Soria 2 Victoria Soria Dean Winther English 101 04 February 2020 Poverty’s Impact on Education in America Most evidently in America children born or brought up in poverty are faced with insignificant education, versus a child with a higher income background. I have chosen this topic for my research assignment being that an impact of poverty can affect a child’s academic accomplishments significantly. This results in them facing challenges such as lacking intellectual and literary skills. The child readiness for school is reduced by poverty because it brings forth poor physical health and motor skills, dwindles the children's ability to concentrate and remember information, reduces curiosity, attentiveness and motivation. Children from lower-income families who manage to complete high school are less likely to proceed to college. Such children end up not achieving their life goals for lack of education. The effects of poverty on education for some children present unique challenges in breaking the cycle of generational poverty. It further reduces their chances of living productive and rewarding lives. Featured Research Exploring the Job Duties That Impact School Counselor Wellness: The Role of RAMP, Supervision, and Support Nicole M. Randick 1 , Shannon Dermer 2 , and Rebecca E. Michel 3 Abstract The authors examined the predictive relationship between the performance of job duties informed by the American School Counselor Association (ASCA) National Model and overall wellness of school counselors. We also examined the relationship between organizational factors (i.e., Recognized ASCA Model Program, supervision, and support), the frequency of job duties performed, and overall wellness. The results revealed a predictive relationship between some of the job duties school counselors perform and wellness. We provide implications for school counseling practice and training programs. Keywords ASCA National Model, organizational factors, school counselors, wellness Wellness, defined as a way of life that fosters “the optimum state of health and well-being that each individual is capable of achieving” (Myers, Sweeny, & Witmer, 2000, p. 252), is a central foundation of the school counseling profession. The American School Counselor Association’s ASCA Ethical Stan- dards for School Counselors require school counselors to per- form duties identified by the ASCA National Model (ASCA, 2012, 2016; Standard B.3.c) and to “monitor their emotional and physical health and practice wellness to ensure optimal professional effectiveness” (Standard B.3.f). Therefore, school counselors must balance the dual task of supporting their stu- dents’ academic, social/emotional, and career development while also ensuring that their own wellness needs are being met (ASCA, 2012, 2016; Bryant & Constantine, 2006; Limberg, Lambie, & Robinson, 2016). School counselors must balance the dual task of supporting their students’ academic, social/ emoti.

1. Soria 2
Victoria Soria
Dean Winther
English 101
04 February 2020
Poverty’s Impact on Education in America
Most evidently in America children born or brought up in
poverty are faced with insignificant education, versus a child
with a higher income background. I have chosen this topic for
my research assignment being that an impact of poverty can
affect a child’s academic accomplishments significantly. This
results in them facing challenges such as lacking intellectual
and literary skills. The child readiness for school is reduced by
poverty because it brings forth poor physical health and motor
skills, dwindles the children's ability to concentrate and
remember information, reduces curiosity, attentiveness and
motivation. Children from lower-income families who manage
to complete high school are less likely to proceed to college.
Such children end up not achieving their life goals for lack of
education. The effects of poverty on education for some
children present unique challenges in breaking the cycle of
generational poverty. It further reduces their chances of living
productive and rewarding lives.
Featured Research
Exploring the Job Duties That Impact
School Counselor Wellness: The Role
of RAMP, Supervision, and Support

2. Nicole M. Randick
1
, Shannon Dermer
2
, and Rebecca E. Michel
3
Abstract
The authors examined the predictive relationship between the
performance of job duties informed by the American School
Counselor Association (ASCA) National Model and overall
wellness of school counselors. We also examined the
relationship
between organizational factors (i.e., Recognized ASCA Model
Program, supervision, and support), the frequency of job duties
performed, and overall wellness. The results revealed a
predictive relationship between some of the job duties school
counselors
perform and wellness. We provide implications for school
counseling practice and training programs.
Keywords
ASCA National Model, organizational factors, school
counselors, wellness
Wellness, defined as a way of life that fosters “the optimum
state of health and well-being that each individual is capable of
achieving” (Myers, Sweeny, & Witmer, 2000, p. 252), is a
central foundation of the school counseling profession. The
American School Counselor Association’s ASCA Ethical Stan-

