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Psychology in the Schools, Vol. 52(4), 2015 C2015 Wiley Periodicals, Inc.
View this article online at wileyonlinelibrary.com/journal/pits DOI: 10.1002/pits.21830
AN INVESTIGATION OF RELATIONS AMONG ACADEMIC ENABLERS
AND READING OUTCOMES
LYNDSAY N. JENKINS
Eastern Illinois University
MICHELLE KILPATRICK DEMARAY
Northern Illinois University
The current study examined the link between academic enablers and different types of reading
achievement measures. Academic enablers are skills and behaviors that support, or enable, students
to perform well academically, such as engagement, interpersonal skills, motivation, and study
skills. The sample in this study consisted of 61 third-, fourth-, and fifth-grade students (54% male).
Academic enablers were rated by classroom teachers via the Academic Competence Evaluation
Scales (ACES; DiPerna & Elliott, 2000). Four different measures of reading achievement were
included: classroom grades, global ratings of reading skills, standardized test scores, and Reading
CBM scores. Results indicated that academic enablers were significantly related to each type of
reading outcome. Academic enablers accounted for the greatest amount of variance for classroom
grades (45%) and the least amount of variance in standardized test scores (11%). Results suggest
that academic enablers are an important part of academic success in reading, particularly classroom
grades, but when considering the variance accounted for by academic enablers, they alone are not
likely to improve Reading CBM scores or standardized test scores. C2015 Wiley Periodicals, Inc.
Academic enablers are skills and behaviors that support learning, such as academic engagement,
interpersonal skills, motivation, and study skills, and are important predictors of academic success
(DiPerna, 2006; DiPerna & Elliott, 2002; DiPerna, Volpe, & Elliott, 2002). Previous research
has found positive relationships between academic enablers and reading outcomes, but a number
of variables have served as outcome variables, including grades, standardized test scores, and
subjective teacher ratings. Though academic enablers have been positively associated with each
of these outcomes, no study has explored the association between academic enablers and each
academic outcome in a single investigation. The degree to which academic enablers are associated
with academic outcomes may vary, which has implications for school professionals involved in
assessment and intervention planning and researchers who study the impact of noncognitive factors
on learning (e.g., Farrington et al., 2012). Academic enablers can play an important role in assessment
and intervention decisions, particularly when assessing skill deficits (e.g., lack of ability to perform
academic tasks) and performance deficits (e.g., the skill to perform academic tasks, but lack of
supporting behaviors such as drive or attention). Some performance deficits could be attributed to
a lack of academic enablers, but the deficit may or may not manifest as differences on various
academic performance measures. Additionally, there is a movement among researchers interested in
the impact of noncognitive variables and academic behaviors (e.g., work completion, participation,
perseverance) on learning (see review by Farrington et al., 2012). These researchers want to determine
the extent to which student intelligence is related to learning compared to the influence of other
student, teacher, and instructional characteristics. Learning can be operationalized in a number of
different ways, but the way in which it is measured may have an impact on the results of the study.
The goal of this study is to compare the association between academic enables and four different
academic outcomes in reading in a single study.
Correspondence to: Lyndsay N. Jenkins, Department of Psychology, Eastern Illinois University, 600 Lincoln
Avenue, Charleston, IL 61920. E-mail: lnjenkins@eiu.edu
379
380 Jenkins and Demaray
Literature Review
To be successful in reading, students must possess a combination of general intelligence, reading
skills, and academic enablers. General intelligence accounts for approximately 50% of the variance
in academic achievement (Elliott, 2007; Glutting, Adams, & Sheslow, 2000; Kaufman & Kaufman,
1993, 2004; Naglieri & Das, 1997; Reynolds & Kamphaus, 2003; Roid, 2003; Wechsler, 2003,
2008; Wechsler & Naglierir, 2006; Woodcock, McGrew, & Mather, 2001), which means that 50%
of the variance in achievement is explained by other variables, such as academic skills, motivation,
engagement, or instructional methods. Haertel, Walberg, and Weinstein (1983) considered 228
variables in the literature as potentially having an influence on academic outcomes. These variables
ranged from student characteristics (e.g., ability and motivation), environmental characteristics
(e.g., classroom and home environment), to more distal variables such as district and state policies.
