research problem example about reading

Preventing Reading Difficulties in Young Children (1998)

Chapter: 1. introduction, 1 introduction.

Reading is essential to success in our society. The ability to read is highly valued and important for social and economic advancement. Of course, most children learn to read fairly well. In fact, a small number learn it on their own, with no formal instruction, before school entry (Anbar, 1986; Backman, 1983; Bissex, 1980; Jackson, 1991; Jackson et al., 1988). A larger percentage learn it easily, quickly, and efficiently once exposed to formal instruction.

SOCIETAL CHALLENGES

Parents, educators, community leaders, and researchers identify clear and specific worries concerning how well children are learning to read in this country. The issues they raise are the focus of this report:

1. Large numbers of school-age children, including children from all social classes, have significant difficulties in learning to read.

2. Failure to learn to read adequately for continued school success is much more likely among poor children, among nonwhite

children, and among nonnative speakers of English. Achieving educational equality requires an understanding of why these disparities exist and efforts to redress them.

3. An increasing proportion of children in American schools, particularly in certain school systems, are learning disabled, with most of the children identified as such because of difficulties in learning to read.

4. Even as federal and state governments and local communities invest at higher levels in early childhood education for children with special needs and for those from families living in poverty, these investments are often made without specific planning to address early literacy needs and sustain the investment.

5. A significant federal investment in providing bilingual education programs for nonnative speakers of English has not been matched by attention to the best methods for teaching reading in English to nonnative speakers or to native speakers of nonstandard dialects.

6. The passage of the Americans with Disabilities Act (ADA) provides accommodations to children and to workers who have reading disabilities. In order to provide full access for the individuals involved, these accommodations should reflect scientific knowledge about the acquisition of reading and the effects of having a reading difficulty.

7. The debate about reading development and reading instruction has been persistent and heated, often obscuring the very real gains in knowledge of the reading process that have occurred.

In this report, we are most concerned with the children in this country whose educational careers are imperiled because they do not read well enough to ensure understanding and to meet the demands of an increasingly competitive economy. Current difficulties in reading largely originate from rising demands for literacy, not from declining absolute levels of literacy (Stedman and Kaestle, 1987). In a technological society, the demands for higher literacy are constantly increasing, creating ever more grievous consequences for those who fall short and contributing to the widening economic disparities in our society (Bronfenbrenner et al., 1996). These economic dispari-

ties often translate into disparities in educational resources, which then have the self-reinforcing effect of further exacerbating economic disparities. Although the gap in reading performance between educational haves and have-nots has shrunk over the last 50 years, it is still unacceptably large, and in recent years it has not shrunk further (National Academy of Education, 1996). These rich-get-richer and poor-get-poorer economic effects compound the difficulties facing educational policy makers, and they must be addressed if we are to confront the full scope of inadequate literacy attainment (see Bronfenbrenner et al., 1996).

Despite the many ways in which American schools have progressed and improved over the last half century (see, for example, Berliner and Biddle, 1995), there is little reason for complacency. Clear and worrisome problems have to do specifically with children's success in learning to read and our ability to teach reading to them. There are many reasons for these educational problems—none of which is simple. These issues and problems led to the initiation of this study and are the focus of this report.

The many children who succeed in reading are in classrooms that display a wide range of possible approaches to instruction. In making recommendations about instruction, one of the challenges facing the committee is the difficult-to-deal-with fact that many children will learn to read in almost any classroom, with almost any instructional emphasis. Nonetheless, some children, in particular children from poor, minority, or non-English-speaking families and children who have innate predispositions for reading difficulties, need the support of high-quality preschool and school environments and of excellent primary instruction to be sure of reading success. We attempt to identify the characteristics of the preschool and school environments that will be effective for such children.

The Challenge of a Technological Society

Although children have been taught to read for many centuries, only in this century—and until recently only in some countries—has there been widespread expectation that literacy skills should be universal. Under current conditions, in many ''literate" societies, 40 to

60 percent of the population have achieved literacy; today in the United States, we expect 100 percent of the population to be literate. Furthermore, the definition of full-fledged literacy has shifted over the last century with increased distribution of technology, with the development of communication across distances, and with the proliferation of large-scale economic enterprises (Kaestle, 1991; Miller, 1988; Weber, 1993). To be employable in the modern economy, high school graduates need to be more than merely literate. They must be able to read challenging material, to perform sophisticated calculations, and to solve problems independently (Murnane and Levy, 1993). The demands are far greater than those placed on the vast majority of schooled literate individuals a quarter-century ago.

Data from the National Education Longitudinal Study and High School and Beyond, the two most comprehensive longitudinal assessments of U.S. students' attitudes and achievements, indicate that, from 1972 through 1994 (the earliest and most recently available data), high school students most often identified two life values as "very important" (see National Center for Educational Statistics, 1995:403). "Finding steady work" was consistently highly valued by over 80 percent of male and female seniors over the 20 years of measurement and was seen as "very important'' by nearly 90 percent of the 1992 seniors—the highest scores on this measure in its 20-year history. "Being successful in work" was also consistently valued as very important by over 80 percent of seniors over the 20-year period and approached 90 percent in 1992.

The pragmatic goals stated by students amount to "get and hold a good job." Who is able to do that? In 1993, the percentage of U.S. citizens age 25 and older who were college graduates and unemployed was 2.6 percent (U.S. Department of Labor, Office of Employment and Unemployment Statistics, quoted in National Center for Education Statistics, 1995:401). By contrast, the unemployment rate for high school graduates with no college was twice as high, 5.4 percent, and for persons with less than a high school education the unemployment rate was 9.8 percent, over three times higher. An October 1994 survey of 1993-1994 high school graduates and dropouts found that fewer than 50 percent of the dropouts were holding

jobs (U.S. Department of Labor, 1995 ; quoted in National Center for Education Statistics, 1995:401).

One researcher found that, controlling for inflation, the mean income of U.S. male high school dropouts ages 25 to 34 has decreased by over 50 percent between 1973 and 1995 (Stringfield, 1995 , 1997). By contrast, the mean incomes of young male high school graduates dropped by about one-third, and those of college graduates by 20 percent in the 1970s and then stabilized. Among the six major demographic groups (males and females who are black, white, or Hispanic), the lowest average income among college graduates was higher than the highest group of high school graduates.

Academic success, as defined by high school graduation, can be predicted with reasonable accuracy by knowing someone's reading skill at the end of grade 3 (for reviews, see Slavin et al., 1994). A person who is not at least a modestly skilled reader by the end of third grade is quite unlikely to graduate from high school. Only a generation ago, this did not matter so much, because the long-term economic effects of not becoming a good reader and not graduating from high school were less severe. Perhaps not surprisingly, when teachers are asked about the most important goal for education, over half of elementary school teachers chose "building basic literacy skills" (National Center for Education Statistics Schools and Staffing Survey, 1990-1991, quoted in National Center for Education Statistics, 1995:31) .

The Special Challenge of Learning to Read English

Learning to read poses real challenges, even to children who will eventually become good readers. Furthermore, although every writing system has its own complexities, English presents a relatively large challenge, even among alphabetic languages. Learning the principles of a syllabic system, like the Japanese katakana, is quite straightforward, since the units represented—syllables—are pronounceable and psychologically real, even to young children. Such systems are, however, feasible only in languages with few possible syllable types; the hiragana syllabary represents spoken Japanese with 46 characters, supplemented with a set of diacritics (Daniels

and Bright, 1996). Spoken English has approximately 5,000 different possible syllables; instead of representing each one with a symbol in the writing system, written English relies on an alphabetic system that represents the parts that make up a spoken syllable, rather than representing the syllable as a unit.

An alphabetic system poses a challenge to the beginning reader, because the units represented graphically by letters of the alphabet are referentially meaningless and phonologically abstract. For example, there are three sounds represented by three letters in the word "but," but each sound alone does not refer to anything, and only the middle sound can really be pronounced in isolation; when we try to say the first or last consonant of the word all by itself, we have to add a vowel to make it a pronounceable entity (see Box 1-1).

Once the learner of written English gets the basic idea that letters represent the small sound units within spoken and heard words, called phonemes, the system has many advantages: a much more limited set of graphemic symbols is needed than in either syllabic (like Japanese) or morphosyllabic (like Chinese) systems; strategies

for sounding out unfamiliar strings and spelling novel words are available; and subsequences, such as prefixes and suffixes, are encountered with enough frequency for the reader to recognize them automatically.

Alphabetic systems of writing vary in the degree to which they are designed to represent the surface sounds of words. Some languages, such as Spanish, spell all words as they sound, even though this can cause two closely related words to be spelled very differently. Writing systems that compromise phonological representations in order to reflect morphological information are referred to as deep orthographies. In English, rather than preserving one-letter-to-one-sound correspondences, we preserve the spelling, even if that means a particular letter spells several different sounds. For example, the last letter pronounced "k" in the written word "electric" represents quite different sounds in the words "electricity" and ''electrician," indicating the morphological relation among the words but making the sound-symbol relationships more difficult to fathom.

The deep orthography of English is further complicated by the retention of many historical spellings, despite changes in pronunciation that render the spellings opaque. The "gh" in "night" and "neighborhood" represents a consonant that has long since disappeared from spoken English. The "ph" in "morphology" and "philosophy" is useful in signaling the Greek etymology of those words but represents a complication of the pattern of sound-symbol correspondences that has been abandoned in Spanish, German, and many other languages that also retain Greek-origin vocabulary items. English can present a challenge for a learner who expects to find each letter always linked to just one sound.

SOURCES OF READING DIFFICULTIES

Reading problems are found among every group and in every primary classroom, although some children with certain demographic characteristics are at greater risk of reading difficulties than others. Precisely how and why this happens has not been fully understood. In some cases, the sources of these reading difficulties

are relatively clear, such as biological deficits that make the processing of sound-symbol relationships difficult; in other cases, the source is experiential such as poor reading instruction.

Biological Deficits

Neuroscience research on reading has expanded understanding of the reading process (Shaywitz, 1996). For example, researchers have now been able to establish a tentative architecture for the component processes of reading (Shaywitz et al., 1998; Shaywitz, 1996). All reading difficulties, whatever their primary etiology, must express themselves through alterations of the brain systems responsible for word identification and comprehension. Even in disadvantaged or other high-risk populations, many children do learn to read, some easily and others with great difficulty. This suggests that, in all populations, reading ability occurs along a continuum, and biological factors are influenced by, and interact with, a reader's experiences. The findings of an anomalous brain system say little about the possibility for change, for remediation, or for response to treatment. It is well known that, particularly in children, neural systems are plastic and responsive to changed input.

Cognitive studies of reading have identified phonological processing as crucial to skillful reading, and so it seems logical to suspect that poor readers may have phonological processing problems. One line of research has looked at phonological processing problems that can be attributed to the underdevelopment or disruption of specific brain systems.

Genetic factors have also been implicated in some reading disabilities, in studies both of family occurrence (Pennington, 1989; Scarborough, 1989) and of twins (Olson et al., 1994). Differences in brain function and behavior associated with reading difficulty may arise from environmental and/or genetic factors. The relative contributions of these two factors to a deficit in reading (children below the local 10th percentile) have been assessed in readers with normal-range intelligence (above 90 on verbal or performance IQ) and apparent educational opportunity (their first language was English and they had regularly attended schools that were at or above national

norms in reading). This research has provided evidence for strong genetic influences on many of these children's deficits in reading (DeFries and Alarcon, 1996) and in related phonological processes (Olson et al., 1989). Recent DNA studies have found evidence for a link between some cases of reading disability and inheritance of a gene or genes on the short arm of chromosome 6 (Cardon et al., 1994; Grigorenko et al., 1997).

It is important to emphasize that evidence for genetic influence on reading difficulty in the selected population described above does not imply genetic influences on reading differences between groups for which there are confounding environmental differences. Such group differences may include socioeconomic status, English as a second language, and other cultural factors. It is also important to emphasize that evidence for genetic influence and anomalous brain development does not mean that a child is condemned to failure in reading. Brain and behavioral development are always based on the interaction between genetic and environmental influences. The genetic and neurobiological evidence does suggest why learning to read may be particularly difficult for some children and why they may require extraordinary instructional support in reading and related phonological processes.

Instructional Influences

A large number of students who should be capable of reading ably given adequate instruction are not doing so, suggesting that the instruction available to them is not appropriate. As Carroll (1963) noted more than three decades ago, if the instruction provided by a school is ineffective or insufficient, many children will have difficulty learning to read (unless additional instruction is provided in the home or elsewhere).

Reading difficulties that arise when the design of regular classroom curriculum, or its delivery, is flawed are sometimes termed "curriculum casualties" (Gickling and Thompson, 1985; Simmons and Kame'enui, in press). Consider an example from a first-grade classroom in the early part of the school year. Worksheets were being used to practice segmentation and blending of words to facili-

tate word recognition. Each worksheet had a key word, with one part of it designated the "chunk" that was alleged to have the same spelling-sound pattern in other words; these other words were listed on the sheet. One worksheet had the word "love" and the chunk "ove.'' Among the other words listed on the sheet, some did indicate the pattern ("glove," "above," "dove"), but others simply do not work as the sheet suggests they should ("Rover," "stove," and "woven"). In lesson plans and instructional activities, such mistakes occur in the accuracy and clarity of the information being taught.

When this occurs consistently, a substantial proportion of students in the classroom are likely to exhibit low achievement (although some students are likely to progress adequately in spite of the impoverished learning situation). If low-quality instruction is confined to one particular teacher, children's progress may be impeded for the year spent in that classroom, but they may overcome this setback when exposed to more adequate teaching in subsequent years. There is evidence, however, that poor instruction in first grade may have long-term effects. Children who have poor instruction in the first year are more seriously harmed by the bad early learning experience and tend to do poorly in schooling across the years (Pianta, 1990).

In some schools, however, the problem is more pervasive, such that low student achievement is schoolwide and persistent. Sometimes the instructional deficiency can be traced to lack of an appropriate curriculum. More often, a host of conditions occur together to contribute to the risk imposed by poor schooling: low expectations for success on the part of the faculty and administration of the school, which may translate into a slow-paced, undemanding curriculum; teachers who are poorly trained in effective methods for teaching beginning readers; the unavailability of books and other materials; noisy and crowded classrooms; and so forth.

It is regrettable that schools with these detrimental characteristics continue to exist anywhere in the United States; since these schools often exist in low-income areas, where resources for children's out-of-school learning are limited, the effects can be very detrimental to students' probabilities of becoming skilled readers (Kozol, 1991; Puma et al., 1997; Natriello et al., 1990). Attending a

school in which low achievement is pervasive and chronic, in and of itself, clearly places a child at risk for reading difficulty. Even within a school that serves most of its students well, an instructional basis for poor reading achievement is possible. This is almost never considered, however, when a child is referred for evaluation of a suspected reading difficulty. Evidence from case study evaluations of children referred for special education indicate that instructional histories of the children are not seriously considered (Klenk and Palincsar, 1996). Rather, when teachers refer students for special services, the "search for pathology" begins and assessment focused on the child continues until some explanatory factor is unearthed that could account for the observed difficulty in reading (Sarason and Doris, 1979).

In sum, a variety of detrimental school practices may place children at risk for poorer achievement in reading than they might otherwise attain. Interventions geared at improving beginning reading instruction, rehabilitating substandard schools, and ensuring adequate teacher preparation are discussed in subsequent chapters.

DEMOGRAPHICS OF READING DIFFICULTIES

A major source of urgency in addressing reading difficulties derives from their distribution in our society. Children from poor families, children of African American and Hispanic descent, and children attending urban schools are at much greater risk of poor reading outcomes than are middle-class, European-American, and suburban children. Studying these demographic disparities can help us identify groups that should be targeted for special prevention efforts. Furthermore, examining the literacy development of children in these higher-risk groups can help us understand something about the course of literacy development and the array of conditions that must be in place to ensure that it proceeds well.

One characteristic of minority populations that has been offered as an explanation for their higher risk of reading difficulties is the use of nonstandard varieties of English or limited proficiency in English. Speaking a nonstandard variety of English can impede the easy acquisition of English literacy by introducing greater deviations

in the representation of sounds, making it hard to develop sound-symbol links. Learning English spelling is challenging enough for speakers of standard mainstream English; these challenges are heightened for some children by a number of phonological and grammatical features of social dialects that make the relation of sound to spelling even more indirect (see Chapter 6).

The number of children who speak other languages and have limited proficiency in English in U.S. schools has risen dramatically over the past two decades and continues to grow. Although the size of the general school population has increased only slightly, the number of students acquiring English as a second language grew by 85 percent nationwide between 1985 and 1992, from fewer than 1.5 million to almost 2.7 million (Goldenberg, 1996). These students now make up approximately 5.5 percent of the population of public school students in the United States; over half (53 percent) of these students are concentrated in grades K-4. Eight percent of kindergarten children speak a native language other than English and are English-language learners (August and Hakuta, 1997).

Non-English-speaking students, like nonstandard dialect speakers, tend to come from low socioeconomic backgrounds and to attend schools with disproportionately high numbers of children in poverty, both of which are known risk factors (see Chapter 4). Hispanic students in the United States, who constitute the largest group of limited-English-proficient students by far, are particularly at risk for reading difficulties. Despite the group's progress in achievement over the past 15 to 20 years, they are about twice as likely as non-Hispanic whites to be reading below average for their age. Achievement gaps in all academic areas between whites and Hispanics, whether they are U.S. or foreign born, appear early and persist throughout their school careers (Kao and Tienda, 1995).

One obvious reason for these achievement differences is the language difference itself. Being taught and tested in English would, of course, put students with limited English proficiency at a disadvantage. These children might not have any reading difficulty at all if they were taught and tested in the language in which they are proficient. Indeed, there is evidence from research in bilingual education that learning to read in one's native language—thus offsetting the

obstacle presented by limited proficiency in English—can lead to superior achievement (Legarreta, 1979; Ramirez et al., 1991). This field is highly contentious and politicized, however, and there is a lack of clear consensus about the advantages and disadvantages of academic instruction in the primary language in contrast to early and intensive exposure to English (August and Hakuta, 1997; Rossell and Baker, 1996).

In any event, limited proficiency in English does not, in and of itself, appear to be entirely responsible for the low reading achievement of these students. Even when taught and tested in Spanish, as the theory and practice of bilingual education dictates, many Spanish-speaking Hispanic students in the United States still demonstrate low levels of reading attainment (Escamilla, 1994; Gersten and Woodward, 1995; Goldenberg and Gallimore, 1991; Slavin and Madden, 1995). This suggests that factors other than lack of English proficiency may also contribute to these children's reading difficulties.

One such factor is cultural differences, that is, the mismatch between the schools and the families in definitions of literacy, in teaching practices, and in defined roles for parents versus teachers (e.g., Jacob and Jordan, 1987; Tharp, 1989); these differences can create obstacles to children's learning to read in school. Others contend that primary cultural differences matter far less than do "secondary cultural discontinuities," such as low motivation and low educational aspirations that are the result of discrimination and limited social and economic opportunities for certain minority groups (Ogbu, 1974, 1982). Still others claim that high motivation and educational aspirations can and do coexist with low achievement (e.g., Labov et al., 1968, working in the African American community; Goldenberg and Gallimore, 1995, in the Hispanic community) and that other factors must therefore explain the differential achievement of culturally diverse groups.

