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Language and Literacy Development: Research-Based, Teacher-Tested Strategies

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“Why does it tick and why does it tock?”

“Why don’t we call it a granddaughter clock?”

“Why are there pointy things stuck to a rose?”

“Why are there hairs up inside of your nose?”

She started with Why? and then What? How? and When? By bedtime she came back to Why? once again. She drifted to sleep as her dazed parents smiled at the curious thoughts of their curious child, who wanted to know what the world was about. They kissed her and whispered, “You’ll figure it out.”

—Andrea Beaty, Ada Twist, Scientist

I have dozens of favorite children’s books, but while working on this cluster about language and literacy development, Ada Twist, Scientist kept coming to mind. Ada is an African American girl who depicts the very essence of what it means to be a scientist. The book is a celebration of children’s curiosity, wonder, and desire to learn.

The more I thought about language and literacy, the more Ada became my model. All children should have books as good as Ada Twist, Scientist read to them. All children should be able to read books like Ada Twist, Scientist by the end of third grade. All children should be encouraged to ask questions about their world and be supported in developing the literacy tools (along with broad knowledge, inquiring minds, and other tools!) to answer those questions. All children should see themselves in books that rejoice in learning.

Early childhood teachers play a key role as children develop literacy. While this cluster does not cover the basics of reading instruction, it offers classroom-tested ways to make common practices like read alouds and discussions even more effective.

The cluster begins with “ Enhancing Toddlers’ Communication Skills: Partnerships with Speech-Language Pathologists ,” by Janet L. Gooch. In a mutually beneficial partnership, interns from a university communication disorders program supported Early Head Start teachers in learning several effective ways to boost toddlers’ language development, such as modeling the use of new vocabulary and expanding on what toddlers say. (One quirk of Ada Twist, Scientist is that Ada doesn’t speak until she is 3; in real life, that would be cause for significant concern. Having a submission about early speech interventions was pure serendipity.) Focusing on preschoolers, Kathleen M. Horst, Lisa H. Stewart, and Susan True offer a framework for enhancing social, emotional, and academic learning. In “ Joyful Learning with Stories: Making the Most of Read Alouds ,” they explain how to establish emotionally supportive routines that are attentive to each child’s strengths and needs while also increasing group discussions. During three to five read alouds of a book, teachers engage children in building knowledge, vocabulary, phonological awareness, and concepts of print.

Next up, readers go inside the lab school at Stepping Stones Museum for Children. In “ Equalizing Opportunities to Learn: A Collaborative Approach to Language and Literacy Development in Preschool ,” Laura B. Raynolds, Margie B. Gillis, Cristina Matos, and Kate Delli Carpini share the engaging, challenging activities they designed with and for preschoolers growing up in an under-resourced community. Devondre finds out how hard Michelangelo had to work to paint the ceiling of the Sistine Chapel, and Sayo serves as a guide in the children’s classroom minimuseum— taking visitors to her artwork!

Moving into first grade, Laura Beth Kelly, Meridith K. Ogden, and Lindsey Moses explain how they helped children learn to lead and participate in meaningful discussions of literature. “ Collaborative Conversations: Speaking and Listening in the Primary Grades ” details the children’s progress (and the teacher’s methods) as they developed discussion-related social and academic skills. Although the first graders still required some teacher facilitation at the end of the school year, they made great strides in preparing for conversations, listening to their peers, extending others’ comments, asking questions, and reflecting on discussions.

Rounding out the cluster are two articles on different aspects of learning to read. In “ Sounding It Out Is Just the First Step: Supporting Young Readers ,” Sharon Ruth Gill briefly explains the complexity of the English language and suggests several ways teachers can support children as they learn to decode fluently. Her tips include giving children time to self-correct, helping them use semantic and syntactic cues, and analyzing children’s miscues to decide what to teach next.

In “ Climbing Fry’s Mountain: A Home–School Partnership for Learning Sight Words ,” Lynda M. Valerie and Kathleen A. Simoneau describe a fun program for families. With game-like activities that require only basic household items, children in kindergarten through second grade practice reading 300 sight words. Children feel successful as they begin reading, and teachers reserve instructional time for phonological awareness, phonics, vocabulary, and other essentials of early reading.

At the end of Ada Twist, Scientist , there is a marvelous illustration of Ada’s whole family reading. “They remade their world—now they’re all in the act / of helping young Ada sort fiction from fact.” It reminds me of the power of reading and of the important language and literacy work that early childhood educators do every day.

—Lisa Hansel

We’d love to hear from you!

Send your thoughts on this issue, as well as topics you’d like to read about in future issues of Young Children , to [email protected] .

Would you like to see your children’s artwork featured? For guidance on submitting print-quality photos (as well as details on permissions and licensing), see NAEYC.org/resources/pubs/authors-photographers/photos .

Is your classroom full of children’s artwork? To feature it in Young Children , see the link at the bottom of the page or email [email protected] for details.

Lisa Hansel, EdD, is the editor in chief of NAEYC's peer-reviewed journal, Young Children .

Vol. 74, No. 1

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Untying the Gordian Knot of Early Language Screening and Improved Developmental Outcomes

• 1 Vanderbilt Kennedy Center, Nashville, Tennessee
• 2 University of Washington, Seattle
• Editorial Recommendations for Speech and Language Screenings Marisha L. Speights, PhD, CCC-SLP; Maranda K. Jones, BA; Megan Y. Roberts, PhD, CCC-SLP JAMA
• US Preventive Services Task Force USPSTF Recommendation: Screening for Speech and Language Delay and Disorders US Preventive Services Task Force; Michael J. Barry, MD; Wanda K. Nicholson, MD, MPH, MBA; Michael Silverstein, MD, MPH; David Chelmow, MD; Tumaini Rucker Coker, MD, MBA; Esa M. Davis, MD, MPH; Katrina E. Donahue, MD, MPH; Carlos Roberto Jaén, MD, PhD, MS; Li Li, MD, PhD, MPH; Carol M. Mangione, MD, MSPH; Gbenga Ogedegbe, MD, MPH; Goutham Rao, MD; John M. Ruiz, PhD; James Stevermer, MD, MSPH; Joel Tsevat, MD, MPH; Sandra Millon Underwood, PhD, RN; John B. Wong, MD JAMA
• US Preventive Services Task Force USPSTF Review: Screening for Speech and Language Delay and Disorders in Children Cynthia Feltner, MD, MPH; Ina F. Wallace, PhD; Sallie W. Nowell, PhD, CCC-SLP; Colin J. Orr, MD, MPH; Brittany Raffa, MD; Jennifer Cook Middleton, PhD; Jessica Vaughan, MPH; Claire Baker; Roger Chou, MD; Leila Kahwati, MD, MPH JAMA
• JAMA Patient Page Patient Information: Screening for Speech and Language Problems in Young Children Jill Jin, MD, MPH JAMA

Early language development is the foundation for communication, social relationships, reading, academic accomplishments, job performance, and other life-long indicators of positive social development and economic success. Early detection of significant delays in language development and effective intervention, when needed, are essential to ensuring optimal developmental outcomes. Estimates of primary language delays in children younger than 5 years vary widely, ranging from less than 5% to nearly 20%, depending on the age of the child, the inclusion of speech and/or language criteria, the specific measures used, and the criteria for identification of significant delays. 1 - 4 Given that only 30% of children younger than 5 years are screened when their primary caregivers or teachers do not express concerns about their speech or language development and only 50% of children eligible for intervention are reported to receive interventions, there is a need for contemporary evidence-based guidance on the potential positive and negative outcomes of screening.

Although there are documented associations of early speech and language delays with subsequent poor academic, social, and behavioral outcomes, 5 , 6 evidence linking screening to effective interventions and subsequent improvements in long-term developmental outcomes is limited. The US Preventive Services Task Force (USPSTF) recommendation statement concluded that “the current evidence is insufficient to assess the balance of benefits and harms of screening for speech and language delay and disorders in children age 5 years or younger” (I statement). 7 , 8 No studies specifically examining the risks and benefits of screening vs no screening were identified. 7 , 8 The reports by the UPSTF 7 and Feltner et al 8 reviewed a total of 38 studies of screening and intervention meeting stringent inclusion criteria for methodological quality and outcomes. In this editorial, we highlight several secondary contributions of the USPSFT recommendations, 7 , 8 suggest additions that might enhance the impact of the recommendations, and make suggestions for research and policy, with particular emphasis on the role of parents as collaborators in screening and intervention.

Contributions of the Report

In addition to the overall recommendation, 7 , 8 the USPSTF makes several important contributions to understanding the “Gordian knot” linking speech and language screening to improved long-term developmental outcomes. First, the mean incidence of primary speech and language delays was 16% across 21 studies enrolling 7489 children younger than 5 years. 7 , 8 There was considerable variability in reported incidence by study, screening measure, language constructs (eg, specific vs global language skills), and informant (eg, parent vs clinician). This variability is important; however, the mean incidence level reported across studies suggests early screening would detect a significant number of children. Second, overall sensitivity and specificity data indicated that early delays in specific language skills and articulation can be detected with available screening instruments used by parents or clinicians. 7 , 8 Again, variability across screening instruments, speech and language constructs, and informants was noted; however, several screening tools appeared promising for immediate practice and candidates for future research studies. Third, across all components of the synthesis, there was evidence that parents were essential partners in screening and effective intervention delivery. 7 , 8 For example, parent reports of specific child language skills were precise, with high levels of sensitivity and specificity similar to examiner levels but with less variability. Most studies in which parents were trained to deliver interventions to their children reported positive outcomes for some measures. Positive outcomes were associated with longer parent implementation. These results, 7 , 8 when paired with meta-analysis of parent-implemented interventions across populations of young children with language impairment, 9 - 11 support the use of parent-implemented interventions to improve language outcomes. In the USPSTF analysis of contextual factors impacting screening, 7 , 8 parent characteristics (eg, socioeconomic status, single parent status, social isolation, primary language other than English) were associated with participation in screening and intervention. These findings suggest that parents may be gatekeepers for their children’s access to a range of supports for language development. 12 The associations between these indicated parent characteristics and expected disparities in health care access deserve notice, since this may be the mediating association between parent characteristics and participating in screening and intervention.

Expanding on Important Information From the Synthesis

All syntheses of empirical studies are limited by the quantity and quality of the studies under review; the USPSTF evidence review and recommendation statement are no exception. 7 , 8 However, 2 additions to the synthesis of the available studies could have contributed important information. First, age is a critical variable in understanding language development and delay. The use of the broad age umbrella, younger than 5 years, for synthesizing studies may have masked important differences associated with age at screening. Accuracy in identification of speech and language delays generally increases with age; assessments after age 36 months are likely to be more reliable than those prior to age 30 months. 2 , 13 , 14 Child age may also impact the accuracy and sensitivity of parent reports of their children’s language development. Parents are likely to be more reliable informants about their children’s early development of specific skills (eg, vocabulary) than later development of more complex skills (eg, morphology, syntax) that may be indicative of a developmental language delay. Analysis of the screening studies to characterize age-related precision in screening could provide preliminary guidance about when to screen and when parents are most valuable as informants.

Second, characterizing the outcomes of intervention studies in terms of measures with statistically significant outcomes may have masked important information about the magnitude of the changes observed across measures and studies. A meta-analysis of the speech and language outcomes would be constrained in the small sample of language intervention studies and even smaller sample of speech studies. However, including the effect sizes in the USPSTF synthesis 7 , 8 would have added important information about the relative benefits of intervention, consistent with contemporary standards for reporting the outcomes of intervention research.

Recommendations for Research

The evidence report by Feltner et al 8 and the USPSTF recommendation statement 7 highlight gaps in evidence related to screening and treatment studies with short-term and long-term follow-up addressing key academic, behavioral, and well-being outcomes. There is a particular absence of studies including young children and families for whom disparities in health care and limited resources are also barriers to accessing screening and intervention. This recommendation again draws attention to the difficulties in resolving the Gordian knot linking screening to functional long-term outcomes. At the center of the knot is the need for funding for inclusive research at scale and with sufficient replication to provide evidence to guide practice and policy recommendations.

Funding is needed for 4 key areas with representative populations of children and families. First, we need screening research that describes trajectories of speech and language development over the first 5 years with follow-up through the transition to reading. Second, validation must be performed for promising, pragmatic screening measures across critical periods in language development in early childhood, including assessing the validity for valued language, academic, and social outcomes. Third, we need intervention research based on contextualized, promising interventions. Such interventions would be calibrated for intensity and dosage associated with optimal developmental outcomes and responsive to the cultural, linguistic, and caregiving contexts of families. Particular attention should be given to caregiver-implemented interventions and interventions provided by teachers in childcare and prekindergarten classrooms. Fourth, there is a need for implementation-level and systems-level research that places screening at the nexus of the health care, community, and education systems. The goal is to understand how to link and supplement existing systems to ensure sustainable delivery of early language screening that leads to effective and timely intervention. This research should also address preparing systems to implement the methods, practices, and policies based on evidence from the research recommended.

Public Education Initiatives to Support Parents

Parents and caregivers of young children are not likely to have extensive knowledge about early language development and how it relates to children’s long-tern academic and social outcomes. Parents need information about language development, why screening is important, and the potential of early intervention to support their child’s development. This information should be accessible and timely, provided in parents’ primary language, and presented without the stigma of labeling children at risk due to poverty, neighborhood, race, ethnicity, home language, or family structure. Without culturally and linguistically accessible, unbiased information, it is unlikely parents will choose to participate in screening their children’s emerging speech and language. Many families need more than information; they need active assistance to access follow-up assessments and opportunities to participate in interventions that reflect their language and culture as well as addressing their children’s needs. Innovative family-centered approaches to providing information, screening, and intervention in communities are needed to support parents as well as children. Health care practitioners, particularly pediatricians, play a critical role in language screenings for all children and in facilitating access to comprehensive assessment and intervention when indicated. Collaboration between health care and educational systems is essential.

Conclusions

There is a critical need for research on screening for early language delays, including evaluating measures that are sensitive and specific in detecting delays in all young children and testing a range of culturally and linguistically contextualized early interventions to effectively address children’s delays. Given the lifelong importance of language related skills, the USPSTF recommendation 7 , 8 must be construed as a challenge rather than a conclusion.

Published: January 23, 2024. doi:10.1001/jamanetworkopen.2023.54529

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Kaiser AP et al. JAMA Network Open .

Corresponding Author: Ann P. Kaiser, PhD, Vanderbilt Kennedy Center, 110 Magnolia Cir, Ste 314, Nashville, TN 37232 ( [email protected] ).

Conflict of Interest Disclosures: None reported.

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Kaiser AP , Chow JC , Baumingham JE. Untying the Gordian Knot of Early Language Screening and Improved Developmental Outcomes. JAMA Netw Open. 2024;7(1):e2354529. doi:10.1001/jamanetworkopen.2023.54529

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Observation

The littlest linguists: new research on language development.

• Bilingualism
• Developmental Psychology
• Language Development

How do children learn language, and how is language related to other cognitive and social skills? For decades, the specialized field of developmental psycholinguistics has studied how children acquire language—or multiple languages—taking into account biological, neurological, and social factors that influence linguistic developments and, in turn, can play a role in how children learn and socialize. Here’s a look at recent research (2020–2021) on language development published in Psychological Science . 

Preverbal Infants Discover Statistical Word Patterns at Similar Rates as Adults: Evidence From Neural Entrainment

Dawoon Choi, Laura J. Batterink, Alexis K. Black, Ken A. Paller, and Janet F. Werker (2020)

One of the first challenges faced by infants during language acquisition is identifying word boundaries in continuous speech. This neurological research suggests that even preverbal infants can learn statistical patterns in language, indicating that they may have the ability to segment words within continuous speech.

Using electroencephalogram measures to track infants’ ability to segment words, Choi and colleagues found that 6-month-olds’ neural processing increasingly synchronized with the newly learned words embedded in speech over the learning period in one session in the laboratory. Specifically, patterns of electrical activity in their brains increasingly aligned with sensory regularities associated with word boundaries. This synchronization was comparable to that seen among adults and predicted future ability to discriminate words.

These findings indicate that infants and adults may follow similar learning trajectories when tracking probabilities in speech, with both groups showing a logarithmic (rather than linear) increase in the synchronization of neural processing with frequent words. Moreover, speech segmentation appears to use neural mechanisms that emerge early in life and are maintained throughout adulthood.

Parents Fine-Tune Their Speech to Children’s Vocabulary Knowledge

Ashley Leung, Alexandra Tunkel, and Daniel Yurovsky (2021)

Children can acquire language rapidly, possibly because their caregivers use language in ways that support such development. Specifically, caregivers’ language is often fine-tuned to children’s current linguistic knowledge and vocabulary, providing an optimal level of complexity to support language learning. In their new research, Leung and colleagues add to the body of knowledge involving how caregivers foster children’s language acquisition.