They determined that student characteristics and environmental variables were more important to
academic success than distal variables. DiPerna and Elliott’s (2002) work builds upon this literature
by emphasizing the importance of student characteristics, including individual’s academic enablers
and academic skills.
The theory proposed by DiPerna and colleagues purports that academic competence refers to
all attitudes, behaviors, and skills that a student needs to be successful in the classroom (DiPerna
et al., 2002) including two main components: academic skills and academic enablers. Academic
skills and academic enablers work together and complement each other. The central tenet of the
academic competence theory is that academic success requires not only academic skills, but also
enabling behaviors that support learning and the application of academic skills. DiPerna’s theory of
academic competence was chosen to guide the current investigation because it looks at academic
success in a comprehensive manner. Additionally, based on this theory of academic competence,
DiPerna and Elliott created a teacher-friendly rating scale to assess academic enablers called the
Academic Competence Evaluation Scales (ACES; DiPerna & Elliott, 2000). The ACES is readily
available and could be a vital part of the process of development academic intervention plans.
Academic Enablers
DiPerna and colleagues include engagement, interpersonal skills, motivation, and study skills
as academic enablers. Each of these has received theoretical and empirical attention in the literature,
which is briefly summarized next. To receive maximum benefit from academic instruction in the
classroom, students should be attentive to what the teacher is saying, be ready to take direction,
participate in discussions, and have appropriate materials ready for class. These behaviors can
collectively be described as academic engagement. DiPerna and Elliott (2000) defined engagement
as “behaviors that reflect attentive, active participation” (p. 6). Students who are academically
engaged are more likely to have higher test scores (Willingham, Pollack, & Lewis, 2002), receive
higher grades (Willingham et al., 2002), and have lower dropout rates (Croninger & Lee, 2001) and
higher attendance (Klem & Connell, 2004).
Interpersonal skills are “cooperative learning behaviors necessary to interact with other people”
(DiPerna & Elliott, 2000, p. 6). Interpersonal skills, also commonly referred to as social skills, have
been explored by numerous researchers. Prosocial behaviors have been positively linked with several
measures of academic achievement, including grade point average, standardized tests, and global
teacher-rated academic competence scores (Malecki & Elliott, 2002; Wentzel, 1993). Although there
is research to link interpersonal skills and academic achievement (Malecki & Elliott, 2002; Wentzel,
1993; Wentzel & Caldwell, 1997), there is little information about why and how these are linked
(Wentzel & Watkins, 2002).
Psychology in the Schools DOI: 10.1002/pits
Reading and Academic Enablers 381
Though there is debate in the field about the definition of motivation, a general definition that
encompasses many critical components was offered by Schunk, Pintrich, and Meece, “Motivation
is the process whereby goal-directed activity is instigated and sustained” (2008, p. 4). Historically,
there have been numerous theories explaining motivation; however, the current prevailing theories of
motivation are from the social cognitive perspective (Wentzel & Wigfield, 1998). The social cognitive
models do not view students as motivated or not motivated, nor do they assign a quantitative value to
motivation. Instead, social cognitive models of motivation emphasize that students can be motivated
in multiple ways and it is important to understand how a student is motivated (Linnenbrink &
Pintrich, 2002). Wentzel and Wigfield (1998) provide a comprehensive review of the literature on
academic motivation from a social cognitive perspective. The current theories of motivation focus on
four constructs: competence-related belief, control beliefs, subjective task values, and achievement
goal orientation. Though theoretical evidence supporting motivation as critical to academic success
is plentiful, Linnenbrink and Pintrich (2002) pointed out that there is a lack of empirical and
practical applications of these motivation theories. It is not clear what classroom characteristics or
interventions increase student motivation, as this has not been studied extensively. However, the
general literature about the relation between motivation and academic achievement is clear: higher
motivation is related to greater academic achievement.
The term study skills includes a range of cognitive skills and processes that work together
for the purpose of enhancing the effectiveness of learning (Devine, 1987), and includes acquiring,
recording, organizing, synthesizing, remembering, and using information (Hoover & Patton, 1995).