Literacy is positively valued by adults in minority communities, and the positive views are often brought to school by young children (Nettles, 1997). Nonetheless, the ways that reading is used by adults and children varies across families from different cultural groups in ways that may influence children's participation in literacy activities

in school, as Heath (1983) found. And adults in some communities may see very few functional roles for literacy, so that they will be unlikely to provide conditions in the home that are conducive to children's acquisition of reading and writing skills (Purcell-Gates, 1991, 1996). The implications of these various views for prevention and intervention efforts are discussed in Part III of this volume.

It is difficult to distinguish the risk associated with minority status and not speaking English from the risk associated with lower socioeconomic status (SES). Studying the differential experiences of children in middle- and lower-class families can illuminate the factors that affect the development of literacy and thus contribute to the design of prevention and intervention efforts.

The most extensive studies of SES differences have been conducted in Britain. Stubbs (1980) found a much lower percentage of poor readers with higher (7.5 percent) than with lower SES (26.9 percent).  Some have suggested that SES differences in reading achievement are actually a result of differences in the quality of schooling; that is, lower-SES children tend to go to inferior schools, and therefore their achievement is lower because of inferior educational opportunities (Cook, 1991). However, a recent study by Alexander and Entwisle (1996) appears to demonstrate that it is during nonschool time—before they start and during the summer months—that low-SES children fall academically behind their higher-SES peers and get progressively further behind. During the school months (at least through elementary school) the rate of progress is virtually identical for high- and low-SES children.

Regardless of the specific explanation, differences in literacy achievement among children as a result of socioeconomic status are pronounced. Thirty years ago Coleman et al. (1966) and Moynihan (1965) reported that the educational deficit of children from low-income families was present at school entry and increased with each year they stayed in school. Evidence of SES differences in reading achievement has continued to accumulate (National Assessment of Educational Progress, 1981, 1995). Reading achievement of children in affluent suburban schools is significantly and consistently higher than that of children in "disadvantaged" urban schools (e.g.,

NAEP, 1994, 1995; White, 1982; Hart and Risley, 1995). An important conceptual distinction was made by White (1982) in a groundbreaking meta-analysis. White discovered that, at the individual level, SES is related to achievement only very modestly. However, at the aggregate level, that is, when measured as a school or community characteristic, the effects of SES are much more pronounced. A low-SES child in a generally moderate or higher-SES school or community is far less at risk than an entire school or community of low-SES children.

The existence of SES differences in reading outcomes offers by itself little information about the specific experiences or activities that influence literacy development at home. Indeed, a look at socioeconomic factors alone can do no more than nominate the elements that differ between middle-class and lower-class homes. Researchers have tried to identify the specific familial interactions that can account for social class differences, as well as describe those interactions around literacy that do occur in low-income homes. For example, Baker et al. (1995) compared opportunities for informal literacy learning among preschoolers in the homes of middle-income and low-income urban families. They found that children from middle-income homes had greater opportunities for informal literacy learning than children of low-income homes. Low-income parents, particularly African-American parents, reported more reading skills practice and homework (e.g., flash cards, letter practice) with their kindergarten-age children than did middle-income parents. Middle-income parents reported only slightly more joint book reading with their children than did low-income families. But these middle-income parents reported more play with print and more independent reading by children. Among the middle-class families in this study, 90 percent reported that their child visited the library at least once a month, whereas only 43 percent of the low-income families reported such visits. The findings of Baker et al. that low-income homes typically do offer opportunities for literacy practice, though perhaps of a different nature from middle-class homes, have been confirmed in ethnographic work by researchers such as Teale (1986), Taylor and Dorsey-Gaines (1988), Taylor and Strickland (1986), Gadsden (1993), Delgado-Gaitan (1990), and Goldenberg et al. (1992).

ABOUT THIS REPORT

Charge to the committee.

The Committee on the Prevention of Reading Difficulties in Young Children has conducted a study of the effectiveness of interventions for young children who are at risk of having problems in learning to read. It was carried out at the request of the U.S. Department of Education's Office of Special Education Programs and its Office of Educational Research and Improvement (Early Childhood Institute) and the National Institute on Child Health and Human Development (Human Learning and Behavior Branch). The sponsors requested that the study address young children who are at -risk for reading difficulties, within the context of reading acquisition for all children. The scope included children from birth through grade 3, in special and regular education settings. The project had three goals: (1) to comprehend a rich research base; (2) to translate the research findings into advice and guidance for parents, educators, publishers, and others involved in the care and instruction of the young; and (3) to convey this advice to the targeted audiences through a variety of publications, conferences, and other outreach activities. In making its recommendations, the committee has highlighted key research findings that should be integrated into existing and future program interventions to enhance the reading abilities of young children, particularly instruction at the preschool and early elementary levels.

The Committee's Perspective

Our recommendations extend to all children. Of course, we are most worried about children at high risk of developing reading difficulties. However, there is little evidence that children experiencing difficulties learning to read, even those with identifiable learning disabilities, need radically different sorts of supports than children at low risk, although they may need much more intensive support. Childhood environments that support early literacy development and

excellent instruction are important for all children. Excellent instruction is the best intervention for children who demonstrate problems learning to read.

Knowledge about reading derives from work conducted in several disciplines, in laboratory settings as well as in homes, classrooms, and schools, and from a range of methodological perspectives. Reading is studied by ethnographers, sociologists, historians, child developmentalists, neurobiologists, and psycholinguists. Reading has been approached as a matter of cognition, culture, socialization, instruction, and language. The committee that wrote this report embraces all these perspectives—but we acknowledge the difficulty of integrating them into a coherent picture.

The committee agrees that reading is inextricably embedded in educational, social, historical, cultural, and biological realities. These realities determine the meaning of terms like literate as well as limits on access to literacy and its acquisition. Literacy is also essentially developmental, and appropriate forms of participation, instruction, and assessment in literacy for preschoolers differ from those for first graders and also from those for sophisticated critical readers.

Reading as a cognitive and psycholinguistic activity requires the use of form (the written code) to obtain meaning (the message to be understood), within the context of the reader's purpose (for learning, for enjoyment, for insight). In children, one can see a developmental oscillation between these foci: the preschool child who can pretend to read a story she has heard many times is demonstrating an understanding that reading is about content or meaning; the same child as a first grader, having been taught some grapheme-phoneme correspondences, may read the same storybook haltingly, disfluently, by sounding out the words she had earlier memorized, demonstrating an extreme focus on form. The mature, fluent, practiced reader shows more rapid oscillations between form-focused and meaning-focused reading: she can rely on automatic processing of form and focus on meaning until she encounters an unfamiliar pharmaceutical term or a Russian surname, whereupon the processing of meaning is disrupted while the form is decoded.

Groups define the nature as well as the value of literacy in culturally specific ways as well. A full picture of literacy from a cultural

and historical perspective would require an analysis of the distribution of literacy skills, values, and uses across classes and genders as well as religious and social groups; it would require a discussion of the connections between professional, religious, and leisure practices and literacy as defined by those practices. Such a discussion would go far beyond the scope of this report, which focuses on reading and reading difficulties as defined by mainstream opinions in the United States, in particular by U.S. educational institutions at the end of the twentieth century. In that context, employability, citizenship, and participation in the culture require high levels of literacy achievement.

Nature of the Evidence

Our review and summary of the literature are framed by some very basic principles of evidence evaluation. These principles derive from our commitment to the scientific method, which we view not as a strict set of rules but instead as a broad framework defined by some general guidelines. Some of the most important are that (1) science aims for knowledge that is publicly verifiable, (2) science seeks testable theories—not unquestioned edicts, (3) science employs methods of systematic empiricism (see Box 1-2). Science renders knowledge public by such procedures as peer review and such mechanisms as systematic replication (see Box 1-3). Testable theories are those that are potentially falsifiable—that is, defined in such a way that empirical evidence inconsistent with them can in principle be accumulated. It is the willingness to give up or alter a theory in the face of evidence that is one of the most central defining features of the scientific method. All of the conclusions reached in this report

are provisional in this important sense: they have empirical consequences that, if proven incorrect, should lead to their alteration.

The methods of systematic empiricism employed in the study of reading difficulties are many and varied. They include case studies, correlational studies, experimental studies, narrative analyses, quasi-experimental studies, interviews and surveys, epidemiological studies, ethnographies, and many others. It is important to understand how the results from studies employing these methods have been used in synthesizing the conclusions of this report.

First, we have utilized the principle of converging evidence. Scientists and those who apply scientific knowledge must often make a judgment about where the preponderance of evidence points. When this is the case, the principle of converging evidence is an important tool, both for evaluating the state of the research evidence and also for deciding how future experiments should be designed. Most areas of science contain competing theories. The extent to which one particular theory can be viewed as uniquely supported by a particular study depends on the extent to which other competing explanations have been ruled out. A particular experimental result is never equally relevant to all competing theoretical explanations. A given experiment may be a very strong test of one or two alternative theories but a weak test of others. Thus, research is highly convergent when a series of experiments consistently support a given theory while collectively eliminating the most important competing explanations. Although no single experiment can rule out all alternative explanations, taken collectively, a series of partially diagnostic studies can

lead to a strong conclusion if the data converge. This aspect of the convergence principle implies that we should expect to see many different methods employed in all areas of educational research. A relative balance among the methodologies used to arrive at a given conclusion is desirable because the various classes of research techniques have different strengths and weaknesses.

Another important context for understanding the present synthesis of research is provided by the concept of synergism between descriptive and hypothesis-testing research methods. Research on a particular problem often proceeds from more exploratory methods (ones unlikely to yield a causal explanation) to methods that allow stronger causal inferences. For example, interest in a particular hypothesis may originally stem from a case study of an unusually successful teacher. Alternately, correlational studies may suggest hypotheses about the characteristics of teachers who are successful. Subsequently, researchers may attempt experiments in which variables identified in the case study or correlation are manipulated in order to isolate a causal relationship. These are common progressions in areas of research in which developing causal models of a phenomenon is the paramount goal. They reflect the basic principle of experimental design that the more a study controls extraneous variables the stronger is the causal inference. A true experiment in controlling all extraneous variables is thus the strongest inferential tool.

Qualitative methods, including case studies of individual learners or teachers, classroom ethnographies, collections of introspective interview data, and so on, are also valuable in producing complementary data when carrying out correlational or experimental studies. Teaching and learning are complex phenomena that can be enhanced or impeded by many factors. Experimental manipulation in the teaching/learning context typically is less ''complete" than in other contexts; in medical research, for example, treatments can be delivered through injections or pills, such that neither the patient nor the clinician knows who gets which treatment, and in ways that do not require that the clinician be specifically skilled in or committed to the success of a particular treatment.

Educational treatments are often delivered by teachers who may enhance or undermine the difference between treatments and controls; thus, having qualitative data on the authenticity of treatment and on the attitudes of the teachers involved is indispensable. Delivering effective instruction occurs in the context of many other factors—the student-teacher relationship, the teacher's capability at maintaining order, the expectations of the students and their parents—that can neither be ignored nor controlled. Accordingly, data about them must be made available. In addition, since even programs that are documented to be effective will be impossible to implement on a wider scale if teachers dislike them, data on teacher beliefs and attitudes will be useful after demonstration of treatment effects as well (see discussion below of external validity).

Furthermore, the notion of a comparison between a treatment group and an untreated control is often a myth when dealing with social treatments. Families who are assigned not to receive some intervention for their children (e.g., Head Start placement, one-on-one tutoring) often seek out alternatives for themselves that approximate or improve on the treatment features. Understanding the dynamic by which they do so, through collecting observational and interview data, can prevent misguided conclusions from studies designed as experiments. Thus, although experimental studies represent the most powerful design for drawing causal inferences, their limitations must be recognized.

Another important distinction in research on reading is that between retrospective and prospective studies. On one hand, retrospective studies start from observed cases of reading difficulties and attempt to generate explanations for the problem. Such studies may involve a comparison group of normal readers, but of course inference from the finding of differences between two groups, one of whom has already developed reading difficulties and one of whom has not, can never be very strong. Studies that involve matching children with reading problems to others at the same level of reading skill (rather than to age mates) address some of these problems but at the cost of introducing other sources of difficulty—comparing two groups of different ages, with different school histories, and different levels of perceived success in school.

Prospective studies, on the other hand, are quite expensive and time consuming, particularly if they include enough participants to ensure a sizable group of children with reading difficulties. They do, however, enable the researcher to trace developmental pathways for participants who are not systematically different from one another at recruitment and thus to draw stronger conclusions about the likely directionality of cause-effect relationships.

As part of the methodological context for this report, we wish to address explicitly a misconception that some readers may have derived from our emphasis on the logic of an experiment as the most powerful justification for a causal conclusion. By such an emphasis, we do not mean to imply that only studies employing true experimental logic are to be used in drawing conclusions. To the contrary, as mentioned previously in our discussion of converging evidence, the results from many different types of investigations are usually weighed to derive a general conclusion, and the basis for the conclusion rests on the convergence observed from the variety of methods used. This is particularly true in the domains of classroom and curriculum research.

For example, it is often (but not always) the case that experimental investigations are high in internal validity but limited in external validity, whereas correlational studies are often high in external validity but low in internal validity. Internal validity concerns whether we can infer a causal effect for a particular variable. The more a study approximates the logic of a true experiment (i.e., includes manipulation, control, and randomization), the more we can make a strong causal inference. The internal validity of qualitative research studies depends, of course, on their capacity to reflect reality adequately and accurately. Procedures for ensuring adequacy of qualitative data include triangulation (comparison of findings from different research perspectives), cross-case analyses, negative case analysis, and so forth. Just as for quantitative studies, our review of qualitative studies has been selective and our conclusions took into account the methodological rigor of each study within its own paradigm.

External validity concerns the generalizability of the conclusion to the population and setting of interest. Internal validity and exter-

nal validity are often traded off across different methodologies. Experimental laboratory investigations are high in internal validity but may not fully address concerns about external validity. Field classroom investigations are often quite high in external validity but, because of the logistical difficulties involved in carrying out such investigations, are often quite low in internal validity. Hence, there is a need to look for a convergence of results—not just consistency across studies conducted with one method. Convergence across different methods increases confidence that the conclusions have both internal and external validity.

A not uncommon misconception is that correlational (i.e., nonexperimental) studies cannot contribute to knowledge. This is false for a number of reasons. First, many scientific hypotheses are stated in terms of correlation or lack of correlation, so that such studies are directly relevant to these hypotheses. Second, although correlation does not imply causation, causation does imply correlation. That is, although a correlational study cannot definitively prove a causal hypothesis, it may rule one out. Third, correlational studies are more useful than they used to be because some of the recently developed complex correlational designs allow for limited causal inferences. The technique of partial correlation, widely used in studies cited in this report, provides a case in point. It makes possible a test of whether a particular third variable is accounting for a relationship.

Perhaps the most important argument for quasi-experimental studies, however, is that some variables (for instance, human malnutrition, physical disabilities) simply cannot be manipulated for ethical reasons. Other variables, such as birth order, sex, and age, are inherently correlational because they cannot be manipulated, and therefore the scientific knowledge concerning them must be based on correlational evidence. Finally, logistical difficulties in carrying out classroom and curriculum research often render impossible the logic of the true experiment. However, this circumstance is not unique to educational or psychological research. Astronomers obviously cannot manipulate the variables affecting the objects they study, yet they are able to arrive at scientifically founded conclusions.

Outline of the Report

In Chapter 2 we present a picture of typical skilled reading and the process by which it develops. We see this as crucial background information for understanding reading difficulties and their prevention.

Part II presents a fuller picture of the children we are addressing in this report. We survey the population of children with reading difficulties in Chapter 3. In Chapter 4 we discuss risk factors that may help identify children who will have problems learning to read.

Part III presents our analysis of preventions and interventions, including instruction. Chapter 5focuses on the preschool years. Chapter 6 discusses prevention and literacy instruction delivered in classrooms in kindergarten and the primary grades. Chapter 7 presents our analysis of organizational factors, at the classroom, school, or district level, that contribute to prevention and intervention for grades 1 through 3. Chapter 8 continues discussion of grades 1 through 3, presenting more targeted intervention efforts to help children who are having reading difficulties.

Part IV presents our discussion of how the information reviewed in the report should be used to change practice. Chapter 9 discusses a variety of domains in which action is needed and obstacles to change in those domains. Chapter 10 presents our recommendations for practice, policy, and research.

While most children learn to read fairly well, there remain many young Americans whose futures are imperiled because they do not read well enough to meet the demands of our competitive, technology-driven society. This book explores the problem within the context of social, historical, cultural, and biological factors.

Recommendations address the identification of groups of children at risk, effective instruction for the preschool and early grades, effective approaches to dialects and bilingualism, the importance of these findings for the professional development of teachers, and gaps that remain in our understanding of how children learn to read. Implications for parents, teachers, schools, communities, the media, and government at all levels are discussed.

The book examines the epidemiology of reading problems and introduces the concepts used by experts in the field. In a clear and readable narrative, word identification, comprehension, and other processes in normal reading development are discussed.

Against the background of normal progress, Preventing Reading Difficulties in Young Children examines factors that put children at risk of poor reading. It explores in detail how literacy can be fostered from birth through kindergarten and the primary grades, including evaluation of philosophies, systems, and materials commonly used to teach reading.

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Organizing Your Social Sciences Research Paper

• The Research Problem/Question
• Purpose of Guide
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• Glossary of Research Terms
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• Theoretical Framework
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• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
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A research problem is a definite or clear expression [statement] about an area of concern, a condition to be improved upon, a difficulty to be eliminated, or a troubling question that exists in scholarly literature, in theory, or within existing practice that points to a need for meaningful understanding and deliberate investigation. A research problem does not state how to do something, offer a vague or broad proposition, or present a value question. In the social and behavioral sciences, studies are most often framed around examining a problem that needs to be understood and resolved in order to improve society and the human condition.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Guba, Egon G., and Yvonna S. Lincoln. “Competing Paradigms in Qualitative Research.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, editors. (Thousand Oaks, CA: Sage, 1994), pp. 105-117; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

Importance of...

The purpose of a problem statement is to:

• Introduce the reader to the importance of the topic being studied . The reader is oriented to the significance of the study.
• Anchors the research questions, hypotheses, or assumptions to follow . It offers a concise statement about the purpose of your paper.
• Place the topic into a particular context that defines the parameters of what is to be investigated.
• Provide the framework for reporting the results and indicates what is probably necessary to conduct the study and explain how the findings will present this information.

In the social sciences, the research problem establishes the means by which you must answer the "So What?" question. This declarative question refers to a research problem surviving the relevancy test [the quality of a measurement procedure that provides repeatability and accuracy]. Note that answering the "So What?" question requires a commitment on your part to not only show that you have reviewed the literature, but that you have thoroughly considered the significance of the research problem and its implications applied to creating new knowledge and understanding or informing practice.

To survive the "So What" question, problem statements should possess the following attributes:

• Clarity and precision [a well-written statement does not make sweeping generalizations and irresponsible pronouncements; it also does include unspecific determinates like "very" or "giant"],
• Demonstrate a researchable topic or issue [i.e., feasibility of conducting the study is based upon access to information that can be effectively acquired, gathered, interpreted, synthesized, and understood],
• Identification of what would be studied, while avoiding the use of value-laden words and terms,
• Identification of an overarching question or small set of questions accompanied by key factors or variables,
• Identification of key concepts and terms,
• Articulation of the study's conceptual boundaries or parameters or limitations,
• Some generalizability in regards to applicability and bringing results into general use,
• Conveyance of the study's importance, benefits, and justification [i.e., regardless of the type of research, it is important to demonstrate that the research is not trivial],
• Does not have unnecessary jargon or overly complex sentence constructions; and,
• Conveyance of more than the mere gathering of descriptive data providing only a snapshot of the issue or phenomenon under investigation.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Brown, Perry J., Allen Dyer, and Ross S. Whaley. "Recreation Research—So What?" Journal of Leisure Research 5 (1973): 16-24; Castellanos, Susie. Critical Writing and Thinking. The Writing Center. Dean of the College. Brown University; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Selwyn, Neil. "‘So What?’…A Question that Every Journal Article Needs to Answer." Learning, Media, and Technology 39 (2014): 1-5; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518.