3. dards for School Counselors require school counselors to per-
form duties identified by the ASCA National Model (ASCA,
2012, 2016; Standard B.3.c) and to “monitor their emotional
and physical health and practice wellness to ensure optimal
professional effectiveness” (Standard B.3.f). Therefore, school
counselors must balance the dual task of supporting their stu-
dents’ academic, social/emotional, and career development
while also ensuring that their own wellness needs are being
met (ASCA, 2012, 2016; Bryant & Constantine, 2006; Limberg,
Lambie, & Robinson, 2016).
School counselors must balance the dual task of
supporting their students’ academic, social/
emotional, and career development while also
ensuring that their own wellness needs are being
met.
When their job duties are aligned with ASCA National
Model (2012) guidelines, school counselors feel more sup-
ported, have a greater commitment to their work, and experi-

4. ence increased job satisfaction (Baggerly & Osborn, 2006;
Pyne, 2011; Scarborough & Culbreth, 2008). Increased support
and supervision create a culture of professional wellness and a
more positive work environment for school counselors
(Bernard & Goodyear, 2009). Specifically, school counselors
who received supervision reported feeling more supported in
their role, competent, and empathetic with students (Moyer,
2011; Murphy & Kaffenberger, 2007; Young & Lambie, 2007).
Although school counseling supervision has been shown to
foster a supportive working environment, other organizational
factors make working in a school challenging. For example,
when school counselors have incomplete information about
how to perform their jobs, they experience role ambiguity,
which can result in decreased job satisfaction, stress, impair-
ment, and burnout (Cervoni & DeLucia-Waack, 2011; Leu-
werke, Walker, & Shi, 2009; Wilkerson & Bellini, 2006).
Other challenges include increased demands, unmanageable
caseloads, working in unsupportive systems, high levels of

5. emotional exhaustion, and receiving little to no supervision
(Culbreth, Scarborough, Banks-Johnson, & Solomon, 2005;
McCarthy, Kerne, Calfa, Lambert, & Guzmán, 2010; Moyer,
2011; Wilkerson & Bellini, 2006).
ASCA encourages programs to align school counselors’
work responsibilities with the ASCA National Model (2012),
and fully aligned programs can apply to receive Recognized
1 Adler Graduate School, Minnetonka, MN, USA
2
Governors State University, University Park, IL, USA
3 DePaul University, Chicago, IL, USA
Corresponding Author:
Nicole M. Randick, EdD, Adler Graduate School, Minnetonka,
MN 55343, USA.
Email: [email protected]
Professional School Counseling
Volume 22(1): 1-11
ª 2019 American School
Counselor Association
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ASCA Model Program (RAMP) designation (Young & Kaf-
fenberger, 2011). School counseling programs that are aligned
with the ASCA National Model have a positive impact on
student academic success (Gruman, Marston, & Koon, 2013;
Salina et al., 2013; Wilkerson, Pérusse, & Hughes, 2013); how-
ever, little is known about such programs’ impact on school
counselors. The purpose of this study was to understand how
school counselors function within their expected roles and what
organizational factors (i.e., RAMP, supervision, and support),
if any, predicted school counselors’ overall wellness.
School Counselor Job Duties
The role of the school counselor has evolved over the past
several decades from one that primarily provided guidance

7. services to one that administers comprehensive school counsel-
ing programs that target academic, career, and social/emotional
development through leadership, advocacy, collaboration, and
accountability (ASCA, 2012; Education Trust, 2009; Pérusse &
Goodnough, 2001). The ASCA National Model (2003, 2005,
2012) established the framework for how a school counselor
should function within a comprehensive school counseling
environment, specifying both appropriate and inappropriate
roles. Reasonable job duties include a combination of counsel-
ing, consultation, curriculum, and coordination duties (ASCA,
2012; Scarborough, 2005). These roles include providing indi-
vidual and small group counseling services to students, con-
sulting with stakeholders, conducting classroom lessons,
analyzing disaggregated data, designing interventions, and
facilitating school-wide responses for crisis management
(ASCA, 2012; Campbell & Dahir, 1997; Scarborough, 2005).
The ASCA National Model (2012) recommends that school
counselors spend 80% or more of their time in direct or indirect

