816339
research-article2018
BBSXXX10.1177/2372732218816339Policy Insights From the Behavioral and Brain SciencesElleman and Oslund
Article
Reading Comprehension Research:
Implications for Practice and Policy
Amy M. Elleman1
Policy Insights from the
Behavioral and Brain Sciences
2019, Vol. 6(1) 3­–11
© The Author(s) 2018
Article reuse guidelines:
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https://doi.org/10.1177/2372732218816339
DOI: 10.1177/2372732218816339
journals.sagepub.com/home/bbs
and Eric L. Oslund1
Abstract
Reading comprehension is one of the most complex cognitive activities in which humans engage, making it difficult to teach,
measure, and research. Despite decades of research in reading comprehension, international and national reading scores
indicate stagnant growth for U.S. adolescents. In this article, we review the theoretical and empirical research in reading
comprehension. We first explore different theoretical models for comprehension and then focus on components shown
to be important across models that represent potential targets for instruction. In the last part of the article, we consider
solutions for translating research to practice and policies for improving instruction. Improving reading scores will require
a concerted and collaborative effort by researchers, educators, and policy makers with a focus on long-term solutions. An
early and sustained focus on developing background knowledge, vocabulary, inference, and comprehension monitoring skills
across development will be necessary to improve comprehension.
Keywords
reading comprehension, instruction, theory, practice, policy
Tweet
To increase reading comprehension, educators will need to
provide early and sustained instruction in knowledge, vocabulary, inference generation, and comprehension monitoring.
Key Points
•• Improving adolescent reading comprehension will
require a concerted effort from researchers, educators,
and policy makers to forgo short-term gains on measures that tap low-level comprehension for long-term
solutions that take years to develop.
•• An early and sustained focus on developing background knowledge, vocabulary, inference, and comprehension monitoring skills is necessary to improve
reading comprehension across grade levels.
•• Despite decades of reading comprehension research, a
limited amount of time is spent using evidence-based
methods in classrooms.
•• Education leaders will need to strengthen teacher
preparation programs and professional development
to ensure teachers are prepared to use evidence-based
practices to meet the literacy needs of their students.
and National Assessment of Educational Progress (National
Assessment of Education Progress [NAEP]), students in the
United States are unable to do relatively easy literacy tasks
such as locate relevant information to determine the main
idea of a text or make simple inferences (Kastberg, Chan, &
Murray, 2016; National Center for Education Statistics,
2017). According to the most recent PISA, U.S. adolescents
rank 15th in literacy skills. Results showed that 19% of the
15-year-olds tested scored below a Level 2 (of 6) indicating
they had difficulty with tasks such as locating explicitly
stated information, recognizing main ideas, and making lowlevel inferences in a familiar topic. Only 10% of U.S. students
achieved a Level 5 indicating that they could organize several
pieces of deeply embedded information, and engage in reflective, evaluative, and interpretative tasks in unfamiliar topics.
Similarly, the NAEP scores showed that 64% of eighth grade
students read at or below a basic level. Unfortunately, these
scores have remained relatively flat for many years and have
led many educators, researchers, and policy makers to question how well students are being prepared for a job market
that increasingly requires self-learning, analytical skills, and
transferable knowledge (e.g., Goldman & Pellegrino, 2015).
1
Middle Tennessee State University, Murfreesboro, USA
Introduction
According to national and international tests of literacy, such
as the Program for International Student Assessment (PISA)
Corresponding Author:
Amy M. Elleman, Middle Tennessee State University, P.O. Box 69,
Murfreesboro, TN 37132, USA.
Email: amy.elleman@mtsu.edu
4
In this article, we briefly review the theoretical and empirical research in comprehension and consider the reasons for
stagnant scores in reading comprehension in the United
States. In the first part of the article, we explore different
theoretical models for comprehension and then focus on
malleable factors that have been shown to be important to
comprehension. We conclude with possible solutions for
translating research to practice and policies for improving
reading comprehension instruction.
The Complexity of Reading
Comprehension
Reading comprehension is one of the most complex behaviors in which humans engage. Reading theorists have grappled with how to comprehensively and meaningfully portray
reading comprehension and many different theoretical models have been proposed in recent decades (McNamara &
Magliano, 2009; Perfetti & Stafura, 2014). These models
range from broad theoretical models depicting the relationships and interactions among comprehension subcomponents to models of specific comprehension processes. We
review different frameworks and models that have significantly impacted theory development, reading comprehension research, and instruction.