Many researchers have demonstrated that students who are academically successful demonstrate
effective study skills, whereas poor students do not demonstrate the same skills (Gettinger & Seibert,
2002). To benefit from instruction, students must be active participants in the learning process, and
utilizing effective study skills can facilitate this active participation. If students are monitoring their
own learning by organizing and synthesizing new information and then reviewing and remembering
information, they will be able to use the information at a later time. Study skills deficits can be seen
in elementary school, but deficits are more commonly seen and have a greater impact in middle and
high school.
Academic Enablers and Measures of Reading Achievement
Prior research has connected individual enablers to academic achievement, as described above,
but since DiPerna and Elliott introduced the term and concept of “academic enablers” research is
emerging about the collective benefit of academic enablers. Academic enablers explain the negative
association between various externalizing behaviors and academic outcomes (Demaray & Jenkins,
2011; Volpe et al., 2006), and account for a significant amount of variance in reading achievement for
children with characteristics of ADHD (DuPaul et al., 2004). DiPerna, Elliott, and colleagues found
support for their initial models regarding the role of academic enablers in reading achievement. The
model suggests that prior reading achievement and interpersonal skills influence motivation, which
in turn influences engagement and study skills. These two variables directly influence current reading
achievement. Prior reading achievement has an indirect effect on current reading achievement, via
its influence on motivation, but also has a direct effect on current reading achievement (DiPerna
et al., 2002). Overall, academic enablers represent a critical piece of the puzzle in determining what
it takes to be academically successful in reading.
Previous research, both theoretical and empirical, has determined that academic enablers play
an important role in reading achievement. However, before this research can be translated into
practical classroom applications, there is a question that needs to be answered. Are academic
enablers more important as determinants of teacher-evaluated classroom performance (i.e., grades),
Psychology in the Schools DOI: 10.1002/pits
382 Jenkins and Demaray
performance on standardized tests or curriculum-based measurement (CBM), or subjective teacher
judgments of academic skills? The current study is designed to test the link between academic
enablers and different measures of reading achievement to assess different relations between these
variables. Previous work by DiPerna and Elliott have only used teacher ratings as an indicator
of reading achievement (DiPerna et al., 2002), but success in reading is more than a score on a
subjective rating scale. Though different measures of reading achievement are positively correlated,
there may be different relations between academic enablers and different outcomes. For example,
classroom grades are likely influenced by academic skills and all four academic enablers (i.e.,
engagement, interpersonal skills, motivation, study skills) because each of the enablers are necessary
to be successful in the classroom. Classroom grades reflect test scores (requiring study skills and
engagement), homework (requiring motivation and engagement), and group projects (requiring
interpersonal skills and motivation). On the other hand, standardized test scores or performance on
curriculum-based measures may be more influenced by natural ability and quality of instruction
received, as well as several academic enablers (i.e., engagement, motivation, study skills).
The main goal of this study was to determine whether academic enablers are differentially
related to the reading outcomes of classroom grades, teacher-rated reading achievement, Reading
CBM, and standardized test scores. It was hypothesized that there would be a positive relation
between academic enablers and all academic outcomes; however, it was also predicted that more
variance would be accounted for between academic enablers and the more subjective measures of
reading achievement: grades and teacher ratings of skills (DiPerna & Elliott, 2000).
METHODS
Participants
There were 61 student participants in the current study with 27 third-grade students (44.3%), 22
fourth-grade students (36.1%), and 12 fifth-grade students (19.7%). The sample contained 33 males
(54.1%) and 28 females (45.9%). The sample was primarily White (n=59, 96.7%). Two cases were
not included in analyses due to incomplete data and were deleted listwise. All student participants
came from one elementary school building that houses students in kindergarten through fifth grade.
The demographic characteristics of this sample are representative of the entire school where the
student body was 90% White, 1% Black, 3% Hispanic, and 5% Asian, and 1% mixed race/other.
Approximately 3% of the student body was low income and 5% received language services due to
limited English proficiency.
In addition to the student participants, there were eight female teacher participants and one
male teacher participant; all teacher participants were White. Teaching experience ranged from 1 to
14 years with an average of 7.5 years. Two teachers held bachelor’s degrees and seven held master’s
degrees. Four of the teacher participants taught third grade, one teacher taught fourth grade, and
four teachers taught a multiage classroom of fourth- and fifth-grade students. Teacher participants
completed the ACES (DiPerna & Elliott, 2000) for students in their class who participated in the
study.