The researchers asked individual parents to play a game with their child (age 2–2.5 years) in which they guided their child to select a target animal from a set. Without prompting, the parents provided more informative references for animals they thought their children did not know. For example, if a parent thought their child did not know the word “leopard,” they might use adjectives (“the spotted, yellow leopard”) or comparisons (“the one like a cat”). This indicates that parents adjust their references to account for their children’s language knowledge and vocabulary—not in a simplifying way but in a way that could increase the children’s vocabulary. Parents also appeared to learn about their children’s knowledge throughout the game and to adjust their references accordingly.

Infant and Adult Brains Are Coupled to the Dynamics of Natural Communication

Elise A. Piazza, Liat Hasenfratz, Uri Hasson, and Casey Lew-Williams (2020)

This research tracked real-time brain activation during infant–adult interactions, providing an innovative measure of social interaction at an early age. When communicating with infants, adults appear to be sensitive to subtle cues that can modify their brain responses and behaviors to improve alignment with, and maximize information transfer to, the infants.

Piazza and colleagues used functional near-infrared spectroscopy—a noninvasive measure of blood oxygenation resulting from neural activity that is minimally affected by movements and thus allows participants to freely interact and move—to measure the brain activation of infants (9–15 months old) and adults while they communicated and played with each other. An adult experimenter either engaged directly with an infant by playing with toys, singing nursery rhymes, and reading a story or performed those same tasks while turned away from the child and toward another adult in the room.

Results indicated that when the adult interacted with the child (but not with the other adult), the activations of many prefrontal cortex (PFC) channels and some parietal channels were intercorrelated, indicating neural coupling of the adult’s and child’s brains. Both infant and adult PFC activation preceded moments of mutual gaze and increased before the infant smiled, with the infant’s PFC response preceding the adult’s. Infant PFC activity also preceded an increase in the pitch variability of the adult’s speech, although no changes occurred in the adult’s PFC, indicating that the adult’s speech influenced the infant but probably did not influence neural coupling between the child and the adult.

Theory-of-Mind Development in Young Deaf Children With Early Hearing Provisions

Chi-Lin Yu, Christopher M. Stanzione, Henry M. Wellman, and Amy R. Lederberg (2020)

Language and communication are important for social and cognitive development. Although deaf and hard-of-hearing (DHH) children born to deaf parents can communicate with their caregivers using sign language, most DHH children are born to hearing parents who do not have experience with sign language. These children may have difficulty with early communication and experience developmental delays. For instance, the development of theory of mind—the understanding of others’ mental states—is usually delayed in DHH children born to hearing parents.

Yu and colleagues studied how providing DHH children with hearing devices early in life (before 2 years of age) might enrich their early communication experiences and benefit their language development, supporting the typical development of other capabilities—in particular, theory of mind. The researchers show that 3- to 6-year-old DHH children who began using cochlear implants or hearing aids earlier had more advanced language abilities, leading to better theory-of-mind growth, than children who started using hearing provisions later. These findings highlight the relationships among hearing, language, and theory of mind.

The Bilingual Advantage in Children’s Executive Functioning Is Not Related to Language Status: A Meta-Analytic Review

Cassandra J. Lowe, Isu Cho, Samantha F. Goldsmith, and J. Bruce Morton (2021)

Acommon idea is that bilingual children, who grow up speaking two languages fluently, perform better than monolingual children in diverse executive-functioning domains (e.g., attention, working memory, decision making). This meta-analysis calls that idea into question.

Lowe and colleagues synthesized data from studies that compared the performance of monolingual and bilingual participants between the ages of 3 and 17 years in executive-functioning domains (1,194 effect sizes). They found only a small effect of bilingualism on participants’ executive functioning, which was largely explained by factors such as publication bias. After accounting for these factors, bilingualism had no distinguishable effect. The results of this large meta-analysis thus suggest that bilingual and monolingual children tend to perform at the same level in executive-functioning tasks. Bilingualism does not appear to boost performance in executive functions that serve learning, thinking, reasoning, or problem solving.

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Podcast: In her final column as APS President, Alison Gopnik makes the case for more effectively and creatively caring for vulnerable humans at either end of life.

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“When families are informed about the importance of conversational interaction and are provided training, they become active communicators and directly contribute to reducing the word gap (Leung et al., 2020).”

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The Impact of Peer Interactions on Language Development Among Preschool English Language Learners: A Systematic Review

• Published: 20 November 2020
• Volume 50 , pages 49–59, ( 2022 )

Cite this article

• Princess-Melissa Washington-Nortey   ORCID: orcid.org/0000-0002-8721-1710 1 ,
• Fa Zhang   ORCID: orcid.org/0000-0003-2839-6820 1 ,
• Yaoying Xu   ORCID: orcid.org/0000-0002-3683-5347 1 ,
• Amber Brown Ruiz   ORCID: orcid.org/0000-0002-3587-3747 1 ,
• Chin-Chih Chen   ORCID: orcid.org/0000-0002-9503-8145 1 &
• Christine Spence   ORCID: orcid.org/0000-0002-6158-7082 1  

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Studies showing that early language skills are important predictors of later academic success and social outcomes have prompted efforts to promote early language development among children at risk. Good social skills, a competence identified in many children who are English Language Learners (ELLs), have been posited in the general literature as facilitators of language development. Yet to date, a comprehensive review on the nature and impact of social interaction on language development among children who are ELLs has not been conducted. Using PRISMA procedures, a systematic review was conducted and 10 eligible studies published between 2008 and 2019 were identified. Findings revealed that despite their limited language capabilities, children who are ELLs can engage in complex speech during peer interaction. However, the nature and frequency of interactions, as well as the unique skill sets of communication partners may affect their development of relevant language skills. These findings have implications for policy and intervention development for preschool settings in the United States.

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Early Language Intervention in School Settings: What Works for Whom?

The Influence of Teachers, Peers, and Play Materials on Dual Language Learners’ Play Interactions in Preschool

An exploration of language and social-emotional development of children with and without disabilities in a statewide pre-kindergarten program.

Aikens, N., Tarullo, L., Hulsey, L., Ross, C., West, J., & Xue, Y. (2010). A Year in Head Start Children Families and Programs (No. 118a1d963bb04e23b24ea60039c88337). Mathematica Policy Research.

Atkins-Burnett, S., Xue, Y., & Aikens, N. (2017). Peer effects on children’s expressive vocabulary development using conceptual scoring in linguistically diverse preschools. Early Education and Development, 28 (7), 901–920.

Article   Google Scholar  

Anderson, S., & Phillips, D. (2017). Is pre-K classroom quality associated with kindergarten and middle-school academic skills? Developmental Psychology, 53 (6), 1063.

Bell, E. R., Greenfield, D. B., Bulotsky-Shearer, R. J., & Carter, T. M. (2016). Peer play as a context for identifying profiles of children and examining rates of growth in academic readiness for children enrolled in head start. Journal of Educational Psychology, 108 (5), 740.

Bernstein, K. A. (2018). The perks of being peripheral: English learning and participation in a preschool classroom network of practice. TESOL Quarterly, 52 (4), 798–844.

Burchinal MR, Pace A, Alper R, Hirsh-Pasek K, Golinkoff RM (2016) Early language outshines other predictors of academic and social trajectories in elementary school. Presented at Assoc. Child. Fam. Conf. (ACF), Washington, DC, p. 11–13.

Bustamante, A. S., & Hindman, A. H. (2019). Classroom quality and academic school readiness outcomes in head start: The indirect effect of approaches to learning. Early Education and Development, 30 (1), 19–35.

Cabell, S. Q., Justice, L. M., McGinty, A. S., DeCoster, J., & Forston, L. D. (2015). Teacher–child conversations in preschool classrooms: Contributions to children’s vocabulary development. Early Childhood Research Quarterly, 30, 80–92.

Carr, R. C., Mokrova, I. L., Vernon-Feagans, L., & Burchinal, M. R. (2019). Cumulative classroom quality during pre-kindergarten and kindergarten and children’s language, literacy, and mathematics skills. Early Childhood Research Quarterly, 47, 218–228.

Franco, X., Bryant, D. M., Gillanders, C., Castro, D. C., Zepeda, M., & Willoughby, M. T. (2019). Examining linguistic interactions of dual language learners using the language interaction snapshot (LISn). Early Childhood Research Quarterly, 48, 50–61.

Galindo, C., & Fuller, B. (2010). The social competence of latino kindergartners and growth in mathematical understanding. Developmental psychology, 46 (3), 579.

Guerrero, A. D., Fuller, B., Chu, L., Kim, A., Franke, T., Bridges, M., & Kuo, A. (2013). Early growth of mexican-american children: Lagging in preliteracy skills but not social development. Maternal and Child Health Journal, 17 (9), 1701–1711.

Hirsh-Pasek, K., Adamson, L. B., Bakeman, R., Owen, M. T., Golinkoff, R. M., Pace, A., & Suma, K. (2015). The contribution of early communication quality to low-income children’s language success. Psychological Science, 26 (7), 1071–1083.

Justice, L. M., Jiang, H., & Strasser, K. (2018). Linguistic environment of preschool classrooms: What dimensions support children’s language growth? Early Childhood Research Quarterly, 42, 79–92.

Justice, L. M., Petscher, Y., Schatschneider, C., & Mashburn, A. (2011). Peer effects in preschool classrooms: Is children’s language growth associated with their classmates’ skills? Child Development, 82 (6), 1768–1777.

Kyratzis, A. (2017). Peer ecologies for learning how to read: Exhibiting reading, orchestrating participation, and learning over time in bilingual Mexican-American preschoolers’ play enactments of reading to a peer. Linguistics and Education, 41, 7–19.

Kyratzis, A., Tang, Y. T., & Koymen, S. B. (2009). Codes, code-switching, and context: Style and footing in peer group bilingual play. Multilingua, 28, 265–290.

Mashburn, A. J., Justice, L. M., Downer, J. T., & Pianta, R. C. (2009). Peer effects on children’s language achievement during pre-kindergarten. Child Development, 80 (3), 686–702.

McWayne, C., & Cheung, K. (2009). A picture of strength: Preschool competencies mediate the effects of early behavior problems on later academic and social adjustment for head start children. Journal of Applied Developmental Psychology, 30 (3), 273–285.

Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine, 151 (4), 264–269.

National Education Association. (2015). Understanding the gaps: Who are we leaving behind and how far.  NEA Education Policy and Practice & Priority Schools Departments and Center for Great Public Schools .

Pace, A., Luo, R., Hirsh-Pasek, K., & Golinkoff, R. M. (2017). Identifying pathways between socioeconomic status and language development. Annual Review of Linguistics, 3, 285–308.

Palermo, F., & Mikulski, A. M. (2014). The role of positive peer interactions and English exposure in Spanish-speaking preschoolers’ English vocabulary and letter-word skills. Early Childhood Research Quarterly , 29 (4), 625–635.

Palermo, F., Mikulski, A. M., Fabes, R. A., Hanish, L. D., Martin, C. L., & Stargel, L. E. (2014). English exposure in the home and classroom: Predictions to spanish-speaking preschoolers’ english vocabulary skills. Applied Psycholinguistics, 35 (6), 1163–1187.

Pancsofar, N., & Vernon-Feagans, L. (2006). Mother and father language input to young children: Contributions to later language development. Journal of Applied Developmental Psychology, 27 (6), 571–587.

Piker, R. A. (2013). Understanding influences of play on second language learning: A microethnographic view in one head start preschool classroom. Journal of Early Childhood Research, 11 (2), 184–200.

Pungello, E. P., Iruka, I. U., Dotterer, A. M., Mills-Koonce, R., & Reznick, J. S. (2009). The effects of socioeconomic status, race, and parenting on language development in early childhood. Developmental Psychology, 45 (2), 544.

Rathbone, J., Hoffmann, T., & Glasziou, P. (2015). Faster title and abstract screening? Evaluating Abstrackr, a semi-automated online screening program for systematic reviewers. Systematic reviews, 4 (1), 80.

Romeo, R. R., Leonard, J. A., Robinson, S. T., West, M. R., Mackey, A. P., Rowe, M. L., & Gabrieli, J. D. (2018). Beyond the 30-million-word gap: Children’s conversational exposure is associated with language-related brain function. Psychological Science, 29 (5), 700–710.

Sawyer, B., Atkins-Burnett, S., Sandilos, L., Scheffner Hammer, C., Lopez, L., & Blair, C. (2018). Variations in classroom language environments of preschool children who are low-income and linguistically diverse. Early Education and Development, 29 (3), 398–416.

Schechter, C., & Bye, B. (2007). Preliminary evidence for the impact of mixed-income preschools on low-income children’s language growth. Early Childhood Research Quarterly, 22 (1), 137–146.

Spencer, T. D., Petersen, D. B., Slocum, T. A., & Allen, M. M. (2015). Large group narrative intervention in head start preschools: Implications for response to intervention. Journal of Early Childhood Research, 13 (2), 196–217.

Stoddart, T., Solis, J., Tolbert, S., Bravo, M. (2010). A framework for the effective science teaching of English language learners in elementary schools. Teaching science with Hispanic ELLs in K-16 classrooms, 151–181.

Suskind, D., Suskind, B., Lewinter-Suskind, L. (2015). Thirty million words: Building a child's brain: tune in, talk more, take turns. Dutton Books.

Vernon-Feagans, L., Mokrova, I. L., Carr, R. C., Garrett-Peters, P. T., Burchinal, M. R., & Family Life Project Key Investigators. (2019). Cumulative years of classroom quality from kindergarten to third grade: Prediction to children’s third grade literacy skills. Early Childhood Research Quarterly, 47, 531–540.

Weiland, C., & Yoshikawa, H. (2014). Does higher peer socio-economic status predict children’s language and executive function skills gains in prekindergarten? Journal of Applied Developmental Psychology, 35 (5), 422–432.

Wong, K., Boben, M., Thomas, M. C. (2018). Disrupting the early learning status quo: Providence Talks as innovative policy in diverse urban communities.

Yeomans-Maldonado, G., Justice, L. M., & Logan, J. A. (2019). The mediating role of classroom quality on peer effects and language gain in pre-kindergarten ECSE classrooms. Applied Developmental Science, 23 (1), 90–103.

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Washington-Nortey, PM., Zhang, F., Xu, Y. et al. The Impact of Peer Interactions on Language Development Among Preschool English Language Learners: A Systematic Review. Early Childhood Educ J 50 , 49–59 (2022). https://doi.org/10.1007/s10643-020-01126-5

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MINI REVIEW article

Early childhood education language environments: considerations for research and practice.

• 1 Department of Human Development and Family Science, Purdue University, West Lafayette, IN, United States
• 2 Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN, United States

The importance of developing early language and literacy skills is acknowledged by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) as a global human rights issue. Indeed, research suggests that language abilities are foundational for a host of cognitive, behavioral, and social–emotional outcomes. Therefore, it is critical to provide experiences that foster language acquisition across early learning settings. Central to these efforts is incorporating assessments of language environments into research and practice to drive quality improvement. Yet, several barriers may be preventing language environment assessments from becoming widely integrated into early education. In this brief, we review evidence on the types of experiences that promote language development, describe characteristics of language environment assessments, and outline practical and philosophical considerations to assist with decision-making. Further, we offer recommendations for future research that may contribute knowledge regarding strategies to assess and support language development. In addressing both areas, we highlight the potential for early childhood language environments to advance equity.

Introduction

Despite compelling evidence indicating the importance of environmental inputs for language acquisition within the first 5 years of life (e.g., Anderson et al., 2021 ), several obstacles have prevented language environment assessments from becoming widely integrated into early education settings (e.g., Mitchell, 2016 ). First, for any program that seeks to enhance language environments, measuring the processes known to drive language development is fundamental prior to developing intervention strategies and monitoring continual quality improvement. Yet, the limited application of language environment assessments in interventions or programs of scale restricts our understanding of how to effectively utilize language assessments to evaluate practice (e.g., Greenwood et al., 2020 ). Thus, we offer opportunities for future research that have the potential to contribute knowledge regarding strategies to assess and support language development and fill critical gaps in the literature. Second, selecting a language environment assessment that meets program goals, can be administered with fidelity, is accommodating to resource constraints, and is appropriate for informing professional development can be arduous (e.g., Zaslow et al., 2009 ; Derrick-Mills et al., 2014 ; Ackerman, 2019 ). To help practitioners overcome this challenge, we review evidence on the types of experiences that promote language development, describe characteristics of language environment assessments, and outline practical and philosophical considerations to assist with decision-making. The overall goal of this mini review is to demystify the complexities of early childhood language environments and articulate the ways in which language environment assessments can drive practice. We believe this is an essential step toward improving early language experiences and evaluating the impacts of education programming on learning in this fundamental developmental domain.