One framework, the Simple View of Reading (SVR), posits that reading comprehension is the product of word decoding and linguistic comprehension (Gough & Tunmer, 1986).
Across many languages, research has shown that reading
comprehension can be explained by individual differences in
these two components, though the relative relationship of the
components changes over time (Catts, 2018). Early in development, decoding is more closely associated with reading
comprehension than linguistic competence, but once decoding is mastered, linguistic comprehension becomes a better
predictor of reading comprehension (e.g., Catts, Adlof, &
Weismer, 2005). The SVR has been useful to researchers and
practitioners by providing a framework for understanding
different profiles of struggling readers including students
who struggle primarily due to word-level problems (i.e., dyslexic), comprehension issues (i.e., poor comprehender), or
both (i.e., garden variety poor reader). As useful as the model
has been, it does not explicate the subcomponents of language or cognitive processes that underlie reading comprehension (Catts, 2018).
Reading comprehension requires the coordination of multiple linguistic and cognitive processes including, but not
limited to, word reading ability, working memory, inference
generation, comprehension monitoring, vocabulary, and
prior knowledge (Perfetti, Landi, & Oakhill, 2005). The multifaceted nature of reading comprehension is reflected in
component models that consider subcomponents of comprehension. Component models such as the direct and inferential mediation model (DIME; Ahmed et al., 2016; Cromley,
Policy Insights from the Behavioral and Brain Sciences 6(1)
Snyder-Hogan, & Luciw-Dubas, 2010; Oslund, Clemens,
Simmons, & Simmons, 2018; Oslund, Clemens, Simmons,
Smith, & Simmons, 2016) have been fairly consistent in their
findings. These models indicate that vocabulary, both directly
and indirectly, is consistently the strongest predictor of reading comprehension for younger adolescents. Furthermore,
these models also demonstrated that, although not as strong
as vocabulary, inference-making and background knowledge
also had strong direct and indirect effects on comprehension.
As students get older, inference-making plays a stronger
direct role in comprehension than vocabulary (Cromley
et al., 2010, replicated by Ahmed et al., 2016). Across studies, vocabulary, inference-making, and background knowledge all influence, both directly and indirectly, reading
comprehension from adolescent to young adult readers.
Whereas models such as the SVR and DIME have
attempted to identify underlying components to reading
comprehension, other theorists have examined the process of
reading comprehension. Most theories of comprehension
align with Kintsch’s (1988) construction integration (CI)
model. During the construction phase, information from the
text and the readers’ related knowledge automatically activate. In the subsequent integration phase, activation spreads
throughout the memory network, settling on concepts with
greater activation and more links to other concepts while
suppressing weakly linked concepts. This process occurs
iteratively as the reader processes ideas in a text. In this way,
readers integrate information from the text with their background knowledge to form an overall mental representation.
Similarly, the RAND reading model, another influential
reading framework for research and practice, defined reading
comprehension as the process of “extracting and constructing meaning through interaction and involvement with written language” (RAND Reading Study Group, 2002, p. 11).
Specifically, reading comprehension is the interaction
between reader, text, and task characteristics within a sociocultural context. This model highlights the context-dependent nature of comprehension. A person may achieve a clear
understanding of a text when the text is easy and the task
simple (e.g., answering multiple choice questions), but the
same reader may struggle when encountering complex text
on an unfamiliar topic.
Effective Reading Comprehension
Instruction
Many linguistic abilities, cognitive processes, and knowledge sources undergird comprehension ability complicating
which comprehension components instruction should target
(Perfetti & Adlof, 2012). To identify which components are
worth measuring, some components serve as “pressure
points” that, if changed, would significantly impact students’
comprehension ability. Such components should be integral
to reading comprehension, vary across individuals, and
5
Elleman and Oslund
represent malleable instructional targets (Perfetti & Adlof,
2012). With this in mind, we briefly review four components
of reading comprehension (i.e., inference, knowledge,
vocabulary, comprehension monitoring) that play prominent
roles across theories of reading comprehension, are integral
for understanding text, and represent potentially malleable
targets for instruction. This review focuses on higher order
comprehension skills but acknowledges the foundational
role that efficient word recognition plays in reading comprehension (see Perfetti & Stafura, 2014).