Measures
The ACES (DiPerna & Elliott, 2000) teacher-rated Academic Enabler subscales (i.e., engage-
ment, interpersonal skills, motivation, and study skills) and teacher-rated Reading subscale of the
Academic Skills scale were used in the current study. The ACES is a norm-referenced rating scale
for evaluating academic functioning of students in kindergarten through college. The ACES has
been standardized on a national sample of teachers and students. The sample for the teacher form
consisted of 1,000 students in four grade clusters.
Psychology in the Schools DOI: 10.1002/pits
Reading and Academic Enablers 383
Reliability for the Academic Skills Reading subscale is demonstrated through strong internal
consistency (coefficient alphas were .98 for Grades 3–5 grade cluster), a good test–retest correlation
of .97, and adequate inter-rater correlations ranging from .65 for the Academic Skills Scale when
rated by one English and one Math teacher. Reliability for Grades 3–5 grade cluster for the Academic
Enablers subscales of interpersonal skills, engagement, motivation, and study skills is demonstrated
through strong internal consistency (coefficient alphas of .97, .95, .97, and .96, respectively), good
test–retest correlations (.92, .92, .96, and .96, respectively). Evidence of inter-rater agreement was
based on English and Math teacher ratings on a sample of 181 students from Grades 6 to 12.
The manual reports correlations of .31, .42, .62, and .42 for the interpersonal skills, engagement,
motivation, and study skills subscales, respectively. Inter-rater agreement was not reported for
elementary students.
Validity for the ACES is demonstrated through factor analysis and correlations with similar
measures. The factor analysis showed a clear two-factor structure (i.e., academic skills and academic
enablers). Factor analysis within each scale demonstrated three and four factors for the Academic
Skills and Academic Enabler scales, respectively. The ACES teacher and student versions have a
moderate to strong associations with criteria of other measures, such as correlations with the Iowa
Test of Basic Skills (ITBS; Hoover, Hieronymus, Frisbie, & Dunbar, 1993) ranging from .38 to .87
and correlations with grade point averages ranged from .56 to .90 (DiPerna & Elliott, 2000).
Fourth quarter classroom reading grades and spring standardized test scores were collected for
all participants via school records. Classroom grades were transformed to the following scale: 4.25
=A+,4.00=A, 3.75 =A–, 3.25 =B+,3.00=B, 2.75 =B–, 2.25 =C+,2.00=C, 1.75 =C–,
1.25 =D+,1.00=D, .75 =D1, and .00 =F.
The standardized test administered to all students in the school as part of the end-of-year
evaluation was the Measures of Academic Progress (MAP), published by the Northwest Evaluation
Association (NWEA). The MAP is designed to identify the skills and concepts that individual stu-
dents have learned, monitor academic growth over time, and provide information about instructional
needs (NWEA, 2007). The test can be taken up to three times per year and is administered on a
computer. The spring scores were used in the current study. Reliability and validity studies have been
conducted on the MAP and published by the NWEA (NWEA, 2007). Internal consistency estimates
range from .94 to .95 for the third-, fourth-, and fifth-grade spring reading tests. Test–retest reliability
ranges from .87 to .91 when the same students took the test in the fall and spring of the same school
year. Concurrent validity was estimated by examining scores on the MAP and the Illinois Standards
Achievement Test; estimates were .80 for both third and fifth grades on the spring reading test.
CBM is a set of standardized and validated tests that measure academic skills in basic skill areas
(e.g., reading, math, and writing). These brief, timed tests can be given on a regular basis to monitor
a student’s academic progress (Shinn, 2002). Standardization is the key component to the usefulness
of this measure. The directions, scoring, choices of testing material, and interpretation of the results
are the same in every situation, so conclusions on progress can be drawn with confidence (Shinn,
2002). Reading fluency, sometimes referred to as oral reading fluency, is a measure of how quickly
and accurately a student can read connected text (Hosp, Hosp, & Howell, 2007). Students read aloud
for 1 minute and the total number of words read correctly (WRC) in 1 minute (total number of words
minus errors) is recorded. This process is repeated three times with three different reading probes
and the median value represents the student’s Reading CBM score. Reading fluency has been shown
to be a reliable and valid measure of reading ability (Hosp et al., 2007). For example, Hosp et al.