8. student services. When secondary school counselors spent
more time engaging in ASCA-aligned duties, they were more
skilled in implementing support systems that directly impacted
student’s academic, social/emotional, and career development
(Olsen, Parikh-Foxx, Flowers, & Algozzine, 2016).
Although the ASCA National Model (2012) clearly speci-
fies appropriate and inappropriate job duties of school counse-
lors, many work within school districts where they are required
to engage in noncounseling duties such as scheduling, main-
taining records, and testing (Hatch & Chen-Hayes, 2008; Leu-
werke et al., 2009; Moyer, 2011; Perera-Diltz & Mason, 2008;
Scarborough & Culbreth, 2008). Some administrators and other
educators may not be aware of school counselors’ training,
appropriate job duties, or how they can make a difference in
students’ lives. Principals may be unaware of the ASCA
National Model or may have different perceptions about the
duties of school counselors (Bringman, Mueller, & Lee, 2010;
Leuwerke et al., 2009; Pérusse, Goodnough, Donegan, &

9. Jones, 2004). For example, McCotter and Cohen (2013) found
that New Jersey middle school counselors and principals had
differing perceptions about student needs across academic,
social/emotional, and career domains. When administrators,
teachers, and students expect school counselors to engage in
duties misaligned with their expertise, counselors are unable to
complete the duties they were trained to perform (DeMato &
Curcio, 2004; Gruman et al., 2013; Scarborough & Culbreth,
2008). Spending time on these noncounseling activities pre-
vents school counselors from engaging in counseling duties,
which have been shown to have the greatest impact on stu-
dents’ academic, social/emotional, and career outcomes (Carey
& Dimmitt, 2012; Lapan, Gysbers, & Kayson, 2006; Olsen
et al., 2016; Wilkerson et al., 2013; Whiston, Tai, Rahardja,
& Eder, 2011).
Organizational Factors
The changing landscape of school missions, goals of school
counseling programs, and student needs (Gruman et al.,

10. 2013; Olsen et al., 2016), coupled with difficult caseloads
(Lawson, 2007; McCarthy et al., 2010), further increase the
demands put on school counselors. For example, the recom-
mended student-to-school-counselor caseload is 250:1; how-
ever, the average caseload is 482:1, nearly twice the
recommended ratio (ASCA, 2017). Maintaining large case-
loads while being responsible for meeting the academic,
social/emotional, and career needs of all their students can be
overwhelming for school counselors (Gruman et al., 2013;
McCarthy et al., 2010; Salina et al., 2013). One way to contend
with increasing demands and complexity of caseloads is to
support school counselors through professional supervision.
The quality and quantity of supervision contributes to school
counselor wellness. Supervision is recognized as an effective
mediator of stress and work overload for school counselors
(Moyer, 2011; Page, Pietrzak, & Sutton, 2001; Young & Lam-
bie, 2007). When school counselors received supervision based
on the ASCA National Model with clearly defined role func-

11. tions within a supportive environment, they experienced
reduced stress and increased wellness (Lambie & Williamson,
2004; Moyer, 2011; Young & Lambie, 2007). Baggerly and
Osborn (2006) found that the combination of performing
ASCA National Model school counseling duties and receiving
supervision increased school counselors’ job satisfaction and
decreased attrition. Similarly, school counselors reported
reduced role stress when they felt their job duties matched their
expectations and training and they had peer supervision avail-
able (Culbreth et al., 2005). On the other hand, lack of super-
vision was a predictor for increased feelings of incompetence,
showing frustration with the school setting, and a lack of com-
passion for students (Moyer, 2011; Page et al., 2001; Witmer &
Granello, 2005).
When school counselors are supported in their role, they are
more likely to perform ASCA-aligned duties that foster posi-
tive student outcomes. For example, in their development of a
school-wide student support program, All Hands on Deck, Sal-