Environments that support early language development

Language is a complex and multifaceted construct. It typically includes the production of speech sounds and patterns (phonetics and phonology), the words and associated knowledge (semantics), and the systems for combining parts of words together and words into sentences to convey meaning (grammar; Bates et al., 1992 ; Hoff, 2013 ). Research examining these underlying components of language has uncovered diverse developmental trajectories starting in early childhood ( Huttenlocher et al., 2010 ). Indeed, children develop language relatively early compared to other domains, not only because it necessary for communication ( Cates et al., 2012 ), but also because it is foundational for the acquisition of higher-order skills ( Kuhn et al., 2014 ). The first 5 years constitutes a sensitive period of development, as children increase their language learning at a rapid rate due to increased neural plasticity in the brain ( Knudsen, 2004 ). By age four, language development becomes more stable and is highly predictive of language abilities in adolescence ( Bornstein et al., 2014 ). For instance, one study demonstrated that children’s oral narrative skills measured at school entry were related to their reading comprehension performance at age 16 ( Suggate et al., 2018 ). Early language skills are also linked to a host of outcomes across developmental domains. These include cognitive skills (e.g., executive functioning), academic achievement, and socioemotional competence ( Bleses et al., 2016 ; Hentges et al., 2021 ; Bruce and Bell, 2022 ). Thus, it is important to provide experiences that promote language acquisition early in life to ensure children are set on a path for success.

Children’s language abilities are influenced by both genetic and environmental factors ( Hoff-Ginsberg, 1998 ; Hayiou-Thomas et al., 2012 ). Notably, the amount of speech children hear has a direct impact on their developing language, suggesting their language development is shaped by social contexts ( Mahr and Edwards, 2018 ). To illustrate, Hart and Risley (1995) documented a 30-million-word gap between children from families with higher socioeconomic status (SES) and children from families with lower SES. Moreover, neurological studies indicate children who experience more conversational turns with adults have more complex speech, which is reflected in brain functioning that underlies language processing ( Hutton et al., 2017 ; Romeo et al., 2018 ). A large body of observational work has also examined specific aspects of adult interactions that affect language development (see Golinkoff et al., 2019 for a review). Recently, a meta-analysis revealed moderate effects of the quality (e.g., diversity and reciprocity) and quantity (e.g., number of words) of language inputs in the home environment on children’s language development ( Anderson et al., 2021 ). Specifically, conversational interactions between infants and adults account for significant variation in vocabulary in school-age children ( Gilkerson et al., 2018 ). Yet, children are exposed to many sources of language input that are not captured by parent–child interactions, potentially underestimating the language environments of children from low SES backgrounds ( Sperry et al., 2019 ). For instance, “social determinants of language development” outside of the immediate family include community resources, educational programs, and public policies ( Di Sante and Potvin, 2022 ). Notably, the majority of children who are under the age of five spend their day in some type of non-parental care ( Pilarz, 2018 ). Therefore, it is necessary to consider the features of child care and education settings that impact language acquisition.

Classroom and home environments provide very different language opportunities for children. Comparisons between child care and home language environments generally reveal more language interactions occurring between children and caregivers in the home relative to teachers and children in the classroom ( Larson et al., 2020 ). Still, research has documented an association between language exposure in early childhood education settings and children’s language abilities and growth (e.g., Turnbull et al., 2009 ). For example, one study projected a difference of 100 adult words heard per 5 min (equivalent to approximately 1,800,000 words per year) that could be attributed to variation in prekindergarten classroom language environments ( Duncan et al., 2023 ). Children from families with low SES are more likely to experience language of more limited complexity and diversity in the home and school context ( Neuman et al., 2018 ; Duncan et al., 2023 ). This may be, in part, due to families having limited access to high-quality early childhood education in higher poverty communities ( Bassok and Galdo, 2016 ). Targeting the quality of early learning environments in areas with greater socioeconomic disadvantage, and dedicating more public funding to these communities, may help to reduce the observed income quality gradient in ECE ( Hatfield et al., 2015 ; Cloney et al., 2016 ). For example, research indicates that improving community-level social determinants, such as increasing the supply of child care, may elevate children’s literacy scores ( Lipscomb et al., 2019 ). Thus, ensuring children have access to rich language environments inside and outside of the home may be one promising approach to enhancing equity in language development.

Assessments of children’s language environments

Assessments of early childhood learning environments serve multiple purposes—they describe the quality of language environments, help to identify best practices, evaluate programs and interventions, and may even guide public policy ( Lambert et al., 2006 ; Halle et al., 2010 ). Yet, there is ongoing debate as to which components of educational environments are most essential to assess and meaningfully link to children’s short- and long-term outcomes ( Layzer and Goodson, 2006 ; Burchinal, 2018 ). Historically, measures have been classified based on whether they assess structural characteristics of classrooms (e.g., adult-child ratios) or the process of teaching (e.g., teacher-child interactions; Mashburn et al., 2008 ). The most frequently administered assessments of children’s learning environments are observational in nature and typically offer a one-time general snapshot of both the physical space and interactions within the setting (see Halle et al., 2010 for a review). For example, the Early Childhood Environment Rating Scale–Revised (ECERS–R) was designed as a global measure of classroom quality that assesses both structural and process aspects of the early childhood environment, including language reasoning ( Cryer et al., 2003 ). However, the ECERS–R only weakly correlates with children’s language outcomes ( r  = 0.05; Brunsek et al., 2017 ), providing little evidence that using the ECERS – R for quality improvement purposes will result in the intended effects among children. Researchers have discovered that domain-specific measures focused on the quality of instruction and stimulation in specific content areas, like language and literacy, are more promising for guiding practice ( Burchinal et al., 2021 ). Even so, domain-specific measures of language environments remain less commonly assimilated into accountability systems than global assessments of quality ( Mitchell, 2016 ).

The early language environment is comprised of classroom features (e.g., activity settings), characteristics of teachers (e.g., pedagogical orientations), and interactions that support language development (e.g., input, responsivity, feedback; Smith and Dickinson, 1994 ; Wiggins et al., 2007 ). Research indicates that teacher communication-facilitating behaviors, those that create and sustain engagement in conversational turns, are the most powerful predictor of growth in children’s vocabulary from preschool to kindergarten ( Cabell et al., 2015 ; Justice et al., 2018 ). Indeed, teachers can bolster children’s language development by providing opportunities for children to speak and extending their responses ( Huttenlocher et al., 2002 ). Given that children ages 4–6 spend approximately 20–30% of their day learning in language and literacy domains, assessments that capture overall exposure to language and support for rich conversations are most promising for examining the features of environments that scaffold language development ( Pelatti et al., 2014 ). We recognize that other assessments have been developed to include an item, subscale, or dimension for measuring language environments [e.g., the Classroom Assessment Scoring System (CLASS); Pianta et al., 2008 , Teacher Behavior Rating Scale (TBRS); Landry et al., 2000 ] or features of teacher language input [e.g., Code for Interactive Recording of Children’s Learning Environments (CIRCLE); Atwater et al., 2009 ]. However, for the purpose of keeping our review brief and focused on the topic at hand, we have decided to only highlight domain-specific assessments of language/literacy. Therefore, we describe characteristics of frequently utilized domain-specific assessments of early childhood language environments in terms of their measurement properties. Importantly, we make the distinction between classroom-level assessments that provide information about the quality of instructional strategies teachers employ to engage all children in literacy activities, and child-level assessments that evaluate the quality and quantity of linguistic interactions individual children have with their teachers and peers.

Classroom-level assessments

Classroom-level assessments of early language environments measure the widespread opportunities that are available to support children’s language development. These assessments typically include multiple dimensions of the early language environment, including the context, materials and activities, and instructional practices (see Table 1 ). Given their focus on general routines and exercises, these assessments offer a macro view of the overall educational processes in classrooms and are predominantly observation based. Because of the risk of rater bias, administrators of classroom-level assessments may need a certain level of education, experience, and familiarity with early childhood development and learning, and must complete training on implementation procedures. However, the length of observation period that is necessary for obtaining reliable estimates can vary for classroom-level assessments. For example, the Early Language and Literacy Classroom Observation Pre-K assessment (ELLCO) assesses the degree to which children receive optimal support in language and literacy development ( Smith et al., 2008 ). Administrators need a strong background and understanding of children’s language and literacy development, classroom teaching experience, and must complete 9 h of training. Yet, the observation only takes approximately 1.0–1.5 h to administer. Alternatively, the Classroom Language Environment Observational Scale (CLEO) captures both implicit language supports and explicit language instruction ( Phillips et al., 2018 ). Administrators should hold a bachelor’s degree or higher and have experience teaching or observing early childhood classrooms. Training includes one full day of instruction plus 6–8 weeks of practice to establish reliability, and the CLEO observation lasts throughout the entire classroom day. Despite these slight variations, both the ELLCO and CLEO have demonstrated moderate to strong internal consistency ( Smith et al., 2008 ; Phillips et al., 2018 ).

Table 1 . Features of commonly utilized language environment assessments.

Child-level assessments

Child-level assessments of early language environments measure the language experiences that individual children are exposed to. These assessments typically focus on the quality and quantity of language interactions and may also capture the context of instruction or activities (see Table 1 ). Given their focus on relational components, these assessments offer a micro view of the child and their immediate exchanges with peers and adults. Because they predominantly rely on technological applications for observations, administrators of child-level assessments need less direct classroom experience or child development knowledge but may be required to complete training to master the software and coding procedures. There is less risk for rater bias, so reliable estimates can be obtained with shorter lengths of observation periods. For example, the Individualizing Student Instruction Classroom Observation System (ISI) is a video observation and coding system that assesses foundational and instructional elements of the language and literacy classroom environment ( Connor et al., 2009 ). The ISI requires one half day workshop to introduce the assessment and software, but it is most successful with ongoing coaching and professional development ( Connor and Morrison, 2016 ). Video observations on the ISI should record about 6–12 min per target child. Alternatively, the Language Environment Analysis System (LENA) is an audio recording device that quantifies the number of words heard, child vocalizations made, and conversational turn taking ( Xu et al., 2009 ). A basic training on how to use the device and audio processing software is required to purchase the LENA technology. Observations should be a minimum of 10 min long, but the LENA device will record up to 16 h. Both the ISI and LENA have demonstrated moderate to strong internal consistency ( Connor et al., 2009 ; Xu et al., 2009 ).

Research gaps and opportunities

Despite the wide range of assessment options, ongoing debates regarding the merit of observational methods (e.g., Purpura, 2019 ) have contributed to a lack of consensus regarding which aspects of language environments are most promising to assess. Since the formative Hart and Risley study (1995), total amount of language heard remains of interest to researchers (e.g., Sperry et al., 2019 ; Duncan et al., 2023 ). Indeed, frequent input of directed speech is important for building early vocabulary and language-learning processes ( Mahr and Edwards, 2018 ). However, there is also evidence indicating the quality of talk is of greater importance for children’s language development than purely the number of words heard ( Golinkoff et al., 2019 ; Anderson et al., 2021 ). Features of adult speech, such as lexical diversity and reciprocity, enable children to adopt word-learning mechanisms ( Hirsh-Pasek et al., 2015 ; Newman et al., 2016 ). While the total amount of talk may be easier to code with language processing devices (e.g., the LENA), the quality of talk often requires more intensive researcher coding or subjective ratings of the experiences (e.g., Justice et al., 2018 ; Anderson et al., 2021 ). Possibly in between the pure counts of adult words heard and quality of language interactions would be the number of conversational turns children experience. These are typically defined as the instances of back and forth between the child and an adult. Conversational turns—usually conceptualized as quantitative metrics—have been linked to number of key child outcomes and brain development ( Gilkerson et al., 2018 ; Romeo et al., 2018 ), and have been shown to have larger effect sizes than pure numbers of adult words heard ( Duncan et al., 2023 ). Still, more research is needed that compares approaches to determine which provides the greatest return on investment both in terms of predictive power and information gained relative to effort expended.

Widespread adoption of language environment assessments has also, in part, been hindered by limited direct application in program evaluation research. As previously noted, interventions that focus on conversational interactions elicited by adults have the strongest potential to foster vocabulary development ( Dowdall et al., 2020 ). For example, dialogic reading has been found to encourage the use of a larger vocabulary, greater conceptual discussion, and longer sentences, which in turn, can impact the neural networks underlying language development ( Wasik et al., 2006 ; Hadley et al., 2022 ). Yet, evidence suggests that Head Start teachers rarely ask open-ended prompts or wait for responses during shared book reading ( Hindman et al., 2019 ). Language environment assessments can therefore be leveraged for the purpose of documenting existing processes and developing strategies for improving interactions. For instance, preliminary results indicate the LENA Start Program—designed to improve knowledge about the importance of the early language environment and provide tips for enriching the early language environment—can effectively increase the number of conversational turns between children and their parents through enhancing parental beliefs about the quality and quantity of language input ( Cunha et al., 2023 ). Therefore, researchers should evaluate whether strategically integrating language environment assessments into large-scale interventions increases awareness and positive attitudes about the importance of conversational turns and impacts children’s learning outcomes.

Relatedly, researchers can utilize language environment assessments to examine the ecological validity of language interventions and programs designed to improve the quality of early learning. For example, it is unclear whether effects of interventions delivered by trained research assistants transfer when administered by practitioners in real world situations ( Piasta et al., 2020a , b ). Indeed, a systematic review synthesizing results from early language interventions implemented by caregivers and parents of young children revealed that only half of studies observationally assessed changes in the quality of the language environment ( Greenwood et al., 2020 ). However, it is critical that language environment assessments are validated for this purpose and can detect discrete changes in all critical aspects of language environments that are known to predict language development, such as diversity and complexity of vocabulary, conversational turn-taking, verbal responsivity, and the supports for primary and secondary language learning ( Anderson et al., 2021 ). Thus, it is important to continue to develop and refine language environment assessments before administering them to examine the fidelity of implementing interventions or programs within authentic settings. Both efforts will provide evidence of the suitability of existing measures to detect targeted changes in language environments.

The effects of language interventions on child- and classroom-level processes have also been under-evaluated in the literature. Previous work indicates the classroom context is an important factor that influences the frequency of language stimulation practices ( Turnbull et al., 2009 ). For instance, in a meta-analysis of language interventions delivered to children between 4 and 9 years old, Rogde et al. (2019) found that studies with small-group interventions demonstrated larger effects on oral language skills than whole-classroom interventions or those involving larger groups. These results imply that high-quality interventions delivered to small groups can be beneficial for children’s language development. However, it is possible for more targeted language interventions to have spillover effects that enhance the larger classroom language environment, or impact future cohorts of students in the classroom ( Cilliers et al., 2022 ). Peers may also make significant contributions to one another’s language skills by serving as language models ( Perry et al., 2018 ; Washington-Nortey et al., 2022 ). Therefore, utilizing both child- and classroom-level language environments assessments to understand the potential for educational interventions to have a ripple or cascading effect may lead to significant discoveries regarding persistence and fadeout.

Language environment assessments are also somewhat limited in their ability to capture the breadth of classroom practices and strategies that promote language development. Beyond interactive or dialogic book reading, approaches involving speech and language therapists have been shown to be effective interventions for supporting language development ( Dobinson and Dockrell, 2021 ). Moreover, a meta-analysis revealed that language and literacy focused professional development in preschool had a medium to small effect on process quality and children’s phonological awareness ( Markussen-Brown et al., 2017 ). However, many language environment assessments are not intended to capture the processes targeted by professional development ( Justice et al., 2018 ), or the direct impacts of coaching or instruction provided by other specialized professionals. Therefore, a complementary line of work should center on the development and modification of language environment assessments to align with a broader conceptualization of what constitutes language supports.

Finally, there are critical gaps concerning the applicability of language environment assessments within diverse educational settings, including classrooms that serve dual language learners (DLLs), that must be filled ( White et al., 2020 ). For example, one analysis determined that most studies on the LENA system have been conducted with English-speaking children ( Ganek and Eriks-Brophy, 2018 ). A lack of representation is also apparent across language intervention research. In a systematic literature review, Walker et al. (2020) demonstrated that less than a quarter of language intervention studies in early education programs reported information about the race or ethnicity of children participating in the intervention, and only a quarter of samples included children who were DLLs. Further, they discovered that only 12% of studies reported on the racial/ethnic backgrounds of the early childhood personnel administering the interventions. Given that DLLs acquire their first and second language best when delivered instruction in their home language (e.g., Barnett et al., 2007 ; Partika et al., 2021 ), it is important that language environment assessments capture the instructional practices that facilitate first and second language development, such as the use of contextualized language ( Sawyer et al., 2018 ). Thus, research that addresses these shortcomings may also help to clarify how to appropriately incorporate language environment assessments into mainstream education.

Considerations for practice

In addition to the limitations of current research on early childhood language environments, there are practical constraints that may be impeding widespread uptake of assessments. Teachers may lack a fundamental understanding of what constitutes oral language and emergent literacy ( Weadman et al., 2023 ), as well as the skills to evaluate their own assessment practices and professional development needs ( Hill, 2017 ). These competencies are critical to develop because educator language and literacy knowledge has been shown to be correlated with more desirable classroom practices and children’s language outcomes ( Piasta et al., 2020a , b ). Researchers argue there is a need for consistent training on language and literacy content and the benefits of teacher talk for children’s language development in educator preparation programs ( Weadman et al., 2021 ). Moreover, ongoing professional development should focus on effective language facilitation and conversation strategies that preschool teachers can implement and should offer practice connecting this procedural knowledge to “in the moment” situations ( Mathers, 2021 ). For example, one study used the Emergent Literacy and Language Early Childhood Checklist for Teachers (ELLECCT) assessment to demonstrate how teachers often miss opportunities to target children’s phonological awareness during shared book reading ( Weadman et al., 2022 ). Therefore, early childhood language environment assessments may serve as a useful framework for training and professional development to help inform teachers of their use of practices associated with language development ( Franco et al., 2019 ).