(2007) reported that Reading CBM word read correct has a test–retest reliability correlation of .90
at 1 week and .82 at 10 weeks (Marston, 1982), parallel forms reliability correlation of .94 (Tindal,
Germann, & Deno, 1983), and evidence of validity via a correlation of .83 with the ITBS (Jenkins,
Fuchs, van den Broek, Espin, & Deno, 2003).
Psychology in the Schools DOI: 10.1002/pits
384 Jenkins and Demaray
Tab le 1
Intercorrelations Matrix of Main Study Variables
1. Engagement
2. Interpersonal
Skills 3. Motivation
4. Study
Skills
5. Classroom
Grades
6. ACES
Reading Skills
7. Reading
CBM
8. Standardized
Test Scores
Mean (SD) 33.34 (7.27) 43.02 (7.40) 40.52 (10.42) 46.97 (8.39) 3.45 (.63) 38.83 (9.51) 50.00 (9.83) 218.85 (10.19)
1-
2.51
** -
3.73
** .71** -
4.66
** .60** .82** -
5.58
** .57** .67** .63** -
6.34
** .33*.49** .30*.54** -
7.32
*.13 .38** .23 .46** .59** -
8.31
*.08 .23 .06 .20 .54** .48** -
*p<.01. **p<.001.
For the current study, the reading fluency probes and administration and scoring procedure
guidelines were from Dynamic Indicators of Basic Early Literacy Skills (DIBELS, 2007). Classroom
teachers administered the reading fluency probes to students in their own classroom. All teachers
undergo CBM training at the beginning of the year, which is conducted by the school psychologist.
Refresher trainings are given prior to each benchmark period.
Procedures
Participants were recruited from a suburban school district in a middle-class community at one
elementary school. Participating teachers gave an informational letter and consent forms to students
to gain parental consent. Of the 180 consent forms that were sent out, 35% of them were returned
with positive consent, 9% of parents denied consent for their child’s participation, and the remaining
consent forms were not returned for unknown reasons. Spring CBM scores were collected by the
classroom teacher in the second and third week of May. The median of three reading probes was used
in analyses. Spring MAP assessments were administered the second week of May. Fourth quarter
grades were provided by the teacher during the final week of school, which was the fourth week of
May. Teachers were given 3 weeks to complete the ACES rating scales, which occurred during the
second to fourth week of May. Teachers rated between 4 and 10 students (M=6.6).
CBM data were collected for each student at their respective grade level. Probes were stan-
dardized to be able to compare scores across all grade levels. Raw scores for Reading CBM were
standardized by transforming the median scores to z-scores by subtracting the respective grade-level
mean from the raw score and dividing by the respective grade-level standard deviation. Then to make
the scores more interpretable, all z-scores were converted to a T-scale by multiplying each score by
10 (the standard deviation of a T-scale) and adding 50 (the mean of a T-scale).
RESULTS
Refer to Table 1 for intercorrelation, means, and standard deviations of the main study variables.
Among the four academic enablers, there were moderate to large positive correlations between the
variables. For classroom grades and teacher-reported reading skills, all enablers were positively
correlated. For Reading CBM, engagement, and motivation were significantly and positively related,
but only engagement was significantly related to standardized test scores.
Four separate simultaneous multiple regressions were conducted to answer the main study
question (i.e., Are academic enablers differentially related to the reading outcomes of classroom
grades, teacher-rated reading achievement, Reading CBM, and standardized test scores?) Academic
Psychology in the Schools DOI: 10.1002/pits
Reading and Academic Enablers 385
Tab le 2
Summary of Regression Analyses, With 95% Confidence Intervals, of Academic Enablers Predicting Academic
Outcomes
Academic Measure Independent Variable BLower Upper SE B βAdjusted R²
Classroom Grades Engagement .014 –.014 .042 .01 .16 .45***
Interpersonal Skills .016 –.010 .041 .01 .19
Motivation .015 –.015 .044 .01 .24
Study Skills .015 –.015 .045 .01 .21
ACES Reading Skill Engagement –.001 –.455 .452 .23 –.00 .22**
Interpersonal Skills –.037 –.462 .388 .21 –.03
Motivation** .688 .226 1.151 .23 .76
Study Skills –.334 –.799 .130 .23 –.29
Reading CBM Engagement .153 –.343 .648 .25 .11 .16**
Interpersonal Skills –.376 –.841 .088 .23 –.28
Motivation*** .689 .184 1.194 .25 .72
Study Skills –.315 –.822 .192 .25 –.26
Standardized Test Engagement .483 –.027 .993 .25 –.14 .11*
Interpersonal Skills –.191 –.669 .287 .24 .35
Motivation .421 –.099 .941 .26 .44
Study Skills* –.532 –1.054 −.009 .26 .45
*p<.05. **p<.01. *** p<.001.