12. ina and colleagues (2013) found the establishment of trust from
administration was a precipitating factor in school counselors’
increased performance of student support services. Similarly,
2 Professional School Counseling
Gruman and colleagues (2013) found the collaboration
between teachers, administrators, and school counselors to be
essential for school counselors to meet the mental health needs
of high school students.
In summary, when counselors lack wellness in their own
lives, they are no longer able to “nurture wellness in others”
(Lawson, Venart, Hazler, & Kottler, 2007, p. 6). Studies on
school counselor wellness have been sparse even though
decreased wellness has been found to reduce the quality of
services that counselors provide (Wilkerson & Bellini, 2006;
Young & Lambie, 2007). Research suggests that when school
counselors work within a comprehensive school counseling
program and perform supervised duties for which they are

13. trained, they have a greater impact on student outcomes, are
more satisfied at work, experience less stress, report greater
wellness, and remain in their jobs longer (Clemens, Milsom,
& Cashwell, 2009; Salina et al., 2013). However, when schools
do not support a comprehensive school counseling program,
this contributes to role ambiguity, conflict, and stress for school
counselors attempting to navigate the roles they were trained to
perform (Cervoni & DeLucia-Waack, 2011; Curry & Bick-
more, 2012; Page et al., 2001).
Method
The purpose of this study was to investigate how school coun-
selors function within their roles and what organizational fac-
tors (i.e., RAMP, supervision, and support), if any, were most
influential in leading to increased levels of school counselor
wellness. Building from existing literature, we used the follow-
ing questions to guide the research study. First, does a positive
relationship exist between performance of actual counseling
duties (i.e., counseling, consultation, curriculum, and coordina-

14. tion) and overall wellness functioning among school counse-
lors? Second, does a negative relationship exist between
performance of noncounseling duties (e.g., clerical, fair share,
administrative) and overall wellness functioning among school
counselors? Third, does performance of actual counseling
duties (i.e., coordination, curriculum, counseling, and consulta-
tion) predict overall wellness functioning among school coun-
selors? Fourth, do organizational demographic factors (i.e.,
working at an RAMP school, supervision, and the degree to
which the counselor feels supported) predict overall wellness
and performance of actual counseling duties?
Derived from the above research questions, the following
hypotheses guided the inquiry:
� Hypothesis 1: A positive relationship exists between the
performance of counseling duties (i.e., counseling
[Hypothesis 1a], consultation [Hypothesis 1b], curricu-
lum [Hypothesis 1c], and coordination [Hypothesis 1d])
and overall wellness functioning.
� Hypothesis 2: A negative relationship exists between

15. performance of noncounseling duties (e.g., clerical, fair
share, administrative) and overall wellness functioning.
� Hypothesis 3: The performance of actual counseling
duties (i.e., coordination [Hypothesis 3a], curriculum
[Hypothesis 3b], counseling [Hypothesis 3c], and con-
sultation [Hypothesis 3d]) predicts overall wellness
functioning.
� Hypothesis 4: Organizational demographic factors (i.e.,
working at an RAMP school [Hypothesis 4a], supervi-
sion [Hypothesis 4b], and the degree to which the coun-
selor feels supported [Hypothesis 4c]) predict frequency
of performing counseling duties (i.e., counseling, con-
sultation, curriculum, coordination).
Participants and Procedures
We invited more than 25,000 school counselor members of the
ASCA via e-mail to voluntarily participate in the study, which
was approved by the institutional review board. We also dis-
tributed a separate e-mail invitation to several state, university,
and professional school counselor listserves. We posted two

16. follow-up messages requesting participation approximately 1
week and 3 weeks after the initial invitation. Participants were
asked to provide informed consent through the SurveyMonkey
online data collection system and complete the School Coun-
selor Activity Rating Scale (SCARS; Scarborough, 2005), the
Five-Factor Wellness Inventory (FFWEL; Myers & Sweeney,
2005b), and an organizational and descriptive questionnaire.
Of the possible respondents, 124 individuals began the sur-
vey and only 108 successfully completed the survey scales;
these constituted the sample employed for this study. Most
participants worked full-time (n ¼ 98, 90.74%) in elementary
schools (n ¼ 41, 37.96%), middle schools (n ¼ 24, 22.22%), or
high schools (n ¼ 43, 39.81%). Experience levels ranged from
less than 5 years of experience (n ¼ 34, 31.48%), to between 5
and 10 years of experience (n ¼ 37, 34.26%), to more than
10 years of experience (n ¼ 37, 34.26%). Participants identi-
fied as female (n ¼ 103, 95.37%) and male (n ¼ 5, 4.63%), and
race was reported as Caucasian (n ¼ 96, 88.89%), African
American (n ¼ 8, 7.41%), and Hispanic (n ¼ 3, 2.78%); one
participant chose not to report race.
Measures
SCARS. The SCARS (Scarborough, 2005) measures the fre-
quency of how school counselors actually spend their profes-