Inference Generation
Inference generation, the ability to integrate information
within or across texts using background knowledge to fill in
information not explicitly stated, is an essential component
of language comprehension (Kendeou, McMaster, & Christ,
2016; Kintsch, 1988). Inference generation is a general skill
important for communication and learning at all stages of
development. When prompted, even preschool age children
can generate causal inferences about events (van den Broek,
Lorch, & Thurlow, 1996). Inference ability has been shown
to be a unique predictor of reading comprehension across
developmental stages (Barth, Barnes, Francis, Vaughn, &
York, 2015). Comparing good and poor comprehenders
(matched on decoding and vocabulary) shows differences on
inferential tasks at the word, sentence, and passage level
(Cain & Oakhill, 1999). Compared to skilled comprehenders,
poor comprehenders demonstrate difficulties with generating
topic-related inferences, integrating words into context,
resolving contextual references, and answering inference
questions in a logical manner (Long, Oppy, & Seely, 1994;
Perfetti & Stafura, 2014).
Not only does inference ability predict reading comprehension, it is also malleable through instruction. In a metaanalysis of inference intervention studies, teaching inferences
improved general comprehension as well as inferential and
literal comprehension skills (Elleman, 2017). Most interventions included fewer than 10 hr of instruction, implying that
teaching inference strategies is useful, and extended practice
as a context-independent skill may not be necessary
(Willingham, 2017). Effective inference instructional techniques include teaching students to use their background
knowledge and integrate it with the information in the text,
self-generated elaborations, graphic organizers that connect
concepts to one another, and text clues (e.g., Elbro & BuchIversen, 2013; Kendeou et al., 2016).
Background Knowledge
A reader’s background knowledge is necessary in building a
coherent representation of a text. Well-connected memory
storage facilitates quicker retrieval and use of relevant information (Kintsch & Rawson, 2005). Prior content knowledge
supports relevant comprehension and learning (Barnes,
Dennis, & Haefele-Kalvaitis, 1996). Readers with more prior
knowledge consistently outperform readers with less, indicating that increased background knowledge in an area may
help less skilled readers compensate for a general comprehension deficit (Schneider, Körkel, & Weinert, 1989). Prior
knowledge of a domain predicts text recall for students
across development and supports the ability to make inferences (Recht & Leslie, 1988) and learn new words (Kaefer,
Neuman, & Pinkham, 2015).
Although educators acknowledge the important role of
knowledge in comprehension, very little time in early elementary school is focused on informational text (Duke,
2000). According to survey research reported in the National
Survey of Science and Mathematics Education, elementary
teachers spend over 80 min on language arts instruction a
day compared to an average of 21 min in science and 18 min
in social studies (Banilower et al., 2013). This is compounded
for less skilled readers who have knowledge deficits
(Compton, Miller, Gilbert, & Steacy, 2013), difficulties
understanding expository text (Saenz & Fuchs, 2002), and
are often pulled from content area classes for additional reading instruction (Banilower et al., 2013).
To alleviate these issues, well-designed programs can
integrate domain knowledge acquisition and comprehension
instruction. A recent meta-analysis of integrated science and
reading programs found a moderate effect for both science
and reading outcomes (Talbert, Parrish, & Elleman, 2016).
Programs focusing on social studies content have also
shown success at promoting knowledge acquisition and
reading comprehension (e.g., Guthrie & Klauda, 2014;
Vaughn et al., 2013).
Vocabulary
Vocabulary is a robust predictor of reading comprehension
across development. Children acquire vocabulary at an
astounding rate, on average 2 to 8 root words per day
(Biemiller & Slonim, 2001). Once children start independently reading, vocabulary acquisition becomes dependent
on exposure to print, not oral language or instruction.
Compared to written language, oral language experiences do
not provide enough unknown words to foster substantial
vocabulary growth (Hayes & Ahrens, 1988). Explicit instruction has also been ruled out as a significant factor in vocabulary acquisition because children are instructed on only a
fraction of the words it would take to accrue the 40,000
words estimated to be known by the average high school student (Stahl & Nagy, 2006). Most words are learned implicitly through repeated exposures in multiple contexts over
time (Landauer & Dumais, 1997).
Unfortunately, large individual differences in vocabulary
size exist in early readers and persist through elementary
school (Biemiller & Slonim, 2001). By the end of second
6
grade, disadvantaged students can lag 2 years behind their
average peers and 4 years behind those in the upper quartile
on vocabulary knowledge. An intense focus on early and continued vocabulary learning makes sense to ameliorate these
differences, but it is unclear if enough vocabulary can be
explicitly taught to impact students’ general comprehension.