Enabler subscales served as independent variables and the four different academic outcomes (i.e.,
classroom reading grades, ACES reading skills, Reading CBM, and standardized test scores) served
as dependent variables. All of the regressions were significant. For classroom reading grades, there
was no unique individual predictor, but collectively, all four academic enablers accounted for 45%
of the variance. For ACES reading skills, motivation was a significant individual predictor (β=
.765, p<.01). Collectively, academic enablers accounted for 22% of the variance. Motivation
was also an individual predictor (β=.719, p<.01) for Reading CBM with academic enablers
collectively accounting for 16% of the variance. Finally, for standardized test scores, study skills
were a significant individual predictor (β=.446, p<.05), and 11% of the variance was accounted for
by academic enablers. Refer to Table 2 for unstandardized betas, standard errors, standardized betas,
and adjusted R². Because previous work has found that the independent variables in these analyses
are correlated, multicollinearity was a concern. The variance inflation factor (VIF) estimates were
below 5.0 in all regressions (ranging from 2.1 to 2.2 for engagement, 1.9 to 2.0 for interpersonal
skills, 3.1 to 3.5 for study skills, and 4.7 to 4.8 for motivation).
DISCUSSION
The academic competence model proposed by DiPerna et al. (2002) stated that academic
competence comprises both academic skills and academic enablers. For example, students could
have high levels of engagement and motivation, but without academic skills they may not be
academically successful. Similarly, the ability to acquire academic skills might be truncated by lack
of motivation, unwillingness to cooperate, inability to remain engaged, and/or inability to synthesize
knowledge and apply it in new contexts.
The purpose of the current study was to examine the relations among academic enablers and
different measures of reading achievement: classroom grades, global ratings of reading achievement,
Reading CBM, and standardized test scores. Little research has been conducted examining specific
Psychology in the Schools DOI: 10.1002/pits
386 Jenkins and Demaray
relations between academic enablers and different reading measures. In general, the findings of the
current study support previous findings that have shown that academic enablers are important for
academic achievement (e.g., DiPerna et al., 2002). Though a student who performs well on one
academic measure (e.g., standardized tests) is likely to perform well on another academic measure
(e.g., classroom reading grades), there may be differences in performance because the various tasks
require students to utilize unique strategies to perform well. Results of the current study underscore
the importance of academic enablers in many types of academic measures, which is a contribution
to the current academic enabler literature since previous research has relied on teacher ratings.
In the current study, results indicate that academic enablers were significantly related to every
measure of reading achievement. There was a significant positive relation between academic enablers
and all measures of academic achievement in reading (i.e., classroom reading grades, teacher-rated
reading skills, reading fluency, and standardized test scores). In addition, motivation emerged as
a significant individual predictor for teacher-rated reading skills and reading fluency. Study skills
were a significant predictor for standardized test scores. These results suggest that, overall, academic
enablers are important for all measures of academic achievement, but motivation and study skills
may play an especially crucial role in reading achievement. Motivation and study skills are two
enablers that might be beneficial across academic settings and tasks. DiPerna (2006) demonstrated
that motivation had the highest correlations with measures of academic achievement. Depending
on the grade level, study skills followed motivation in terms of correlations with achievement. At
younger grade levels, academic engagement had higher correlations with achievement than study
skills, but as students approach late elementary school, study skills become more important than
engagement. Study skills can be used in many different settings and with all academic tasks and allow
students to independently gain and process new information. Motivation, in particular, may be a key
to success in school. In fact, there is evidence that motivation not only works as an indirect “enabler”
of success, but also directly impacts academic achievement (Wentzel, 1999, 2002; Wigfield et al.,
2006).