17. sional time versus how they would prefer to spend their time
performing professional activities informed by the ASCA
National Model. The 48-item scale was designed to closely
follow the recommendations of best practices found in the
ASCA National Model and the results of a literature review
of the common activities of counselors, including (a) counsel-
ing, (b) consultation, (c) curriculum, (d) coordination, and
(e) other activities (e.g., clerical, fair share, and administrative
duties). Participants rate each item on a Likert-type scale that
ranges from 1 (I never do this) to 5 (I routinely do this). The
Randick et al. 3
SCARS scores can be reported as total or mean scores for both
actual and preferred activities (Scarborough, 2005). For this
study, we used only the actual job duties portion of the scale
to collect frequency ratings. Cronbach’s as for this sample
were as follows: .86 for counseling, .82 for consultation, .94
for curriculum, and .89 for coordination.
Five-Factor Wellness Inventory. The FFWEL measures compo-

18. nents of wellness in the Indivisible Self Model of Wellness
(IS-Wel; Myers & Sweeney, 2005a). The IS-Wel was devel-
oped based on the Wellness Evaluation of Lifestyle (WEL;
Myers & Sweeney, 2005a), which is a holistic model of well-
ness grounded in Adlerian theory. This includes the idea that
the self is composed of the mind, body, and soul, which
together influence the meaning we give to our experiences
within our social context. Exploratory and confirmatory factor
analyses of the WEL yielded a single-order factor, total well-
ness, 5 second-order factors (i.e., Creative Self, Coping Self,
Essential Self, Physical Self, and Social Self), and 17 third-
order factors (e.g., love, nutrition, self-care).
The FFWEL was designed to be taken in approximately 15
min, with different versions for children, adolescents, and
adults. We used the adult version (FFWEL-A) of the instru-
ment in this study; it includes 7 demographic items and 91
items measuring each of the wellness factors in the IS-Wel.
The first section of the FFWEL consists of items focused

19. around the areas of wellness. These items elicit information
from individuals about behaviors, emotions, and feelings
relating to one’s health, quality of life, and longevity. The
items appear in random order and each is answered using a
Likert-type scale, ranging from 1 (strongly agree) to
4 (strongly disagree). Calculating the scores produces a score
in the range of 25–100, with higher scores indicating higher
levels of wellness (Myers & Sweeney, 2005b). For the pur-
pose of this study, we used only the total wellness score
because it encompasses a total score for all the five factors
of wellness, representing the level of wellness for optimal
functioning (Myers & Sweeney, 2005b).
Analysis of consistency (using Cronbach’s a) performed
during the development of the FFWEL supported the overall
wellness score and each of the secondary factors. The authors
of the instrument reported a high degree of construct validity
(Myers & Sweeney, 2005b) and examined internal consistency
again after a 5-year period. Myers and Sweeney (2005b) estab-
lished and reported reliabilities for the subscales as follows:

20. Total Wellness ¼ .98, Creative Self ¼ .96, Coping Self ¼ .89,
Social Self ¼ .96, Essential Self ¼ .95, and Physical Self ¼ .90.
Organizational and descriptive questionnaire. We developed the
12-item questionnaire based on existing literature, guiding
research questions, and feedback from experts in the field of
school counseling. The choices for most questions were yes,
somewhat, or no. Some items required respondents to choose
from a list of answers. The questionnaire was designed to col-
lect information specific to RAMP, supervision, support, and
training. Table 1 presents the questions and results. The ques-
tionnaire also included questions about grade level, employ-
ment status, years of experience (reported above), and what
activities counselors felt least supported in performing
(reported in results).
Data Analysis
We analyzed the data using SPSS Version 22.0. A preliminary
analysis of the data included identifying (a) if the assumptions
of the analyses were met, (b) reliability and validity of the
measures, (c) distributions of the variables, and (e) the extent

