Fuchs, L. S., Fuchs, D., Seethaler, P. M., Cutting, L. E., & Mancilla-Martinez, J. (2019). Connections between reading comprehension and word-problem solving via oral language
comprehension: Implications for comorbid learning disabilities. In L. S. Fuchs & D. L.
Compton (Eds.), Models for Innovation: Advancing Approaches to Higher-Risk and HigherImpact Learning Disabilities Science. New Directions for Child and Adolescent Development,
165, 1–18.
5
Connections Between Reading
Comprehension and Word-Problem
Solving via Oral Language Comprehension:
Implications for Comorbid Learning
Disabilities
Lynn S. Fuchs, Douglas Fuchs, Pamela M. Seethaler,
Laurie E. Cutting, Jeannette Mancilla-Martinez
Abstract
In this article, we discuss the approach adopted within the Vanderbilt University
Learning Disabilities Innovation Hub, which focuses on students with higherorder comorbidity: students with concurrent difficulty with reading comprehension and word-problem solving. The aim of the Hub’s Research Project is to test
what we refer to as the higher-order comorbidity hypothesis: that language comprehension plays a critical role in reading comprehension and word-problem
solving. In the Hub’s study, we test the hypothesize that language comprehension offers a coordinated approach for improving both outcomes and that this
approach thus provides direction for understanding higher-order comorbidity
and support for the validity of reading comprehension and word-problem solving
This research was supported by 2 P20 HD075443 and Core Grant HD15052 from the
Eunice Kennedy Shriver National Institute of Child Health & Human Development to
Vanderbilt University. The content is solely the responsibility of the authors and does not
necessarily represent the official views of the Eunice Kennedy Shriver National Institute
of Child Health & Human Development or the National Institutes of Health.
NEW DIRECTIONS FOR CHILD AND ADOLESCENT DEVELOPMENT, no. 165, May 2019 © 2019 Wiley Periodicals, Inc.
Published online in Wiley Online Library (wileyonlinelibrary.com). • DOI: 10.1002/cad.20288
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comorbidity as a learning disabilities subtyping framework. In the first segment
of this article, we describe a model that connects reading comprehension and
word-problem solving development via oral language comprehension, and we
provide a brief overview of prior related research on these connections. This
first section provides the basis for the second segment of this article, in which
we discuss the Vanderbilt Hub’s innovative approach for investigating these connections. This study tests a theoretically-coordinated framework on students’
performance in both high-priority domains of academic development, while
exploring effects for boys versus girls and for linguistically diverse learners.
© 2019 Wiley Periodicals, Inc.
T
he Vanderbilt Learning Disabilities Innovation Hub, funded by the
Eunice Kennedy Shriver National Institute of Child Health and
Human Development, addresses a vulnerable, understudied, and
underserved subgroup of the learning disabilities population: students with
comorbid difficulty in two critical areas, reading comprehension and math
word-problem solving. This form of learning disability occurs frequently
(Landerl & Moll, 2010; Mann Koepke & Miller, 2013), and as Koponen
et al. (2018) observed, half of children with poor performance in one
domain also have difficulty in the other domain.
Moreover, students with such comorbidity experience worse outcomes
in each area than do peers with difficulty in only one of these domains
(Cirino, Fuchs, Elias, Powell, & Schumacher, 2015; Willcutt, Petrill et al.,
2013), and comorbidity is associated with inadequate response to generally effective intervention (Fuchs, Fuchs, & Prentice, 2004). Nonetheless,
the problem of cooccurring reading and math difficulty is understudied:
The literature is small; most studies are descriptive; and most investigations focused on reading and math difficulty define comorbidity in terms
of lower-order skill: calculations and word reading. In this article, we refer
to difficulty across reading comprehension and word-problem solving as
higher-order comorbidity.
Students with higher-order comorbidity also represent an especially
vulnerable learning disability subtype for two reasons. First, reading
comprehension is a strong predictor of quality of life, financial security, and
life expectancy (Batty, Kivimaki, & Deary, 2010; Meneghetti, Carretti, &
De Beni, 2006; Ritchie & Bates, 2013; Taraban, Rynearson, & Kerr, 2000).