Choosing an assessment that aligns with program goals and meets the needs of children and educators can, however, be a challenge in and of itself ( Zaslow et al., 2009 ). For instance, the ELLCO provides teachers with an understanding of the quality of the language and literacy environment of the classroom, while the LISn offers details on the quality of interactions between peers and adults, including the frequency and types of languages spoken. There are also tradeoffs according to the amount of information ascertained with reasonable effort. Classroom-level metrics can be captured by only observing and rating the teacher (i.e., the behaviors the teacher shows that would impact all children in the classroom). Conversely, child-level metrics would potentially better capture the unique experiences of children within the classroom, as opposed to assuming all children have the same experiences. Depending on whether the purpose of the assessment is to understand granular language engagement processes or general indices of the quality of language environment, some measures may be more sensitive to pick up discrete characteristics than others ( Justice et al., 2018 ). Thus, one consideration may be whether to administer classroom-level assessments to inform universal teaching practices ( Baker and Páez, 2018 ), or child-level assessments to provide guidance on individualized interventions for children ( Franco et al., 2019 ).

Additionally, it may be unrealistic for educational programs to accumulate the capital necessary for precise measurement and communication of language environment assessment findings. As described earlier, many assessments require extensive training and experience within early childhood classrooms, and programs may not have staff with relevant background to dedicate to this purpose ( Ackerman, 2019 ). For instance, the protocols for several assessments recommend administration by individuals with certain education levels or observation history. It may not be feasible for a teacher to administer individual assessments when they must also manage the classroom environment and facilitate children’s learning and development. Similarly, substantial training is often needed to become a reliable observer and maintain adherence to the procedures of language environment assessments ( Zaslow et al., 2009 ). Meeting these prerequisites can be costly and labor intensive, especially for programs that do not have a robust administrative infrastructure in place. The amount of support a program receives from their leadership to overcome these obstacles may be a critical factor in determining assessment participation ( Derrick-Mills et al., 2014 ).

Even after a language environment assessment has been chosen and implemented, programs may need specific resources to leverage the data to inform professional development. At a very basic level, human capacity is needed to analyze and translate data, which sometimes involves individuals who have pertinent technical skills to interpret statistics and graphs ( Isaacs et al., 2015 ). Programs may also need staff who can manage complex equipment, technology, and datasets. For example, child-level assessments like the LENA and ISI rely on hardware for collecting data and software for analyzing and/or storing data and developing reports ( Derrick-Mills et al., 2014 ). Beyond these logistical parameters, another challenge is effectively using the information to promote positive practices. One issue that can arise is teachers may assume they should emphasize only the discrete aspects of instruction addressed through the assessment itself rather than supporting broader integration ( Hirsh-Pasek et al., 2005 ). Thus, hiring coaches who have relevant funds of knowledge to make developmentally appropriate and evidence-based recommendations may be essential ( Ackerman, 2019 ). As Mathers (2022) contests, adoption of an observation tool itself cannot guarantee successful application without the focus on professional learning.

Another barrier that may be necessary to overcome is creating buy-in around language environment assessment use. For example, research suggests that teachers generally do not find kindergarten readiness assessments beneficial for instruction, and further, they view them as administratively burdensome and as taking time away from instruction, rather than contributing useful information for practice ( Schachter et al., 2020 ). Although there has been limited investigation into teacher perspectives on classroom environment assessments, one study found that administrators experience difficulties finding the time to conduct observations of classroom quality, but they report using the data for a variety of purposes, including individual teacher development ( Zweig et al., 2015 ). One framework that has been proposed for conceptualizing emergent literacy data practices is through examining: (1) how teachers prefer to gather data, (2) how they interpret data, (3) and how they use the data ( Schachter and Piasta, 2022 ). Given that educators play a critical role in supporting young children’s language development, it will be important for administrators to incentivize the implementation of language environment assessments and be prepared to engage in best practices around collecting and using data.

A final consideration for educators selecting assessments is whether to operationalize high-quality language environments beyond simply examining average levels of exposure. Studies have documented substantial variation in language environments within and across school days ( Chaparro-Moreno et al., 2019 ; Duncan et al., 2020 ), which may have implications for vocabulary development. For instance, research suggests that inconsistency in instructional quality, including concept development, language modeling, and quality of feedback, may be negatively associated with children’s vocabulary development in prekindergarten ( Finders et al., 2021 ). In early education settings where teachers do the majority of talking, persistent language use by the teacher could reflect a lack of responsivity. Indeed, one study demonstrated that children spend very little time in the preschool classroom engaged in responsive interactions with their teachers ( Dickinson et al., 2008 ). Responsiveness, which refers to promoting reciprocity in language interactions, involves teachers providing children opportunities to use language by asking open-ended questions and modeling talk, and is one of the strongest indicators of DLL’s language development ( Kane et al., 2023 ). Therefore, the degree to which assessments are designed to pick up on small changes in the quality of language provision throughout the day may be important factor to weigh when determining which measure to utilize. To sum, there are many factors that need to be balanced when selecting a language environment assessment, and without adequate resources and support, programs may struggle to navigate this complex territory.

Despite a robust literature underscoring aspects of language input that matter for children’s language development, language environment assessments have not been widely integrated into early childhood programming. In this mini review, we argue that in order to promote high-quality learning experiences within early education settings, we must be able to operationalize the essential features of these environments through assessment. Therefore, we provide concrete considerations for research and practice that have the potential to build awareness of and capacity to effectively utilize language environment assessments to improve the quality of language environments for diverse learners. We maintain that incorporating assessment practices into early education is a critical first step toward addressing socioeconomic disparities in language development and enhancing equitable opportunities for children worldwide ( Jemeli and Fakandu, 2019 ).

Author contributions

JF, EW, and RD contributed to conception of the manuscript and wrote sections of the manuscript. JF developed the framework and overall structure. All authors contributed to manuscript revision, read, and approved the submitted version.

Publication of this article was funded in part by Purdue University Libraries Open Access Publishing Fund.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Ackerman, D. (2019). “Early childhood care and education workforce issues in implementing assessment policies” in The Wiley handbook of early childhood care and education . eds. C. P. Brown, M. B. McMullen, and N. File (Hoboken, NJ: Wiley), 537–567.

Google Scholar

Anderson, N. J., Graham, S. A., Prime, H., Jenkins, J. M., and Madigan, S. (2021). Linking quality and quantity of parental linguistic input to child language skills: a meta-analysis. Child Dev. 92, 484–501. doi: 10.1111/cdev.13508

PubMed Abstract | CrossRef Full Text | Google Scholar

Atwater, J. B., Lee, Y., Montagna, D., Reynolds, L. H., and Tapia, Y. (2009). Classroom CIRCLE: Classroom Code for Interactive Recording of Children’s Learning Environments (Version 2.0). Kansas City: Juniper Gardens Children’s Project, University of Kansas.

Atkins-Burnett, S., Sprachman, S., and Caspe, M. (2010). Language interaction snapshot (LISn) . Princeton, NJ: Mathematica Policy Research.

Baker, M., and Páez, M. (2018). The language of the classroom: dual language learners in head start, public pre-K, and private preschool programs . Washington, DC: Migration Policy Institute.

Barnett, W. S., Yarosz, D. J., Thomas, J., Jung, K., and Blanco, D. (2007). Two-way and monolingual English immersion in preschool education: an experimental comparison. Early Child. Res. Q. 22, 277–293. doi: 10.1016/j.ecresq.2007.03.003

CrossRef Full Text | Google Scholar

Bassok, D., and Galdo, E. (2016). Inequality in preschool quality? Community-level disparities in access to high-quality learning environments. Early Educ. Dev. 27, 128–144. doi: 10.1080/10409289.2015.1057463

Bates, E., Thal, D., and Janowsky, J. S. (1992). “Early language development and its neural correlates” in Handbook of neuropsychology, 7 . eds. S. Broman and J. Fletcher (New York, NY: Oxford University Press), 69–110.

Bleses, D., Makransky, G., Dale, P. S., Højen, A., and Ari, B. A. (2016). Early productive vocabulary predicts academic achievement 10 years later. Appl. Psycholinguist. 37, 1461–1476. doi: 10.1017/S0142716416000060

Bornstein, M. H., Hahn, C. S., Putnick, D. L., and Suwalsky, J. T. (2014). Stability of core language skill from early childhood to adolescence: a latent variable approach. Child Dev. 85, 1346–1356. doi: 10.1111/cdev.12192

Bruce, M., and Bell, M. A. (2022). Vocabulary and executive functioning: a scoping review of the unidirectional and bidirectional associations across early childhood. Hum. Dev. 66, 167–187. doi: 10.1159/000524964

Brunsek, A., Perlman, M., Falenchuk, O., McMullen, E., Fletcher, B., and Shah, P. S. (2017). The relationship between the early childhood environment rating scale and its revised form and child outcomes: a systematic review and meta-analysis. PLoS One 12:e0178512. doi: 10.1371/journal.pone.0178512

Burchinal, M. (2018). Measuring early care and education quality. Child Dev. Perspect. 12, 3–9. doi: 10.1111/cdep.12260

Burchinal, M., Garber, K., Foster, T., Bratsch-Hines, M., Franco, X., and Peisner-Feinberg, E. (2021). Relating early care and education quality to preschool outcomes: the same or different models for different outcomes? Early Child. Res. Q. 55, 35–51. doi: 10.1016/j.ecresq.2020.10.005

Cabell, S. Q., Justice, L. M., McGinty, A. S., DeCoster, J., and Forston, L. D. (2015). Teacher–child conversations in preschool classrooms: contributions to children's vocabulary development. Early Child. Res. Q. 30, 80–92. doi: 10.1016/j.ecresq.2014.09.004

Cates, C. B., Dreyer, B. P., Berkule, S. B., White, L. J., Arevalo, J. A., and Mendelsohn, A. L. (2012). Infant communication and subsequent language development in children from low income families: the role of early cognitive stimulation. J. Dev. Behav. Pediatr. 33, 577–585. doi: 10.1097/dbp.0b013e318264c10f

Chaparro-Moreno, L. J., Justice, L. M., Logan, J. A., Purtell, K. M., and Lin, T. J. (2019). The preschool classroom linguistic environment: children’s first-person experiences. PLoS One 14:e0220227. doi: 10.1371/journal.pone.0220227

Cilliers, J., Fleisch, B., Kotze, J., Mohohlwane, M., and Taylor, S. (2022). The challenge of sustaining effective teaching: spillovers, fade-out, and the cost-effectiveness of teacher development programs. Econ. Educ. Rev. 87:102215. doi: 10.1016/j.econedurev.2021.102215

Cloney, D., Tayler, C., Hattie, J., Cleveland, G., and Adams, R. (2016). The selection of ECEC programs by Australian families: quality, availability, usage and family demographics. Australas. J. Early Childhood 41, 16–27. doi: 10.1177/183693911604100403

Connor, C. M., and Morrison, F. J. (2016). Individualizing student instruction in reading: implications for policy and practice. Policy Insights Behav. Brain Sci. 3, 54–61. doi: 10.1177/2372732215624931

Connor, C. M., Morrison, F. J., Fishman, B. J., Ponitz, C. C., Glasney, S., Underwood, P. S., et al. (2009). The ISI classroom observation system: examining the literacy instruction provided to individual students. Educ. Res. 38, 85–99. doi: 10.3102/0013189X09332373

Cryer, D., Harms, T., and Riley, C. (2003). All about the ECERS-R . Lewisville: NC Pact House Publishing.

Cunha, F., Gerdes, M., Qinyou, H., and Nihtianova, S. (2023). Language environment and maternal expectations: an evaluation of the Lena start program. No. w30837 National Bureau of Economic Research Available at: https://www.nber.org/system/files/working_papers/w30837/w30837.pdf .

Derrick-Mills, T., Sandstrom, H., Pettijohn, S. L., Fyffe, S. D., and Koulish, J. (2014). Data use for continuous quality improvement: What the head start field can learn from other disciplines-a literature review and conceptual framework (report no. 2014–77) . Washington, DC: Office of Planning, Research, and Evaluation. Available at: https://www.acf.hhs.gov/opre/report/data-use-continuous-quality-improvement-what-head-start-field-can-learn-other

Di Sante, M., and Potvin, L. (2022). We need to talk about social inequalities in language development. Am. J. Speech Lang. Pathol. 31, 1894–1897. doi: 10.1044/2022_AJSLP-21-00326

Dickinson, D. K., Darrow, C. L., and Tinubu, T. A. (2008). Patterns of teacher–child conversations in head start classrooms: implications for an empirically grounded approach to professional development. Early Educ. Dev. 19, 396–429. doi: 10.1080/10409280802065403

Dobinson, K. L., and Dockrell, J. E. (2021). Universal strategies for the improvement of expressive language skills in the primary classroom: a systematic review. First Lang. 41, 527–554. doi: 10.1177/0142723721989471

Dowdall, N., Melendez-Torres, G. J., Murray, L., Gardner, F., Hartford, L., and Cooper, P. J. (2020). Shared picture book reading interventions for child language development: a systematic review and meta-analysis. Child Dev. 91, e383–e399. doi: 10.1111/cdev.13225

Duncan, R. J., Anderson, K. L., King, Y. A., Finders, J. K., Schmitt, S. A., and Purpura, D. J. (2023). Predictors of preschool language environments and their relations to children's vocabulary. Infant Child Dev. 32:e2381. doi: 10.1002/icd.2381

Duncan, R. J., King, Y. A., Finders, J. K., Elicker, J., Schmitt, S. A., and Purpura, D. J. (2020). Prekindergarten classroom language environments and children’s vocabulary skills. J. Exp. Child Psychol. 194:104829. doi: 10.1016/j.jecp.2020.104829

Finders, J. K., Budrevich, A., Duncan, R. J., Purpura, D. J., Elicker, J., and Schmitt, S. A. (2021). Variability in preschool CLASS scores and children’s school readiness. AERA Open 7:233285842110389. doi: 10.1177/23328584211038938

Franco, X., Bryant, D. M., Gillanders, C., Castro, D. C., Zepeda, M., and Willoughby, M. T. (2019). Examining linguistic interactions of dual language learners using the language interaction snapshot (LISn). Early Child. Res. Q. 48, 50–61. doi: 10.1016/j.ecresq.2019.02.007

Freedson, M., Figueras-Daniel, A., Frede, E., Jung, K., and Sideris, J. (2011). “The classroom assessment of supports for emergent bilingual acquisition” in Dual language learners in the early childhood classroom . eds. C. Howes, J. Downer, and R. Pianta (Baltimore, MD: Brookes Publishing), 233–258.

Ganek, H., and Eriks-Brophy, A. (2018). Language ENvironment analysis (LENA) system investigation of day long recordings in children: a literature review. J. Commun. Disord. 72, 77–85. doi: 10.1016/j.jcomdis.2017.12.005

Gilkerson, J., Richards, J. A., Warren, S. F., Oller, D. K., Russo, R., and Vohr, B. (2018). Language experience in the second year of life and language outcomes in late childhood. Pediatrics 142:e20174276. doi: 10.1542/peds.2017-4276

Golinkoff, R. M., Hoff, E., Rowe, M. L., Tamis-LeMonda, C. S., and Hirsh-Pasek, K. (2019). Language matters: denying the existence of the 30-million-word gap has serious consequences. Child Dev. 90, 985–992. doi: 10.1111/cdev.13128

Goodson, B. D., Layzer, C. J., and Smith, W. C. (2006). Observation measures of language and literacy in early childhood (OMLIT) . Cambridge, MA: Abt Associates.

Greenwood, C. R., Schnitz, A. G., Carta, J. J., Wallisch, A., and Irvin, D. W. (2020). A systematic review of language intervention research with low-income families: a word gap prevention perspective. Early Child. Res. Q. 50, 230–245. doi: 10.1016/j.ecresq.2019.04.001

Grehan, A., and Smith, L. J. (2004). The early literacy observation tool (E-LOT) . Memphis, TN: University of Memphis Center for Research in Educational Policy.

Hadley, E. B., Barnes, E. M., Wiernik, B. M., and Raghavan, M. (2022). A meta-analysis of teacher language practices in early childhood classrooms. Early Child. Res. Q. 59, 186–202. doi: 10.1016/j.ecresq.2021.12.002

Halle, T., Vick Whittaker, J. E., and Anderson, R. (2010). Quality in early childhood care and education settings: a compendium of measures. Washington, DC: Child Trends. Prepared by Child Trends for the Office of Planning, Research and Evaluation, Administration for Children and Families, US Department of Health and Human Services.