21. of missing data (Cone & Foster, 2006). We also screened the
data for skewness, kurtosis, and outliers. The sample showed
skewness between �.8 and þ.8 and kurtosis between �2 and
þ2, showing no issues. Missing data analyses found that 16 of
the respondents did not respond to all of the questions; we
discarded those responses, leaving our sample size relatively
small (N ¼ 108). We computed the mean and standard devia-
tion (SD) for the Total Wellness score from the FFWEL and
calculated frequencies and percentages for all descriptive and
organizational variables.
Table 1. Frequencies and Percentages of Organizational
Variables.
Organizational Variable Sample Percent Frequency
Working in RAMP school
Yes 4.63 5
No 95.37 103
Implement ASCA National Model
Yes 19.44 21
Somewhat 58.33 63
No 22.22 24
Training in ASCA National Model
Yes 48.15 52
Somewhat 25 27
No 26.85 29

22. Familiar with ASCA National Model
Yes 85.19 92
Somewhat 12.96 14
No 1.85 2
School support for ASCA National Model
Yes 25 27
Somewhat 55.56 60
No 19.44 21
Supervision
No 47.22 51
Licensed school counselor 4.63 5
School principal 38.89 42
Teacher 0 0
A faculty member 1.85 2
Other 7.41 8
Supervision based on ASCA National Model
Yes 7.37 7
No 92.63 88
Note. RAMP ¼ Recognized ASCA Model Program; ASCA ¼
American School
Counselor Association.
4 Professional School Counseling
To answer the first and second hypotheses, we performed a
bivariate correlation by examining participants’ mean subscale
scores from the SCARS (Scarborough, 2005) and the overall

23. wellness score from the FFWEL (Myers & Sweeney, 2005b).
An analysis of the Pearson correlation coefficients determined
the degree to which the variables were related. We analyzed the
remaining two hypotheses using regression analysis to deter-
mine which variables best predicted the criterion variable. To
determine the distinct contribution of actual counseling duties
from the SCARS (i.e., counseling, consultation, curriculum,
and coordination) on the overall wellness score from the
FFWEL (Myers & Sweeney, 2005b), we used a hierarchal
regression. And to analyze each predictor variable (i.e., RAMP
school, supervision, and support) to determine whether they
contributed any new information in predicting the criterion
variable (Total Score on the Actual Job Duties Scale), we used
a backward stepwise regression.
Results
On the SCARS, school counselors reported the frequency of
performing actual job duties. The job activities reported most
often included coordination duties (M ¼ 37.97, SD ¼ 10.08),

24. followed by “other” noncounseling duties (M ¼ 30.34, SD ¼
6.96) and counseling duties (M ¼ 29.29, SD ¼ 6.612). The least
reported activities were curriculum duties (M ¼ 24.45, SD ¼
10.078) and consulting duties (M ¼ 24.30, SD ¼ 5.29).
We also collected information on the ASCA National Model
activities in which school counselors felt least supported. The
least supported activities, listed in rank order, were delegating
clerical or noncounseling duties (n ¼ 77, 71.3%), appropriate
use of counselor time (n ¼ 63, 58.3%), ability to carry out
classroom guidance curriculum (n ¼ 41, 38%), collecting and
analyzing data (n ¼ 34, 31.5%), preventive role in school dis-
cipline (n ¼ 33, 30.6%), system support duties (n ¼ 31, 28.7%),
ability to provide individual student planning (n ¼ 20, 18.5%),
and responsive services/interventions (n ¼ 16, 14.8%).
Hypothesis 1
To test the first hypothesis, we conducted Pearson correlations
for each counseling-related subscale of the SCARS (Scarbor-
ough, 2005) and the total wellness score on the FFWEL (Myers
& Sweeney, 2005b). Employing Cohen’s (2008) effect size
cutoffs, we found a small to moderate positive relationship
between counseling and wellness, r(106) ¼ .234, p < .05, thus
supporting Hypothesis 1a. Similarly, a small to moderate pos-
itive relationship between consultation and wellness, r(106) ¼
.216, p < .05, provided support for Hypothesis 1b. With regard