Limited reading comprehension decreases access to content knowledge
and undermines learning during and after formal schooling. Second,
word-problem solving is the best school-age predictor of adult employment
and wages (Every Child a Chance Trust, 2009; Murnane, Willett, Braatz, &
Duhaldeborde, 2001), and it represents a major emphasis in almost every
strand of the math curriculum from kindergarten through high school.
So word-problem solving difficulty limits school as well as occupational
success. It is therefore highly problematic that schools struggle to provide
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students with intervention in more than one domain. Typically, reading
intervention takes priority over math intervention, which leaves students
with comorbid reading and math learning disability without the math
intervention they require to succeed.
In this article, we discuss the Vanderbilt Hub’s approach to studying
students with higher-order comorbidity. In the first segment of this article,
we describe a framework that connects reading comprehension and wordproblem solving development via oral language comprehension, and we
establish connections between oral language comprehension and reading
comprehension (Catts, Hogan, & Adolf, 2005; Gough & Tunmer, 1986;
Peng et al., 2019) and between language comprehension and word-problem
solving (Bernardo, 1999; Fuchs et al., 2010a, 2008; Van der Schoot, Bakker
Arkema, Horsley, & Van Lieshout, 2009). This first segment provides the
basis for the article’s second segment, focused on the Vanderbilt Hub’s innovative approach for investigating connections between reading comprehension and word-problem solving via language comprehension. This study
tests a theoretically coordinated framework for scaffolding performance in
both high-priority domains of academic development, while exploring disaggregated effects for boys versus girls and for native and nonnative English
speakers.
Connections Between Reading Comprehension and
Word-Problem Solving via Oral Language Comprehension
Framework. Reading comprehension and word-problem solving differ in some transparent ways. For example, most reading passages, because
they are more extended than the typical word problem, make stronger
demands on inferencing and background knowledge than occurs with word
problems. On the other hand, in word problems, representing the text is
not the final goal. Instead, students answer the word problem’s question,
which requires representing the text with a number sentence that includes
a missing quantity, deriving the mathematical result, evaluating whether the
answer is computationally reasonable and correct, and communicating the
solution (Jiménez & Verschaffe, 2014).
Even so, based on theories of reading comprehension, discourse processing, and word-problem solving (Perfetti, Yang, & Schmalhofer, 2008;
Rapp, van den Broek, McMaster, Kendeou, & Espin, 2007; Verschaffel &
De Corte, 1997), representations of texts, including reading passages and
word-problem statements, necessarily have three components. The first
involves constructing a coherent microstructure and deriving a hierarchical
macrostructure to capture the text’s essential ideas. The second component
is the situation model, which requires supplementing the text with inferences based on the reader’s prior knowledge. With the third component,
the reader derives a problem model or schema to match the passage’s or
word-problem statement’s content.
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Kintsch and Greeno (1985) posited that although the comprehension
strategies, the nature of required knowledge structures, and the form of
resulting structures, inferences, and problem models differ by task, the general features of this process apply across stories, informational passages,
and word problems. Reading passages and word-problem statements alike
require individuals to build the propositional text structure, inference, and
identify schema, and this processing makes strong demands on reasoning
and working memory. In reading passages or word-problem statements, the
child processes the propositional text base to sequentially fill the slots of a
model that evolve over the passage. This involves coding relevant objects,
actors, and actions (as well as quantities for word problems), across segments of text, while resorting information as new ideas alter hypotheses
about the situation and the schema.
Because the processes by which stories and informational text are
understood more thoroughly (e.g., Perfetti, Yang, & Schmalhofer, 2008;
Rapp, van den Broek, McMaster, Kendeou, & Espin, 2007) than is the case
for word-problem solving, we illustrate text comprehension processes in
the context of word problems. Note, however, that the Vanderbilt Hub and
its Project study address text comprehension and word-problem solving in
equal measure and in parallel ways.