Two reviews examining the impact of vocabulary instruction
on comprehension found gains on comprehension measures
that contained the taught words, but not for general comprehension measures (Elleman, Lindo, Morphy, & Compton,
2009; Wright & Cervetti, 2017). Considering only researcher
designed comprehension measures, while all readers
benefited from vocabulary instruction, less skilled readers
benefited more than typical readers, highlighting the importance of vocabulary for these students (Elleman et al., 2009).
Interactive approaches to word learning appear more
effective than ones that rely on definitional types of instruction (Wright & Cervetti, 2017). However, some studies show
gains with very little instructional time spent per word (in
some cases less than a minute per word), suggesting that at
least some type of vocabulary instruction is better than none.
Thus, if the instructional goal in a lesson is to improve comprehension, providing brief explanations of words before or
during reading may be an efficient way to promote word
learning and increase text comprehension. Other generative
word learning strategies that go beyond learning individual
words—such as learning to use context to derive word meanings (Fukkink & deGlopper, 1998) and morphological analysis (Goodwin & Ahn, 2013)—also improve word learning. In
addition, leveraging knowledge networks may be another
way to more efficiently teach vocabulary and knowledge
simultaneously (Neuman & Wright, 2014).
Comprehension Monitoring and Strategy
Instruction
Comprehension monitoring is a metacognitive skill that
refers to readers’ ability to reflect on their understanding of a
written text (Language and Reading Research Consortium &
Yeomans-Maldonado, 2017). Strategic monitoring of text
understanding matters (Oakhill, Hartt, & Samols, 2005). The
ability to monitor comprehension correlates with reading
comprehension and increases over development (Language
and Reading Research Consortium & Yeomans-Maldonado,
2017). Young readers and less skilled readers demonstrate
weaknesses in detecting inconsistencies within a text
(Oakhill et al., 2005). Readers must be able to monitor and
use fix-up strategies when comprehension breaks down.
The intent of comprehension strategy instruction is to
teach students to actively monitor their comprehension and
employ an appropriate strategy to make sense of the text.
Comprehension strategy instruction improves comprehension for typically developing (e.g., National Institute of Child
Health and Human Development [NICHD], 2000) and
Policy Insights from the Behavioral and Brain Sciences 6(1)
struggling readers (e.g., Gersten, Fuchs, Williams, & Baker,
2001). Comprehension strategy instruction is beneficial
when multiple strategies are taught, strategies are explicitly
modeled, and students gradually assume more responsibility
in using strategies independently (Pearson & Dole, 1987).
Implications for Policy
Having covered some contemporary theories and research in
reading comprehension, we consider why reading scores for
U.S. adolescents have stagnated. We then discuss policy
implications and suggest recommendations to improve reading comprehension.
Curriculum and Instruction
Knowledge and vocabulary development. Comprehension strategy instruction is one of the most highly recommended
instructional methods for improving comprehension (e.g.,
NICHD, 2000). Critics, however, contend that an overemphasis on strategy instruction at the expense of knowledge
building has led to the stagnation of scores (Willingham,
2006). Also, strategy instruction may result in a shallow representation of a text and interfere with deeper processing of
the content (Compton, Miller, Elleman, & Steacy, 2014).
Often, the focus of instruction becomes the strategy itself
(e.g., learning how to make main idea statements in different
texts), instead of flexibly using the strategy to build a coherent representation of the texts being read. Early reviews of
strategy instruction revealed that no matter which strategies
were combined in a program, effects were the same (Rosenshine & Meister, 1994), suggesting that the strategies themselves might not be the causal mechanism for increasing
comprehension, but instead a third variable such as increased
engagement and comprehension monitoring might be
responsible (Wilkinson & Son, 2011). As noted, knowledge
is a key factor in comprehension, and young students get
little content exposure in the elementary grades. Some critics
cite the pressures from No Child Left Behind (NCLB) legislation, which they believe unintentionally narrowed the curriculum and made school seek short-term gains focusing on
skills and strategies to increase standardized test scores
(Jones & Workman, 2016).