25. to Hypothesis 1c, we found a small yet significant positive
relationship between curriculum and wellness, r(106) ¼ .013,
p < .05. Finally, we found the strongest relationship in this
sample between coordination and wellness, r(106) ¼ .35, p <
.01, and this moderate positive relationship provided support
for Hypothesis 1d. All in all, our results fully supported
Hypotheses 1a, 1b, 1c, and 1d.
Hypothesis 2
To assess Hypothesis 2, we calculated a Pearson correlation
between total wellness score on the FFWEL (Myers & Swee-
ney, 2005b) and noncounseling duties (i.e., other activities) as
measured by the SCARS (Scarborough, 2005). The total well-
ness score and noncounseling duties were not significantly
related, r(106) ¼ .019, p ¼ .848.
Hypothesis 3
To evaluate Hypothesis 3, we conducted a hierarchical regres-
sion to determine whether any of the four counseling-related
subscales from the SCARS (Scarborough, 2005) could be used
to predict total wellness on the FFWEL (Myers & Sweeney,

26. 2005b). We entered the variables one at a time in the model to
determine predictability and potential changes to the value of
the coefficient of determination. Based on theory, the order of
entry was coordination, curriculum, counseling, and consulta-
tion. The entry of each variable added the controlling effect of
that variable and how the new variable interacted with the
previous to determine overall predictability. The results are
displayed in Table 2.
The first model, which included only coordination, showed
a significant result in determining wellness, B ¼ 0.230, t(107)
¼ 30.38, p < .001. That model accounted for 11.7% of varia-
bility explained in the criterion variable, providing support for
Hypothesis 3a. Adding curriculum to the model increased the
overall variation explained to 13.6%, but curriculum itself was
not shown to be a significant predictor, B ¼�0.131, t(107) ¼
�1.819, p ¼ .072. The third variable, counseling, did not
change the overall value of r
2
, still contributing 13.6% of the
variation explained. The variable itself was not seen to be
Table 2. Prediction of Counseling Duties on Wellnessa From

27. Regression Analysis.
Model Variable b SE t p r2 p
1 Intercept 70.397 2.317 30.388 <.001 .117 <.001
Coordination 0.230 0.059 3.901 <.001
2 Intercept 71.588 2.384 30.034 <.001 .136 <.001
Coordination 0.283 0.065 4.340 <.001
Curriculum �0.131 0.072 �1.819 .072
3 Intercept 70.128 2.801 25.035 <.001 .136 <.001
Coordination 0.248 0.074 3.350 .001
Curriculum �0.156 0.076 �2.045 .043
Counseling 0.116 0.117 0.993 .323
4 Intercept 70.264 3.031 23.180 <.001 .128 .001
Coordination 0.252 0.080 3.163 .002
Curriculum �0.156 0.077 �2.034 .044
Counseling 0.123 0.129 0.947 .346
Consultation �0.019 0.156 �0.121 .904
aCriterion variable ¼ wellness.
Randick et al. 5
significant, B ¼ 0.116, t(107) ¼ 0.993, p < .323. Last, we
introduced consultation into the overall model; this caused the
overall variance explained to drop to 12.8%. Consultation also
was shown not to be a significant predictor of wellness, B ¼
�0.019, t(107) ¼�0.121, p < .904. Coordination was the only
model shown to be significant and thus fully supported Hypoth-

28. esis 3a.
Hypothesis 4
To test Hypothesis 4, we used a backward stepwise regression
with an exclusion level of .05 to determine whether any orga-
nizational demographics (i.e., RAMP, supervision, and sup-
port) could be used to predict frequency of counseling duties
(i.e., counseling, consultation, curriculum, and coordination),
as measured by the SCARS (Scarborough, 2005). Table 3 lists
the results of the unstandardized coefficients. The stepwise
modeling showed significance (p < .05) for all subscales. Sup-
port was the only significant variable for all subscales of the
SCARS (Scarborough, 2005). Support was a significant pre-
dictor for counseling, B ¼ 1.08, t(107) ¼ 3.06, p ¼ .003;
consulting, B ¼ 0.74, t(107) ¼ 2.53, p ¼ .013; curriculum, B
¼ 1.87, t(107) ¼ 3.878, p < .001; and coordination, B ¼ 11.22,
t(107) ¼ 5.203, p < .00. Thus, Hypothesis 4b was fully sup-
ported. RAMP was a significant predictor for coordination, B ¼
2.56, t(107) ¼ 2.796, p ¼ .006, and counseling, B ¼ 5.81,
t(107) ¼ 2.02, p ¼ .046, thus providing partial support for
Hypothesis 4a. Supervision did not show any predictability
on the SCARS (Scarborough, 2005) subscales; thus, Hypoth-
esis 4c was not supported. As such, 11% of the variation of the