Hart, B., and Risley, T. R. (1995). Meaningful differences in the everyday experience of young American children . Baltimore, MD: Brookes Publishing.

Hatfield, B. E., Lower, J. K., Cassidy, D. J., and Faldowski, R. A. (2015). Inequities in access to quality early care and education: associations with funding and community context. Early Child. Res. Q. 30, 316–326. doi: 10.1016/j.ecresq.2014.01.001

Hayiou-Thomas, M. E., Dale, P. S., and Plomin, R. (2012). The etiology of variation in language skills changes with development: a longitudinal twin study of language from 2 to 12 years. Dev. Sci. 15, 233–249. doi: 10.1111/j.1467-7687.2011.01119.x

Hentges, R. F., Devereux, C., Graham, S. A., and Madigan, S. (2021). Child language difficulties and internalizing and externalizing symptoms: a meta-analysis. Child Dev. 92, e691–e715. doi: 10.1111/cdev.13540

Hill, K. (2017). Understanding classroom-based assessment practices: a precondition for teacher assessment literacy. Papers Lang. Test. Assess. 6, 1–17. doi: 10.58379/YIWZ4710

Hindman, A. H., Wasik, B. A., and Bradley, D. E. (2019). How classroom conversations unfold: Exploring teacher–child exchanges during shared book reading. Early Educ. Dev. 30, 478–495. doi: 10.1080/10409289.2018.1556009

Hirsh-Pasek, K., Adamson, L. B., Bakeman, R., Owen, M. T., Golinkoff, R. M., Pace, A., et al. (2015). The contribution of early communication quality to low-income children’s language success. Psychol. Sci. 26, 1071–1083. doi: 10.1177/0956797615581493

Hirsh-Pasek, K., Kochanoff, A., Newcombe, N. S., and de Villiers, J. (2005). Using scientific knowledge to inform preschool assessment: making the case for empirical validity. Soc. Policy Rep. XIX, 3–19. doi: 10.1002/j.2379-3988.2005.tb00042.x

Hoff, E. (2013). Language development . (5th ed.) Cengage Learning.

Hoff-Ginsberg, E. (1998). The relation of birth order and socioeconomic status to children's language experience and language development. Appl. Psycholinguist. 19, 603–629. doi: 10.1017/S0142716400010389

Huttenlocher, J., Vasilyeva, M., Cymerman, E., and Levine, S. (2002). Language input and child syntax. Cogn. Psychol. 45, 337–374. doi: 10.1016/S0010-0285(02)00500-5

Huttenlocher, J., Waterfall, H., Vasilyeva, M., Vevea, J., and Hedges, L. V. (2010). Sources of variability in children’s language growth. Cogn. Psychol. 61, 343–365. doi: 10.1016/j.cogpsych.2010.08.002

Hutton, J. S., Phelan, K., Horowitz-Kraus, T., Dudley, J., Altaye, M., DeWitt, T., et al. (2017). Shared reading quality and brain activation during story listening in preschool-age children. J. Pediatr. 191, 204–211.e1. doi: 10.1016/j.jpeds.2017.08.037

Isaacs, J., Sandstrom, H., Rohacek, M., Lowenstein, C., Healy, O., and Gearing, M. (2015). How head start grantees set and use school readiness goals (report no. 2015-12a) . Washington, DC: Office of Planning, Research and Evaluation. Available at: https://www.acf.hhs.gov/archive/blog/2015/02/how-head-start-grantees-set-and-use-school-readiness-goals

Jemeli, C. M., and Fakandu, A. M. (2019). Equitable access to education and development in a knowledgeable society as advocated by UNESCO. Educ. Res. Rev. 14, 200–205. doi: 10.5897/ERR2018.3647

Justice, L. M., Jiang, H., and Strasser, K. (2018). Linguistic environment of preschool classrooms: what dimensions support children’s language growth? Early Child. Res. Q. 42, 79–92. doi: 10.1016/j.ecresq.2017.09.003

Kane, C., Sandilos, L., Hammer, C. S., Komaroff, E., Bitetti, D., and López, L. (2023). Teacher language quality in preschool classrooms: examining associations with DLLs' oral language skills. Early Child. Res. Q. 63, 352–361. doi: 10.1016/j.ecresq.2023.01.006

Knudsen, E. I. (2004). Sensitive periods in the development of the brain and behavior. J. Cogn. Neurosci. 16, 1412–1425. doi: 10.1162/0898929042304796

Kuhn, L. J., Willoughby, M. T., Wilbourn, M. P., Vernon-Feagans, L., and Blair, C. B., Family Life Project Key Investigators (2014). Early communicative gestures prospectively predict language development and executive function in early childhood. Child Dev. 85, 1898–1914. doi: 10.1111/cdev.12249

Lambert, R., Abbott-Shim, M., and Sibley, A. (2006). “Evaluating the quality of early childhood educational settings” in Handbook of research on the education of young children . Eds. B. Spodek and O. N. Saracho (Mahwah, NJ: Lawrence Erlbaum Associates Publishers), 475–494.

Landry, S. H., Crawford, A., Gunnewig, S., and Swank, P. R. (2000). The CIRCLE–Teacher Behavior Rating Scale. Unpublished research instrument, center for improving the readiness for children for learning and education. University of Texas Health Science Center at Houston, TX.

Larson, A. L., Barrett, T. S., and McConnell, S. R. (2020). Exploring early childhood language environments: a comparison of language use, exposure, and interactions in the home and childcare settings. Lang. Speech Hear. Serv. Sch. 51, 706–719. doi: 10.23641/asha.12042678

Layzer, J. I., and Goodson, B. D. (2006). The “quality” of early care and education settings: definitional and measurement issues. Eval. Rev. 30, 556–576. doi: 10.1177/0193841X06291524

Lipscomb, S. T., Miao, A. J., Finders, J. K., Hatfield, B., Kothari, B. H., and Pears, K. (2019). Community-level social determinants and children’s school readiness. Prev. Sci. 20, 468–477. doi: 10.1007/s11121-019-01002-8

Mahr, T., and Edwards, J. (2018). Using language input and lexical processing to predict vocabulary size. Dev. Sci. 21:e12685. doi: 10.1111/desc.12685

Markussen-Brown, J., Juhl, C. B., Piasta, S. B., Bleses, D., Højen, A., and Justice, L. M. (2017). The effects of language-and literacy-focused professional development on early educators and children: a best-evidence meta-analysis. Early Child. Res. Q. 38, 97–115. doi: 10.1016/j.ecresq.2016.07.002

Mashburn, A. J., Pianta, R. C., Hamre, B. K., Downer, J. T., Barbarin, O. A., Bryant, D., et al. (2008). Measures of classroom quality in prekindergarten and children’s development of academic, language, and social skills. Child Dev. 79, 732–749. doi: 10.1111/j.1467-8624.2008.01154.x

Mathers, S. J. (2021). Using video to assess preschool teachers’ pedagogical knowledge: explicit and higher-order knowledge predicts quality. Early Child. Res. Q. 55, 64–78. doi: 10.1016/j.ecresq.2020.10.010

Mathers, S. J. (2022). Considerations when using rating scales to support teacher professional development: a commentary on Weadman, Serry and Snow (2022). First Lang. 42, 588–591. doi: 10.1177/01427237221096512

Mitchell, S. (2016). Comprehensive assessment systems in preschool development and expansion grant states . Preschool Development and Expansion Grant Technical Assistance (PDGTA): Washington, DC.

Neuman, S. B., Kaefer, T., and Pinkham, A. M. (2018). A double dose of disadvantage: language experiences for low-income children in home and school. J. Educ. Psychol. 110, 102–118. doi: 10.1037/edu0000201

Newman, R. S., Rowe, M. L., and Ratner, N. B. (2016). Input and uptake at 7 months predicts toddler vocabulary: the role of child-directed speech and infant processing skills in language development. J. Child Lang. 43, 1158–1173. doi: 10.1017/S0305000915000446

Partika, A., Johnson, A. D., Phillips, D. A., Luk, G., and Dericks, A., Tulsa SEED Study Team (2021). Dual language supports for dual language learners? Exploring preschool classroom instructional supports for DLLs' early learning outcomes. Early Child. Res. Q. 56, 124–138. doi: 10.1016/j.ecresq.2021.03.011

Pelatti, C. Y., Piasta, S. B., Justice, L. M., and O’Connell, A. (2014). Language-and literacy-learning opportunities in early childhood classrooms: Children's typical experiences and within-classroom variability. Early Child. Res. Q. 29, 445–456. doi: 10.1016/j.ecresq.2014.05.004

Perry, L. K., Prince, E. B., Valtierra, A. M., Rivero-Fernandez, C., Ullery, M. A., Katz, L. F., et al. (2018). A year in words: The dynamics and consequences of language experiences in an intervention classroom. PloS one. 13:e0199893.

PubMed Abstract | Google Scholar

Phillips, B. M., Zhao, Y., and Weekley, M. J. (2018). Teacher language in the preschool classroom: initial validation of a classroom environment observation tool. Early Educ. Dev. 29, 379–397. doi: 10.1080/10409289.2017.1408371

Pianta, R. C., La Paro, K. M., and Hamre, B. K. (2008). Classroom Assessment Scoring System™. Manual Pre-K. Paul H Brookes.

Piasta, S. B., Farley, K. S., Mauck, S. A., Soto Ramirez, P., Schachter, R. E., O'Connell, A. A., et al. (2020a). At-scale, state-sponsored language and literacy professional development: impacts on early childhood classroom practices and children’s outcomes. J. Educ. Psychol. 112, 329–343. doi: 10.1037/edu0000380

Piasta, S. B., Park, S., Farley, K. S., Justice, L. M., and O'Connell, A. A. (2020b). Early childhood educators' knowledge about language and literacy: associations with practice and children's learning. Dyslexia 26, 137–152. doi: 10.1002/dys.1612

Pilarz, A. R. (2018). Multiple child care arrangements and school readiness in kindergarten. Early Child. Res. Q. 42, 170–182. doi: 10.1016/j.ecresq.2017.09.004

Purpura, D. J. (2019). Language clearly matters; methods matter too. Child Dev. 90, 1839–1846. doi: 10.1111/cdev.13327

Rogde, K., Hagen, A. M., Melby-Lervag, M., and Lervag, A. (2019). The effect of linguistic comprehension instruction on generalized language and reading comprehension skills: a systematic review. Campbell Syst. Rev. 15:e1059. doi: 10.1002/cl2.1059

Romeo, R. R., Leonard, J. A., Robinson, S. T., West, M. R., Mackey, A. P., Rowe, M. L., et al. (2018). Beyond the 30-million-word gap: Children’s conversational exposure is associated with language-related brain function. Psychol. Sci. 29, 700–710. doi: 10.1177/0956797617742725

Sawyer, B., Atkins-Burnett, S., Sandilos, L., Scheffner Hammer, C., Lopez, L., and Blair, C. (2018). Variations in classroom language environments of preschool children who are low income and linguistically diverse. Early Educ. Dev. 29, 398–416. doi: 10.1080/10409289.2017.1408373

Schachter, R. E., Flynn, E. E., Napoli, A. R., and Piasta, S. B. (2020). Teachers’ perspectives on year two implementation of a kindergarten readiness assessment. Early Educ. Dev. 31, 778–795. doi: 10.1080/10409289.2019.1679606

Schachter, R. E., and Piasta, S. B. (2022). Doing assessment: a multicase study of preschool teachers’ language and literacy data practices. Read. Res. Q. 57, 515–535. doi: 10.1002/rrq.419

Smith, M. W., Brady, J. P., and Anastasopoulos, L. (2008). User’s guide to the early language and literacy classroom observation pre-K tool (ELLCO pre-K) . Baltimore, MD: Brookes Publishing.

Smith, S., Davidson, S., Weisenfeld, G., and Katsaros, S. (2001). Supports for early literacy assessment for early childhood programs serving preschool-age children (SELA) . New York, NY: New York University.

Smith, M. W., and Dickinson, D. K. (1994). Describing oral language opportunities and environments in head start and other preschool classrooms. Early Child. Res. Q. 9, 345–366. doi: 10.1016/0885-2006(94)90014-0

Sperry, D. E., Sperry, L. L., and Miller, P. J. (2019). Language does matter: but there is more to language than vocabulary and directed speech. Child Dev. 90, 993–997. doi: 10.1111/cdev.13125

Suggate, S., Schaughency, E., McAnally, H., and Reese, E. (2018). From infancy to adolescence: the longitudinal links between vocabulary, early literacy skills, oral narrative, and reading comprehension. Cogn. Dev. 47, 82–95. doi: 10.1016/j.cogdev.2018.04.005

Turnbull, K. P., Anthony, A. B., Justice, L., and Bowles, R. (2009). Preschoolers' exposure to language stimulation in classrooms serving at-risk children: the contribution of group size and activity context. Early Educ. Dev. 20, 53–79. doi: 10.1080/10409280802206601

Walker, D., Sepulveda, S. J., Hoff, E., Rowe, M. L., Schwartz, I. S., Dale, P. S., et al. (2020). Language intervention research in early childhood care and education: a systematic survey of the literature. Early Child. Res. Q. 50, 68–85. doi: 10.1016/j.ecresq.2019.02.010

Washington-Nortey, P. M., Zhang, F., Xu, Y., Ruiz, A. B., Chen, C. C., Spence, C., et al. (2022). The impact of peer interactions on language development among preschool English language learners: A systematic review. Early Child. Educ. J. 50, 49–59. doi: 10.1007/s10643-020-01126-5

Wasik, B. A., Bond, M. A., and Hindman, A. (2006). The effects of a language and literacy intervention on head start children and teachers. J. Educ. Psychol. 98, 63–74. doi: 10.1037/0022-0663.98.1.63

Weadman, T., Serry, T., and Snow, P. C. (2021). Australian early childhood teachers' training in language and literacy: a nation-wide review of pre-service course content. Aust. J. Teach. Educ. 46, 29–56. doi: 10.14221/ajte.2021v46n2.3

Weadman, T., Serry, T., and Snow, P. C. (2022). Oral language and emergent literacy strategies used by Australian early childhood teachers during shared book reading. Early Childhood Educ. J. , 1–14. doi: 10.1007/s10643-022-01381-8

Weadman, T., Serry, T., and Snow, P. C. (2023). The oral language and emergent literacy skills of preschoolers: early childhood teachers’ self-reported role, knowledge and confidence. Int. J. Lang. Commun. Disord. 58, 154–168. doi: 10.1111/1460-6984.12777

White, L. J., Fernandez, V. A., and Greenfield, D. B. (2020). Assessing classroom quality for Latino dual language learners in head start: DLL-specific and general teacher-child interaction perspectives. Early Educ. Dev. 31, 599–627. doi: 10.1080/10409289.2019.1680785

Wiggins, A. K., MarshaLL, K. A., and FrieL, S. A. (2007). Assessing classroom language and literacy richness: assessment in emergent literacy . New York, NY: Plural Publishing.

Xu, D., Yapanel, U., and Gray, S. (2009). Reliability of the LENA language environment analysis system in young children’s natural home environment . Boulder, CO: Lena Foundation.

Zaslow, M., Tout, K., Halle, T., and Forry, N. (2009). Multiple purposes for measuring quality in early childhood settings: implications for collecting and communicating information on quality . Washington, DC: Issue Brief.

Zweig, J., Irwin, C. W., Kook, J. F., and Cox, J. (2015). Data collection and use in early childhood education programs: Evidence from the northeast region (REL 2015–084) . Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Northeast and Islands. Available at: http://ies.ed.gov/ncee/edlabs .

Keywords: language development, early childhood education, assessments, instructional practices, quality

Citation: Finders J, Wilson E and Duncan R (2023) Early childhood education language environments: considerations for research and practice. Front. Psychol . 14:1202819. doi: 10.3389/fpsyg.2023.1202819

Received: 18 April 2023; Accepted: 06 September 2023; Published: 22 September 2023.

Reviewed by:

Copyright © 2023 Finders, Wilson and Duncan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jennifer Finders, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Early Childhood Language Development

Early childhood is an age where children are learning at a rapid pace! In the blink of an eye our children go from infants in need of support with nearly everything, to preschoolers with their own sense of autonomy and independence. There are many areas of development happening with our young children from gross motor skills to speech and language. When entering kindergarten, many parents are unsure of where their children should be with various aspects of development and when to seek additional support. When a child is having difficulty with gross motor skills, it may be seemingly easier for a parent to identify the need for support. However, in areas of speech and language many parents have identified that the need for support can be harder to recognize.

Our UNH Extension team interviewed a Speech Language Pathologist who specializes in early childhood to answer the questions many parents have been asking. Emily Leavitt Creteau, who is licensed in Maine and holds a Certificate of Clinical Competence from the American Speech, Language, and Hearing Association, provides services to students with a variety of needs related to speech, language development and literacy.