Structure and Writing Style

I.  Types and Content

There are four general conceptualizations of a research problem in the social sciences:

• Casuist Research Problem -- this type of problem relates to the determination of right and wrong in questions of conduct or conscience by analyzing moral dilemmas through the application of general rules and the careful distinction of special cases.
• Difference Research Problem -- typically asks the question, “Is there a difference between two or more groups or treatments?” This type of problem statement is used when the researcher compares or contrasts two or more phenomena. This a common approach to defining a problem in the clinical social sciences or behavioral sciences.
• Descriptive Research Problem -- typically asks the question, "what is...?" with the underlying purpose to describe the significance of a situation, state, or existence of a specific phenomenon. This problem is often associated with revealing hidden or understudied issues.
• Relational Research Problem -- suggests a relationship of some sort between two or more variables to be investigated. The underlying purpose is to investigate specific qualities or characteristics that may be connected in some way.

A problem statement in the social sciences should contain :

• A lead-in that helps ensure the reader will maintain interest over the study,
• A declaration of originality [e.g., mentioning a knowledge void or a lack of clarity about a topic that will be revealed in the literature review of prior research],
• An indication of the central focus of the study [establishing the boundaries of analysis], and
• An explanation of the study's significance or the benefits to be derived from investigating the research problem.

NOTE:   A statement describing the research problem of your paper should not be viewed as a thesis statement that you may be familiar with from high school. Given the content listed above, a description of the research problem is usually a short paragraph in length.

II.  Sources of Problems for Investigation

The identification of a problem to study can be challenging, not because there's a lack of issues that could be investigated, but due to the challenge of formulating an academically relevant and researchable problem which is unique and does not simply duplicate the work of others. To facilitate how you might select a problem from which to build a research study, consider these sources of inspiration:

Deductions from Theory This relates to deductions made from social philosophy or generalizations embodied in life and in society that the researcher is familiar with. These deductions from human behavior are then placed within an empirical frame of reference through research. From a theory, the researcher can formulate a research problem or hypothesis stating the expected findings in certain empirical situations. The research asks the question: “What relationship between variables will be observed if theory aptly summarizes the state of affairs?” One can then design and carry out a systematic investigation to assess whether empirical data confirm or reject the hypothesis, and hence, the theory.

Interdisciplinary Perspectives Identifying a problem that forms the basis for a research study can come from academic movements and scholarship originating in disciplines outside of your primary area of study. This can be an intellectually stimulating exercise. A review of pertinent literature should include examining research from related disciplines that can reveal new avenues of exploration and analysis. An interdisciplinary approach to selecting a research problem offers an opportunity to construct a more comprehensive understanding of a very complex issue that any single discipline may be able to provide.

Interviewing Practitioners The identification of research problems about particular topics can arise from formal interviews or informal discussions with practitioners who provide insight into new directions for future research and how to make research findings more relevant to practice. Discussions with experts in the field, such as, teachers, social workers, health care providers, lawyers, business leaders, etc., offers the chance to identify practical, “real world” problems that may be understudied or ignored within academic circles. This approach also provides some practical knowledge which may help in the process of designing and conducting your study.

Personal Experience Don't undervalue your everyday experiences or encounters as worthwhile problems for investigation. Think critically about your own experiences and/or frustrations with an issue facing society or related to your community, your neighborhood, your family, or your personal life. This can be derived, for example, from deliberate observations of certain relationships for which there is no clear explanation or witnessing an event that appears harmful to a person or group or that is out of the ordinary.

Relevant Literature The selection of a research problem can be derived from a thorough review of pertinent research associated with your overall area of interest. This may reveal where gaps exist in understanding a topic or where an issue has been understudied. Research may be conducted to: 1) fill such gaps in knowledge; 2) evaluate if the methodologies employed in prior studies can be adapted to solve other problems; or, 3) determine if a similar study could be conducted in a different subject area or applied in a different context or to different study sample [i.e., different setting or different group of people]. Also, authors frequently conclude their studies by noting implications for further research; read the conclusion of pertinent studies because statements about further research can be a valuable source for identifying new problems to investigate. The fact that a researcher has identified a topic worthy of further exploration validates the fact it is worth pursuing.

III.  What Makes a Good Research Statement?

A good problem statement begins by introducing the broad area in which your research is centered, gradually leading the reader to the more specific issues you are investigating. The statement need not be lengthy, but a good research problem should incorporate the following features:

1.  Compelling Topic The problem chosen should be one that motivates you to address it but simple curiosity is not a good enough reason to pursue a research study because this does not indicate significance. The problem that you choose to explore must be important to you, but it must also be viewed as important by your readers and to a the larger academic and/or social community that could be impacted by the results of your study. 2.  Supports Multiple Perspectives The problem must be phrased in a way that avoids dichotomies and instead supports the generation and exploration of multiple perspectives. A general rule of thumb in the social sciences is that a good research problem is one that would generate a variety of viewpoints from a composite audience made up of reasonable people. 3.  Researchability This isn't a real word but it represents an important aspect of creating a good research statement. It seems a bit obvious, but you don't want to find yourself in the midst of investigating a complex research project and realize that you don't have enough prior research to draw from for your analysis. There's nothing inherently wrong with original research, but you must choose research problems that can be supported, in some way, by the resources available to you. If you are not sure if something is researchable, don't assume that it isn't if you don't find information right away--seek help from a librarian !

NOTE:   Do not confuse a research problem with a research topic. A topic is something to read and obtain information about, whereas a problem is something to be solved or framed as a question raised for inquiry, consideration, or solution, or explained as a source of perplexity, distress, or vexation. In short, a research topic is something to be understood; a research problem is something that needs to be investigated.

IV.  Asking Analytical Questions about the Research Problem

Research problems in the social and behavioral sciences are often analyzed around critical questions that must be investigated. These questions can be explicitly listed in the introduction [i.e., "This study addresses three research questions about women's psychological recovery from domestic abuse in multi-generational home settings..."], or, the questions are implied in the text as specific areas of study related to the research problem. Explicitly listing your research questions at the end of your introduction can help in designing a clear roadmap of what you plan to address in your study, whereas, implicitly integrating them into the text of the introduction allows you to create a more compelling narrative around the key issues under investigation. Either approach is appropriate.

The number of questions you attempt to address should be based on the complexity of the problem you are investigating and what areas of inquiry you find most critical to study. Practical considerations, such as, the length of the paper you are writing or the availability of resources to analyze the issue can also factor in how many questions to ask. In general, however, there should be no more than four research questions underpinning a single research problem.

Given this, well-developed analytical questions can focus on any of the following:

• Highlights a genuine dilemma, area of ambiguity, or point of confusion about a topic open to interpretation by your readers;
• Yields an answer that is unexpected and not obvious rather than inevitable and self-evident;
• Provokes meaningful thought or discussion;
• Raises the visibility of the key ideas or concepts that may be understudied or hidden;
• Suggests the need for complex analysis or argument rather than a basic description or summary; and,
• Offers a specific path of inquiry that avoids eliciting generalizations about the problem.

NOTE:   Questions of how and why concerning a research problem often require more analysis than questions about who, what, where, and when. You should still ask yourself these latter questions, however. Thinking introspectively about the who, what, where, and when of a research problem can help ensure that you have thoroughly considered all aspects of the problem under investigation and helps define the scope of the study in relation to the problem.

V.  Mistakes to Avoid

Beware of circular reasoning! Do not state the research problem as simply the absence of the thing you are suggesting. For example, if you propose the following, "The problem in this community is that there is no hospital," this only leads to a research problem where:

• The need is for a hospital
• The objective is to create a hospital
• The method is to plan for building a hospital, and
• The evaluation is to measure if there is a hospital or not.

This is an example of a research problem that fails the "So What?" test . In this example, the problem does not reveal the relevance of why you are investigating the fact there is no hospital in the community [e.g., perhaps there's a hospital in the community ten miles away]; it does not elucidate the significance of why one should study the fact there is no hospital in the community [e.g., that hospital in the community ten miles away has no emergency room]; the research problem does not offer an intellectual pathway towards adding new knowledge or clarifying prior knowledge [e.g., the county in which there is no hospital already conducted a study about the need for a hospital, but it was conducted ten years ago]; and, the problem does not offer meaningful outcomes that lead to recommendations that can be generalized for other situations or that could suggest areas for further research [e.g., the challenges of building a new hospital serves as a case study for other communities].

Alvesson, Mats and Jörgen Sandberg. “Generating Research Questions Through Problematization.” Academy of Management Review 36 (April 2011): 247-271 ; Choosing and Refining Topics. Writing@CSU. Colorado State University; D'Souza, Victor S. "Use of Induction and Deduction in Research in Social Sciences: An Illustration." Journal of the Indian Law Institute 24 (1982): 655-661; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); How to Write a Research Question. The Writing Center. George Mason University; Invention: Developing a Thesis Statement. The Reading/Writing Center. Hunter College; Problem Statements PowerPoint Presentation. The Writing Lab and The OWL. Purdue University; Procter, Margaret. Using Thesis Statements. University College Writing Centre. University of Toronto; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518; Trochim, William M.K. Problem Formulation. Research Methods Knowledge Base. 2006; Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Walk, Kerry. Asking an Analytical Question. [Class handout or worksheet]. Princeton University; White, Patrick. Developing Research Questions: A Guide for Social Scientists . New York: Palgrave McMillan, 2009; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

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The Comprehension Problems of Children with Poor Reading Comprehension despite Adequate Decoding: A Meta-Analysis

The purpose of this meta-analysis was to examine the comprehension problems of children who have a specific reading comprehension deficit (SCD), which is characterized by poor reading comprehension despite adequate decoding. The meta-analysis included 86 studies of children with SCD who were assessed in reading comprehension and oral language (vocabulary, listening comprehension, storytelling ability, and semantic and syntactic knowledge). Results indicated that children with SCD had deficits in oral language ( d = −0.78, 95% CI [−0.89, −0.68], but these deficits were not as severe as their deficit in reading comprehension ( d = −2.78, 95% CI [−3.01, −2.54]). When compared to reading comprehension age-matched normal readers, the oral language skills of the two groups were comparable ( d = 0.32, 95% CI [−0.49, 1.14]), which suggests that the oral language weaknesses of children with SCD represent a developmental delay rather than developmental deviance. Theoretical and practical implications of these findings are discussed.

Reading comprehension, or the process of engaging text for the purpose of extracting and constructing meaning ( Snow, 2002 ), has paramount importance to academic success and future life outcomes ( National Institute of Child Health and Human Development [NICHD], 2000 ; Snow, 2002 ). Yet only about 36% of fourth graders and 34% eighth graders in the United States have reading comprehension scores at or above proficiency by the end of the academic year ( U.S. Department of Education, 2015 ). Furthermore, nearly 31% of fourth graders and nearly 24% of eighth graders continue to attain reading comprehension scores that are below even the basic level. This indicates that a substantial proportion of fourth and eighth graders would have problems with more complex activities that extend beyond the text itself (e.g., comparing and contrasting ideas or making inferences beyond the text). This is particularly troubling given the importance of comprehension skills for success in school, in the workplace, and in daily life (e.g., understanding newspapers and forms and contracts to be signed).

Given the importance of decoding to reading comprehension it is not surprising that decoding deficits often result in comprehension difficulties ( Perfetti, 1985 ; Perfetti & Hart, 2001 ; Perfetti & Hogaboam, 1975 ; Perfetti, Landi & Oakhill, 2005 ; Shankweiler et al., 1999 ; Snow, Burns, & Griffin, 1998 ). However, it is estimated that between 10 and 15% of 7- to 8-year-old children have normal performance on decoding measures yet still experience deficits in reading comprehension ( Nation & Snowling, 1997 ; Stothard & Hulme, 1995 ; Yuill & Oakhill, 1991 ); that is, these children are characterized as having a specific reading comprehension deficit (SCD). Although this estimate varies depending on the criteria used to identify children with SCD (see Rønberg & Petersen, 2015 ), large-scale identification studies have shown that the prevalence of SCDis most likely around 8% for children between the ages of 9 and 14 years ( Keenan et al., 2014 ). Even an 8% prevalence rate would mean an average of two students in a classroom could meet the criteria for SCD.

Reading comprehension is a complex process, involving a variety of cognitive and linguistic skills. As a result, deficits in any cognitive ability important to the comprehension process can potentially lead to deficits in reading comprehension performance. Perfetti and colleagues ( Perfetti et al., 2005 ; Perfetti & Stafura, 2014 ) provide a comprehensive framework for understanding the processes and skills involved in reading comprehension; deficits in comprehension could result from a variety of sources beyond decoding, including differences in sensitivity to story structure, inference making, comprehension monitoring, syntactic processing, verbal working memory, and oral language skills ( Cain & Oakhill, 1996 , 1999 ; Cain, Oakhill, Barnes, & Bryant, 2001 ; Nation, Adams, Bowyer-Crane, & Snowling, 1999 ; Nation & Snowling, 1998b , 1999 ; Oakhill, Hartt, & Samols, 2005 ; Pimperton & Nation, 2010a ; Snowling & Hulme, 2012 ).

Existing studies of children with SCD show that they perform poorly on a range of oral language assessments ( Cain, 2003 ; Cain, 2006 ; Cain et al., 2005 ; Cain & Oakhill, 1996 ; Carretti et al., 2014 ; Nation & Snowling, 2000 ; Oakhill et al., 1986 ; Stothard & Hulme, 1996 ; Tong, Deacon, & Cain, 2014 ; Tong, Deacon, Kirby, Cain, & Parrila, 2011 ; Yuill & Oakhill, 1991 ). However, relatively little is known about whether the comprehension problems of children with SCD are the result of their oral language deficits. Although it is possible that the documented deficits in oral language account for the observed deficits in reading comprehension, they may only be a contributing factor. A better understanding of the comprehension problems for children with SCD may be a first step towards better identification and remediation.

We briefly describe relevant theories of reading comprehension because existing theories may inform our understanding of the comprehension problems of children with SCD and understanding the comprehension problems of children with SCD in turn may inform theories of comprehension.

Several theories of reading comprehension have emerged over the years. These include the bottom-up view, the top-down view, the interactive view, the metacognitive view, and the simple view of reading comprehension. Each of these theories are relevant within the present context. Thus, we briefly discuss each theory below.

According to the bottom-up view of reading comprehension, readers move from an understanding of parts of language (e.g., letters, words) to an understanding of meaning or the whole (e.g., phrases, passages; Gough, 1972 ; Holmes, 2009 ; LaBerge & Samuels, 1974 ). Comprehension is thought to be a product of the acquisition of hierarchically arranged subskills ( Dole et al., 1991 ). Thus, lower-level word recognition skills precede the development of more complex skills that lead to an eventual understanding of phrases, sentences, and paragraphs. Automaticity in processing and understanding written text is also thought to affect text comprehension ( LaBerge & Samuels, 1974 ). Automaticity refers to the fact that proficient readers can read text automatically and that they do not need to focus consciously on lower-level word recognition. Thus, children with decoding problems allot greater cognitive resources to word recognition – and less to comprehension – whereas proficient readers are able to devote greater cognitive resources to higher-level cognitive processes (e.g., working memory; Daneman & Carpenter, 1980; Perfetti, 1985 ; Perfetti & Hogaboam, 1975 ).

Based on the top-down (i.e., conceptually-driven) view of reading comprehension, readers are moving from meaning down to the component parts of words as they engage with text ( Rumelhart, 1980 ; Shank & Abelson, 1977 ). According to this view, a reader's mental frameworks or schemas are the driving force behind successful reading comprehension ( Rumelhart, 1980 ). Readers are actively integrating new information that is encountered in the text with information that they have already stored within their previously established mental representations (i.e., background knowledge).

Top-down and bottom-up aspects are combined in the interactive view of reading comprehension. Based on this view, reading comprehension requires the reader to devote attentional resources to the more basic features of the text (e.g., letters, words) while simultaneously focusing on the more general aspects (e.g., syntax, semantics) and actively interpreting what is being read ( Perfetti et al., 2005 ). Proficient readers are those who successfully engage with multiple sources of information provided within the text and information that is not readily available from the text (Kintsch, 1998; Perfetti & Stafura, 2014 ; van Dijk & Kintsche, 1983 ). Good readers are are able to recognize and interact with key features of the text, such as lexical characteristics, at the same time that they are more broadly identifying the purpose of a passage or a paragraph ( Rayner, 1986 ; Rayner et al., 2001 ).

The simple view of reading asserts that reading comprehension is the product of decoding ability and language comprehension ( Gough & Tunmer, 1986 ; Hoover & Gough, 1990 ). The simple view also has substantial empirical validation. For example, decoding has emerged as a reliable predictor of reading comprehension ability in a variety of instances (e.g., Kendeou, van den Broek, White, & Lynch, 2009 ; Shankweiler et al., 1999 ). In fact, poor decoding skills are associated with reading comprehension problems ( Perfetti, 1985 ). Additionally, oral language skills remain a robust and unique predictor of reading comprehension over and above word reading skills ( Nation & Snowling, 2004 ).

Oral language is defined as the ability to comprehend spoken language ( National Early Literacy Panel, 2008 ) and includes a wide variety of skills, such as expressive and receptive vocabulary knowledge, grammar, morphology, syntactic knowledge, conceptual knowledge, and knowledge about narrative structure ( Beck, Perfetti, & McKeown, 1982 ; Bishop & Adams, 1990 ; Bowey, 1986 ; Perfetti, 1985 ; Roth, Speece, & Cooper, 2002 ). Oral language skills impact reading comprehension directly, such as through the understanding of the words presented in a text, as well as indirectly via other literacy-related skills (e.g., phonological awareness; NICHD, 2000 ; Wagner & Torgesen, 1987 ). Furthermore, the unique contribution of oral language to reading comprehension remains even after accounting for word recognition ( Oullette, 2006 ).

The simple view provides a potential explanation for the reading comprehension problems of children with SCD that is consistent with their observed oral language deficits: Reading comprehension requires both adequate decoding and adequate oral language comprehension. This would explain the observation that children with SCD have adequate decoding but not adequate oral language comprehension. Catts, Adolf, and Weismer (2006) and Nation and Norbury (2005) applied this simple view of reading framework to identify different types of reading problems in eighth graders and 8-year-old children, respectively. According to this classification system, children with good decoding and good comprehension are adequate readers; children with poor decoding and poor comprehension are garden-variety poor readers; children with good comprehension and poor decoding meet criteria for dyslexia; and children with good decoding and poor comprehension have SCD. Thus, a mastery of both decoding and language comprehension is necessary for reading proficiency.

Developmental Delay or Developmental Deficit?

Developmental delay and developmental deficit are two hypotheses that are often discussed in relation to the nature of reading disability (e.g., dyslexia; see Francis, Shaywitz, Stuebing, Shaywitz, & Fletcher, 1996 ). The developmental delay hypothesis asserts that poor reading performance results from a delayed acquisition of reading-related skills ( Francis et al., 1996 ). However, these children follow the same developmental trajectory as typical readers ( Francis et al., 1996 ). The developmental deficit hypothesis, on the other hand, states that the underlying skill shows a different or deviant developmental trajectory ( Francis et al., 1996 ). For the case of reading disability, the underlying skill examined was phonological processing. We are interested in determining whether an oral language weakness represents a developmental delay or deficit for children with SCD. This hypothesis could be tested within studies that matched children with SCD to a younger group of typically-developing children (comprehension-age matching; see Cain, Oakhill, & Bryant, 2000 ). If children with SCD demonstrated similar performance to the comprehension-age matched group this would support developmental delay. If children with SCD had worse performance than the comprehension-age matched group, this outcome would support developmental deviance.