29. frequency of performing counseling duties can be attributed to
support and RAMP, 5% of the variation in consultation can be
attributed to support, 12% of the variation in curriculum to
support, and 25% of the variation in coordination to support
and RAMP.
Discussion
The purpose of …
Soria 2
Victoria Soria
Dean Winther
English 101
10 March 2020
RAVENArticle 1 by Theresa Capra (2009).
Reputation. The author is a renowned researcher at Mercer
County Community College who holds a Ph.D. and specializes
in issues of education and children.
Ability to Observe. Being a researcher, the author is in a
position to access reliable evidence from other scholarly
researchers like her. Working as a director in the College also
allows her to observe the effects of poverty on the education of
children.
Vested Interest. Being a researcher, the author has no personal
interest in the topic. Instead, she seeks to inform the general
public about the effects of poverty.
Expertise. The author is an expert in the field of education such
that she is even pursuing her Ph.D. She also refers to scholarly
sources written by experts as evidence in the article.
Neutrality. The author is neutral about poverty and education.
She provides a discussion of the causes, effects, and possible
solutions that can be applied to curb the problem. Article 2 by
Sean Slade (2015)

30. Reputation. The author is the director of Global Outreach at
ASCD which aims at providing quality education that will grow
children emotionally, physically, psychologically, and socially
(ASCD, 2020). Thus, the author is in a position of authority.
Ability to Observe. The author is in a position that allows him
to access reliable evidence. Being the director of Global
Outreach at ASCD, the author works and interacts with children
and this allows him to observe how poverty can affect their
education.
Vested Interest. The author has some personal interest in the
topic. He is a contributor to news being posted on the website.
Thus, to get more views and reads, the author has to write
something captivating and which will get more reads. This will
increase his image in the online world.
Expertise. The author is not an expert in the field of poverty and
education. Judging from the website, the author is just a
contributor. It is only one evidence that quotes scholarly
research. All the other evidence is from news and politics.
Neutrality. The author is biased about the issue of poverty and
its impact on education. The author decided to focus on the
negative side of poverty only. This painted a bad picture on the
government and rich countries who, it is claimed, are the ones
who cause poverty. Although this is partially true, the author
fails to recognize intervention efforts from these rich countries
that have worked to curb poverty. In this biased state, the
author presents a one-sided argument only. Article 3 by Kelley
Taylor (2017)
Reputation. The author is a contributor to contents on the
Insight website which reports news about various issues facing
the world today. being a magazine website, the source is not in
a position of authority.
Ability to Observe. Being a news reporter, the author is in a
position to access reliable evidence through researching on the
internet and conducting interviews.
Vested Interest. The author has a personal stake in the topic.
Being a reporter, telling the truth or lying will provide the

31. author with exposure and more clicks to the website.
Expertise. The author is not a specialist in the issue of poverty
and education. The evidence quoted, however, comes from
reliable sources such as directors in institutions that research
child poverty and education.
Neutrality. The author is neutral about the issue of poverty.
Although highlighting its negative impacts, the author also
discusses the possible interventions that can be implemented to
address the impact of poverty on education.
Works Cited
Theresa Capra (2009). Poverty and its Impact on Education:
Today and Tomorrow.
http://www.nea.org/assets/docs/HE/TA09PovertyCapra.pdf
ASCD (2020). Sean Slade-Senior Director of Global Outreach.
http://www.ascd.org/news-media/Sean-Slade-Director-
Outreach.aspx
Kelley Taylor (2017). Poverty Long-Lasting Effects on
Students’ Education and Success.
https://www.insightintodiversity.com/povertys-long-lasting-
effects-on-students-education-and-success/