Consider the text processing required for a combine word problem
(Part 1 plus Part 2 equals Total or P1 + P2 = T): Joe has 3 marbles. Tom
has 5 marbles. Tom also has 2 balls. How many marbles do the boys have in
all? A low-risk child processes sentence 1’s propositional text base to identify that object = marbles; quantity = 3; actor = Joe; but Joe’s role = to
be determined (TBD). This is placed in short-term memory. In sentence 2,
propositions are similarly coded and held in memory. In sentence 3, balls
fails to match the object code in sentences 1 and 2, signaling the number 2
as perhaps irrelevant; this is added to memory. In sentence 4, the question,
the quantitative proposition how many marbles and the phrase in all cues the
child to identify the combine schema; assign the role of superset (Total) to
the question; assign subset roles (Parts 1 and 2) to the TBDs in memory; and
reject 2 balls. Filling in these slots of the schema triggers a set of problemsolving strategies.
With typical school instruction, children gradually construct the
combine schema on their own, just as they devise their own strategies for
handling the demands on reasoning and working memory that this text processing, problem-solving sequence involves. Errors are viewed as failures
(a) to produce the intended mental representations with respect to the three
components in preceding paragraph or (b) to manage demands on reasoning and working memory. Such demands are well documented for reading
comprehension (e.g., Berninger et al., 2010; Eason, Goldberg, Young, Geist,
& Cutting, 2012; Swanson, & Jerman, 2007) and word-problem solving
(e.g., Fuchs et al., 2010a, 2010b).
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Unfortunately, children with reading comprehension or word-problem
solving difficulty fail to discover schemas on their own, and demands often
exceed their reasoning and working memory capacity. Direct skills intervention (in reading comprehension or word-problem solving) for students
with reading comprehension or word-problem solving difficulty explicitly
teaches step-by-step strategies to help children derive the intended mental representation and formulate connections among the propositional text
base, the situation model, and the schema (or model) in ways that reduce
reasoning and working memory demands.
For example, schema-based word-problem solving tutoring (Fuchs
et al., 2009, 2014) explicitly teaches at-risk children step-by-step strategies
that begin with identifying word-problem statements as combine, compare,
or change schema. Then children are taught to build the propositional
text structure. Schema-based word-problem solving tutoring facilitates
connections among the situation model, schema, and productive solution
strategies by making these connections explicit, while reducing demands on
reasoning and working memory.
More specifically, with schema-based word-problem solving tutoring,
the child RUNs through the problem: Reads it, Underlines the question
in which the object code (marbles) is revealed, and Names the explicitly
taught (combine) schema. This prompts the child to write the combine
meta-equation, P1 + P2 = T (Part 1 plus Part 2 equals Total). The child then
rereads the problem statement and while rereading, writes replacements for
P1 and P2 (quantities for each relevant “part”) and crosses out irrelevant
objects and numbers. This reduces the burden on reasoning and working
memory and provides the equation for problem solving. This in turn
prompts the counting-up adding strategy (also taught in schema-based
word-problem solving tutoring). Word-problem solving and reading
comprehension interventions that compensate for reasoning and working
memory demands with explicit skills instruction, such as schema-based
word-problem solving tutoring, have proven effective in improving reading
comprehension (Fuchs et al., in press; Jitendra, Hoppes, & Xin, 2000;
Williams, Hall, & Lauer, 2004; Williams et al., 2014) or word-problem
solving (Fuchs et al., 2014; Fuchs et al., 2009).
More pertinent to Vanderbilt Hub and the present article, Kintsch
and Greeno (1985) and Rapp, van den Broek, McMaster, Kendeou, and
Espin (2007) further posited that competent performance in each domain
also relies heavily on language comprehension processes. As per Kintsch
and Greeno, in word-problem solving, children “understand important
vocabulary and language constructions prior to school entry” (p. 111) and
“through instruction in arithmetic and word-problem solving, learn to treat
these words in a special, task-specific way, including extensions to ordinary
usage for terms (e.g., all or more) to more complicated constructions involving sets (in all and more than)” (p. 111). In reading comprehension, because
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or therefore acquires special meaning within cause-effect passages to prime
readers to search for and connect consequences with trigger events.