A: This is such a tough question because there is such a wide range of "normal." I always like to encourage parents to trust their feelings and seek a professional to talk to if they have concerns. Some language and literacy skills that your 4- 5-year-old should be developing prior to entering kindergarten include:

• Asking and answering questions that start with "who", "what", "when", "where", and "why"
• Following directions with concepts like "on", "under", "in", and "out"
• Pointing and labeling body parts
• Counting groups of objects up to 10
• Talking in full sentences
• Using speech that can be understood at least 75% of the time
• Telling or telling back stories
• Recognizing their name in print
• Pretending to read books or following along while you read to them
• Knowing and reciting nursery rhymes or singing songs with rhymes

A: By kindergarten children should be speaking in complete sentences and be understood at least 75% of the time. They can tell stories about themselves and events in their day as well as tell back stories they have been told. At this age children should use language for lots of uses including to describe things, ask questions, answer questions, share their emotions, and tell where things are. We would expect to be able to have a conversation that lasts a couple of back-and-forth turns at this age as well.

A: Any sequence of sounds that the child is using as a label consistently, independently, and in a meaningful way counts as a word. For example, if a child says "choo choo" every time they see a train that would count as a word. Words children use like "uh no!", "wwweeeee!", and "yuck" also count as words if they are used spontaneously.

A: Baby talk is great to use with babies and young toddlers. By the time your child is reaching preschool age however, you want to use more natural adult talk. This helps your child develop more complex language skills in order to understand and use longer sentences.

A: The answers to both of these is a definitive "NO!" This has been a longstanding myth in our country but research has fully supported that learning another language (spoken or signed) does not delay their language development. Some research shows it to even be very beneficial.

A: By kindergarten children should be articulating, or correctly pronouncing, most sounds accurately and be understood at least 75% of the time by people who aren't very familiar with the child. The latest developing sounds are S, R, L, and Th. These should be mastered by age 6, however, so if those errors persist you can talk to your pediatrician or speech language pathologist.

A: While language skills are developing, errors with pronouns and verbs are fairly common. By the time children are entering kindergarten these errors should be limited though. If you notice pronouns are tricky for your child, you can do a couple of things. Using gestures is an effective method for emphasizing pronouns. Direct attention to yourself while saying "I" or "my" by pointing to your chest. Assist your child in patting their chest to indicate "me" or "my." When observing others, point and talk about their actions. You can also help by demonstrating correct pronoun usage in your speech. While talking with infants, it's common to say things like "Mommy will get it" however, once your child starts speaking, try to use pronouns accurately and say "I will get it." Photos of your child and family as well as books serve as valuable resources for teaching pronouns. You can narrate the actions of others, emphasizing pronouns along the way. Similar strategies to these can be used if your child is having trouble with verb tenses, saying "I hided the egg" instead of "I hid the egg." These types of errors should again be pretty infrequent by the time the child is kindergarten age.

A: This could be an example of developmental stuttering which is present in as many as 90% of children as their speech and language skills are rapidly developing. You might notice your child adding a sound or word like "ummm", repeating words or phrases, changing words in a sentence, not finishing a thought, repeating parts of words, dragging out sounds (SSSSSStop please), or pausing in the middle of a sentence. This type of dysfluency can last up to 6 months. If it lasts longer than that you should speak to your pediatrician or speech language pathologist.

• A: Read out loud daily or listen to audiobooks together in the car. Pause and ask your kids questions during reading. Narrate your thoughts about the book at times; for example, "Oh no! Jack fell down the hill, I wonder if he is OK!." Talk about the character's feelings and make predictions as well.
• A: Let your children see you reading. Fifty-seven percent of kids who are frequent readers have parents who read books 5-7 days a week compared to only 15% of kids whose parents are infrequent readers.
• A: So many language and literacy skills can be learned through fun activities like singing and playing games. "I spy" is such a great one to play in the car, it's a boredom buster and can develop skills like listening, rhyming, and talking. You could play around with rhyming words this way, "I see something that rhymes with word" (bird), letter sounds, "I see something that starts with /k/" (car), or concepts like colors, "I see something blue." One of my favorite songs to sing with children round age 4 or 5 is "Down By the Bay" because it targets rhyming skills and is super silly.

A: There are so many! Some of my favorite songs and nursery rhymes are:

• Down by the Bay
• Wheels on the Bus
• Old MacDonald Had a Farm
• Head, Shoulders, Knees and Toes
• If You're Happy and You Know It
• 5 Little Monkeys
• Ten in the Bed

A: Talking to your pediatrician is a great place to start. It is often helpful to write down your observations and concerns prior to the meeting so you don't get flustered or feel rushed. Pediatricians know of so many resources in the community such as early childhood educators,  speech language pathologists, occupational therapists etc. that they can refer you to. Reaching out to the early intervention program in your state is also a step you could take if you are concerned about your child's kindergarten readiness.

You can learn more about speech and language development milestones here:

https://www.nidcd.nih.gov/health/speech-and-language

You can find local family centered and early supports in this directory:

https://nhfv.org/resources/nhdhhs-family-centered-early-supports-and-services/

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The Gesell Program in Early Childhood

2024 - Gesell: Who We Are

Gesell: Watch to Learn More

Can you conduct a reliable child assessment, remotely?

Going forward (not back) to school, gesell remembers dr. edward zigler, investment in the early years helps in the long-run, nurturing security in uncertain times, learning to play, playing to learn.

• Insights & Impact

Spotlight on New Early Childhood Resources, Trainings, Insights, and Research

Posted on 04.23.2024

The resources in this Spotlight focus on early childhood interventions and education, with a new tool to help early childhood professionals self-assess group care programs, an insider’s Q&A with an early childhood intervention specialist, and practical advice on programs and practices that encourage early literacy.

New Tool Guides Early Childhood Professionals Through Care Program Self-Evaluations

PITC PARS simplifies the difficult process of assessment by grouping its standards for promoting children’s learning, development, health, and well-being into quality indicators in five different areas:

• quality of adult interactions with children
• family partnerships, cultural responsiveness, and inclusive care
• organization of group care
• physical environment
• routines and record keeping

Practitioners are guided through the process of collecting evidence of their performance in each area and then evaluating how that evidence contributes to the total picture of care quality.

Improving Outcomes for Children with Early Interventions: Q&A with Angela McGuire

In this Q&A with Angela McGuire, CEITAN’s lead on early intervention professional development; technical assistance; and consulting for national, state, and local agencies serving children with disabilities and their families (and a parent of a child with disabilities), she speaks on the benefits of enrolling parents into intervention services, CEITAN’s contributions to the field, and current challenges.

Early Literacy Resources: Teaching Young Children to Read and Write 

• Joyful Literacy Practices in Early Childhood Settings
• Research-Based Early Literacy Resources
• Early Literacy: The Teaching and Learning Cycle

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Stay informed about WestEd’s research, resources, services, events, and career opportunities by  subscribing to our E-Bulletin. Our April 2024, Volume 2 issue examines research and shares resources for early childhood educators and education leaders. The issue features the following:

• New Resource to Support High-Quality Care for Children Ages 0–3
• Become a Program for Infant/Toddler Care (PITC) Certified Trainer
• Caring for Infants and Toddlers in Group Settings
• Improving Outcomes for Young Children With Disabilities
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• Supporting Young Children Through Stress and Trauma
• Pre-Referral Processes for Multilingual Children in Preschool
• Moving Toward High-Quality PreK Systems for All

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Learn about and buy PITC PARS, a tool for observing, documenting, and reflecting on the essential aspects of infant/toddler group care—from caregiving interactions to the ...

Leading Voices Podcast Series Episode 11: The Critical Role of Early Intervention—A Conversation With Angela McGuire

In this episode of the Leading Voices podcast, host Danny Torres talks with Project Director Angela McGuire about the critical role of early intervention in improving outcomes ...

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Understanding Child Outcomes from Early to Middle Childhood

• January 8, 2024

In This Post

A follow-up study.

Involving approximately 1,500 children across 80 local kindergartens and childcare centers, the Singapore Kindergarten Impact Project (SKIP) tracked the development of the children from the start of Kindergarten 1 to the start of Primary 1.

“The study found that the strongest predictors of outcomes in a child’s early development were the child’s starting competency level in areas such as English literacy, socioemotional skills and executive functioning; socioeconomic status (SES); and non-verbal intelligence,” says Dr Fannie Khng, also Assistant Dean of Research Management at Office of Education Research (OER).

A follow-up study, named “SKIP-Up” for short, was launched to continue exploring the long-term effects of early childhood skills attainment as well as the roles home and school environments play in a child’s development as they grow into middle childhood.

Skills Attainment during Childhood

SKIP-Up examines both early and concurrent predictors of skills and well-being outcomes important for children as they exit middle childhood. The study involves a subset of the same group of children as SKIP, and additionally, some of these children’s classmates in Primary 5 or 6. The study investigates childhood outcomes such as academic skills, executive functioning and self-regulation as well as attributes such as mindset, resilience and school engagement. “The attributes and skills children have developed near the end of primary school will be important for their next phase in development,” she emphasizes.

Preliminary findings show that early childhood executive functioning and fine motor skills continue to directly (and indirectly) predict late primary school math and reading fluency. “Furthermore, a child who exhibits executive functioning difficulties in school during early childhood is more likely to experience similar difficulties during upper primary school,” Fannie shares. She adds that the study is still in progress and more comprehensive findings are anticipated in the near future.

Classroom and Home Environments

SKIP-Up also seeks to examine potential moderators within the child or the child’s environment – such as child environmental sensitivity, intervening activities/experiences, and classroom climate – that may influence outcomes.

Fannie notes that the earlier SKIP study had found negligible impact of classroom quality on early childhood outcomes. However, there have been studies conducted in Europe that found process quality at preschools to have small but lasting effects on children’s language literacy and math outcomes in primary school.

“Given the negligible impact of classroom quality on early child outcomes found in SKIP, SKIP-Up will seek to examine whether the quality of early childhood education classrooms in Singapore contribute towards children’s longer-term development,” she shares.

SKIP also found that familial SES was an important predictor of preschoolers’ executive functioning, numeracy, and language and literacy skills.

“More research should be done on the longer-term impact of the early home environment, as well as the continuing influence of home factors” Fannie says. “Of interest is whether SES, like the early competencies, continue to be influential predictors of outcomes at middle childhood, and if the predictive links can be moderated by other intervening processes and contexts.”

Another direction the study is taking is investigating children found to be at-risk of poor outcomes.

“Investigations will also be focused on the later development of children found in early childhood to be at-risk of poor outcomes, as well as the early predictors of children later found to be at-risk in middle childhood,” she explains.

The study will also look closely at the link between SES and socioemotional well-being that becomes more apparent in middle childhood, especially in terms of externalizing problems such as behavioural regulation, and internalizing problems such as depression.

“SKIP-Up will seek to examine whether the quality of early childhood education classrooms in Singapore contribute towards children’s longer-term development.” –  Fannie ,  on the aims of the study

Optimizing Children’s Outcomes

Fannie acknowledges that there is currently limited knowledge on the delayed effects of early childhood factors, such as quality of preschool classrooms. Lack of research into these areas can underestimate implications for policy and practice regarding early childhood education.

“Understanding the longer-term effects will better inform practice and policy, for instance, on teacher training, as teachers can be trained to provide greater classroom support in various domains”, she remarks.

SKIP-Up will also allow school leaders and teachers to have a better understanding of the effectiveness of the different intervention programmes available for learners.

“Understanding if participating in activities or interventions – including school-based programmes – moderates the link between early childhood competencies and later competencies can inform the design and provision of supportive activities for children, especially those with disadvantaged backgrounds or starting states, to enhance their outcomes,” she attests.

This study was funded by Singapore Ministry of Education (MOE) under the Education Research Funding Programme and administered by National Institute of Education (NIE), Nanyang Technological University, Singapore. Any opinions, findings and conclusions or recommendations expressed in this site are those of the author(s) and do not necessarily reflect the views of the Singapore MOE and NIE.

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Translational research on early language development: Current challenges and future directions

Marjorie beeghly.

Harvard Medical School and Children’s Hospital, Boston

There is a pressing need for the early and accurate identification of young children at risk for language and other developmental disabilities and the provision of timely, age-appropriate intervention, as mandated by Part C of the Individuals with Disabilities Education Act. Research has shown that early intervention is effective for many language impaired children in different etiological groups, and can reduce the functional impact of persistent disorders on children and their families. Yet, the accurate identification of infants and toddlers at risk for language impairment remains elusive, especially for late-talking children without obvious genetic or neurological conditions. In this paper, the need for translational research on basic processes in early language development in typical and atypical populations and the contextual factors that affect them are discussed, along with current challenges and future directions for its successful implementation. Implications of this research for clinical evidence-based practice are also considered.

Of the 12–16% of American children with neurodevelopmental or behavioral disorders ( American Academy of Pediatrics Committee on Children with Disabilities, 2001 ), a majority has delayed or deviant language ( Feldman, 2005 ; Grizzle & Simms, 2005 ). This is especially the case when disorders result from genetic or chromosomal abnormalities such as Down syndrome ( Abbeduto & Murphy, 2004 ; Chapman & Hesketh, 2001 ), fragile X syndrome ( Abbeduto & Hagerman, 1997 ; Dykens, Hodapp, & Finucane, 2000 ), or Williams syndrome ( Bellugi, Wang, & Jernigan, 1994 ; Karmiloff-Smith & Thomas, 2003 ), or from complex syndromes such the autism spectrum disorders ( Happe & Frith, 1996 ; Lord & Paul, 1997 ). Although these disorders are fairly rare, prevalence estimates for preschool-aged children with language impairment with no known genetic etiology and normal nonverbal intelligence (e.g., specific language impairment)are substantially higher, ranging between 2 and 8% (median 5.95%; Feldman, 2005 ). A sizable percentage of late-talking preschoolers with normal nonverbal intelligence will continue to manifest language problems in later childhood ( Grizzle & Simms, 2005 ; Paul, 1996 ), augmenting clinical concerns for this group of children.

Given that language and speech problems are associated with academic, socioemotional, and psychiatric problems ( Catts, 1993 ; Cohen, Davine, Horodezky, Lipsett, & Isaacson, 1993 ; Rice, Hadley, & Alexander, 1993 ), there is a pressing need for early and accurate identification of young children with emergent language problems and the provision of age-appropriate intervention. Moreover, Part C of the Individuals with Disabilities Education Act mandates the early identification and provision of intervention for infants and toddlers with developmental disabilities (birth to age 2)through the development of community-based systems. Studies have shown that early intervention is effective for many language impaired children in different etiological groups ( Guralnick, 1997 ; Leonard, 1998 ; Ramey, Campbell, & Ramey, 1999 ), and can reduce the functional impact of persistent disorders on children and their families. Improvements in sociocommunicative skills are especially well documented.

Unfortunately, accurate detection of true developmental delays or deviations in early childhood remains elusive, especially for late-talking children without obvious genetic or neurological conditions ( Dale, Price, Bishop, & Plomin, 2003 ). This is likely due to the wide range of normal variability in the early stages of typical language development ( Bates, Bretherton, & Snyder, 1988 ; Fenson et al., 1994 ; Goldfield & Snow, 2005 ; Shore, 1995 ) and the fact that many toddlers with delayed language development and normal cognitive and motor development function within normal limits on language assessments by school age ( Leonard, 1998 ; Rescorla, 2002 ). Moreover, children’s early language development in both typical and atypical populations is a dynamic process that is affected by a complex array of transacting factors from multiple levels of influence, such as genetics, gender, temperament, the child’s own skills in other developmental domains (cognitive, motor, socioemotional), and a host of biological and social risk and resilience factors, for example, premature birth, prenatal exposure to substances, parental education, caregiver interactive style, parent–child mutual regulation, bilingualism, and other cultural influences ( Bates, 2003 ; Bates, Bretherton, Beeghly, & McNew, 1982 ; Beeghly, 1997 ; Beeghly & Cicchetti, 1994 ; Cicchetti, 1984 ; Elman et al., 1996 ; Landry, Smith, Miller-Loncar, & Swank, 1997 ; Luthar, Cicchetti, & Becker, 2000 ; Sameroff & Fiese, 1990 ; Spiker, Boyce, & Boyce, 2002 ; Thorpe, Rutter, & Greenwood, 2003 ). This complexity has made it difficult for clinicians to pinpoint the exact nature of the presenting problem and to make unequivocal diagnoses of clinically significant language impairments, especially when children are younger than 3 or 4 years of age ( Leonard, 1998 ; Thal & Katich, 1996 ; Thal, Reilly, Seibert, Jeffries, & Fenson, 2004 ).

Need for Translational Research on Early Language Development

Thus, there is a pressing clinical need for accurate, detailed information on multiple aspects of early typical and atypical language functioning and the diverse cognitive, behavioral, and contextual factors that affect them. In response, the NIH has recently called for collaborative translational (“bench to bedside”) research on basic developmental processes in both typical and atypical populations to better inform and guide clinical practice with children with developmental disorders, including language impairment, and to encourage basic behavioral scientists to seek a further understanding of how behavioral processes (such as language)are altered by developmental disorders. Until recently, however, advancement in collaborative translational language research has been hampered by fragmentation among multidisciplinary fields, related funding constraints, and poor communication among investigators from different disciplines ( McCardle, Cooper, & Freund, 2005 ; Nelson et al., 2002 ; Rice & Warren, 2005b ).