Knowledge and vocabulary acquisition take time to
develop. Given this, an early and sustained focus on knowledge and vocabulary acquisition is necessary across all grade
levels. The Common Core State Standards in English
Language Arts (CCSS/ELA), adopted by most U.S. states,
reflect this focus on knowledge acquisition by recommending an increase in informational text at all grade levels with
an increasing emphasis on informational text as students get
older (Cervetti & Hiebert, 2015). Yet, standards do not guide
curricular decisions about content. Domain knowledge must
be thoughtfully presented as concepts build on one another
7
Elleman and Oslund
over time. Similarly, vocabulary instruction must be broad
and include systematic instruction in academic vocabulary
and word learning strategies. Rich instruction in knowledge
acquisition and vocabulary development must start as early
as possible and continue throughout children’s school career.
Strategy instruction. Although it would be easy to blame strategy instruction as the reason for stagnant scores, strategy
instruction does effectively increase comprehension. Also,
students with poor comprehension are passive in applying
their knowledge and demonstrate difficulties making inferences, even when they have the necessary background
knowledge to do so (Barnes et al., 1996). So, increasing
background knowledge and vocabulary is only part of the
answer to improving reading comprehension. Students also
need to become strategic readers who can independently
learn from text. What is unclear from research is how to do
this most effectively. We know very little about when to
teach certain strategies in development. As readers develop,
they require more specialized strategies for engaging in text.
Content such as history, science, and mathematics require
different types of text analysis skills (Shanahan & Shanahan,
2008). It is unclear when it is most beneficial to start teaching advanced disciplinary strategies.
Another question to resolve is how much time to spend on
strategies. As noted, just a few hours of inference instruction
can be effective (Elleman, 2017), suggesting extended practice may be unnecessary (Willingham, 2017). Research
should examine which strategies are most generally effective, which specific strategies at what ages, and how long
instruction should last. Awaiting more information, practitioners should teach inference generation and comprehension
monitoring across development, while simultaneously teaching vocabulary and domain knowledge.
Text complexity. Another explanation for the lack of growth
in adolescent reading comprehension is that students are
being exposed to less complex text than in the past (Adams,
2011). A 2-year gap separates the complexity of 12th grade
high school student texts and texts for college freshman.
What distinguishes students on some standardized tests is the
ability to understand more difficult passages (ACT, 2006;
Kulesz, Francis, Barnes, & Fletcher, 2016). Variability in
text difficulty impacts reading comprehension (McNamara,
Graesser, & Louwerse, 2012). Certain linguistic text features
make a text more difficult, such as use of rarer words and
longer sentences (Williamson, Fitzgerald, & Stenner, 2013).
Other factors—such as referential cohesion (i.e., the overlap
of concepts across a text), deep cohesion (i.e., words that
connect the relationship between ideas in the text), and text
type (e.g., narrative, expository)—also affect comprehension
(McNamara et al., 2012). Consequently, the CCSS dedicates
an entire standard to text complexity, to ensure students are
exposed to increasingly difficult text across grades and are,
therefore, ready to understand texts when they enter college
or the workforce (Hiebert & Mesmer, 2013).
However, some questions about text complexity remain
unresolved. Some researchers are concerned about the potential negative impact of increasing text difficulty at younger
ages or with less skilled readers (Hiebert & Mesmer, 2013).
Most states allow different types of text complexity measurement systems to ensure students are exposed to increasingly
complex texts over time. We know little about the impact of
increasing text complexity on comprehension, nor do we
know the impact of using different measurement systems.
Although some methods help to identify increases in text
complexity features like sentence length and word frequency,
they do little to help teachers identify sets of texts that are
topically relevant and cohesive. Text complexity measurement systems that help teachers choose challenging texts and
provide information about conceptual overlap among texts
would be useful to ensure students are exposed to complex
text that supports efficient and effective knowledge and
vocabulary acquisition (see Compton et al., 2014).
Assessment
This review focuses on comprehension theory and instruction, but measurement is crucial in comprehension research
and practice. The complexity of comprehension makes it difficult to capture. Indeed, comprehension tests are not highly
correlated with one another, differentially measure underlying skills, and cannot reliably identify children with comprehension difficulties across different tests (Cutting &
Scarborough, 2006; Keenan & Meenan, 2014). Therefore,
research and educational decision making must use multiple
tests and interpret their scores based on the specific test’s
characteristics.