The assumption is that students have the necessary language comprehension abilities to understand text and problem statements to derive
appropriate problem models. Yet, assuming children with limitations in language comprehension will learn to treat domain-specific words in a special
task-specific manner through school exposure to reading comprehension
and word-problem solving tasks is tenuous, and this may be particularly so
for nonnative English speakers (Mancilla-Martinez & Lesaux, 2010, 2011)
and other at-risk and diverse populations.
In the case of word problems, Cummins, Kintsch, Reusser, & Weiner
(1988) computationally modeled errors with two types of defects: incorrect math problem-solving processes versus language comprehension processing errors. Correct problem representation depended more on language
comprehension, and changing wording in minor ways dramatically affected
accuracy. To illustrate how word-problem solving taxes language comprehension, consider this combine problem: Joe has 3 cats. Tom has 5 dogs.
Tom has 2 plants. How many pets do the boys have in all? Objects in this
text increase demands on language comprehension for assigning roles for
the propositional text structure (despite similar demand for inducing the
schema), due to more sophisticated representations of vocabulary involving
taxonomic relations at superordinate levels and subtle distinctions among
categories (dogs + cats = pets; plants are not pets). All this suggests that
instruction focused on language comprehension processes as well as the
mathematical aspects of word-problem solving is required within tutoring,
with an explicit focus on strengthening word-problem language for building
propositional, situational, and schema representations. These ideas apply
equally well in the domain of reading comprehension.
For this reason, the Hub’s innovative approach involves embedding reading comprehension–language comprehension instruction within
reading comprehension direct skills instruction and embedding parallel
word-problem solving-language comprehension instruction within wordproblem solving direct skills intervention. Before explaining that approach,
we briefly describe some recent studies examining connections between
reading comprehension, word-problem solving, and oral language comprehension.
Some Recent Studies. Some prior work examining concurrent relations between reading comprehension and word-problem solving suggest an association. For example, Vilenius-Tuohimaa, Aunola, and Nurmi
(2008) reported substantial shared variance across reading comprehension
and word-problem solving when controlling for foundational reading skill.
Swanson, Cooney, and Brock (1993) identified reading comprehension as a
correlate of word-problem solving while controlling for working memory,
knowledge of operations, word-problem propositions, and calculation skill.
Boonen, van der Schoot, Florytvan, de Vries, and Jolles (2013) found that
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reading comprehension had medium to large relations with word-problem
solving. Although this relation was not evident at the word-problem itemlevel in Boonen, van Wesel, Jolles, and van der Schoot (2014), the authors
indicated that their word-problem items did not involve the semantic complexity that warrants strong reliance on reading comprehension.
Cirino, Child, and Mcdonald (2018) extended the concurrent literature by longitudinally assessing the role of domain-specific and general
predictors in kindergarten and multiple types of reading and mathematics
outcomes in first grade. The correlation between first-grade reading comprehension and math problem solving was .67. After partialling all 11 predictors, the correlation decreased to .21, which corresponds to an R2 value
of .04. This suggests commonality in the underlying sources of variance
contributing to reading comprehension and word-problem solving. Surprisingly, however, language was differentially predictive of math problem
solving compared to reading comprehension. This may be due to the age
level of the participants, because first-grade reading comprehension relies
more heavily on word reading than vocabulary knowledge (Garcia & Cain,
2014).
Also relying on a longitudinal design, Fuchs, Fuchs, Compton,
Hamlett, and Wang (2015) assessed second graders early in the year on general language comprehension, working memory, nonlinguistic reasoning,
processing speed, and foundational reading and math skill. At the end of the
year, the children were assessed on word-problem specific language, reading comprehension, and word-problem solving. Path analytic mediation
analysis indicated the effect of general language comprehension on reading
comprehension was entirely direct, whereas the effect of general language
comprehension on word-problem solving was partially mediated by wordproblem specific language comprehension. Yet, across both domains, effects
of working memory and reasoning operated in parallel ways. These findings
are in line with Kintsch and Greeno (1985), who suggested that operating
on word problems and conventional reading passages require parallel processes that tax language comprehension, working memory, and reasoning.