The importance of the distinction between developmental delay and developmental deficit is that a skill that is characterized as a developmentally deficit is more likely to be a contributing factor in the development of the reading problem. Developmental delay implies that the skill is consistent with the observed delay in reading and is therefore less likely to be a contributing factor. To our knowledge, an empirical examination of these two hypotheses has not yet been conducted for the observed oral language deficits in children with SCD.

Below, we describe a study conducted by Cain and Oakhill (2006) that has several characteristics that are typical of studies involving children with SCD. In this investigation, the authors were interested in the cognitive profiles of 7- to 8-year-old children with SCD; this age range is very common for investigations of children with SCD (e.g., Cain, 2003 ; Cain & Oakhill, 1996 , 2007; Jerman, 2007; Oakhill, 1982 ). Children were selected based on their performance on measures of reading comprehension and word reading accuracy and were followed longitudinally. In this case, the Neale Analysis of Word Reading Ability was used to categorize children into groups of good and poor comprehenders. Age-appropriate word reading accuracy was defined as being between 6 (lower limit) and 12 months (upper limit) of their chronological age (e.g., Clarke, 2009 ). Poor reading comprehension was defined as a 12-month discrepancy between comprehension age and chronological age and their reading accuracy age and comprehension age (e.g., Nation & Snowling, 1999 , 2000 ; Weekes, Hamilton, Oakhill, & Holliday, 2008 ). Typical readers are defined as attaining reading comprehension scores that are at or above word reading accuracy performance. Due to one-to-one matching and the low proportion of SCD in the population, final groups were small (23 children per group); this is typical of many studies involving children with SCD (e.g., Ehrlich & Remond, 1997 ; Geva & Massey-Garrison, 2012 ; Nation & Snowling, 1998a , 1998b ). In this study, children were given a battery of assessments that included a combination of standardized and experimenter-created measures (e.g., Nation et al., 1999 ; Nation & Snowling, 2000 ). A unique aspect of this investigation is that children were followed longitudinally; many studies involving children with SCD are single time point studies (e.g., Cain & Oakhill, 1999 ; Oakhill, 1983 ).

SCD has been defined in a variety of ways across different studies. Although researchers tend to agree on the need for a discrepancy between an individual's decoding ability and their reading comprehension skills, individuals with SCD (also referred to as poor comprehenders or less-skilled comprehenders in the literature) have been identified using one of four criteria:

• A discrepancy between reading comprehension and decoding (e.g., Isakson & Miller, 1976 ; Nation & Snowling, 1998a ; Oakhill, Yuill, & Parkin, 1986 ; Pimperton & Nation, 2010a );
• A discrepancy between reading comprehension and decoding with an additional requirement that decoding skills are within the normal range (e.g., Cain et al., 2001 ; Cataldo & Oakhill, 2000 ; Cragg & Nation, 2006 ; Torppa et al., 2009);
• Discrepancies between reading comprehension, decoding, and chronological age with an additional requirement that decoding skills are within the normal range ( Cain, 2003 ; Cain, 2006 ; Cain et al., 2000 ; Cain & Oakhill, 2006 , 2011 ; Cain, Oakhill, & Elbro, 2003 ; Cain, Oakhill, & Lemmon, 2004 ; Cain & Towse, 2008 ; Clarke, 2009 ; Marshall & Nation, 2003 ; Nation & Snowling, 1997 , 2000 ; Nation et al., 2001 ; Oakhill et al., 2005 ; Spooner, Gathercole, & Baddeley 2006 ; Stothard & Hulme, 1995 ; Yuill, 2009 ; Yuill & Oakhill, 1991 );
• A discrepancy between reading comprehension and word-level decoding with additional requirements that decoding skills are within the normal range and that comprehension scores fall below a given percentile or cut point ( Cain & Towse, 2008 ; Carretti, Motta, & Re, 2014 ; Catts et al., 2006 ; Henderson, Snowling, & Clarke, 2013 ; Kasperski & Katzir, 2012; Megherbi, Seigneuric, & Ehrlich, 2006 ; Nation, Clarke, Marshall, & Durand, 2004 ; Nation, Snowling & Clark, 2007 ; Nesi, Levorato, Roch & Cacciari, 2006 ; Pelegrina, Capodieci, Carretti, & Cornoldi, 2014 ; Pimperton & Nation, 2014 ; Ricketts, Nation, & Bishop, 2007 ; Shankweiler et al., 1999 ; Tong et al., 2011 ; Tong et al., 2014 ).

Despite the fact that differences in identification criteria influence the percentage of children identified as having SCD (see Rønberg & Petersen, 2015 ), children with SCD likely represent a small but significant proportion of struggling readers. Moreover, across studies included within the present review, SCD was identified using all of these different criteria. Therefore, our findings provide an overall estimate of the nature of children's comprehension problems regardless of identification method.

The purpose of the present meta-analysis is to better understand the comprehension deficits of children who have SCD. The framework for the present meta-analysis grew out of a recent investigation that tested three hypotheses regarding the nature of the comprehension problem in a large sample of over 425,000 first-, second-, and third graders with SCD ( Spencer, Quinn, & Wagner, 2014 ). The three hypotheses tested whether comprehension problems for these children were largely specific to reading, general to oral language, or both (i.e., a mixture). Children were obtained from a statewide database, and prevalence of SCD was calculated based on percentile cutoffs. The results indicated that over 99 percent of children in each grade who had SCD also had deficits in vocabulary knowledge. This finding indicates that children's comprehension deficits were general to reading and at least one important aspect of oral language.

Although these results provide compelling evidence that comprehension problems are general to at least one aspect of oral language (i.e., vocabulary knowledge), three limitations of the study need to be noted. First, participants included mostly children attending Reading First schools, a Federal program for improving reading performance for students from low socioeconomic backgrounds. Because poverty is a risk factor for delayed development of oral language, the results may not generalize to students not living in poverty. Second, the assessments were brief and receptive vocabulary knowledge served as the only measure of oral language comprehension, when in fact, oral language is potentially comprised of a variety of different skills that might affect reading comprehension. Third, the study did not compare the relative magnitudes of the deficits observed in reading comprehension and vocabulary, a potentially important new source of data that could be used to compare alternative hypotheses about the nature of the comprehension problems of children with SCD.

These limitations suggest the need for a comprehensive review of the literature on the nature of the comprehension problems of children who have SCD. Such a review could incorporate results from studies with more representative samples and using a variety of measures. By examining magnitudes as well as the existence of deficits in reading versus oral-language comprehension, it would be possible to test a previously neglected hypothesis in Spencer et al. (2014) , namely that children with SCD could have deficits in oral language that are not as severe as their deficits in reading comprehension.

Thus, in addition to testing two hypotheses from Spencer et al. (2014) – (a) Children with SCD have comprehension deficits are specific to reading, such that they demonstrate impaired reading comprehension but no impairments in oral language and (b) children with SCD have comprehension deficits are general to reading and oral language, such that they demonstrate equal impairment in reading comprehension and oral language – we also test a third hypothesis in the present meta-analysis, (c) children with SCD have comprehension deficits that extend beyond reading to oral language, but they demonstrate greater impairment in reading comprehension than in oral language.

Hypothesis one: children with SCD have comprehension problems that are specific to reading

Theoretical support for this hypothesis comes from the bottom-up view of reading comprehension and from the automaticity of reading ( Gough, 1972 ; Holmes, 2009 ; LaBerge & Samuels, 1974 ). It is possible that children might have adequate decoding but their adequate decoding requires processing resources that are then not available for comprehension while reading. If this were the case, their comprehension would be impaired for reading comprehension because decoding is required but not impaired for oral language.

Empirical support for this hypothesis comes from studies that demonstrate the existence of individuals who have been identified as having SCD in the presence of intact or relatively intact vocabulary knowledge ( Cain, 2006 ; Nation, et al., 2010 ). Moreover, some studies that compared children with and without SCD matched them on vocabulary performance (e.g., Cain, 2003 , Cain, 2006 ; Spooner et al., 2006 ; Tong et al., 2014 ). That it was possible to do this match supports the possibility that comprehension problems are specific to the domain of reading.

Hypothesis two: children with SCD have comprehension problems that are general to reading and oral language

Several theoretical perspectives provide a rationale for this hypothesis, including the simple view, top-down view, and interactive views of reading comprehension. The simple view ( Gough & Tunmer, 1986 ; Hoover & Gough, 1990 ) provides support for this hypothesis because it explains SCD as resulting from a deficit in oral language comprehension ( Catts et al., 2006 ; Nation et al., 2004 ). The top-down and interactive views are in line with this hypothesis because both frameworks emphasize the readers' mental frameworks ( Rumelhart, 1980 ; Shank & Abelson, 1977 ). The top down processing highlighted in both frameworks would affect comprehension regardless of whether the context is written or oral language.

Empirical support for this hypothesis comes from studies showing that oral language ability is a predictor of future reading comprehension success and failure ( Nation & Snowling, 2004 ; Snow et al., 1998 ); children with reading comprehension problems tend to have deficits in oral language ( Catts, Fey, Tomblin, & Zhang, 2002 ). For example, Catts, Fey, Zhang, and Tomblin (1999) investigated relations between oral language and reading comprehension skills in second graders. Results indicated that children with reading comprehension deficits were significantly more likely to have had oral language weaknesses in kindergarten compared to students with more typical comprehension development (see also Elwer, Keenan, Olson, Byrne, & Samuelsson, 2013 ).

The view that comprehension problems are general to oral language and reading is supported by multiple investigations. Children with SCD have demonstrated weaknesses related to a variety of oral language domains, such as semantic processing, listening comprehension, and syntactic ability ( Carretti, Motta, & Re, 2014 ; Nation & Snowling, 2000 ; see Cain & Oakhill, 2011 and Justice, Mashburn, & Petscher, 2013 for longitudinal evidence). When compared to typical readers, these children also tend to perform significantly poorer on measures tapping verbal working memory skills (see Carretti, Borella, Cornoldi, & De Beni, 2009 ). Differences between typically-developing readers and individuals with SCD have also been reported using a wide variety of behavioral and EEG/ERP measures (e.g., Landi & Perfetti, 2007 ).

Hypothesis three: children with SCD have comprehension problems that extend to oral language but are less severe for oral language than for reading

Theoretical support for this hypothesis is provided by a combination of theoretical rationales discussed for the previous two hypotheses. Specifically, a deficit that is general to oral language as well as reading comprehension is assumed, combined with additional deficits that are specific to reading. For example, a deficit in vocabulary would impair performance in reading comprehension and oral language. Simultaneously, decoding and orthographic processing could require attention and cognitive resources that are not required by listening, such as visual processing. The combined result would be impairments in both oral language and reading comprehension, but the impairment would be greater for reading comprehension.

Empirical support for this hypothesis comes from studies showing that these children demonstrate differential performance across various oral language tasks ( Cain, 2003 ; Cain, 2006 ; Cain, Oakhill, & Lemmon, 2005 ; Stothard & Hulme, 1992 ; Tong et al., 2014 ). For example, Cain (2003) examined language and literacy skills in children with SCD who were matched to typical readers based on vocabulary; however, these same children exhibited significantly poorer performance on other oral language tasks, such as listening comprehension and a story structure task. Similarly, Tong et al. (2014) included children with SCD who were vocabulary-matched to typical readers. Yet, children with SCD exhibited poor performance on a morphological awareness task. Therefore, it may be that the comprehension problems of children with SCD affects some but not all aspects of oral language.

Additionally, we were interested in examining the effect of several potential moderators of effect size outcomes, specifically the effects of (a) publication type, (b) participant age, and (c) type of oral language measure. The rationale for these moderators are as follows: First, if publication type (e.g., published journal article versus unpublished dissertation) significantly predicts effect size outcomes, we would attribute this, at least partially, to publication bias. Thus, we wanted to include this variable within each meta-analysis. Second, we were interested in participant age as a moderator of effect sizes ( Catts et al., 2006 ; Elwer et al., 2013 ; Nation, Cocksey, Taylor, & Bishop, 2010 ). Previous research has also indicated that younger children with SCD tend to have weaker reading comprehension skills compared to older children ( Authors, 2017 ). We sought to investigate whether this finding would be replicated within a different sample and also whether these differences transfer to oral language skills as well. Finally, type of oral language measure was included as a potential moderator due to the fact that oral language measures vary greatly in the skills that they assess ( Cain & Oakhill, 1999 ; Nation et al., 2004 , 2010 ; Tong et al., 2011 ). For instance, a receptive vocabulary assessment is likely to be much less difficult for a child with SCD compared with a syntactic or morphological task. Therefore, examining the potential effects of type of oral language measure may provide additional insight into which tasks may be best to use for identifying children with SCD.

Across four decades, multiple systematic reviews of reading comprehension have been conducted. These reviews have examined a variety of topics, including an examination the component skills of reading comprehension and intervention research for struggling readers (e.g., Bus & van Ijzendoorn, 1999 ; Ehri, Nunes, Stahl, & Willows, 2001 ; Swanson, Tranin, Necoechea, & Hammill, 2003 ). In more recent years, there have been several narrative reviews focusing specifically on children with SCD ( Hulme & Snowling, 2011 ; Nation & Norbury, 2005 ; Oakhill, 1993 ), but only one known meta-analysis to date has investigated the cognitive skills of these individuals ( Carretti et al., 2009 ). However, Carretti et al. (2009) focused exclusively on working memory skills whereas the present investigation examines performance of children with and without SCD on a wide array of oral language tasks in addition to verbal working memory.

In the present review, we examine studies using five methods. First, we conducted between-group meta-analyses comparing the reading comprehension performance of children with SCD with the reading comprehension performance of typically-developing readers. Second, we conducted between-group analyses comparing the oral language performance (as indexed by measures of vocabulary, listening comprehension, storytelling ability, morphological awareness, and semantic and syntactic knowledge) of children with SCD with the oral language performance of typically-developing readers. Third and fourth, we conducted the same meta-analyses for reading comprehension and oral language performance for studies that included a comprehension-age matched group (see Cain et al., 2000 ). The existence of such studies makes it possible to determine whether impaired oral language performance represents developmental delay (i.e., performance similar to younger normal comprehenders) or a developmental difference (i.e., performance different than that of younger normal comprehenders; Francis et al., 1996 ). Finally, we conducted a separate meta-analysis for studies reporting performance on standardized reading comprehension and oral language measures for the same participants (i.e., a within-child comparison of reading comprehension and oral language) because we were interested in the comparability of oral language skills to reading comprehension within children who have SCD.

Study Collection

The current meta-analysis includes studies published in English from January 1, 1970 to February 20, 2016. Several electronic databases and keywords were used to locate relevant studies. These databases included PsycINFO, ERIC, Medline, and ProQuest Dissertations. In an effort to reduce the likelihood of publication bias within the present review, we also searched several gray literature databases (i.e., SIGLE, ESRC, and Web of Science ). We used title-based keywords related to reading comprehension and reading disabilities ( specific comprehension deficit*, poor comprehender*, comprehension difficult*, less-skilled comprehen*, comprehension failure, reading difficult*, difficulty comprehending, poor comprehension, struggling reader*, specific reading comprehension difficult*, specific reading comprehension disabilit*, low comprehender*, weak reading comprehen*, reading comprehension disab*, poor reading comprehension ) in combination with other reading-related keywords ( reader*, reading, subtype*, subgroup ). Our search spanned peer-reviewed and non-peer-reviewed journal articles, dissertations and theses, book chapters, reports, and conference proceedings. The references of relevant articles were also hand searched, and we contacted researchers who had at least three relevant publications (first authored or not) as a way of including unpublished data within the present review. We conducted additional searches for these same researchers using author- and abstract-based keyword searches [au( author ) AND ab( comprehen* )].

Inclusionary criteria

Several inclusionary criteria were used to select studies to be included within the present synthesis. Studies were required to: (a) report original data (i.e., sample means, standard deviations, correlations, sample sizes, t -tests, and/or F -tests); (b) include native speakers of a language; (c) assess children between the ages of 4 and 12 years; (d) contain at least one measure of reading comprehension, decoding ability, and oral language; (e) include a sample of children with SCD based on their performance on measures of reading comprehension and decoding ability; and (f) include a typically-developing group of readers for comparisons 2 .

We applied the language-based criterion because we wanted to be able to investigate the relation between poor reading comprehension and oral language skills separate from language status because language status is known to affect reading comprehension (e.g., Kieffer, 2008 ). However, studies could include monolingual samples that spoke a language other than English (e.g., Italian) provided that the study was reported in English. Acceptable measures of reading comprehension included assessments that measured individuals' comprehension of the text beyond word reading ability; acceptable measures of decoding ability included assessments that measured real word decoding, nonword decoding, and/or reading accuracy; and acceptable measures of oral language included tasks that assessed vocabulary knowledge, syntactic and semantic processing, listening comprehension, and/or storytelling ability.

Exclusionary criteria

Three exclusionary criteria were applied for studies included in the current meta-analysis: (a) teacher and parent ratings were not acceptable methods for identifying children with SCD, (b) samples of non-native speakers, and (c) samples could not also contain children characterized as having intellectual disability, attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), aphasia, hydrocephalus, or hearing or vision impairments.

Final study selection

The initial search yielded approximately 3,050 results. After eliminating duplicates, studies that did not adhere to our inclusion/exclusion criteria, and studies reporting results from identical participants, a total of 86 studies remained.

A random sample of 10% of the studies was coded twice by the first author and a graduate student in order to establish inter-coder reliability; studies were coded based on study features (i.e., study type, sample size, operational definition of SCD, matching variables, language spoken, and sample age) and reading comprehension- and oral language-related constructs (i.e., reported reliabilities, correlations with oral language measures, means and standard deviations for each assessment, and reported t values or F ratios). We additionally coded participant age, type of oral language measure (i.e., vocabulary knowledge, narrative, listening comprehension, syntactic/grammar, semantic knowledge, and figurative language), and type of publication (i.e., journal article, book chapter, theses/dissertations, and unpublished data). Cohen's kappa was used to measure inter-coder reliability (96% for study features; 98% for reading comprehension-related constructs; 94% for the oral language-related constructs). The overall reliability exceeded acceptability of kappa ≥ .70 (kappa = 96%). Discrepancies were resolved through discussion or by referring to the article.

The final sample included 84 studies for between ( k brc = 152 effect sizes for reading comprehension ; k bol = 309 effect sizes for oral language) and within-group analyses ( k wrc = 97 effect sizes). The between-group analyses were twofold. One was a comparison of children with SCD to typical readers and another was a comparison of children with SCD to a comprehension-age matched group of children. Between-group comparisons of children with SCD to typical readers allowed for a test of the three hypotheses outlined previously: (a) children with SCD have comprehension problems that are specific to reading; (b) children with SCD have comprehension problems that are general to reading and oral language; or (c) children with SCD have comprehension problems that extend to oral language but are less severe for oral language than for reading. Between-group comparisons of children with SCD to a comprehension-age matched group allowed for a test of the delay versus deficit hypotheses for the anticipated oral language difficulties. A subsample of the original study sample ( n = 4) included comprehension-age matched groups for additional analyses ( k brc = 4 effect sizes for reading comprehension ; k bol = 30 effect sizes for oral language).