Most extant research on early language acquisition in children with language disorders has focused on a narrow range of language behaviors (e.g., vocabulary or morphosyntax) within one specific clinical group (e.g., Down syndrome, autism, or specific language impairment), describing single deficits relative to various control groups or evaluating within-group profiles of specific linguistic and cognitive skills within a particular group ( Rice & Warren, 2005a ; Rice, Warren, & Betz, 2005 ). Despite this limited focus, this research has provided a wealth of valuable information about the nature and process of those particular aspects of language development in specific populations. Results of profile analyses within different populations have been especially helpful in debunking stereotypes about different etiologic groups and have highlighted methodological caveats for future research, including the need for longitudinal research and the continued need to evaluate multiple dimensions of language (e.g., vocabulary/semantics, grammar/syntax, and pragmatics) in diverse groups. This research has also fueled and sparked continuing debates among researchers regarding the age-old philosophical question of the ontogenetic association between language and cognition (e.g., Elman et al., 1996 ; Karmiloff-Smith & Thomas, 2003 ; Thelen & Bates, 2003 ).

For illustrative purposes, a brief summary of some of the key research findings for four clinical groups of children with delayed or disordered language development that have been investigated intensively (Down syndrome, autism spectrum disorders, Williams syndrome, and specific language impairment) is provided here. This summary is not meant to be exhaustive.

Down syndrome

With a prevalence of approximately 1 in 700 to 1,000, Down syndrome is the most common genetic cause of mental retardation ( Rozien, 1997 ). Children with Down syndrome have been of particular interest to language development researchers because Down syndrome is etiologically distinct and can be identified and studied very early in life. As is true for children with other genetic disorders, children with Down syndrome manifest a unique profile of linguistic, cognitive, affective-motivational, and social abilities in early childhood. Although developmentally delayed, children with Down syndrome vary in the level of their general cognitive functioning from severely retarded to nearly normal ( Chapman & Hesketh, 2001 ). Their delayed yet variable development allows for a more precise examination of the sequences of various aspects of their language and nonverbal development than is possible with typical children with more rapid development ( Cicchetti & Beeghly, 1990 ).

Evidence for both delayed and deviant aspects of early language and nonverbal cognitive development has been reported for children with Down syndrome ( Abbeduto & Murphy, 2004 ; Beeghly, Weiss-Perry, & Cicchetti, 1990 ; Chapman & Hesketh, 2001 ; Fowler, 1990 ; Miller, 1990 ). With increasing age, young children with Down syndrome exhibit increasing linguistic deficits in relation to their nonverbal cognitive abilities ( Chapman, 2003 ; Chapman & Hesketh, 2001 ), including pretend play ( Beeghly, 1997 ; Beeghly, Perry, & Cicchetti, 1989 ; Cielinski, Vaughn, Seifer, & Contreras, 1995 ). However, production delays tend to exceed comprehension delays, and syntactic skills are more severely compromised than lexical or pragmatic abilities ( Beeghly et al., 1990 ; Fowler, 1990 ; Miller, 1990 ). Fowler (1990) has reported that many children with Down syndrome do not progress beyond the early stages of morphological and syntactic development. Strengths and weaknesses have also been reported for cognitive skills associated with language functioning. For instance, children with Down syndrome exhibit deficits in auditory short-term memory relative to visual short-term memory and other cognitive skills ( Chapman, 2003 ).

Of note, specific results for particular domains of functioning within language often vary among studies, depending on the age of the children being evaluated and the specific assessment contexts and dependent measures used. For instance, in an observational study of children with Down syndrome interacting with their mothers during semistructured and unstructured play contexts, children with Down syndrome exhibited pragmatic skills (diversity of speech acts, turn taking skills, connected discourse) that were consistent with their general cognitive abilities ( Beeghly & Cicchetti, 1997 ). In contrast, in an experimental study using a variety of elicitation prompts and dependent measures, children with Down syndrome exhibited both strengths and weaknesses in pragmatic skills ( Abbeduto & Murphy, 2004 ), raising methodological caveats for future studies.

Autism and pervasive developmental disorders

Despite the relatively low incidence of autism (approximately 4–10 cases in every 10,000 live births; Happe, 1995 ), the early language and cognitive development of children with autism and related disorders has been intensively studied during the past 2 decades (see reviews by Baron-Cohen, 1995 ; Cicchetti, Beeghly, & Weiss-Perry, 1994 ; Lord & Paul, 1997 ; Mundy, Sigman, & Kasari, 1990 ; Sigman, 1994 ). Children with autism exhibit a triad of severe impairments, including language/communicative deficits, social cognitive (theory of mind) difficulties, and social behavioral differences ( American Psychiatric Association, 1994 ), as well as wide individual differences in functioning ( Dawson & Castelloe, 1992 ; Lord, Risi, & Pickles, 2004 ).

In prior reviews, investigators estimated that approximately half of children with autism were nonverbal (see Lord & Rutter, 1994 ). However, this estimate appears to be changing, perhaps due to the broader diagnostic criteria currently used for autism and the increasing prevalence of autistic disorders ( Newschaffer, Falb, & Gurney, 2005 ). For instance, in a recent analysis using combined data from several different studies, Lord and colleagues ( Lord et al., 2004 ) estimated that, by age 9, 14–20% of children with autism had no consistent words, 10–14% had “words but not three-word phrases,” 23–35% had “phrases but not fluent,” and 41– 43% had fluent language.

Delays and differences in particular aspects of language have been reported for children with autistic spectrum disorders. Generally speaking, pragmatic skills (e.g., discourse processes, communicating intended meaning to others)are more severely compromised than lexical or syntactic skills ( Lord & Paul, 1997 ), but delays in the latter aspects of language are also present. Tager-Flusberg (2004a) has recently hypothesized that there may be a subgroup of children with autism who exhibit deficits in morphosyntactic skills that are similar to those observed in children with specific language impairment ( Tager-Flusberg, 2004a ). In addition to language deficits, many children with autism exhibit comorbid difficulties in working memory and executive functions such as planning, sequencing, and set shifting, which could interfere with their language and sociocommunicative performance ( Happe & Frith, 1996 ; Joseph, 1999 ).

Although less well studied, an uneven profile of emergent language and nonverbal communicative skills has also been reported for young children with autism spectrum disorder. In a study of toddlers and preschoolers with autism spectrum disorder using the Mac-Arthur Communicative Development Inventory—Infant Form (CDI; Charman, Drew, Baird, & Baird, 2003 ), children with autism exhibited significant delays in language and gestural communication, relative to typically developing children. However, word comprehension was delayed relative to word production, and the production of early gestures involving shared reference was delayed relative to the production of late gestures involving actions with objects. Considerable variability in language acquisition was also observed, which is consistent with the typical pattern ( Fenson et al., 1994 ).

Others have reported that young children with autism consistently have impairments on early nonverbal symbolic skills that are thought to be precursors and correlates of later language development and theory of mind, that is, joint attention skills, imitation, and pretend play ( Baron-Cohen, 1987 ; Charman, 1997 ; Charman et al., 2000 ; Mundy, Sigman, & Kasari, 1994 ; Phillips, Baron-Cohen, & Rutter, 1992 ; Roeyers, VanOost, & Bothuyne, 1998 ; Yirmiya, Pilowsky, Solomonica-Levy, & Shulman, 1999 ). For instance, in a study of nonverbal communication in young children with autism and children with developmental delays or language impairments using a battery of structured communication tasks ( Stone, Ousley, Yoder, Hogan, & Hepburn, 1997 ), children with autism requested more often but commented less often than the comparison children. Consistent with other research ( Mundy, Sigman, & Kasari, 1993 ), children with autism were less likely to point, show objects, or use eye gaze to communicate, but were more likely to directly manipulate the experimenter’s hand. The autistic group also used less complex combinations of behaviors to communicate. Of note, other research has shown that these nonverbal communicative differences cannot be explained solely by the presence of motor deficits, attention problems, or low sociability ( Phillips et al., 1992 ).

Williams syndrome

Williams syndrome is a rare genetic disorder (incidence between 1/10,000 and 1/20,000 live births) that is caused by a microdeletion of about 20 genes on chromosome 7q11.23 and associated with a highly unusual neuropsychological profile ( Karmiloff-Smith & Thomas, 2003 ; Mervis, 2003 ; Morris, 2004 ). Despite moderate mental retardation (average IQ scores range from 50 to 70), individuals with this disorder have surprisingly complex language skills ( Bellugi et al., 1994 ; Singer, Bellugi, Bates, Jones, & Rossen, 1994 ) and tend to be quite affectively expressive and socially attuned ( Reilly, Klima, & Bellugi, 1991 ). At the same time, these persons have profound deficits in their fine motor and visual–spatial cognitive functioning, which exceed the level of their general cognitive impairment ( Bellugi et al., 1994 ). Some investigators in early studies of this disorder have claimed that the marked language/cognition dissociations observed in individuals with Williams syndrome provide strong support for a “modularity” hypothesis regarding the relationship between language and cognition in ontogeny. However, recent studies evaluating a greater variety of language and cognitive measures at diverse ages have indicated a more complex relationship ( Bates, 2003 ; Karmiloff-Smith & Thomas, 2003 ; Mervis, 2003 ).

Evidence for both delayed and deviant aspects of language has been reported for school-aged children with Williams syndrome. For instance, Robinson, Mervis, and Robinson (2003) reported that 10-year-olds with Williams syndrome relied on their working memory to a greater extent than grammar-matched typical children during language tasks, even when differences in receptive vocabulary skills were covaried. This finding suggests a deviant pattern of language development (see also Karmiloff-Smith & Thomas, 2003 ). However, other research has provided evidence for a delayed pattern of language production. For instance, Zukowski (2004) reported that the errors made by children with autism when producing sentences containing relative clauses and negative questions were similar to those made by typically developing children at younger ages ( Zukowski, 2004 ). Further research evaluating multiple aspects of language in this population is needed to resolve these apparent inconsistencies.

Although understudied, it appears that young children with Williams syndrome also exhibit delays and differences in early language acquisition, when compared to typical children or children in other clinical groups. However, specific results vary. It is generally agreed that children with Williams syndrome are delayed in the onset of their first words and first word combinations, relative to age-matched typical children. Once productive vocabulary emerges, however, toddlers with Williams syndrome have higher expressive vocabularies than age-matched toddlers with Down syndrome, as measured using the MacArthur CDI ( Mervis & Robinson, 2000 ), a pattern consistent with their relative strengths in lexical development later in ontogeny.

A somewhat different pattern of findings was reported for young children with Williams syndrome in another cross-population comparison study using the MacArthur CDI ( Singer et al., 1994 ). In that study, the early language and nonverbal communicative skills of children with William syndrome were compared to those of children with Down syndrome (average chronological age = 12–76 months). Consistent with other research, children in both groups were significantly delayed in the onset of first productive words, relative to typically developing children. However, when children were classified by level of expressive vocabulary (<50 vs. ≥50 words), differences in nonverbal communicative and grammatical skills emerged. Among children producing fewer than 50 words, children with Williams syndrome produced significantly fewer communicative and pretend gestures (e.g., intentional communicative gestures such as pointing and pretend/referential gestures such as holding a phone to the ear) than children with Down syndrome. In contrast, among children producing 50 words or more, children with Williams syndrome showed significant advances in grammatical development relative to the children with Down syndrome.

In a series of studies on the nonverbal communicative precursors to language, Laing et al. (2002) found that preschoolers with Williams syndrome were impaired in triadic communicative processes, which have been linked with the referential uses of language in typical development (see also Mervis et al., 2003 ). Despite higher levels of expressive vocabulary, children with Williams syndrome also exhibited dissociations between comprehension and the production of referential pointing, which could not be explained solely by motor impairment. These findings suggest that the course of early language acquisition for children with Williams syndrome may follow an atypical pathway, which challenges prior claims that children with Williams syndrome have preserved linguistic and social skills ( Laing et al., 2002 ).

Taken together, these findings from studies of early language development in different clinical groups raise several methodological caveats. Investigators in future cross-population studies of language acquisition in young children with language disorders should control for both level of language development and chronological age, and evaluate multiple aspects of language and nonverbal communicative behavior. Moreover, longitudinal studies of the complex, dynamic interplay between different aspects of language and nonverbal communicative skills would be especially helpful to clarify discrepant findings among studies.

Specific language impairment

By definition, children with specific language impairment perform below age expectations on standardized language measures but within normal limits on measures of nonverbal intelligence, and have no hearing loss or known genetic or neurological disorders. Thus, in contrast to the other populations described above, language impairment is the defining feature of this condition ( Leonard, 1998 ). The prevalence of preschool-aged children with specific language impairment ranges from 2 to 8% (median 5.95%), with a higher prevalence among boys, children with a family history of language, speech, or reading disorders, children born prematurely, and children from families with low socioeconomic status (SES; Feldman, 2005 ; Law, Boyle, Harris, Harkness, & Nye, 2000 ; Tomblin, Smith, & Zhang, 1997 ). About a quarter to one-half of language delayed preschoolers with normal nonverbal intelligence will continue to manifest language problems in later childhood ( Grizzle & Simms, 2005 ; Paul, 1996 ).

Despite much research, many questions remain concerning the causes and characteristics of specific language impairment. As is the case with other language disorders, considerable attention has been given to evaluating whether the language deficits observed in this group are delayed or deviant compared to typical children ( Rice & Warren, 2005b ; Wulfeck, Bates, Krupa-Kwiatkowski, & Saltzman, 2004 ). This research has shown that, although multiple aspects of their spoken language are delayed, relative to that observed in age peers, children with specific language impairment appear to have particular difficulty with phonological processing (measured by nonword repetition tasks; Conti-Ramsden, Botting, & Faragher, 2001 ) and specific morphosyntactic features of language (i.e., morphemes that denote grammatical finiteness of a sentence, such as third person singular “–s,” past tense “–ed,” irregular past tense forms, copula “be,” and auxiliary “be” and “do”; Rice et al., 2005 ; Rice, Wexler, Marquis, & Hershberger, 2000 ). That is, children with specific language impairment perform below both age-matched and language-matched peers on these measures, suggesting a deviant pattern of these aspects of linguistic growth ( Leonard, 1998 ; Tager-Flusberg, 2004a ; Wulfeck et al., 2004 ). In contrast, their receptive vocabulary skills and mean length of utterance in morphemes appear to be consistent with that observed in language-matched peers, suggesting a delayed rather than deviant pattern of lexical and general syntactic development ( Rice, 2004 ). However, other research has shown that a subset of children with specific language impairment exhibit a relatively high level of pragmatically inappropriate responses to conversational solicitations that cannot be explained by limited grammar or vocabulary ( Bishop, Chan, Adams, Hartley, & Weir, 2000 ), indicating that specific language impairment is a heterogeneous group.

How specific language impairment manifests during infancy and toddlerhood is unclear. When “late talkers” are followed from early to later childhood, half to three-quarters score in the normal range on language development tests ( Paul, 1996 ; Rescorla, 2002 ), and the others continue to exhibit delayed expressive language development in later childhood (and often develop reading and learning problems). It is unclear what specific factors may underlie such diverse outcomes. Given that specific language impairment is associated with male gender and tends to run in families ( Leonard, 1998 ), genetic etiological factors are likely; however, the specific genetic factors associated with this disorder have not yet been identified ( Rice, 2004 ).

Given the heterogeneity of outcome this group, researchers and clinicians are beginning to reevaluate current diagnostic criteria in this group. For instance, a growing number of studies has reported that children in this group exhibit below-age level performance on specific nonlinguistic skills such as processing capacity and the ability to encode temporal characteristics of auditory stimuli ( Bishop, 1994 ; Tallal, Merzenich, Miller, & Jenkins, 1998 ). This indicates that general omnibus measures of nonverbal intelligence may not be adequate for diagnostic purposes for these children, and suggests avenues for future research in this population ( Rice, 2004 ).

Cross-Population Studies

Given the momentum in genetic and biobehavioral investigations within particular language disorders during the past decade, Rice and colleagues have recently heralded the need for further collaborative cross-population research to document the ways in which language disorders are manifest across clinical conditions (see Rice et al., 2005 ; Rice & Warren, 2004 ). Such research could lead to a deeper understanding of the commonalities and differences across conditions, the specific symptom profiles associated with each condition, and how general intellectual impairment with a specific genetic basis may affect the process of language acquisition in multiple domains. Cross-population comparisons would also facilitate the identification of subtypes of disability within diverse clinical conditions and enhance our ability to identify early in development young children who are likely to develop clinically significant language-learning problems ( Reilly, Losh, Bellugi, & Wulfeck, 2004 ; Thal et al., 2004 ). In turn, the documentation of subtypes and the specific contextual factors associated with individual differences within conditions would augment our understanding of the different levels of risk that may predispose very young children in different groups for persistent language impairment. More generally, such research would contribute to our understanding of the nature and variability possible in human language development and would enhance our understanding of the brain bases of language and language development ( Rice & Warren, 2004 ; Thal et al., 2004 ).