More recently, Fuchs, Gilbert, Fuchs, Seethaler, and Martin (2018)
extended this literature by testing effects of initial reading comprehension
using a broad-based measure of reading comprehension (Gates–MacGinitie
Reading-Comprehension [MacGinitie et al., 2002]), on year-end wordproblem solving. We examined the specificity of effects by contrasting
the contribution of the Gates to later word-problem solving against
Gates’s effects on later calculations. Based on studies indicating (a) shared
concurrent variance between reading comprehension and word-problem
solving (Boonen et al., 2013, 2014; Swanson et al., 1993; Vilenius-Tuohimaa
et al., 2008), (b) substantially similar patterns of cognitive and linguistic
predictors across reading comprehension and word-problem solving (Fuchs
et al., 2015), and (c) shared but some distinctive predictive patterns for
word-problem solving versus calculations (Fuchs et al., 2008; Swanson &
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Beebe-Frankenberger, 2004), we hypothesized that the effects of Gates are
stronger on word-problem solving than on pure calculations. Conversely,
we expected simple, initial arithmetic skill to predict year-end, more complex calculations more strongly than either of the year-end word-problem
measures.
More highly relevant to the Vanderbilt Hub’s focus, we also explored
the role of start-of-year language comprehension in word-problem solving
while controlling for start-of-year Gates performance. Consistent with
Kintsch and Greeno (1985) and given studies documenting connections
between language comprehension and reading comprehension (Catts,
Hogan, & Adolf, 2005; Gough & Tunmer, 1986; Peng et al., 2019) and
between language comprehension and word-problem solving (Bernardo,
1999; Fuchs et al., 2010a, 2008; Van der Schoot et al., 2009), we expected
the effects of start-of-second-grade language comprehension to be stronger
on both end-of-second-grade word-problem solving outcomes than on
calculations.
On one hand, we found that language comprehension strongly and
uniquely predicted later word-problem solving. We also found that Gates
performance was a strong predictor of later word-problem solving. On the
other hand, we found that Gates was not a specific predictor of wordproblem solving (i.e., it also predicted later calculations), which raises
questions about what general measures of reading comprehension actually
assess. (A discussion of this finding is beyond the scope of the present article. See instead Fuchs et al., 2018.)
More pertinently, finding a stronger role for language comprehension in
word-problem solving than in calculations, while controlling for effects of
reading comprehension (which is expected to share variance with language
comprehension and therefore compete with language comprehension
as a predictor of word-problem solving), strengthens prior evidence
for the importance of language comprehension within word-problem
solving. Moreover, a common role for language comprehension across
word-problem solving and reading comprehension represents an important
connection between the two academic domains.
A Theoretically Coordinated Framework for Synergistically
Improving Performance in Both High-Priority Domains of
Academic Development
Finding that the cognitive, linguistic, and academic predictors of wordproblem solving are separable from those involving pure calculations,
while finding a stronger role for language comprehension in word-problem
solving over calculations, also indicates that word-problem solving is
connected to reading comprehension. At the same time, the literature
convincingly demonstrates the critical role language plays in reading
comprehension (e.g., Catts et al., 2005; Gough & Tunmer, 1986; Peng et al.,
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2019). Together, this suggests an important role for reading comprehension
instruction within word-problem solving instruction as well as the need for
a focus on language instruction in improving performance in both domains.
For word problems, a strong focus on language includes but is not
limited to word-problem-specific vocabulary and syntactic knowledge (e.g.,
understanding the distinction between more than and then there were more;
that the cause and effect in change word-problem solving may be presented
in either order within word-problem statements). Such an approach is consistent with recent calls (Catts & Kamhi, 2017; Ukrainetz, 2017) to intimately connect an instructional focus on oral language to specific reading
comprehension task demands, even as that instruction targets the subset of
learners with language deficits for such embedded language comprehension
instruction.