Within-child analyses require that both measures within a single study use the same scale. Thus, in order to be included within the within-child analysis, studies had to include standardized measures of reading comprehension and oral language and report standard scores, scaled scores, z -scores, or t -scores. Our within-child analyses allowed us to test the robustness of the pattern of results observed in the between-group comparison. That is, we were able to compare the reading comprehension and oral language skills within children who had SCD.

Meta-Analytic Methods

All analyses were conducted using Microsoft Excel (Version 14.0), and Metafor ( Viechtbauer, 2010 ) and Robumeta packages in R ( Fisher & Tipton, 2015 ). Effect sizes were calculated using Hedge's g (Hedges, 1981), which is Cohen's d ( Cohen, 1977 ) after incorporating a correction for small sample sizes. Negative effect size values indicate that children with SCD had a lower group mean than typically developing readers. In several instances, groups were vocabulary-matched (i.e., children with SCD were selected on the basis of having average vocabulary performance compared to a group of typical readers). 3

Average weighted effect sizes for each meta-analysis were calculated using random-effects models, which assume all parameters to be random as opposed to fixed ( Shadish & Haddock, 2013 ). We used random-effects models in the present investigation because Q (i.e., homogeneity of effect size; Hedges & Olkin, 1985 ) was rejected across most comparisons. For one comparison, Q was not rejected; for this meta-analysis, we used a fixed-effects model. We also estimated I 2 , which calculates the percentage of variance due to heterogeneity. We used random-effects models to calculate a 95% confidence interval (CI) in order to determine whether each calculated average weighted effect size was statistically significant (i.e., different from zero). A CI within random-effects models assumes systematic study variability (i.e., that differences across studies do not result from random sampling error; Shadish & Haddock, 2013 ). We additionally conducted an Egger test for funnel plot asymmetry within each meta-analysis as a means of testing whether publication bias was present (significant plot asymmetry) or absent (non-significant plot asymmetry; Egger, Smith, Schneider, & Minder, 1997 ).

Across meta-analyses, there were several instances in which a single study resulted in multiple effect size estimates. We used robust variance estimation with the small sample size correction to handle dependent effect sizes ( Hedges, Tipton, & Johnson, 2010 ; Tipton, 2015 ). This relatively recent approach has advantages over alternative approaches to handling dependent effect sizes such as including only one effect size per study, creating an average effect size, or using multivariate approaches to model the dependency. Robust variance estimation allows one to use all effect sizes including multiple ones from the same sample in the meta-analysis for estimating average weighted effect sizes and for testing possible moderators, then corrects for the effects of the dependencies in the significance testing. Although robust variance estimation can be implemented in macros to common statistical packages such as SPSS, an efficient way of doing so is by using the Robumeta package available in R ( Fisher & Tipton, 2015 ). We carried out meta-regressions analyses of potential moderators using Robumeta when there were dependent effect sizes. For meta-analyses that did not demonstrate dependency among effect size estimates (i.e., between group comparison of reading comprehension for children with SCD and comprehension-age matched children), we calculated the average weighted effect size estimate using traditional methods in Metafor.

A total of 86 independent studies were included within the analyses. Effect sizes for each comparison are reported in Table 1 (see also Appendices A, B, and C). A substantial portion of studies included English-speaking samples (Study n = 72). Fourteen studies included children who spoke Italian ( n = 5), French ( n = 3), Finnish ( n = 1), Hebrew ( n = 1), Chinese ( n = 2), Portuguese ( n = 1), and Spanish ( n = 1). Across studies, children were between the ages of 4 and 12 years.

Note. k = Number of effect sizes; d = Average-weighted effect size estimate; CI = Confidence interval; SCD = Children with specific reading comprehension deficits;

Effect Size Analyses

Comparisons of children with scd to typical readers.

We compared children with SCD to typical readers on measures of reading comprehension and oral language. These analyses served as a means to test whether: (a) children with SCD have comprehension problems that are specific to reading; (b) children with SCD have comprehension problems that are general to reading and oral language; or (c) children with SCD have comprehension problems that extend to oral language but are less severe for oral language than for reading.

Reading comprehension

One hundred and fifty-two comparisons were made for the reading comprehension of children with SCD and typically-developing readers (Study n = 84). Across studies, there were 17,600 children with SCD ( M = 209.53; SD = 703.14; range: 7-3,236) who were compared with 155,874 typically developing children ( M = 1,855.64; SD = 6,737.96; range: 8-29,676). The average weighted effect size was negative, large, and statistically significant (random-effects robust variance estimation: d = −2.78, 95%CI [−3.01, −2.54]). Because the CI does not include zero, this indicates that the effect size estimate is significantly different from zero. This suggests that children with SCD performed substantially poorer on measures of reading comprehension compared to their typically developing peers, which was expected. Study-specific effect sizes for reading comprehension, participant ages, and sample sizes for these comparisons are reported in Appendix A ; effect sizes are reported in descending order. There was a large variability in effect size estimates across studies due to heterogeneity, I 2 = 94.39 (see Table 1 ). Sensitivity analyses indicated that varying values of rho (ρ) from 0 to 1 in .20 increments did not affect tau squared (τ 2 ), the subsequent weights, and the average weighted effect size estimate. This outcome suggests that the observed effect size is fairly robust. An Egger test of funnel plot asymmetry was significant, z = −7.09, p < .0001 (see Figure 1 ), indicating asymmetry in effect size estimates across studies.

Funnel plots for between- and within-group comparisons. Note . RC = Reading comprehension; OL = Oral language; WM = Working memory; CAM = Reading-comprehension age-match.

Oral language

Three hundred and nine comparisons were made for the oral language skills of children with SCD and typically-developing children, (Study n = 76). There were 16,494 children with SCD ( M = 219.93; SD = 706.39; range: 7-3,016) who were compared with 144,857 typically developing children ( M = 1,931.43; SD = 6,676.47; range: 8-28,970). The average weighted effect size was also negative, large, and statistically significant (random-effects robust variance estimation: d = −0.78, 95% CI [−0.89, −0.68]). Thus, when compared to children without comprehension problems, children with SCD additionally exhibit difficulty completing oral language tasks; however this deficit was not as severe as for reading comprehension. Study-specific effect sizes for oral language, participant ages, and sample sizes for these comparisons are reported in Appendix A ; effect sizes are reported in descending order. Variability due to heterogeneity was large across studies, I 2 = 85.55 (see Table 1 ). Sensitivity analyses indicated that the observed effect size is fairly robust; varying values of ρ resulted in no differences. An Egger test of funnel plot asymmetry was significant, z = −2.11, p < .05 (see Figure 1 ), suggesting some asymmetry in estimates. Additionally, we also examined verbal working memory for studies that were already included in the analysis, which added 91 additional comparisons to the analysis. The average weighted effect size remained negative, large, and statistically significant (random-effects robust variance estimation: d = −0.77, 95% CI [−0.87, −0.67]; I 2 = 85.12; see Table 1 ).

It is important to note that across comparisons of reading comprehension and oral language, different studies were available for analyses; however, when we analyzed only overlapping studies (Study n = 74), the effects for reading comprehension (random-effects robust variance estimation: d = −2.80, 95% CI [−3.05, −2.55]; I 2 = 94.68) and oral language were nearly identical (random effects robust variance estimation: d = −0.79, 95% CI [−0.90, −0.68]; I 2 = 85.50).

Comparisons of children with SCD to comprehension-age matched readers

Given that we found evidence that children with SCD do exhibit deficits in oral language, we were additionally interested in how such deficits were best characterized. Thus, we conducted a between-groups meta-analysis that compared the performance of children with SCD to younger comprehension-age matched readers. Children in the comprehension-age matched group were selected on the basis of having performance equivalent to children with SCD (see Cain et al., 2000 ). 4 Across studies, children within the comprehension-age matched group were approximately two years younger than children with SCD.

Four comparisons were made for the reading comprehension skills of children with SCD and comprehension-age matched control children (Study n = 4). There were 73 children with SCD ( M = 18.25; SD = 7.23; range: 14-29) compared with 68 typically-developing children across studies ( M = 17.00; SD = 6.78; range: 14-27). Study-specific effect sizes for reading comprehension, participant ages, and sample sizes for these comparisons are reported in Appendix B ; effect sizes are reported in descending order. The average weighted effect size was moderate and negative, but it was not statistically significant (fixed-effects: d = −0.31, 95% CI [−0.31, 0.02)]; Q (3) = .38, p = .94, I 2 = <1%; see Table 1 ). This outcome was expected given that the two groups were matched for reading comprehension performance. An Egger test of funnel plot asymmetry was non-significant, z = −.13, p = .90 (see Figure 1 ).

Thirty comparisons were made for the oral language skills of children with SCD and children within comprehension-age matched groups (Study n = 4). There were 73 children with SCD ( M = 18.25; SD = 7.23; range: 14-29) and 68 typically-developing children across studies ( M = 17.00; SD = 6.78; range: 14-27). The average weighted effect size was moderate and in favor of comprehension age-matched readers, but it was not statistically significant (random-effects robust variance estimation: d = 0.32, 95% CI [−0.49, 1.14]). These findings suggest that the oral language performance of children with SCD is similar to the performance of younger typical readers. In other words, there is a developmental delay in the oral language skills of children with SCD. Study-specific effect sizes for oral language, participant ages, and sample sizes for these comparisons are reported in Appendix B ; effect sizes are reported in descending order. Across studies, the variability due to heterogeneity was relatively high, I 2 = 77.13 (see Table 1 ). Sensitivity analyses indicated that the observed effect size was quite robust; varying values of ρ resulted in a .02 difference (τ 2 =.402 when ρ = 0; .423 when ρ = 1), which was minimal. However, because the degrees of freedom for these analyses were less than four, it is important to interpret these results cautiously ( Fisher & Tipton, 2015 ). An Egger test of funnel plot asymmetry was non-significant, z = −0.71, p = .48 (see Figure 1 ).

Within-child comparisons of reading comprehension and oral language for children with SCD

In addition to comparing the language and literacy skills of children with SCD to typically-developing readers and comprehension age-matched readers, we also compared the oral language skills to reading comprehension within children who have SCD. The aim of this meta-analysis was so test to robustness of the results (i.e., would the same pattern of findings emerge if comparisons were made for the same group of children [within-group] as opposed to comparisons across different groups [between-group]). Thus, we additionally conducted analyses that examined the reading comprehension and oral language skills within individuals.

Ninety-seven comparisons were included within the analysis (Study n = 32). There were 12,711 children with SCD ( M = 397.22; SD = 822.21; range:7-2,830). Because these analyses included children with SCD, we corrected correlations for range restriction using Thorndike's (1949) correction equation. 5 The average weighted effect size was moderate, negative, and statistically significant (random-effects robust variance estimation: d = −0.84, 95% CI [−1.06, −0.62]), which indicates that the reading comprehension skills of children with SCD are significantly weaker than their oral language skills. These results can be found in Table 1 . Study-specific effect sizes, participant ages, and sample sizes for these comparisons are reported in Appendix C ; effect sizes are reported in descending order. Across studies, the variability due to heterogeneity was substantial, I 2 = 96.06. However, sensitivity analyses indicated that the observed effect size was fairly robust; varying values of ρ resulted in no difference in estimates of τ 2 . An Egger test of funnel plot asymmetry was non-significant for these comparisons, z = 1.33, p = .18 (see Figure 1 ).

It is important to note that different sets of studies were included within our analyses of between-group and within-child comparisons. This may explain why the difference between reading comprehension and oral language performance within children ( d = −0.84) was not equivalent to the differences found between groups for reading comprehension and oral language (effect size difference between −2.78 and −0.78 was −2.00). We empirically tested this by analyzing only those studies that were included within the between-group reading comprehension (random-effects robust variance estimation: d = −2.73, 95% CI [−3.05, −2.42]; I 2 = 96.82) and oral language comparisons (random-effects robust variance estimation: d = −0.95, 95% [CI −1.06, −0.83]; I 2 = 91.00) and the within-child comparisons. Applying this method, we achieved anoticeable reduction in the effect size differences across comparisons (effect size difference between −2.73 and −0.95 was 1.78). This outcome may be a partially due to the absence of publication bias within the within-group comparisons relative to the potential presence of publication bias within the reading comprehension and oral language comparisons.

Moderator Analyses

Metaregressions of study type, age, and oral language measures for comparisons of children with scd to typical readers.

Due to the substantial amount of heterogeneity across studies, we were interested in examining three possible moderators – age, type of oral language measure, and study type (i.e., published journal article, book chapter, thesis/dissertation, unpublished data) – that may explain effect size differences among various studies (see Table 1 and Appendices D and E ). Due to the dependency of effect sizes across studies, we used robust variance estimation to conduct moderator analyses for the present comparisons.

Study type, β = .14, p > .05, t (11.8) = 1.05, was not a significant moderator of differences in effect size estimates for reading comprehension for comparisons of children with SCD to typical readers. However, age, β = −.47, p < .05, t (23.9) = −2.53, was a significant moderator of effect size differences. Next, we examined moderators for comparisons of oral language. Neither study type nor age were significant moderators of differences in effect size outcomes for oral language, β = −.04, p > .05, t (17) = −0.77 for study; β = −.06, p > .05, t (20.1) = −0.85 for age. Because oral language was assessed using different measures across studies, we also conducted a metaregression to examine the potential for differences in oral language measures to be a moderator of effect size outcomes. Because oral language varied both within and across studies, it is important to include both the mean (i.e., between-study covariate) and mean-centered predictors (i.e., within-study covariate) within the moderator analyses to account for the potentially hierarchical structure of the effect size dependencies ( Fisher & Tipton, 2015 ). Using this method, type of oral language measure was not a significant moderator of effect size across studies, β m = −.05, p > .05, t (16.5) = −0.91; β mc = .00, p > .05, t (16.9) = 0.02.

Metaregressions of study type, age, and oral language measures for comparisons of children with SCD to comprehension-age matched readers

We also examined potential moderators within our reading comprehension age-matched comparisons (see Table 2 ). Similar to our between group comparisons, the type of oral language measure, β m = −.10, p > .05, t (1.08) = −0.18; β mc = −.23, p > .05, t (1.20) = −1.05, was not a significant moderator of effect size for the oral language comparisons. 6 However, because the degrees of freedom were less than four, this finding should be interpreted cautiously. Study type and the age range of participants was constant across studies, thus negating the need to conduct moderator analyses for these constructs for the reading comprehension and oral language comparisons.

Note . SCD = Children with specific reading comprehension deficits;

Metaregressions of study type, age, and oral language measures for within-child comparisons

We examined the moderators of study type, age, and oral language measure within our within-group comparisons as well, which are summarized in Table 2 . Study type was a significant predictor of differences in effect size, β = −.24, p < .01, t (15.3) = −2.77. Similarly, type of oral language measure was a significant predictor at the mean, β m = .20, p < .01, t (15.40) = 2.35; β mc = −.03, p > .05, t (8.30) = −0.85. Age, however, was a non-significant predictor in the model, β = −.00, p > .05, t (12.9) = −0.02.

The aim of the present meta-analysis was to determine the nature of the comprehension problems for children with SCD. This investigation was guided by three competing hypotheses: (a) children with SCD have comprehension deficits that are specific to reading; (b) children with SCD have comprehension deficits that are general to reading and oral language; or (c) children with SCD have comprehension problems that extend beyond reading but are more severe for reading than for oral language. The findings of the present meta-analysis support the third hypothesis. Children's weakness in oral language was substantial ( d = −0.78), but not as severe as their deficit in reading comprehension ( d = −2.78). The effects size estimates for oral language were comparable regardless of whether verbal working memory was included in the analysis ( d = −0.77). Within-child comparisons also indicated that performance in reading comprehension was worse than for oral language ( d = −0.84). The pattern of poorer performance in reading comprehension compared to oral language was consistent across all analyses.

When compared to comprehension age-matched readers, children with SCD tended to have comparable oral language ( d = 0.32, ns ) and reading comprehension skills ( d = −0.31, ns ). The fact that older children with SCD did not differ from younger normal readers on reading comprehension was expected rather than informative because the groups were matched on reading comprehension. However, the fact that they did not differ in oral language is informative. It supports the idea that the oral language weaknesses for children with SCD are best characterized as arising from a developmental delay as opposed to a developmental deviance ( Francis et al., 1996 ). A developmental deviance would have been supported had the oral language performance of the older children with SCD been worse than that of the younger comprehension-age matched normal readers.

Overall, our results are consistent with previous investigations. Children with SCD perform poorly on a range of oral language assessments including receptive and expressive vocabulary knowledge, listening comprehension, story structure, knowledge of idioms, awareness of syntactic structure, and morphological awareness among others ( Cain, 2003 ; Cain, 2006 ; Cain & Oakhill, 1996 ; Cain et al., 2005 ; Carretti et al., 2014 ; Nation & Snowling, 2000 ; Oakhill et al., 1986 ; Stothard & Hulme, 1996 ; Tong et al., 2011 , 2014 ; Yuill & Oakhill, 1991 ). These weaknesses emerged despite children's adequate decoding and seemingly intact phonological processing abilities ( Nation & Snowling, 2000 ; Nation et al., 2007 ; Stothard & Hulme, 1992 ). Yet, this pattern makes sense given that phonological processing appears to underlie decoding ability ( Nation et al., 2007 ; Shankweiler et al., 1999 ; Stothard & Hulme, 1996 ).

Explanations for Greater Deficits in Reading Comprehension than in Oral Language

A number of possible explanations for the observed discrepancies between reading comprehension and oral language exist. Although it is not possible to test alternative explanations in the context of the present meta-analysis, they could be tested in future studies.

A latent decoding deficit

At first glance, it seems counterintuitive that a decoding deficit would explain comprehension differences in children with SCD. However, in several studies, only decoding accuracy was used to categorize children (e.g., Cain & Oakhill, 2006 ). It is possible to be adequate in decoding accuracy yet inadequate in decoding fluency. In fact, this is a common outcome of intervention studies (e.g., de Jong & van der Leij, 2003; Torgesen & Hudson, 2006 ). The effortful application of phonics rules or other decoding strategies can result in accurate but slow decoding. This could impair reading comprehension because children's reading would be less automatic ( LaBerge & Samuels, 1974 ) and/or because fewer cognitive resources would be available for comprehension (e.g., Perfetti, 1985 ). This possible explanation could be tested in future studies by using measures of decoding fluency as well as accuracy. A dual-task paradigm could also be used to determine whether the cognitive resources required by decoding were comparable for children with and without SCD.

Differences between written and oral language

Written language differs from oral language in important ways ( Perfetti et al., 2005 ). Written language oftentimes contains more complex sentence structures and more difficult vocabulary than spoken language ( Akinnaso, 1982 ; Halliday, 1989 ). Thus, if children are having difficulty completing tasks that require the use of syntactic knowledge, for instance, they will most likely have difficulty reading grammatically complex texts. Fundamental differences between written and spoken text may also extend to increased demands on background knowledge (e.g., Wolfe & Woodwyck, 2010 ). Background knowledge has been identified as a critical component within several models of reading comprehension ( Kintsch, 1988 ; Kintsch, & van Dijk, 1983 ; Rumelhart, 1980 ). For instance, Kintsche and van Dijk's (1983) situation model describes the comprehension process as arising from an interaction of three mental models: the reader's text representation, semantic or meaning-based representation, and situational representation (i.e., prior knowledge, experiences, and interest).

