:10.15241/cs.6.3.203
Smith, H. M., Evans-McCleon, T. N., Urbanski, B., & Justice, C. (2015). Check-In/Check-Out intervention with peer monitoring for a student with emotional-behavioral difficulties. Journal of Counseling & Development, 93, 451-459. doi:10.1002/jcad.12043
Steiger, J. H., & Lind, J. C. (1980). Statistically based tests for the number of factors. Paper presented at the annual spring meeting of the Psychometric Society, Iowa City, IA.
Sugai, G., & Horner, R. H. (2009). Responsiveness-to-intervention and school-wide positive behavior supports: Integration of multi-tiered approaches. Exceptionality, 17, 223-237. doi:10.1080/09362830903235375
Sugai, G., Simonsen, B., Bradshaw, C., Horner, R., & Lewis, T. (2014). Delivering high quality school-wide positive behavior support in inclusive schools. In J. McLeskey, N. L. Waldron, F. Spooner, & B. Algozzine (Eds.), Handbook of effective inclusive schools: Research and practice (pp. 306-321). New York, NY: Routledge.
Vega, D., Moore, J. L., & Miranda, A. H. (2015). In their own words: Perceived barriers to achievement by African American and Latino high school students. American Secondary Education, 43(3), 36-59.
Vincent, C. G., Randall, C., Cartledge, G., Tobin, T J., & Swain-Bradway, J. (2011). Toward a conceptual integration of cultural responsiveness and schoolwide positive behavior support. Journal of Positive Behavior Interventions, 13, 219-229. doi:10.1177/1098300711399765
Whiston, S. C., & Quinby, R. F. (2009). Review of school counseling outcome research. Psychology in the Schools, 46, 267-272. doi:10.1002/pits.20372
Whiston, S. C., Tai, W. L., Rahardja, D., & Eder, K. (2011). School counseling outcome: A meta-analytic examination of interventions. Journal of Counseling & Development, 89(1), 37-55. doi:10.1002/j.1556-6678.2011.tb00059.x
Wilkerson, K., Perusse, R., & Hughes, A. (2013). Comprehensive school counseling programs and student achievement outcomes: A comparative analysis of RAMP versus non-RAMP schools. Professional School Counseling, 16, 172-184. doi:10.5330/PSC.n.2013-16.172
Ziomek-Daigle, J., Goodman-Scott, E., Cavin, J., & Donohue, P. (2016). Integrating a multi-tiered system of supports with comprehensive school counseling programs. The Professional Counselor, 6(3), 220-232. doi:10.15241/jzd.6.3.220
Caption: FIGURE 1 RECOMMENDED MODEL BASED ON BEST EH STATISTICS.
TABLE 1 DESCRIPTIVE STATISTICS FOR STUDY VARIABLES (N = 4,066) Variable M SD Minimum Maximum SCPIS Programmatic Orientation (PO) 3.02 .60 1 4 Software and Data (CS) 3.43 .65 1 4 School Counseling Services (SER) 3.37 .45 1 4 SCKSS Specialized Behavior (SB) 3.60 .74 1 5 Targeted Intervention (TI) 3.68 .69 1 5 School-Wide MTSS (SW) 3.50 .92 1 5 Individualized Curriculum (IC) 3.37 .86 1 5 Positive Classroom (PC) 3.61 .77 1 5 Challenges Need More Training (CHTR) 2.22 .62 1 3 Need More Admin. Support (CHAD) 2.12 .75 1 3 Need More Time (CHTI) 2.50 .62 1 3 Need More Staff Buy-In (CHBU) 2.40 .65 1 3 Extent of MTSS training (TRAIN) 2.56 .92 1 4 Note. SCPIS = School Counseling Program Implementation Survey; SCKSS = School Counselor Knowledge and Skills Survey. TABLE 2 STANDARDIZED PATH COEFFICIENTS FOR RECOMMENDED MODEL Path Estimate SE Est/SE Measurement ASCA BY PO .823 .015 53.659 CS .526 .019 28.044 SER .679 .017 40.991 Measurement MTSS BY SB .944 .003 299.096 TI .935 .003 270.248 SW .806 .008 100.071 IC .855 .006 135.718 PC .879 .005 161.657 Direct Path MTSS ON ASCA .452 .022 20.414 Indirect Path ASCA ON TRAIN .299 .028 10.686 CHTR -.105 .028 -3.692 SECOND .071 .026 2.725 Direct Path MTSS ON TRAIN .146 .024 6.008 CHTR -.115 .023 -4.995 SECOND -.066 .021 -3.127 Sum of TRAIN to MTSS .104 .013 8.030 Indirect CHTR to MTSS -.053 .017 3.155 SECOND to MTSS .046 .018 2.601 Path p value Measurement ASCA BY PO < .001 CS < .001 SER < .001 Measurement MTSS BY SB < .001 TI < .001 SW < .001 IC < .001 PC < .001 Direct Path MTSS ON ASCA < .001 Indirect Path ASCA ON TRAIN < .001 CHTR < .001 SECOND .006 Direct Path MTSS ON TRAIN < .001 CHTR < .001 SECOND .002 Sum of TRAIN to MTSS < .000 Indirect CHTR to MTSS .002 SECOND to MTSS .009 Note. ASCA = Time spent on ASCA aligned activities; PO = Programmatic Orientation; CS = Software and Data; SER = School Counseling Services; MTSS = Knowledge and skills of MTSS; SB = Specialized Behavior; TI = Targeted Intervention; SW = School-Wide MTSS; IC = Individualized Curriculum; PC = Positive Classroom; TRAIN = Extent of MTSS training.
|Printer friendly Cite/link Email Feedback|
|Title Annotation:||FEATURED RESEARCH|
|Author:||Olsen, Jacob; Parikh-Foxx, Sejal; Flowers, Claudia; Algozzine, Bob|
|Publication:||Professional School Counseling|
|Date:||Jan 1, 2016|
|Previous Article:||ADVOCACY COMPETENCY OF SCHOOL COUNSELORS: AN EXPLORATORY FACTOR ANALYSIS.|
|Next Article:||EVALUATION OF A BRIEF, SCHOOL-BASED BULLYING BYSTANDER INTERVENTION FOR ELEMENTARY SCHOOL STUDENTS.|