An integrated approach with a deliberate focus on the reading
comprehension demands of word-problem solving and the language that
connects reading passage and word-problem processing may also include
methods to assist students in constructing explicit text-level representations, generating text-connecting inferences, retrieving general as well as
math-specific background knowledge, and integrating that knowledge with
information in text-level representations (Perfetti et al., 2008; Rapp et al.,
2007; Verschaffel & De Corte, 1997). All this is in the service of building the
situation and the problem model or schema of the reading passage or word
problem statement.
In this vein, the Vanderbilt Hub’s research project innovatively tests
whether the effects of conceptual scaffolding designed to connect reading comprehension, word-problem solving, and language comprehension
may ultimately provide direction for a theoretically coordinated approach
for simultaneously improving performance across reading comprehension
and word-problem solving. This includes, for example, addressing causeeffect informational text structure (a topic typically reserved for reading
comprehension) in conjunction with change word problems (in which an
event serves to increase or decrease a starting amount, thereby creating a
new ending amount) or connecting compare-contrast informational text
structure (again, a topic typically reserved for reading comprehension) in
conjunction with word problems that compare quantities.
Testing effects of an approach that is designed to focus on reading
comprehension and word problems in coordinated fashion would extend
theoretical understanding of both domains. This line of work is potentially important for three additional reasons, as discussed at the beginning of this article. First, students with comorbid learning disorders across
reading comprehension and word-problem solving represent an especially
vulnerable subset of the learning disabilities population; reading comprehension is a strong predictor of quality of life, financial security, and life
expectancy (Batty et al., 2010; Meneghetti et al., 2006; Ritchie & Bates,
2013); and word-problem solving is the best school-age predictor of later
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employment and wages (Every Child a Chance Trust, 2009; Murnane et al.,
2001). Second, students with concurrent difficulty perform lower in each
domain than students with difficulty in just one academic domain (Willcutt
et al., 2013). Third, schools experience substantial challenges in providing
students with intervention on more than one academic domain. Because
reading often takes priority over math in the early grades, many comorbid
students receive reading intervention as they fall further behavior in math.
A coordinated approach for addressing reading comprehension and wordproblem solving would alleviate this logistical problem.
In the Vanderbilt Hub’s study, we randomly assign second-grade children with comorbid difficulty across reading comprehension and wordproblem solving to three study conditions. The first condition focuses on
conceptual scaffolding on reading comprehension with an embedded focus
on language comprehension that spans reading comprehension and wordproblem solving. The second condition provides conceptual scaffolding on
word-problem solving with an embedded focus on language comprehension
that spans word-problem solving and reading comprehension. The third
condition is a business-as-usual control group (the classroom and interventions schools typically provide). This study ran its first cohort of participants during the 2017–2018 academic year. At the time of this publication,
the study was still in progress.
The study’s specific aim is to test what we refer to as the higher-order
comorbidity hypothesis: Language comprehension plays a critical role in
reading comprehension and word-problem solving and provides direction
for understanding higher-order comorbidity, thus offering a coordinated
approach for improving both outcomes and lending support for the validity
of reading comprehension and word-problem solving comorbidity as an LD
subtyping framework.
We ask two questions. The first is whether conceptual scaffolding
on one academic domain with an embedded focus on language comprehension that spans both academic domains (reading comprehension and
word-problem solving (conditions 1 and 2) produces aligned and reciprocal advantages over the control group. We expect aligned effects favoring
reading comprehension scaffolding over control on reading comprehension
outcomes and favoring word-problem solving scaffolding over control on
word-problem solving outcomes. More central to the comorbidity hypothesis, we also hypothesize reciprocal effects, with stronger performance over
control for embedded language comprehension within reading comprehension on word-problem solving outcomes and with stronger performance
over control for embedded language comprehension within word-problem
solving on reading comprehension outcomes. Our second question is
whether aligned and reciprocal effects in part occur indirectly, via improved
understanding of the language of reading comprehension or the language of
word-problem solving. We hypothesize indirect effects via the aligned form
of domain-specific language comprehension on both outcomes.