There is also empirical evidence for the importance of background knowledge in reading comprehension (e.g., Stahl, Hare, Sinatra, & Gregory, 1991 ). This may explain why children with SCD also have problems with elaborative inference making and comprehension monitoring ( Cain et al., 2001 ; Oakhill, 1984 , 1993 ; Oakhill & Yuill, 1996 ). Further, differences in the amount of background knowledge required across oral language and reading comprehension tasks may explain the present pattern of skill deficits. This explanation could be tested in future studies by having children perform reading comprehension and listening comprehension tasks on identical passages and have the tasks counterbalanced across two groups. However, deficits in background knowledge may not sufficiently explain why children have SCD. In some instances, children with SCD continue to perform below expectations even after background knowledge is controlled (e.g., Cain & Oakhill, 1999 ; Cain et al., 2001 ).

Regression to the mean

Another potential explanation for the discrepancy between the reading comprehension and oral language skills of children with SCD is regression to the mean. Across studies, children were selected on the basis of poor reading comprehension. This design can lead to an over-representation of children whose observed reading comprehension score is below their true score. Consequently, they will regress to their true score on almost any subsequent measure that is correlated with the original measure. In the present context, children who were selected on the basis of poor reading comprehension may perform less poorly on oral language due to regression to the mean. Future studies could test this hypothesis by administering a second reading comprehension measure and then comparing performance on this measure to oral language. Using another design that does not involve selection based on poor reading comprehension performance would also be helpful to rule out this explanation.

Theoretical and Practical Implications of the Findings

We began this article with a review of theories of reading comprehension. We now consider the implications of our results for the theories that we reviewed. We first consider our results within the simple view of reading framework. ( Gough & Tunmer, 1986 ; Hoover & Gough, 1990 ). Based on this framework, the view is that reading comprehension is the product of decoding and oral language comprehension. Our results are not consistent with the common version of the simple view in which reading comprehension is predicted by additive effects (i.e., main effects) of decoding and oral language comprehension. If the simple view is operationalized as the interaction (i.e., multiplicative effects) between decoding and oral language comprehension, however, the results could be considered consistent with this framework. Essentially, the oral language deficit of children with SCD interacts with their decoding to produce reading comprehension that is more impaired than would be accounted for by the simple main effects. This same logic would apply to interactive activation models of reading to the extent that the interactive activation is truly interactive.

As is emphasized by the simple view and interactive models of reading comprehension, oral language is a critical component of reading comprehension. This assertion is supported by the current findings and previous studies ( Kendeou et al., 2009 ; Roth et al., 2002 ). For instance, two studies included within the present meta-analysis, Catts et al. (2006) and Nation et al. (2004) , found that a substantial portion of children who are identified as having specific language impairment (SLI) also have coexisting reading comprehension difficulties. In both investigations, 30% or one-third of children with SCD were eligible for SLI identification. Even children who were not identified as having SLI were identified as having subclinical levels of poor language comprehension (Catts et al.). Children with SCD had very poor performance on the vocabulary measure and grammatical understanding task. Catts et al. and Nation et al. referred to this subclinical poor language comprehension as hidden language impairment because these children are not typically classified as having SLI. Yet, these impairments could still potentially lead to the comprehension problems observed in these children.

If we allow for the possibility of a latent decoding problem, then nearly all of the theories of reading comprehension could account for the pattern of results that were obtained. Similarly, if we allow for the possibility of differences between written and oral language, the results would be consistent with multiple theories of reading. It will be important to carry out research to determine the best explanation for the pattern of a greater deficit in reading comprehension than in oral language. The outcome of this research will potentially affect implications for theories of reading. For example, if the pattern of a greater deficit in reading comprehension than in oral language is found when (a) groups are matched on decoding fluency as well as accuracy, (b) the reading and oral language tasks are for equivalent material, and (c) the study design eliminates the possible confound of regression to the mean, the results would only be consistent with a theory of reading that had an interactive component in addition to whatever main effects might be represented.

The implications for practice are threefold. First, the results suggest that early oral language measures may serve as a means of identifying children who are at risk for later reading comprehension problems ( Cain & Oakhill, 2011 ; Justice et al., 2013 ; Kendeou et al., 2009 ; Nation & Snowling, 2004 ; Nation et al., 2010 ; Roth et al. 2002 ). Oral language weaknesses for children with SCD are evident fairly early on, are relatively stable over time, and are predictive of future reading comprehension performance (e.g., Cain & Oakhill, 2011 ; Justice et al., 2013 ; Nation et al., 2010 ). Thus, oral language measures can potentially serve as a screening method to identify which children have weaknesses in language skills. However, this must be approached cautiously because not all oral language measures are equally predictive of a child's future reading comprehension status. For instance, Tong et al. (2011) gave children with SCD morphological tasks that assessed derivational morphological awareness. Performance of readers with SCD in Grade 3 did not significantly differentiate children with SCD from those with normal reading comprehension in Grade 5. Yet, performance on this morphological task in Grade 5 did result in significant differences between the two groups. This suggests that measures of derivational morphological awareness, for instance, may not be ideal for assessing early oral language skills (see Nippold & Sun, 2008 ). Consequently, it is important to consider this when selecting potential screening measures.

Second, the findings suggest that children with deficits in critical oral language skills should receive targeted oral language instruction and intervention. Intervention studies focusing specifically on children with SCD have indicated that interventions containing an oral language component are more effective. For example, Clarke, Snowling, Truelove, and Hulme (2010) randomly assigned three groups of 8- and 9-year-olds with SCD to receive three different types of interventions: text comprehension training, oral language training (without reading or writing), and a combined text comprehension-oral language training format. All three groups showed reliable and statistically significant gains in reading comprehension compared to the control group; however, the group that received the oral language training maintained the greatest gains after an 11-month follow up (for a review, see Snowling & Hulme, 2012 ). These outcomes are also aligned with the findings of the present review. Thus, classroom instruction and intervention that incorporate elements that encourage comprehension proficiency, such as reading fluency ( NICHD, 2000 ) and oral language ( Snow et al., 1998 ), will likely be more effective at remediating reading comprehension difficulties.

Third, the current investigation highlights the need to develop a consistent operational definition of SCD (see Rønberg & Petersen, 2015 ). For studies included in the present investigation, there were multiple ways in which children with SCD were identified. Differences in identification criteria are potentially problematic because it can lead to over- or under-identification. Such differences can also potentially lead to different groups of children being identified as having SCD over time. Yet, variability in identification criteria is not exclusive to the present population of poor readers. There remains much discourse about this issue more broadly within the field of learning disabilities ( Mellard, Deshler, & Barth, 2004 ).

Limitations and Future Directions

There are several limitations of the present meta-analysis that must be addressed. First, the present review focused specifically on monolingual school-age children. Consequently, the results may not apply to second-language learner or adult populations. Second, several studies included in the present review used the Neale Analysis of Reading to assess reading comprehension and decoding ability without incorporating an additional measure of either skill. This is potentially problematic because both decoding and comprehension scores are obtained simultaneously as children read passages. Decoding problems could therefore affect comprehension scores (see Spooner et al., 2004 ). Third, we did not examine the effect of IQ on the obtained effect size estimates. It may be the case that variability in IQ may affect effect size outcomes. Fourth, it is important to acknowledge the potential presence of some publication bias for the between-group comparisons of reading comprehension and oral language. This may contribute to the larger deficits seen between these skills.

Another limitation of this meta-analysis is that it does not address possible causal relations between the deficits in oral language and reading comprehension. It is certainly possible that poor oral language skills may contribute to the deficits in reading comprehension; children must know a substantial portion of the words in a text in order to comprehend it ( Hu & Nation, 2000 ; Kendeou et al., 2009 ). However, it is also possible that poor reading comprehension constrains future vocabulary growth because text reading provides a basis for incidental word learning ( Cain et al., 2004 ). These relations may also be reciprocal (e.g., Wagner, Muse, & Tannenbaum, 2007 ). Additionally, the general absence of longitudinal data did not allow for a more comprehensive examination of the developmental delay versus deficit hypotheses. A final limitation of the present study is that it was limited to children who were monolingual speakers of their native language. It is increasingly common for children to know more than one language. Would the results of the present meta-analysis generalize to children who were second-language learners? We decided to answer this question by carrying out a similar meta-analysis of children with poor reading comprehension yet adequate decoding, but for children who were second-language learners ( Authors, 2017 ). Sixteen studies were identified that met inclusionary and exclusionary criteria. Hedge's g was used as the effect-size measure, random-effects models were used, and robust variance estimation was used to correct significance testing for dependent effect sizes. The results were remarkably consistent with those of the present meta-analysis. A deficit in oral language was replicated with an average weighted effect size of -0.80. The pattern of the deficit in oral language being only about a third as large as the deficit in reading comprehension was also replicated, with an average weighed effect size of -2.47. In summary, the pattern of results found in the present meta-analysis of studies whose participants were monolingual children generalize to children who are second language learners.

In conclusion, children who have SCD are typically impaired in oral language, but not to the degree they are impaired in reading comprehension. Consequently, the oral language impairment is not sufficient to explain the impairment in reading comprehension. Possible explanations for this pattern of results were considered, including a latent decoding deficit, differences between written and oral language, regression to the mean, and interactive effects. Testing these alternative explanations and others that might be considered represents a critical next step to advance our understanding of an important problem in reading.

Acknowledgments

This research was supported by Grant Numbers P50 HD52120 and 1F31HD087054-01 from the National Institute of Child Health and Human Development, Grant Numbers R305F100005 and R305F100027 from the Institute for Education Sciences, and a Predoctoral Interdisciplinary Training Grant Number R305B090021 from the Institute for Education Sciences.

Appendix A. 

Study descriptions and effect size estimates for children with specific reading comprehension deficits and typical readers (Study n = 86).

Note. RC = Reading comprehension; OL = Oral language; SCD = Children with specific reading comprehension deficits; TR = Typical readers.

Appendix B. 

Study descriptions and effect sizes for children with specific reading comprehension deficits compared with comprehension-age matched readers (Study n = 4).

Appendix C. 

Study descriptions and effect size estimates for within-child comparisons (Study n = 32).

Appendix D. 

Coding scheme for study type, participant age, and type of oral language measure.

Appendix E. 

Types of oral language skills assessed across studies (Study n = 86).

Note. For some studies, oral language was assessed but not explicitly reported.

2 For some comparisons, this comparison included skilled comprehenders.

3 Although groups were matched, correlations for the same measure between the two groups were not reported in most instances; thus, independent effect sizes were calculated.

4 Although groups were matched, correlations for the same measure between the two groups were not reported in most instances; thus, independent effect sizes were calculated.

5 In several instances, studies did not report correlations. For these studies, an estimated correlation was substituted.

6 We also conducted moderator analyses for type of oral language measure without accounting for hierarchical structure and the results remained the same [β #x0003D; −0.31, p > .05, t(1.40) = −0.98].

References marked with an asterisk indicate studies included in the meta-analysis. The in-test citations to studies selected for meta-analysis are not preceded by asterisks.

45 Research Problem Examples & Inspiration

A research problem is an issue of concern that is the catalyst for your research. It demonstrates why the research problem needs to take place in the first place.

Generally, you will write your research problem as a clear, concise, and focused statement that identifies an issue or gap in current knowledge that requires investigation.

The problem will likely also guide the direction and purpose of a study. Depending on the problem, you will identify a suitable methodology that will help address the problem and bring solutions to light.

Research Problem Examples

In the following examples, I’ll present some problems worth addressing, and some suggested theoretical frameworks and research methodologies that might fit with the study. Note, however, that these aren’t the only ways to approach the problems. Keep an open mind and consult with your dissertation supervisor!

Psychology Problems

1. Social Media and Self-Esteem: “How does prolonged exposure to social media platforms influence the self-esteem of adolescents?”

• Theoretical Framework : Social Comparison Theory
• Methodology : Longitudinal study tracking adolescents’ social media usage and self-esteem measures over time, combined with qualitative interviews.

2. Sleep and Cognitive Performance: “How does sleep quality and duration impact cognitive performance in adults?”

• Theoretical Framework : Cognitive Psychology
• Methodology : Experimental design with controlled sleep conditions, followed by cognitive tests. Participant sleep patterns can also be monitored using actigraphy.

3. Childhood Trauma and Adult Relationships: “How does unresolved childhood trauma influence attachment styles and relationship dynamics in adulthood?

• Theoretical Framework : Attachment Theory
• Methodology : Mixed methods, combining quantitative measures of attachment styles with qualitative in-depth interviews exploring past trauma and current relationship dynamics.

4. Mindfulness and Stress Reduction: “How effective is mindfulness meditation in reducing perceived stress and physiological markers of stress in working professionals?”

• Theoretical Framework : Humanist Psychology
• Methodology : Randomized controlled trial comparing a group practicing mindfulness meditation to a control group, measuring both self-reported stress and physiological markers (e.g., cortisol levels).

5. Implicit Bias and Decision Making: “To what extent do implicit biases influence decision-making processes in hiring practices?

• Theoretical Framework : Cognitive Dissonance Theory
• Methodology : Experimental design using Implicit Association Tests (IAT) to measure implicit biases, followed by simulated hiring tasks to observe decision-making behaviors.

6. Emotional Regulation and Academic Performance: “How does the ability to regulate emotions impact academic performance in college students?”

• Theoretical Framework : Cognitive Theory of Emotion
• Methodology : Quantitative surveys measuring emotional regulation strategies, combined with academic performance metrics (e.g., GPA).

7. Nature Exposure and Mental Well-being: “Does regular exposure to natural environments improve mental well-being and reduce symptoms of anxiety and depression?”

• Theoretical Framework : Biophilia Hypothesis
• Methodology : Longitudinal study comparing mental health measures of individuals with regular nature exposure to those without, possibly using ecological momentary assessment for real-time data collection.

8. Video Games and Cognitive Skills: “How do action video games influence cognitive skills such as attention, spatial reasoning, and problem-solving?”

• Theoretical Framework : Cognitive Load Theory
• Methodology : Experimental design with pre- and post-tests, comparing cognitive skills of participants before and after a period of action video game play.

9. Parenting Styles and Child Resilience: “How do different parenting styles influence the development of resilience in children facing adversities?”

• Theoretical Framework : Baumrind’s Parenting Styles Inventory
• Methodology : Mixed methods, combining quantitative measures of resilience and parenting styles with qualitative interviews exploring children’s experiences and perceptions.

10. Memory and Aging: “How does the aging process impact episodic memory , and what strategies can mitigate age-related memory decline?

• Theoretical Framework : Information Processing Theory
• Methodology : Cross-sectional study comparing episodic memory performance across different age groups, combined with interventions like memory training or mnemonic strategies to assess potential improvements.

Education Problems

11. Equity and Access : “How do socioeconomic factors influence students’ access to quality education, and what interventions can bridge the gap?

• Theoretical Framework : Critical Pedagogy
• Methodology : Mixed methods, combining quantitative data on student outcomes with qualitative interviews and focus groups with students, parents, and educators.

12. Digital Divide : How does the lack of access to technology and the internet affect remote learning outcomes, and how can this divide be addressed?

• Theoretical Framework : Social Construction of Technology Theory
• Methodology : Survey research to gather data on access to technology, followed by case studies in selected areas.

13. Teacher Efficacy : “What factors contribute to teacher self-efficacy, and how does it impact student achievement?”

• Theoretical Framework : Bandura’s Self-Efficacy Theory
• Methodology : Quantitative surveys to measure teacher self-efficacy, combined with qualitative interviews to explore factors affecting it.

14. Curriculum Relevance : “How can curricula be made more relevant to diverse student populations, incorporating cultural and local contexts?”

• Theoretical Framework : Sociocultural Theory
• Methodology : Content analysis of curricula, combined with focus groups with students and teachers.

15. Special Education : “What are the most effective instructional strategies for students with specific learning disabilities?

• Theoretical Framework : Social Learning Theory
• Methodology : Experimental design comparing different instructional strategies, with pre- and post-tests to measure student achievement.

16. Dropout Rates : “What factors contribute to high school dropout rates, and what interventions can help retain students?”

• Methodology : Longitudinal study tracking students over time, combined with interviews with dropouts.

17. Bilingual Education : “How does bilingual education impact cognitive development and academic achievement?

• Methodology : Comparative study of students in bilingual vs. monolingual programs, using standardized tests and qualitative interviews.

18. Classroom Management: “What reward strategies are most effective in managing diverse classrooms and promoting a positive learning environment?

• Theoretical Framework : Behaviorism (e.g., Skinner’s Operant Conditioning)
• Methodology : Observational research in classrooms , combined with teacher interviews.

19. Standardized Testing : “How do standardized tests affect student motivation, learning, and curriculum design?”

• Theoretical Framework : Critical Theory
• Methodology : Quantitative analysis of test scores and student outcomes, combined with qualitative interviews with educators and students.

20. STEM Education : “What methods can be employed to increase interest and proficiency in STEM (Science, Technology, Engineering, and Mathematics) fields among underrepresented student groups?”

• Theoretical Framework : Constructivist Learning Theory
• Methodology : Experimental design comparing different instructional methods, with pre- and post-tests.

21. Social-Emotional Learning : “How can social-emotional learning be effectively integrated into the curriculum, and what are its impacts on student well-being and academic outcomes?”

• Theoretical Framework : Goleman’s Emotional Intelligence Theory
• Methodology : Mixed methods, combining quantitative measures of student well-being with qualitative interviews.

22. Parental Involvement : “How does parental involvement influence student achievement, and what strategies can schools use to increase it?”

• Theoretical Framework : Reggio Emilia’s Model (Community Engagement Focus)
• Methodology : Survey research with parents and teachers, combined with case studies in selected schools.

23. Early Childhood Education : “What are the long-term impacts of quality early childhood education on academic and life outcomes?”

• Theoretical Framework : Erikson’s Stages of Psychosocial Development
• Methodology : Longitudinal study comparing students with and without early childhood education, combined with observational research.

24. Teacher Training and Professional Development : “How can teacher training programs be improved to address the evolving needs of the 21st-century classroom?”

• Theoretical Framework : Adult Learning Theory (Andragogy)
• Methodology : Pre- and post-assessments of teacher competencies, combined with focus groups.

25. Educational Technology : “How can technology be effectively integrated into the classroom to enhance learning, and what are the potential drawbacks or challenges?”

• Theoretical Framework : Technological Pedagogical Content Knowledge (TPACK)
• Methodology : Experimental design comparing classrooms with and without specific technologies, combined with teacher and student interviews.

Sociology Problems

26. Urbanization and Social Ties: “How does rapid urbanization impact the strength and nature of social ties in communities?”

• Theoretical Framework : Structural Functionalism
• Methodology : Mixed methods, combining quantitative surveys on social ties with qualitative interviews in urbanizing areas.

27. Gender Roles in Modern Families: “How have traditional gender roles evolved in families with dual-income households?”

• Theoretical Framework : Gender Schema Theory
• Methodology : Qualitative interviews with dual-income families, combined with historical data analysis.

28. Social Media and Collective Behavior: “How does social media influence collective behaviors and the formation of social movements?”

• Theoretical Framework : Emergent Norm Theory
• Methodology : Content analysis of social media platforms, combined with quantitative surveys on participation in social movements.

29. Education and Social Mobility: “To what extent does access to quality education influence social mobility in socioeconomically diverse settings?”

• Methodology : Longitudinal study tracking educational access and subsequent socioeconomic status, combined with qualitative interviews.

30. Religion and Social Cohesion: “How do religious beliefs and practices contribute to social cohesion in multicultural societies?”

• Methodology : Quantitative surveys on religious beliefs and perceptions of social cohesion, combined with ethnographic studies.