One theory of academic motivation, the expectancy-value theory, posits that motivation is the
product of expectations for success (i.e., an individual’s belief that they will be successful) and
values (i.e., the importance that an individual places on a task). Expectations are strongly related to
actual classroom achievement, but values are strongly related to initiating and persisting toward a
short- or long-term goal (e.g., Schunk et al., 2008). Because components of motivation are related
to task initiation and completion, as well as classroom achievement, motivation may serve as an
“enabler of enablers.” Motivated students may be positively reinforced by their parents and teachers
for demonstrating skills and may seek out additional opportunities to continue to learn and apply
their skills.
When examining the variance accounted for by academic enablers, classroom grades had the
greatest amount of variance accounted for (45%), followed by global rating of reading skill (22%),
Reading CBM (16%), and standardized test scores (11%). It seems that academic enablers play a
fairly large role in classroom grades, but additional variable(s) are at work for skill-based assessments
such as Reading CBM and standardized test scores. Natural ability, instructional and curricular
effectiveness, parental support, etc., might play a large role, which are not directly accounted for
by the academic enabler ratings. The reading achievement measures in the current study could
be conceptualized into two different categories: academic skills and academic success. Academic
skills, which are quantitative and objective in nature, might include the Reading CBM scores and
standardized test scores. Academic success, on the other hand, may represent achievement indicators
that are more qualitative or subjective, in this case classroom grades and teacher-rated reading skills.
Students who are viewed as “academically successful” are likely the students who not only receive
high grades and possess strong academic skills, but those who also are engaged, motivated, and get
Psychology in the Schools DOI: 10.1002/pits
Reading and Academic Enablers 387
along with others in their classroom. In the current study, academic enablers accounted for the most
variance in classroom grades (45%) and teacher-rated reading skills (22%), which would fall into the
hypothetical class of academic success, instead of academic skills. Classroom grades and subjective
teacher ratings are based on many variables, including academic skills, but are also influenced by
other variables such as class participation, ability to work in a group, and homework completion, all
of which require or are considered academic enablers.
Limitations and Future Directions
There are several notable limitations that could be addressed in future studies. First, the sample
was limited in size as well as was highly homogeneous. Future studies should use larger sample
sizes as well as seek out a more heterogeneous sample with respect to grade level, ethnicity, and
socioeconomic status. Second, given the small sample size it is was not possible to explore gender
differences in the levels of academic enablers or associations with the different reading achievement
outcomes. Previous work has noted that girls tend to be rated as having higher levels of academic
enablers (DiPerna et al., 2005), so differences in these associations might be expected. Third, the
current study focused only on reading achievement measures. DiPerna and colleagues (2002, 2005)
found slightly different relations between academic enablers and academic achievement when testing
models for reading and Math achievement. Fourth, though it was not within the scope of the current
study, future studies should consider examining differences between students with and without
learning difficulties with respect to the pattern of how different enablers are associated with various
academic outcomes. Preliminary evidence suggests that students with school difficulties have lower
levels of academic enablers (Demaray & Jenkins, 2011; DiPerna & Elliott, 2000), therefore it is
likely to expect differences in the interrelations between these variables and academic achievement.
Finally, the manual for the ACES does not provide evidence of inter-rater agreement for elementary
students, which was the population of interest in the current study. The level of inter-rater agreement
between English and Math teachers for Grades 6–12, which was reported, was not strong, ranging
from .31 to .62, with motivation having the lowest level of inter-rater agreement.
Generalization and Implications
To be successful in academics, one not only has to have academic skills, but also academic
enablers. When a student is struggling in academics, school psychologists and educators are en-
couraged to determine whether the problem is due to a performance deficit or a skill deficit. If the
student has a skill deficit in a particular area, then an academic skill intervention may be successful
by itself. However, if the problem is due to a performance issue, then increasing academic enablers
(i.e., study skills, motivation, and engagement) could make an academic skill intervention more
successful. Overall, while academic enabler interventions alone may not always solve academic
achievement issues, when coupled with an intervention that teaches a skill, the student may have
a better likelihood of succeeding. Results suggest that academic enablers are an important part of
academic success in reading, but when considering the variance accounted for by academic enablers,
they alone are not likely to improve Reading CBM scores or standardized test scores. Finally, for
researchers studying academic enablers and related concepts, the strength of the association between
academic enablers and academic outcomes may vary based on the way that the academic outcome
is measured.
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