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Thus, our focus on language comprehension is the vocabulary
and syntax addressed in the reading comprehension and word-problem
solving scaffolding. This focus maps onto prior studies documenting
relations of vocabulary and syntax with various forms of mathematics. For
example, Hornburg, Schmitt, and Purpura (2018) found that preschoolers’
mathematical language was more strongly related than general expressive
vocabulary to word-problem performance and other numeracy skills.
Chow and Ekholm (2019) identified concurrent relations between receptive
syntax and addition operations and understanding at first and second grade.
Gjicali, Astuto, and Lipnevich (2019) examined longitudinal relations
between language and numeracy skills in predominantly high-poverty children. Children were 1–4 years when language skills were assessed; 4–7 years
when number skills were assessed. Language comprehension was indirectly
related to number identification and number relations via oral counting.
Exploratory Hypotheses and Development of a Neuroimaging
Paradigm
We also consider two exploratory issues to provide insight into the robustness of effects and to address issues of diversity and inclusiveness: whether
aligned and reciprocal effects for comorbid students differ for boys versus
girls or for nonnative English speakers versus native English speakers and
whether pretest English proficiency among nonnative English speakers
moderates intervention effects.
Across studies on the mathematics performance for girls versus boys,
performance differences between males versus females appear to increase
with three variables: as grade level increases, with more complex mathematics demands on visual-spatial resources, and among higher-achievers
(Stoet, Bailey, Moore, & Geary, 2016). On this basis, we do not expect a
main effect for girls versus boys in second-grade students with comorbid
learning disability. Our exploratory issue is, however, about an interaction:
whether the pattern of word-problem solving scaffolding effects differs for
boys versus girls. We did not locate any study disaggregating word-problem
solving intervention effects for boys versus girls. Because differential effects
of word-problem solving intervention for girls versus boys have been tested
infrequently if at all, we examine scaffolding effect sizes for boys versus girls
to explore the robustness of effects.
In reading comprehension intervention research, the issue of differential effects for girls versus boys also has received little attention. Here, we
also did not locate any intervention study separating effects. In a synthesis, however, Suggate (2016) reported a correlation between percentage of
boys in the studies and outcome (outcome was aggregated across reading
constructs, i.e., it was not specific to reading comprehension). The correlation was −.15 at posttest; −.31 at follow up (favoring girls). As with wordproblem solving, because few relevant analyses are available and none for
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comorbid samples, we examine effect sizes for boys versus girls to explore
the robustness of effects.
The literature on differential word-problem solving or reading comprehension intervention effects for nonnative English speakers versus native
English speakers is similarly thin. It fails to provide the basis for hypotheses, especially for comorbid nonnative English speaking samples. Yet, the
school-age population of nonnative English speakers is growing rapidly
(National Center for Education Statistics, 2017; McFarland et al., 2017),
and databases reveal a main effect, in which nonnative English speakers’ math and reading performance falls substantially below that of native
English speakers (National Center for Education Statistics, 2017). Moreover, in this population, studies document the relation of vocabulary
and/or syntax with word-problem solving (e.g., Foster, Anthony, Zucker, &
Branum-Martin, 2019; Méndez, Hammer, Lopez, & Blair, 2019) and reading
comprehension (Mancilla-Martinez & Lesaux, 2017; Nakamoto, Lindsey, &
Manis, 2008; Proctor, Carlo, August, & Snow, 2005).
It is of theoretical and clinical importance to explore (a) whether
the pattern of effect sizes differs for nonnative English speakers versus
native English speakers for comorbid children and (b) a pattern of moderation in which the relation between English proficiency and performance
is expected to be less strong with embedded language comprehension
instruction in word-problem solving scaffolding and in reading comprehension scaffolding than in control. This is because language comprehensionembedded scaffolding is designed to compensate for poor language
comprehension. We note that the Hub’s Project is not powered for formally
assessing these robustness and diversity questions, but our hope is that it
will provide insight into whether effects for English language learners differs from effects for monolingual counterparts.
A final component of the Hub’s work is development of a neuroimaging paradigm to capture the brain mechanisms that underlie connections
among reading comprehension, word-problem solving, and language comprehension. Development of a paradigm may provide the foundation for
future studies focused on how the brain mechanisms associated with language comprehension serve as a potential link between reading comprehension and word-problem solving.