31. Consumer Culture and Identity Formation: “How does consumer culture influence individual identity formation and personal values?”

• Theoretical Framework : Social Identity Theory
• Methodology : Mixed methods, combining content analysis of advertising with qualitative interviews on identity and values.

32. Migration and Cultural Assimilation: “How do migrants negotiate cultural assimilation and preservation of their original cultural identities in their host countries?”

• Theoretical Framework : Post-Structuralism
• Methodology : Qualitative interviews with migrants, combined with observational studies in multicultural communities.

33. Social Networks and Mental Health: “How do social networks, both online and offline, impact mental health and well-being?”

• Theoretical Framework : Social Network Theory
• Methodology : Quantitative surveys assessing social network characteristics and mental health metrics, combined with qualitative interviews.

34. Crime, Deviance, and Social Control: “How do societal norms and values shape definitions of crime and deviance, and how are these definitions enforced?”

• Theoretical Framework : Labeling Theory
• Methodology : Content analysis of legal documents and media, combined with ethnographic studies in diverse communities.

35. Technology and Social Interaction: “How has the proliferation of digital technology influenced face-to-face social interactions and community building?”

• Theoretical Framework : Technological Determinism
• Methodology : Mixed methods, combining quantitative surveys on technology use with qualitative observations of social interactions in various settings.

Nursing Problems

36. Patient Communication and Recovery: “How does effective nurse-patient communication influence patient recovery rates and overall satisfaction with care?”

• Methodology : Quantitative surveys assessing patient satisfaction and recovery metrics, combined with observational studies on nurse-patient interactions.

37. Stress Management in Nursing: “What are the primary sources of occupational stress for nurses, and how can they be effectively managed to prevent burnout?”

• Methodology : Mixed methods, combining quantitative measures of stress and burnout with qualitative interviews exploring personal experiences and coping mechanisms.

38. Hand Hygiene Compliance: “How effective are different interventions in improving hand hygiene compliance among nursing staff, and what are the barriers to consistent hand hygiene?”

• Methodology : Experimental design comparing hand hygiene rates before and after specific interventions, combined with focus groups to understand barriers.

39. Nurse-Patient Ratios and Patient Outcomes: “How do nurse-patient ratios impact patient outcomes, including recovery rates, complications, and hospital readmissions?”

• Methodology : Quantitative study analyzing patient outcomes in relation to staffing levels, possibly using retrospective chart reviews.

40. Continuing Education and Clinical Competence: “How does regular continuing education influence clinical competence and confidence among nurses?”

• Methodology : Longitudinal study tracking nurses’ clinical skills and confidence over time as they engage in continuing education, combined with patient outcome measures to assess potential impacts on care quality.

Communication Studies Problems

41. Media Representation and Public Perception: “How does media representation of minority groups influence public perceptions and biases?”

• Theoretical Framework : Cultivation Theory
• Methodology : Content analysis of media representations combined with quantitative surveys assessing public perceptions and attitudes.

42. Digital Communication and Relationship Building: “How has the rise of digital communication platforms impacted the way individuals build and maintain personal relationships?”

• Theoretical Framework : Social Penetration Theory
• Methodology : Mixed methods, combining quantitative surveys on digital communication habits with qualitative interviews exploring personal relationship dynamics.

43. Crisis Communication Effectiveness: “What strategies are most effective in managing public relations during organizational crises, and how do they influence public trust?”

• Theoretical Framework : Situational Crisis Communication Theory (SCCT)
• Methodology : Case study analysis of past organizational crises, assessing communication strategies used and subsequent public trust metrics.

44. Nonverbal Cues in Virtual Communication: “How do nonverbal cues, such as facial expressions and gestures, influence message interpretation in virtual communication platforms?”

• Theoretical Framework : Social Semiotics
• Methodology : Experimental design using video conferencing tools, analyzing participants’ interpretations of messages with varying nonverbal cues.

45. Influence of Social Media on Political Engagement: “How does exposure to political content on social media platforms influence individuals’ political engagement and activism?”

• Theoretical Framework : Uses and Gratifications Theory
• Methodology : Quantitative surveys assessing social media habits and political engagement levels, combined with content analysis of political posts on popular platforms.

Before you Go: Tips and Tricks for Writing a Research Problem

This is an incredibly stressful time for research students. The research problem is going to lock you into a specific line of inquiry for the rest of your studies.

So, here’s what I tend to suggest to my students:

• Start with something you find intellectually stimulating – Too many students choose projects because they think it hasn’t been studies or they’ve found a research gap. Don’t over-estimate the importance of finding a research gap. There are gaps in every line of inquiry. For now, just find a topic you think you can really sink your teeth into and will enjoy learning about.
• Take 5 ideas to your supervisor – Approach your research supervisor, professor, lecturer, TA, our course leader with 5 research problem ideas and run each by them. The supervisor will have valuable insights that you didn’t consider that will help you narrow-down and refine your problem even more.
• Trust your supervisor – The supervisor-student relationship is often very strained and stressful. While of course this is your project, your supervisor knows the internal politics and conventions of academic research. The depth of knowledge about how to navigate academia and get you out the other end with your degree is invaluable. Don’t underestimate their advice.

I’ve got a full article on all my tips and tricks for doing research projects right here – I recommend reading it:

• 9 Tips on How to Choose a Dissertation Topic

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 17 Behaviorism Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 25 Positive Psychology Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 15 Animism Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 10 Magical Thinking Examples

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Research Title: The Impact of Reading Difficulties in Relation to Academic Performance of the Grade VI pupils of Caidiocan Elementary School

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Home » Research Problem – Examples, Types and Guide

Research Problem – Examples, Types and Guide

Table of Contents

Research Problem

Definition:

Research problem is a specific and well-defined issue or question that a researcher seeks to investigate through research. It is the starting point of any research project, as it sets the direction, scope, and purpose of the study.

Types of Research Problems

Types of Research Problems are as follows:

Descriptive problems

These problems involve describing or documenting a particular phenomenon, event, or situation. For example, a researcher might investigate the demographics of a particular population, such as their age, gender, income, and education.

Exploratory problems

These problems are designed to explore a particular topic or issue in depth, often with the goal of generating new ideas or hypotheses. For example, a researcher might explore the factors that contribute to job satisfaction among employees in a particular industry.

Explanatory Problems

These problems seek to explain why a particular phenomenon or event occurs, and they typically involve testing hypotheses or theories. For example, a researcher might investigate the relationship between exercise and mental health, with the goal of determining whether exercise has a causal effect on mental health.

Predictive Problems

These problems involve making predictions or forecasts about future events or trends. For example, a researcher might investigate the factors that predict future success in a particular field or industry.

Evaluative Problems

These problems involve assessing the effectiveness of a particular intervention, program, or policy. For example, a researcher might evaluate the impact of a new teaching method on student learning outcomes.

How to Define a Research Problem

Defining a research problem involves identifying a specific question or issue that a researcher seeks to address through a research study. Here are the steps to follow when defining a research problem:

• Identify a broad research topic : Start by identifying a broad topic that you are interested in researching. This could be based on your personal interests, observations, or gaps in the existing literature.
• Conduct a literature review : Once you have identified a broad topic, conduct a thorough literature review to identify the current state of knowledge in the field. This will help you identify gaps or inconsistencies in the existing research that can be addressed through your study.
• Refine the research question: Based on the gaps or inconsistencies identified in the literature review, refine your research question to a specific, clear, and well-defined problem statement. Your research question should be feasible, relevant, and important to the field of study.
• Develop a hypothesis: Based on the research question, develop a hypothesis that states the expected relationship between variables.
• Define the scope and limitations: Clearly define the scope and limitations of your research problem. This will help you focus your study and ensure that your research objectives are achievable.
• Get feedback: Get feedback from your advisor or colleagues to ensure that your research problem is clear, feasible, and relevant to the field of study.

Components of a Research Problem

The components of a research problem typically include the following:

• Topic : The general subject or area of interest that the research will explore.
• Research Question : A clear and specific question that the research seeks to answer or investigate.
• Objective : A statement that describes the purpose of the research, what it aims to achieve, and the expected outcomes.
• Hypothesis : An educated guess or prediction about the relationship between variables, which is tested during the research.
• Variables : The factors or elements that are being studied, measured, or manipulated in the research.
• Methodology : The overall approach and methods that will be used to conduct the research.
• Scope and Limitations : A description of the boundaries and parameters of the research, including what will be included and excluded, and any potential constraints or limitations.
• Significance: A statement that explains the potential value or impact of the research, its contribution to the field of study, and how it will add to the existing knowledge.

Research Problem Examples

Following are some Research Problem Examples:

Research Problem Examples in Psychology are as follows:

• Exploring the impact of social media on adolescent mental health.
• Investigating the effectiveness of cognitive-behavioral therapy for treating anxiety disorders.
• Studying the impact of prenatal stress on child development outcomes.
• Analyzing the factors that contribute to addiction and relapse in substance abuse treatment.
• Examining the impact of personality traits on romantic relationships.

Research Problem Examples in Sociology are as follows:

• Investigating the relationship between social support and mental health outcomes in marginalized communities.
• Studying the impact of globalization on labor markets and employment opportunities.
• Analyzing the causes and consequences of gentrification in urban neighborhoods.
• Investigating the impact of family structure on social mobility and economic outcomes.
• Examining the effects of social capital on community development and resilience.

Research Problem Examples in Economics are as follows:

• Studying the effects of trade policies on economic growth and development.
• Analyzing the impact of automation and artificial intelligence on labor markets and employment opportunities.
• Investigating the factors that contribute to economic inequality and poverty.
• Examining the impact of fiscal and monetary policies on inflation and economic stability.
• Studying the relationship between education and economic outcomes, such as income and employment.

Political Science

Research Problem Examples in Political Science are as follows:

• Analyzing the causes and consequences of political polarization and partisan behavior.
• Investigating the impact of social movements on political change and policymaking.
• Studying the role of media and communication in shaping public opinion and political discourse.
• Examining the effectiveness of electoral systems in promoting democratic governance and representation.
• Investigating the impact of international organizations and agreements on global governance and security.

Environmental Science

Research Problem Examples in Environmental Science are as follows:

• Studying the impact of air pollution on human health and well-being.
• Investigating the effects of deforestation on climate change and biodiversity loss.
• Analyzing the impact of ocean acidification on marine ecosystems and food webs.
• Studying the relationship between urban development and ecological resilience.
• Examining the effectiveness of environmental policies and regulations in promoting sustainability and conservation.

Research Problem Examples in Education are as follows:

• Investigating the impact of teacher training and professional development on student learning outcomes.
• Studying the effectiveness of technology-enhanced learning in promoting student engagement and achievement.
• Analyzing the factors that contribute to achievement gaps and educational inequality.
• Examining the impact of parental involvement on student motivation and achievement.
• Studying the effectiveness of alternative educational models, such as homeschooling and online learning.

Research Problem Examples in History are as follows:

• Analyzing the social and economic factors that contributed to the rise and fall of ancient civilizations.
• Investigating the impact of colonialism on indigenous societies and cultures.
• Studying the role of religion in shaping political and social movements throughout history.
• Analyzing the impact of the Industrial Revolution on economic and social structures.
• Examining the causes and consequences of global conflicts, such as World War I and II.

Research Problem Examples in Business are as follows:

• Studying the impact of corporate social responsibility on brand reputation and consumer behavior.
• Investigating the effectiveness of leadership development programs in improving organizational performance and employee satisfaction.
• Analyzing the factors that contribute to successful entrepreneurship and small business development.
• Examining the impact of mergers and acquisitions on market competition and consumer welfare.
• Studying the effectiveness of marketing strategies and advertising campaigns in promoting brand awareness and sales.

Research Problem Example for Students

An Example of a Research Problem for Students could be:

“How does social media usage affect the academic performance of high school students?”

This research problem is specific, measurable, and relevant. It is specific because it focuses on a particular area of interest, which is the impact of social media on academic performance. It is measurable because the researcher can collect data on social media usage and academic performance to evaluate the relationship between the two variables. It is relevant because it addresses a current and important issue that affects high school students.

To conduct research on this problem, the researcher could use various methods, such as surveys, interviews, and statistical analysis of academic records. The results of the study could provide insights into the relationship between social media usage and academic performance, which could help educators and parents develop effective strategies for managing social media use among students.

Another example of a research problem for students:

“Does participation in extracurricular activities impact the academic performance of middle school students?”

This research problem is also specific, measurable, and relevant. It is specific because it focuses on a particular type of activity, extracurricular activities, and its impact on academic performance. It is measurable because the researcher can collect data on students’ participation in extracurricular activities and their academic performance to evaluate the relationship between the two variables. It is relevant because extracurricular activities are an essential part of the middle school experience, and their impact on academic performance is a topic of interest to educators and parents.

To conduct research on this problem, the researcher could use surveys, interviews, and academic records analysis. The results of the study could provide insights into the relationship between extracurricular activities and academic performance, which could help educators and parents make informed decisions about the types of activities that are most beneficial for middle school students.

Applications of Research Problem

Applications of Research Problem are as follows:

• Academic research: Research problems are used to guide academic research in various fields, including social sciences, natural sciences, humanities, and engineering. Researchers use research problems to identify gaps in knowledge, address theoretical or practical problems, and explore new areas of study.
• Business research : Research problems are used to guide business research, including market research, consumer behavior research, and organizational research. Researchers use research problems to identify business challenges, explore opportunities, and develop strategies for business growth and success.
• Healthcare research : Research problems are used to guide healthcare research, including medical research, clinical research, and health services research. Researchers use research problems to identify healthcare challenges, develop new treatments and interventions, and improve healthcare delivery and outcomes.
• Public policy research : Research problems are used to guide public policy research, including policy analysis, program evaluation, and policy development. Researchers use research problems to identify social issues, assess the effectiveness of existing policies and programs, and develop new policies and programs to address societal challenges.
• Environmental research : Research problems are used to guide environmental research, including environmental science, ecology, and environmental management. Researchers use research problems to identify environmental challenges, assess the impact of human activities on the environment, and develop sustainable solutions to protect the environment.

Purpose of Research Problems

The purpose of research problems is to identify an area of study that requires further investigation and to formulate a clear, concise and specific research question. A research problem defines the specific issue or problem that needs to be addressed and serves as the foundation for the research project.

Identifying a research problem is important because it helps to establish the direction of the research and sets the stage for the research design, methods, and analysis. It also ensures that the research is relevant and contributes to the existing body of knowledge in the field.

A well-formulated research problem should:

• Clearly define the specific issue or problem that needs to be investigated
• Be specific and narrow enough to be manageable in terms of time, resources, and scope
• Be relevant to the field of study and contribute to the existing body of knowledge
• Be feasible and realistic in terms of available data, resources, and research methods
• Be interesting and intellectually stimulating for the researcher and potential readers or audiences.

Characteristics of Research Problem

The characteristics of a research problem refer to the specific features that a problem must possess to qualify as a suitable research topic. Some of the key characteristics of a research problem are:

• Clarity : A research problem should be clearly defined and stated in a way that it is easily understood by the researcher and other readers. The problem should be specific, unambiguous, and easy to comprehend.
• Relevance : A research problem should be relevant to the field of study, and it should contribute to the existing body of knowledge. The problem should address a gap in knowledge, a theoretical or practical problem, or a real-world issue that requires further investigation.
• Feasibility : A research problem should be feasible in terms of the availability of data, resources, and research methods. It should be realistic and practical to conduct the study within the available time, budget, and resources.
• Novelty : A research problem should be novel or original in some way. It should represent a new or innovative perspective on an existing problem, or it should explore a new area of study or apply an existing theory to a new context.
• Importance : A research problem should be important or significant in terms of its potential impact on the field or society. It should have the potential to produce new knowledge, advance existing theories, or address a pressing societal issue.
• Manageability : A research problem should be manageable in terms of its scope and complexity. It should be specific enough to be investigated within the available time and resources, and it should be broad enough to provide meaningful results.

Advantages of Research Problem

The advantages of a well-defined research problem are as follows:

• Focus : A research problem provides a clear and focused direction for the research study. It ensures that the study stays on track and does not deviate from the research question.
• Clarity : A research problem provides clarity and specificity to the research question. It ensures that the research is not too broad or too narrow and that the research objectives are clearly defined.
• Relevance : A research problem ensures that the research study is relevant to the field of study and contributes to the existing body of knowledge. It addresses gaps in knowledge, theoretical or practical problems, or real-world issues that require further investigation.
• Feasibility : A research problem ensures that the research study is feasible in terms of the availability of data, resources, and research methods. It ensures that the research is realistic and practical to conduct within the available time, budget, and resources.
• Novelty : A research problem ensures that the research study is original and innovative. It represents a new or unique perspective on an existing problem, explores a new area of study, or applies an existing theory to a new context.
• Importance : A research problem ensures that the research study is important and significant in terms of its potential impact on the field or society. It has the potential to produce new knowledge, advance existing theories, or address a pressing societal issue.
• Rigor : A research problem ensures that the research study is rigorous and follows established research methods and practices. It ensures that the research is conducted in a systematic, objective, and unbiased manner.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Check your sources —

Google’s “ai overview” can give false, misleading, and dangerous answers, from glue-on-pizza recipes to recommending "blinker fluid," google's ai sourcing needs work..

Kyle Orland - May 24, 2024 11:00 am UTC

Further Reading

Factual errors can pop up in existing LLM chatbots as well, of course. But the potential damage that can be caused by AI inaccuracy gets multiplied when those errors appear atop the ultra-valuable web real estate of the Google search results page.

"The examples we've seen are generally very uncommon queries and aren’t representative of most people’s experiences," a Google spokesperson told Ars. "The vast majority of AI Overviews provide high quality information, with links to dig deeper on the web."

After looking through dozens of examples of Google AI Overview mistakes (and replicating many ourselves for the galleries below), we've noticed a few broad categories of errors that seemed to show up again and again. Consider this a crash course in some of the current weak points of Google's AI Overviews and a look at areas of concern for the company to improve as the system continues to roll out.

Treating jokes as facts

• The bit about using glue on pizza can be traced back to an 11-year-old troll post on Reddit. ( via ) Kyle Orland / Google
• This wasn't funny when the guys at Pep Boys said it, either. ( via ) Kyle Orland / Google
• Weird Al recommends "running with scissors" as well! ( via ) Kyle Orland / Google

Some of the funniest example of Google's AI Overview failing come, ironically enough, when the system doesn't realize a source online was trying to be funny. An AI answer that suggested using "1/8 cup of non-toxic glue" to stop cheese from sliding off pizza can be traced back to someone who was obviously trying to troll an ongoing thread . A response recommending "blinker fluid" for a turn signal that doesn't make noise can similarly be traced back to a troll on the Good Sam advice forums , which Google's AI Overview apparently trusts as a reliable source.

In regular Google searches, these jokey posts from random Internet users probably wouldn't be among the first answers someone saw when clicking through a list of web links. But with AI Overviews, those trolls were integrated into the authoritative-sounding data summary presented right at the top of the results page.

What's more, there's nothing in the tiny "source link" boxes below Google's AI summary to suggest either of these forum trolls are anything other than good sources of information. Sometimes, though, glancing at the source can save you some grief, such as when you see a response calling running with scissors "cardio exercise that some say is effective" ( that came from a 2022 post from Little Old Lady Comedy ).