To better understand the contextualized nature of comprehension and provide more information on existing comprehension measures, researchers have started modeling the
complex interactions between readers, text, and tasks on different comprehension measures using the RAND framework
(Kulesz et al., 2016; Miller et al., 2014). For instance, in a
study examining reader, text, and test characteristics (Kulesz
et al., 2016) adolescent readers with better vocabulary and
background knowledge outperformed others on a standardized reading comprehension measure. Also, the types of
questions asked on the test (e.g., literal and inferential) did
not predict item difficulty, but the type of text did matter
(expository passages were more difficult than narrative passages), underscoring the need to consider the contextual
dependencies at play when measuring comprehension.
Most researchers and practitioners would agree that most
standardized reading comprehension measures fall short of
fully capturing the process of comprehension (Fuchs et al.,
2018). In addition to analyzing current measures, researchers
and education leaders should design measures that go beyond
8
the low-level skills tapped by multiple choice questions and
closed-ended items to measures that provide information
about students’ deeper processing of text. As part of the
Reading for Understanding (RFU) initiative funded by the
Institutes of Education Sciences (IES), one research team has
designed a measure intended to capture deeper comprehension than current multiple choice tests (Sabatini, O’Reilly,
Halderman, & Bruce, 2014). The Global Integrated Scenariobased Assessments (GISA) require students to integrate
information across multiple materials to complete a literacybased task (e.g., designing a website) and defend a position
based on what they learn. ESSA (2015) requires that states
use assessments that measure higher order thinking.
Besides globally measuring deep learning, few diagnostic
tests pinpoint specific difficulties children encounter in comprehension (Francis et al., 2006). These tests are necessary,
so teachers can identify areas of needed support, provide
appropriate interventions, and monitor students’ progress
(Kendeou et al., 2016). Developing and testing these types of
measures across grades and types of learners is necessary to
move comprehension instruction forward.
Translating Comprehension Research to Practice
The inadequate translation of research to practice may also
contribute to stagnant adolescent reading scores. Despite
decades of experimental research in reading comprehension
(Scammacca et al., 2016), little classroom time is used to
teach evidence-based comprehension practices (Swanson
et al., 2016). Current policies advocate evidence-based
instructional policies. ESSA emphasizes evidence-based
instructional methods, as first proposed by the NCLB.
However, these methods are not making their way into practitioners’ hands. One federal agency, IES, has taken an active
role in the promotion of evidence-based practices through
the evaluation of programs (e.g., What Works Clearinghouse)
and the dissemination of findings (e.g., practitioner-friendly
practice guides containing practices and strategies vetted
through science). IES has also supported important research
initiatives in reading comprehension such as the Reading for
Understanding initiatives in which interdisciplinary research
teams examined different aspects of development in language and reading development. The research findings from
these studies are just now being published, but the question
remains on whether the findings will be successfully translated to regular classroom practice.
Translating research to practice is complex and will
require a multipronged approach. One area of growing interest is the use of practice-embedded educational research
(Snow, 2015) in which researchers and practitioners partner
to identify solutions for real problems in practice settings
using rigorous research methods. Evidence-based programs
for increasing vocabulary and comprehension (e.g., Word
Generation and STARI) have been successfully developed
Policy Insights from the Behavioral and Brain Sciences 6(1)
and widely disseminated using this research framework
(Snow, 2015). These types of on-going partnerships between
practitioners and researchers may help shrink the researchto-practice gap in literacy by producing effective interventions that practitioners want to use.
In addition to developing and disseminating effective
research practices and programs, teacher preparation and
professional development will need to be strengthened to
improve reading comprehension instruction. One first step is
for all states to require that teachers are knowledgeable about
evidence-based literacy practices and have expertise in the
content they plan to teach. Ensuring that all teachers meet
these standards will require collaboration among policy
makers, state and district leaders, teacher preparation programs, and accrediting agencies.
Concluding Remarks
Reading comprehension is complex and multifaceted, making it difficult to improve. Stagnant scores of adolescents are
likely due to multiple reasons including the ones outlined in
this article. Improving adolescent reading comprehension
will require a concerted effort from researchers, educators,
and policymakers to forgo short-term gains on measures that
tap low-level comprehension for long-term solutions that
take years to develop. An early and sustained focus on developing background knowledge, vocabulary, inference, and
comprehension monitoring skills is necessary to improve
reading comprehension across grade levels.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
ORCID iD
Amy M. Elleman
https://orcid.org/0000-0001-6686-589X
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