Conclusion
The overall hope is that the Vanderbilt Hub’s Project will impact science by
(a) deepening understanding about language comprehension as a process
involved in higher-order comorbidity; (b) providing theoretically guided
and empirical bases for the link between reading comprehension and wordproblem solving; (c) strengthening support for the validity of this form of
comorbidity as a learning disabilities subtyping framework; and (d) providing insight into the robustness of this approach (by gender and English
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READING COMPREHENSION AND WORD-PROBLEM SOLVING LEARNING DISABILITY
13
proficiency status). Also, our focus on scaffolding language comprehension
within reading comprehension and word-problem solving tutoring provides
a platform for transdisciplinary work across learning sciences, second language learning, learning disabilities, and developmental psychology. This is
critical because evidence is growing that language comprehension difficulty
contributes to poor responsiveness to reading comprehension or wordproblem solving intervention among students with developmental learning
disabilities (e.g., Catts et al., 2008; Fuchs et al., 2019).
In sum, the Vanderbilt Hub’s science is innovative in four important
ways. First, we focus on an especially vulnerable subset of the learning
disabilities population, which is understudied, may suffer from disproportionately poor reading comprehension and word-problem solving outcomes
and may have a distinctive set of cognitive deficits: students with comorbid
difficulty with reading comprehension and word-problem solving. Second,
with this understudied population, we adopt an innovative approach:
conceptual scaffolding across language comprehension and one academic
domain, with parallel structure what is required in the second academic
domain. If this approach reveals improved performance in both academic
domains, it would offer an innovative direction for treating this understudied, vulnerable population. Third, the Hub’s study provides the most stringent test to date on the connection among language comprehension, reading
comprehension, and word-problem solving. Fourth, our exploratory issues
address the robustness of effects as well as diversity and inclusiveness. The
long-term goal of this proof-of-concept science is to impact clinical practice
by offering an innovative direction aimed at improving learning for this
understudied, vulnerable population.
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LYNN S. FUCHS is the Dunn Family Endowed Chair of Psychoeducational Assessment, Professor of Special Education, and Alexander Heard Distinguished Service Professor at Vanderbilt University and Professor of Pediatrics at Vanderbilt
University Medical School. She conducts research on mathematics and reading
disabilities and interventions, on longitudinal predictors of mathematics development, and on assessment practices to improve identification of students in
need of intervention and to guide teachers’ instructional decision making.
DOUG FUCHS is the Nicholas Hobbs Endowed Chair in Special Education and
Human Development and Alexander Heard Distinguished Service Professor at
Vanderbilt University and Professor of Pediatrics at Vanderbilt Medical School.
He conducts randomized control trials to develop effective reading and mathematics programs and moderator and mediator analyses to better understand
how these programs work and for whom.
PAMELA SEETHALER is a Research Associate with the Department of Special Education at Vanderbilt University. Currently, she serves as co-Principal Investigator for a study assessing the efficacy of mathematics and reading comprehension
tutoring for second-grade students at risk for developing mathematics and reading disability. Her interests include the early identification of and intervention
for students with mathematics disability.
LAURIE E. CUTTING is the Patricia and Rhodes Hart Professor of Special Education and Psychology at Vanderbilt University and Professor of Radiology and
Pediatrics at Vanderbilt University Medical School. She is also Associate Director of the Vanderbilt Kennedy Center and a Senior Scientist at Haskins Laboratories. She conducts cognitive neuroscience research focusing on academic development in order to understand the neurocognitive bases of typical and atypical
development.
JEANNETTE MANCILLA-MARTINEZ is an Associate Professor of Literacy Instruction
in the Department of Teaching and Learning, with a secondary appointment in
the Department of Special Education, as well as Associate Dean of Graduate
Education for Peabody College. Her program of research is focused on advancing students’ language and reading comprehension outcomes, including those of
students from Spanish-speaking, low-income homes.
NEW DIRECTIONS FOR CHILD AND ADOLESCENT DEVELOPMENT • DOI: 10.1002/cad