Bad sourcing

• Washington University in St. Louis says this ratio is accurate, but others disagree. ( via ) Kyle Orland / Google
• Man, we wish this fantasy remake was real. ( via ) Kyle Orland / Google

Sometimes Google's AI Overview offers an accurate summary of a non-joke source that happens to be wrong. When asking about how many Declaration of Independence signers owned slaves, for instance, Google's AI Overview accurately summarizes a Washington University of St. Louis library page saying that one-third "were personally enslavers." But the response ignores contradictory sources like a Chicago Sun-Times article saying the real answer is closer to three-quarters. I'm not enough of a history expert to judge which authoritative-seeming source is right, but at least one historian online took issue with the Google AI's answer sourcing .

Other times, a source that Google trusts as authoritative is really just fan fiction. That's the case for a response that imagined a 2022 remake of 2001: A Space Odyssey , directed by Steven Spielberg and produced by George Lucas. A savvy web user would probably do a double-take before citing citing Fandom's "Idea Wiki" as a reliable source, but a careless AI Overview user might not notice where the AI got its information.

reader comments

Promoted comments.

View attachment 81471

• garbage in, garbage out. Even the LLM says it's from a Reddit post.
• people having unrealistic expectations about LLMs. Perhaps this will convince everyone that they're parroting what they're fed and have no understanding or self consciousness.
• google shooting themselves in the foot. It's one thing to give a result like the Reddit suggesion as a link to the original post on Reddit. It's another one entirely to get it in this overview where it sounds like it's endorsed by Google.

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Public’s Positive Economic Ratings Slip; Inflation Still Widely Viewed as Major Problem

Majorities in both parties remain fearful about the state of the country, table of contents.

• Views of top problems facing the nation
• Americans’ views of the state of the nation
• Similar shares in both parties view personal financial situation positively
• Americans’ views on the future of the economy and their financial situation
• Changes in views of the country’s top problems
• Acknowledgments
• The American Trends Panel survey methodology

Pew Research Center conducted this study to understand Americans’ views of the economy and problems facing the country. For this analysis, we surveyed 8,638 adults from May 13-19, 2024. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this report , along with responses, and the survey methodology .

Inflation may be cooling , but it continues to loom large over Americans’ evaluations of the country and the economy.

Today, 23% of U.S. adults say the economy is in excellent or good shape, down from 28% in January but higher than the 19% who rated the economy positively last April.

• The recent negative slide in economic ratings has mainly taken place among Democrats and those who lean to the Democratic Party: 37% rate the economy positively today, down from 44% in January (but up from 28% last spring).
• Republicans and Republican leaners’ views are little changed over this period – only one-in-ten rate the economy positively.

The public again sees inflation as one of the top problems facing the nation, with 62% saying inflation is a very big problem for the country – only slightly down from the 65% who said this last year.

But another economic concern – unemployment – is not widely viewed as a very big problem for the country. Just 25% of Americans currently say it’s a very big problem.

What’s in this report?

• National economic and personal financial ratings (Chapter 1)
• Trends in views of the top problems facing the nation (Chapter 2)

Two other economic concerns – the affordability of health care and the federal budget deficit – continue to be seen as very big problems for the country.

The public’s list of the top problems facing the nation also includes drug addiction, illegal immigration, gun violence and violent crime. Each of these is seen as a very big problem by roughly half of the public.

• “The ability of Republicans and Democrats to work together” also continues to rate as a top problem.
• Of the 16 concerns included in the survey, it’s the only one that majorities in both partisan coalitions (57% of Republicans and 63% of Democrats) say is a very big problem for the country.

In contrast, the Pew Research Center survey of U.S. adults, conducted May 13-19 among 8,638 members of the Center’s nationally representative American Trends Panel, finds:

• Republicans and GOP leaners are far more likely than Democrats and Democratic leaners to see illegal immigration, the federal budget deficit and inflation as major problems.
• Democrats are considerably more likely than Republicans to view climate change, gun violence and racism as major national problems.

Americans continue to be more likely to feel fearful and angry about the state of the nation than to feel hopeful or proud – and this has largely been the case since Pew Research Center first asked these questions in June 2020.

Since Joe Biden won the 2020 presidential election, Democrats have been considerably more likely than Republicans to express positive emotions about the state of the country (and less likely to express negative emotions). This is a reversal of the partisan patterns on these questions during the Trump administration.

Still, majorities in both parties – 64% of Republicans and 56% of Democrats – say they are fearful about the state of the country.

The public also continues to express much more dissatisfaction than satisfaction with the state of the nation – a trend that dates back decades. Today, 78% of Americans are dissatisfied with national conditions, while 22% are satisfied (34% of Democrats and 10% of Republicans).

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• How to Define a Research Problem | Ideas & Examples

How to Define a Research Problem | Ideas & Examples

Published on 8 November 2022 by Shona McCombes and Tegan George.

A research problem is a specific issue or gap in existing knowledge that you aim to address in your research. You may choose to look for practical problems aimed at contributing to change, or theoretical problems aimed at expanding knowledge.

Some research will do both of these things, but usually the research problem focuses on one or the other. The type of research problem you choose depends on your broad topic of interest and the type of research you think will fit best.

This article helps you identify and refine a research problem. When writing your research proposal or introduction , formulate it as a problem statement and/or research questions .

Table of contents

Why is the research problem important, step 1: identify a broad problem area, step 2: learn more about the problem, frequently asked questions about research problems.

Having an interesting topic isn’t a strong enough basis for academic research. Without a well-defined research problem, you are likely to end up with an unfocused and unmanageable project.

You might end up repeating what other people have already said, trying to say too much, or doing research without a clear purpose and justification. You need a clear problem in order to do research that contributes new and relevant insights.

Whether you’re planning your thesis , starting a research paper , or writing a research proposal , the research problem is the first step towards knowing exactly what you’ll do and why.

Prevent plagiarism, run a free check.

As you read about your topic, look for under-explored aspects or areas of concern, conflict, or controversy. Your goal is to find a gap that your research project can fill.

Practical research problems

If you are doing practical research, you can identify a problem by reading reports, following up on previous research, or talking to people who work in the relevant field or organisation. You might look for:

• Issues with performance or efficiency
• Processes that could be improved
• Areas of concern among practitioners
• Difficulties faced by specific groups of people

Examples of practical research problems

Voter turnout in New England has been decreasing, in contrast to the rest of the country.

The HR department of a local chain of restaurants has a high staff turnover rate.

A non-profit organisation faces a funding gap that means some of its programs will have to be cut.

Theoretical research problems

If you are doing theoretical research, you can identify a research problem by reading existing research, theory, and debates on your topic to find a gap in what is currently known about it. You might look for:

• A phenomenon or context that has not been closely studied
• A contradiction between two or more perspectives
• A situation or relationship that is not well understood
• A troubling question that has yet to be resolved

Examples of theoretical research problems

The effects of long-term Vitamin D deficiency on cardiovascular health are not well understood.

The relationship between gender, race, and income inequality has yet to be closely studied in the context of the millennial gig economy.

Historians of Scottish nationalism disagree about the role of the British Empire in the development of Scotland’s national identity.

Next, you have to find out what is already known about the problem, and pinpoint the exact aspect that your research will address.

Context and background

• Who does the problem affect?
• Is it a newly-discovered problem, or a well-established one?
• What research has already been done?
• What, if any, solutions have been proposed?
• What are the current debates about the problem? What is missing from these debates?

Specificity and relevance

• What particular place, time, and/or group of people will you focus on?
• What aspects will you not be able to tackle?
• What will the consequences be if the problem is not resolved?

Example of a specific research problem

A local non-profit organisation focused on alleviating food insecurity has always fundraised from its existing support base. It lacks understanding of how best to target potential new donors. To be able to continue its work, the organisation requires research into more effective fundraising strategies.

Once you have narrowed down your research problem, the next step is to formulate a problem statement , as well as your research questions or hypotheses .

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement.

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis – a prediction that will be confirmed or disproved by your research.

Research objectives describe what you intend your research project to accomplish.

They summarise the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

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Slack under attack over sneaky AI training policy

On the heels of ongoing issues around how big tech is appropriating data from individuals and businesses in the training of AI services, a storm is brewing among Slack users upset over how the Salesforce-owned chat platform is charging ahead with its AI vision.

The company, like many others, is tapping its own user data to train some of its new AI services. But, it turns out that if you don’t want Slack to use your data, you have to email the company to opt out.

And the terms of that engagement are tucked away in what appears to be an out-of-date, confusing privacy policy that no one was paying attention to. That was the case with Slack, until a miffed person posted about them on a community site hugely popular with developers, and then that post went viral…which is what happened here.

It all kicked off last night, when a note on Hacker News raised the issue of how Slack trains its AI services, by way of a straight link to its privacy principles — no additional comment was needed. That post kicked off a longer conversation — and what seemed like news to current Slack users — that Slack opts users in by default to its AI training, and that you need to email a specific address to opt out.

That Hacker News thread then spurred multiple conversations and questions on other platforms : There is a newish , generically named product called “ Slack AI ” that lets users search for answers and summarize conversation threads, among other things, but why is that not once mentioned by name on that privacy principles page in any way, even to make clear if the privacy policy applies to it? And why does Slack reference both “global models” and “AI models?”

Between people being confused about where Slack is applying its AI privacy principles, and people being surprised and annoyed at the idea of emailing to opt-out — at a company that makes a big deal of touting that “Your control your data” — Slack does not come off well.

The shock might be new, but the terms are not. According to pages on the Internet Archive , the terms have been applicable since at least September 2023. (We have asked the company to confirm.)

Per the privacy policy, Slack is using customer data specifically to train “global models,” which Slack uses to power channel and emoji recommendations and search results. Slack tells us that its usage of the data has specific limits.

“Slack has platform-level machine learning models for things like channel and emoji recommendations and search results. We do not build or train these models in such a way that they could learn, memorize or be able to reproduce some part of customer data,” a company spokesperson told TechCrunch. However, the policy does not appear to address the overall scope and the company’s wider plans for training AI models.

In its terms, Slack says that if customers opt out of data training, they would still benefit from the company’s “globally trained AI/ML models.” But again, in that case, it’s not clear then why the company is using customer data in the first place to power features like emoji recommendations.

The company also said it doesn’t use customer data to train Slack AI.

“Slack AI is a separately purchased add-on that uses large language models (LLMs) but does not train those LLMs on customer data. Slack AI uses LLMs hosted directly within Slack’s AWS infrastructure, so that customer data remains in-house and is not shared with any LLM provider. This ensures that customer data stays in that organization’s control and exclusively for that organization’s use,” a spokesperson said.

Some of the confusion is likely to be addressed sooner rather than later. In a reply to one critical take on Threads from engineer and writer Gergely Orosz, Slack engineer Aaron Maurer conceded that the company needs to update the page to reflect “how these privacy principles play with Slack AI.”

Maurer added that these terms were written at the time when the company didn’t have Slack AI, and these rules reflect the company’s work around search and recommendations. It will be worth examining the terms for future updates, given the confusion around what Slack is currently doing with its AI.

The issues at Slack are a stark reminder that, in the fast-moving world of AI development, user privacy should not be an afterthought and a company’s terms of service should clearly spell out how and when data is used or if it is not.

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• About Adverse Childhood Experiences
• Risk and Protective Factors
• Program: Essentials for Childhood: Preventing Adverse Childhood Experiences through Data to Action
• Adverse childhood experiences can have long-term impacts on health, opportunity and well-being.
• Adverse childhood experiences are common and some groups experience them more than others.

What are adverse childhood experiences?

Adverse childhood experiences, or ACEs, are potentially traumatic events that occur in childhood (0-17 years). Examples include: 1

• Experiencing violence, abuse, or neglect.
• Witnessing violence in the home or community.
• Having a family member attempt or die by suicide.

Also included are aspects of the child’s environment that can undermine their sense of safety, stability, and bonding. Examples can include growing up in a household with: 1

• Substance use problems.
• Mental health problems.
• Instability due to parental separation.
• Instability due to household members being in jail or prison.

The examples above are not a complete list of adverse experiences. Many other traumatic experiences could impact health and well-being. This can include not having enough food to eat, experiencing homelessness or unstable housing, or experiencing discrimination. 2 3 4 5 6

Quick facts and stats

ACEs are common. About 64% of adults in the United States reported they had experienced at least one type of ACE before age 18. Nearly one in six (17.3%) adults reported they had experienced four or more types of ACEs. 7

Preventing ACEs could potentially reduce many health conditions. Estimates show up to 1.9 million heart disease cases and 21 million depression cases potentially could have been avoided by preventing ACEs. 1

Some people are at greater risk of experiencing one or more ACEs than others. While all children are at risk of ACEs, numerous studies show inequities in such experiences. These inequalities are linked to the historical, social, and economic environments in which some families live. 5 6 ACEs were highest among females, non-Hispanic American Indian or Alaska Native adults, and adults who are unemployed or unable to work. 7

ACEs are costly. ACEs-related health consequences cost an estimated economic burden of $748 billion annually in Bermuda, Canada, and the United States. 8

ACEs can have lasting effects on health and well-being in childhood and life opportunities well into adulthood. 9 Life opportunities include things like education and job potential. These experiences can increase the risks of injury, sexually transmitted infections, and involvement in sex trafficking. They can also increase risks for maternal and child health problems including teen pregnancy, pregnancy complications, and fetal death. Also included are a range of chronic diseases and leading causes of death, such as cancer, diabetes, heart disease, and suicide. 1 10 11 12 13 14 15 16 17

ACEs and associated social determinants of health, such as living in under-resourced or racially segregated neighborhoods, can cause toxic stress. Toxic stress, or extended or prolonged stress, from ACEs can negatively affect children’s brain development, immune systems, and stress-response systems. These changes can affect children’s attention, decision-making, and learning. 18

Children growing up with toxic stress may have difficulty forming healthy and stable relationships. They may also have unstable work histories as adults and struggle with finances, jobs, and depression throughout life. 18 These effects can also be passed on to their own children. 19 20 21 Some children may face further exposure to toxic stress from historical and ongoing traumas. These historical and ongoing traumas refer to experiences of racial discrimination or the impacts of poverty resulting from limited educational and economic opportunities. 1 6

Adverse childhood experiences can be prevented. Certain factors may increase or decrease the risk of experiencing adverse childhood experiences.

Preventing adverse childhood experiences requires understanding and addressing the factors that put people at risk for or protect them from violence.

Creating safe, stable, nurturing relationships and environments for all children can prevent ACEs and help all children reach their full potential. We all have a role to play.

• Merrick MT, Ford DC, Ports KA, et al. Vital Signs: Estimated Proportion of Adult Health Problems Attributable to Adverse Childhood Experiences and Implications for Prevention — 25 States, 2015–2017. MMWR Morb Mortal Wkly Rep 2019;68:999-1005. DOI: http://dx.doi.org/10.15585/mmwr.mm6844e1 .
• Cain KS, Meyer SC, Cummer E, Patel KK, Casacchia NJ, Montez K, Palakshappa D, Brown CL. Association of Food Insecurity with Mental Health Outcomes in Parents and Children. Science Direct. 2022; 22:7; 1105-1114. DOI: https://doi.org/10.1016/j.acap.2022.04.010 .
• Smith-Grant J, Kilmer G, Brener N, Robin L, Underwood M. Risk Behaviors and Experiences Among Youth Experiencing Homelessness—Youth Risk Behavior Survey, 23 U.S. States and 11 Local School Districts. Journal of Community Health. 2022; 47: 324-333.
• Experiencing discrimination: Early Childhood Adversity, Toxic Stress, and the Impacts of Racism on the Foundations of Health | Annual Review of Public Health https://doi.org/10.1146/annurev-publhealth-090419-101940 .
• Sedlak A, Mettenburg J, Basena M, et al. Fourth national incidence study of child abuse and neglect (NIS-4): Report to Congress. Executive Summary. Washington, DC: U.S. Department of Health an Human Services, Administration for Children and Families.; 2010.
• Font S, Maguire-Jack K. Pathways from childhood abuse and other adversities to adult health risks: The role of adult socioeconomic conditions. Child Abuse Negl. 2016;51:390-399.
• Swedo EA, Aslam MV, Dahlberg LL, et al. Prevalence of Adverse Childhood Experiences Among U.S. Adults — Behavioral Risk Factor Surveillance System, 2011–2020. MMWR Morb Mortal Wkly Rep 2023;72:707–715. DOI: http://dx.doi.org/10.15585/mmwr.mm7226a2 .
• Bellis, MA, et al. Life Course Health Consequences and Associated Annual Costs of Adverse Childhood Experiences Across Europe and North America: A Systematic Review and Meta-Analysis. Lancet Public Health 2019.
• Adverse Childhood Experiences During the COVID-19 Pandemic and Associations with Poor Mental Health and Suicidal Behaviors Among High School Students — Adolescent Behaviors and Experiences Survey, United States, January–June 2021 | MMWR
• Hillis SD, Anda RF, Dube SR, Felitti VJ, Marchbanks PA, Marks JS. The association between adverse childhood experiences and adolescent pregnancy, long-term psychosocial consequences, and fetal death. Pediatrics. 2004 Feb;113(2):320-7.
• Miller ES, Fleming O, Ekpe EE, Grobman WA, Heard-Garris N. Association Between Adverse Childhood Experiences and Adverse Pregnancy Outcomes. Obstetrics & Gynecology . 2021;138(5):770-776. https://doi.org/10.1097/AOG.0000000000004570 .
• Sulaiman S, Premji SS, Tavangar F, et al. Total Adverse Childhood Experiences and Preterm Birth: A Systematic Review. Matern Child Health J . 2021;25(10):1581-1594. https://doi.org/10.1007/s10995-021-03176-6 .
• Ciciolla L, Shreffler KM, Tiemeyer S. Maternal Childhood Adversity as a Risk for Perinatal Complications and NICU Hospitalization. Journal of Pediatric Psychology . 2021;46(7):801-813. https://doi.org/10.1093/jpepsy/jsab027 .
• Mersky JP, Lee CP. Adverse childhood experiences and poor birth outcomes in a diverse, low-income sample. BMC pregnancy and childbirth. 2019;19(1). https://doi.org/10.1186/s12884-019-2560-8 .
• Reid JA, Baglivio MT, Piquero AR, Greenwald MA, Epps N. No youth left behind to human trafficking: Exploring profiles of risk. American journal of orthopsychiatry. 2019;89(6):704.
• Diamond-Welch B, Kosloski AE. Adverse childhood experiences and propensity to participate in the commercialized sex market. Child Abuse & Neglect. 2020 Jun 1;104:104468.
• Shonkoff, J. P., Garner, A. S., Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood, Adoption, and Dependent Care, & Section on Developmental and Behavioral Pediatrics (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232–e246. https://doi.org/10.1542/peds.2011-2663
• Narayan AJ, Kalstabakken AW, Labella MH, Nerenberg LS, Monn AR, Masten AS. Intergenerational continuity of adverse childhood experiences in homeless families: unpacking exposure to maltreatment versus family dysfunction. Am J Orthopsych. 2017;87(1):3. https://doi.org/10.1037/ort0000133 .
• Schofield TJ, Donnellan MB, Merrick MT, Ports KA, Klevens J, Leeb R. Intergenerational continuity in adverse childhood experiences and rural community environments. Am J Public Health. 2018;108(9):1148-1152. https://doi.org/10.2105/AJPH.2018.304598 .
• Schofield TJ, Lee RD, Merrick MT. Safe, stable, nurturing relationships as a moderator of intergenerational continuity of child maltreatment: a meta-analysis. J Adolesc Health. 2013;53(4 Suppl):S32-38. https://doi.org/10.1016/j.jadohealth.2013.05.004 .

Adverse Childhood Experiences (ACEs)

ACEs can have a tremendous impact on lifelong health and opportunity. CDC works to understand ACEs and prevent them.