Although cross-population studies of language disorders are relatively rare to date, those that exist have raised some important questions and offered a few surprises. For instance, in a series of comparative studies conducted by a multidisciplinary group of collaborators in San Diego, aspects of children’s language processing and acquisition were evaluated across several clinical populations at different ages. The clinical groups included “late-talking” toddlers, children with early focal brain injuries in either the right or left hemisphere (similar to those observed in adult aphasia patients), children with Williams syndrome, children with Down syndrome, and school-aged children with a diagnosis of specific language impairment, as well as appropriate typically developing controls ( Bates, 2003 ).

For instance, in a longitudinal study comparing the lexical and syntactic development of late-talking toddlers, children with early focal brain injury, and typically developing children from 2 to 3 years of age ( Thal et al., 2004 ), a number of interesting findings were reported. First, children in both at-risk groups exhibited significant delays in both vocabulary and grammatical development at both ages, and exhibited greater variability in language functioning than typical children (see also Kennedy, Sheridan, Radlinsky, & Beeghly, 1991 ). Second, different longitudinal associations between language comprehension and syntactic development were observed in each group, suggesting that different language skills may be organized differently in specific clinical groups. Third, qualitative analyses indicated that the at-risk groups produced the same kinds of errors (despite relative delays). However, the late talkers produced a substantially greater proportion of errors in obligatory contexts than did children with early focal brain injury, a pattern consistent with that observed in older children with specific language impairment.

In several other studies from the San Diego collaborative group, the linguistic and pragmatic skills of school-aged children in different clinical groups were compared ( Marchman, Saccuman, & Wulfeck, 2003 ; Reilly et al., 2004 ; Weckerly, Wulfeck, & Reilly, 2003 ; Wulfeck et al., 2004 ). Results showed that, by school age, children with early focal brain injury performed in the normal range on most language measures, regardless of lesion size or location, and outperformed children with specific language impairment. These findings shed light on the extent and nature of brain plasticity and recovery for language functioning in these groups. In addition, contrary to expectations, specific morphosyntactic measures of the children with specific language impairment with no frank neurological impairment clustered with those of the children with Williams syndrome, who were moderately retarded. Moreover, the performance of children with Williams syndrome on these language tasks was solidly linked to mental age (and often resembled that of children with specific language impairment), suggesting that children with Williams syndrome are not “language savants,” at least for the measures evaluated in these studies, as several investigators in early studies have claimed ( Bates, 2003 ). Reilly et al.’s (2004) results also highlight aspects of language and discourse that may be dissociable.

Contrasting results regarding the morphosyntactic development of children with Williams syndrome have been reported by other researchers ( Clahsen & Almazan, 1998 ), which may reflect, in part, methodological differences across studies. For instance, Rice and others reported that 7-year-olds with Williams syndrome performed at near ceiling level in an elicited production task of finiteness morphemes, in contrast to the lower performance of language-matched children with specific language impairment and typical children ( Rice, 2003 ).

In another series of cross-population studies, Tager-Flusberg and colleagues (see Tager-Flusberg, 2004a , for a review) demonstrated that a subgroup of children with autism with language impairment and language-matched children with specific language impairment exhibited a strikingly similar pattern of language skills. Children in both groups exhibited similarly poor performance and error patterns on tasks of nonword repetition and finite-verb morphology, suggesting that these children may share similar deficits in phonological processing and morphosyntactic knowledge. At the same time, children in both groups exhibited a relative sparing of articulation skills and verbal fluency. Interestingly, neuropathological findings in these groups are consistent with these language findings, suggesting the possibility of a common genetic etiological pathway to language disorder in the two groups ( Tager-Flusberg, 2004a ).

Need for Longitudinal Research

Further longitudinal studies of multiple aspects of language development in different clinical populations of children with language disorders are needed, especially during the period of time in ontogeny when language is acquired ( Bates, 2003 ). Although costly and time consuming, such studies will allow us to evaluate the manner in which specific language behaviors in different domains emerge and change over time within different groups, and their potential linkages at various ages with genetic and neurocortical functions ( Karmiloff-Smith & Thomas, 2003 ; Tallal & Benasich, 2002 ), higher order cognitive and socioemotional processes, and biological and social risk and resilience factors. Longitudinal designs will also allow us to evaluate within-group individual differences in profiles of language, cognitive, and behavioral skills over time, and describe the language phenotypes of subgroups of children more clearly and precisely ( Tager-Flusberg, 2004b ). Such research is critically needed to support and inform emerging studies evaluating the genetic and neurobiological etiology of different developmental language disorders.

To illustrate this need, Lord et al. (2004) noted that investigators in many prior studies of autism have tended to use general measures of verbal functioning (usually as control measures when evaluating the effect of autism on other cognitive or social skills such as theory of mind or central coherence). As a result, little is known about variations in different aspects of language (e.g., phonologic, semantic, morphosyntactic, pragmatic) among verbal children with autism, or (especially) how profiles among these different skills may change from early to later childhood. For instance, it is currently unclear whether children in the autistic spectrum disorders (or subgroups within this category) exhibit unique trajectories of language development from early to later childhood. Lord et al. contended that further understanding of the nature of these trajectories will have important implications for our understanding of the etiology and nature of developmental change within the autistic spectrum disorders, and children’s potential response to treatment within this population.

In a rare long-term longitudinal study, children with autism exhibited an uneven developmental trajectory of their language and cognitive skills from the preschool period to adolescence ( Sigman, 2005 ). Although about one-third of the children with autism made dramatic gains in cognitive and language skills from the preschool to the mid-school period, these gains had diminished dramatically (to less than half the change in their chronological age) by adolescence. Moreover, adolescents with autism and mental retardation exhibited almost no language gains. Notably, significant predictors of children’s language functioning in adolescence were children’s earlier functional play skills, responsiveness to others’ bids for joint attention, and the frequency of requesting behaviors during the pre-school period.

Further longitudinal studies in autism and other clinical populations are needed to shed light on how specific verbal and nonverbal cognitive and behavioral measures may be associated (or dissociated) at various points in time in ontogeny, and how functioning in different cognitive or socioemotional domains may support or derail language functioning in particular conditions or subgroups. An example of this type of longitudinal study comes from Mundy’s programmatic research (see Mundy et al., 1993 , for a review). In a 13-month longitudinal study of children with autism, Mundy et al. (1990) assessed the joint attention skills, pretend play behaviors, and language abilities of young children with autism and language-matched, mentally retarded children. All children were less than 5 years of age and were matched on receptive and expressive language age ( M = 12.5 and 13.6 months, respectively). At the initial observation, joint attention deficits (but not requesting deficits) were observed in the children with autism, before functional or symbolic play deficits were observed in this sample. Of note, joint attention deficits were also observed for the children with autism at the follow-up visit, when play deficits were present. Moreover, children’s initial joint attention (but not requesting) scores significantly predicted their symbolic play abilities at the time of the follow-up visit in the mentally retarded sample and approached significance in the autistic sample.

Mundy et al. (1990) speculated that nonverbal communicative and symbolic skills (i.e., joint attention and symbolic play skills) share a common source of variance and hypothesized that each may contribute to the development of children’s language and social–cognitive and theory of mind abilities. Of note, Baron-Cohen, Allen, and Gillberg (1992) provided corroborative evidence that the joint attention and symbolic play deficits of children with autism are lawfully related. In their autism screening studies, the majority of toddlers who showed impairments in both joint attention skills and symbolic play in the second year received a diagnosis of autism later in childhood. In contrast, none of the toddlers who had deficits in only one domain or who had no deficits were diagnosed with autism.

Taken together, these findings suggest that joint attention skills precede the emergence of language and nonverbal symbolic play skills in children with autism, and may share variance with factors associated with the subsequent emergence of verbal and nonverbal symbolic functioning. Moreover, these results indicate that the type of associations and dissociations among cognitive and socioaffective behaviors associated with language development in children with autism may change in ontogeny.

Longitudinal cross-population studies such as these are necessary if we are to capture the dynamic, changing nature of language learning and its correlates in various clinical groups over time. One-time “static” snapshots of language behavior so often described in prior language studies are inadequate to capture the dynamic, transactional process of early language development and may yield misleading results ( Karmiloff-Smith & Thomas, 2003 ).

In an intriguing treatise, Karmiloff-Smith (2001) argued that a key to understanding developmental disorders lies in the study of the dynamics of development itself, using a neuroconstructivist approach. Rather than focusing on single behaviors and “unidirectional chains” of single behaviors, she contended that investigators of language development in atypical populations need to evaluate the dynamic interplay among multiple contextual factors (e.g., genetics, brain/behavioral relations, and cognitive, behavioral, and environmental factors) on language and related processes from early infancy onward (see also Cicchetti et al., 1991 ; Thelen & Bates, 2003 ). Cicchetti et al. (1991) have further argued that it will be important to assess children’s language and communicative competencies in multiple observational contexts that focus on stage-salient developmental issues (i.e., tasks that require the child to coordinate language, cognition, affect, and behavior)and vary in the degree of structure and challenge placed on the child. The overarching promise in such multifactorial longitudinal research is that it will yield detailed, age-specific information on early language and associated processes that will be useful to clinicians, educators, and other professionals in guiding and timing comprehensive intervention and rehabilitation programs for children exhibiting delayed or deviant language development and their families ( Bates, 2003 ).

Genetic Bases of Language Disorders

Inquiry into the genetic bases of language disorders has gained momentum in the past decade, partly in response to the increasing number of behavioral phenotypic studies in different clinical groups, and partly from the hope that further knowledge of the genetic and environmental underpinnings of complex cognitive disorders can lead to more effective diagnoses and therapeutic interventions ( Smith & Morris, 2005 ). In behavioral genetics studies of early language development in typically developing children, results of multivariate genetic modeling revealed a consistently high genetic correlation between vocabulary and grammar at 2 and 3 years, suggesting the same genetic influences operate for both vocabulary and grammar ( Dionne, Dale, Boivin, & Plomin, 2003 ), a finding that is inconsistent with an “autonomy” hypothesis. In addition, results of crosslagged longitudinal genetic models showed that both lexical and syntactic bootstrapping operate from 2 to 3 years. In other behavioral genetics research, a complex interplay between genetic and environmental influences was associated with the timing and process of early language development ( Spinath, Price, Dale, & Plomin, 2004 ), suggesting the need for complex, dynamic systems approaches in future genetic studies of language disorders ( Thelen & Bates, 2003 ).

Two contrasting neurocognitive approaches (“top-down” and “bottom-up”) have recently been described that hold promise for future studies examining genetic contributions to language disorders. Generally speaking, in a top-down approach, the investigator focuses on an “optimal” phenotypic description of language behavior in a genetic disorder and then attempts to understand its genetic and biological underpinnings, often using electro-physiological brain measures ( Phillips, 2005 ). In contrast, in a bottom-up approach, the investigator focuses on primary etiological pathways for language disorders and attempts to explain complex “outcome phenotypes” in terms of more fundamental, underlying difficulties, such as those observed in early-emerging sensorimotor behavior ( Muller, 2005 ).

Both approaches are likely to be valuable, and each has the potential to identify gene effects at various levels of language processing and to describe specific genetic and neurological pathways contributing to language disorders ( Rice & Warren, 2005b ). For instance, advances in neuroimaging techniques (e.g., event-related potential, functional magnetic resonance imaging [fMRI], and near infrared spectroscopy) during the past 15 years have indicated that neurocortical measures such as these hold great promise for top-down genetic research in developmental language disorders. In studies of typically developing older children and adults, functional neuroimaging data have led to a greater understanding of the ways that dynamic neurocortical systems subserve higher level cognitive processes such as language. Moreover, fMRI studies in older children with specific language impairment or autism have yielded interesting corroborative information regarding behavioral findings in these disorders, with implications for our understanding of brain/behavior relations ( Carpenter et al., 2001 ; Nelson et al., 2002 ).

However, caution is needed in interpreting findings from this literature, given methodological variations in the use of these techniques across laboratories and related validity and reliability issues ( Billingsley-Marshall, Simos, & Papanicolaou, 2004 ). Further development and refinement of these techniques are needed. A major obstacle for the incorporation of these techniques in research on early language acquisition is that some neuroimaging techniques (e.g, fMRI) cannot be used successfully with infants and young children. This is due to technological limitations regarding movement artifacts, as well as ethical problems associated with sedation (see Nelson et al., 2002 ; Phillips, 2005 , for reviews).

Another methodological obstacle to genetic research in language disorders is that both the top-down and bottom-up methods require accurate, thorough descriptions of language phenotypes (and related cognitive and behavioral processes) in different populations of children with language delays and disorders. Clearly defined phenotypic measures are also necessary to inform and support cellular and molecular studies that will, in turn, lead to the identification of genes that contribute to the complex pathways affect language development and disorders ( McCardle et al., 2005 ).

Unfortunately, precise phenotypic descriptions of many aspects of language and related phenomena do not currently exist ( Rice & Warren, 2005b ). Part of the problem in coming up with a set of precise, “optimal” measures of language phenotypes in different clinical populations is that investigators from different disciplines have tended to focus on different language phenomena at different ages, with concomitant differences in preferred assessment paradigms and operational definitions of measures. To address and overcome some of these obstacles, Mervis and colleagues ( Mervis & Klein-Tasman, 2004 ; Mervis & Robinson, 2005 ) have provided several helpful methodological caveats for researchers in this field.

First, the most useful dependent measures of “optimal language phenotypes” (at least in initial studies) are those that assess narrowly defined language behaviors, can be used longitudinally with demonstrated reliability and validity, and can be utilized reliably by different investigators in different laboratories. This is especially important in multisite, cross-population comparative studies. In addition, given the growing cultural diversity in the United States, measures should be selected that recently have been normed (or renormed) for age and gender on geographically and racially representative national samples. Measures that are “culture free” and can be used appropriately in multicultural groups are especially desirable. Moreover, particular phenotypic measures should be selected for genetic evaluation that have known genetically related variation (heritability) in different populations, ideally those that have been shown to be consistent over time and within families, as determined in prior behavioral genetics studies ( Mervis & Robinson, 2005 ).

Second, Mervis and Klein-Tasman (2004) provide caveats pertaining to group-matching designs, which are commonly used to identify diagnosis-specific characteristics of children with language disorders. For instance, they describe the alpha levels needed for control variable comparisons, recommend the use of raw or standard scores rather than age equivalent scores when evaluating group differences on developmental matching variables, and advocate the use of sensitivity and specificity criteria to delineate membership in the target and control groups.

Third, Mervis et al. recommend that investigators eliminate from their study samples (or control for as much as possible) subjects with secondary behavioral or psychiatric conditions (e.g., attention deficit/hyperactivity disorder, depression)or environmental and biological risk factors (e.g., prematurity, prenatal substance exposure, teen parenting) that can co-occur with language disorders and confound interpretation in genotype/phenotype analyses. Assurance that target and comparison groups are matched carefully for gender, race/ethnicity, and sociodemographic characteristics (in addition to developmental features) is also of critical importance.

Fourth and finally, collaborative, multisite cross-population studies of language disorders are encouraged, because they can increase sample size in studies of rare disorders (such as Williams syndrome), overcome problems associated with subject attrition, and make the maximum use of the data. Furthermore, ideal collaborations would be multidisciplinary and incorporate input from scholars in genetics, molecular biology, linguistics, neuroscience, and psychology.

However, cross-site communication in multisite collaborative research is not a simple or easy task. To initiate and maintain effective, successful collaborative research, it will be important to coordinate efforts and methods across multidisciplinary groups prior to start up. As detailed by Mervis and Robinson (2005) , key constructs to be measured need to be identified, agreed-upon, and defined, using similar measures, instruments, and assessment paradigms across laboratories. In addition, investigators at different sites should utilize the same design (including specific child ages of assessment and control groups) and statistical analyses, to allow for data archiving and data sharing. Accomplishing these goals will require the implementation of procedures to promote excellent cross-site communication and reliable systems (e.g., a central site) for monitoring quality control at all phases of data collection and reduction.

Individual Differences and the Effects of Biological and Social Risk and Resilience Factors

Within-group variation in language and associated cognitive and behavioral skills is a hallmark feature of many clinical groups of children with delayed or disordered development ( Kennedy et al., 1991 ; Lord et al., 2004 ; Mervis, 2003 ; Tager-Flusberg, 2004a ; Thal et al., 2004 ; Tomblin, Zhang, Weiss, Catts, & Weismer, 2004 ), yet the primary focus in many prior comparative studies has been on describing average group differences in language performance, which can obscure within-group variations. Thus, there is an urgent need for investigators in future translational language research to evaluate individual differences within clinical groups of children with language delays and disorders. This shift in focus will allow for further analysis of data collected in within-group studies and the identification of possible subgroups of children with unique profiles of linguistic, cognitive, and behavioral skills, with implications for both genetic and intervention studies ( Lord et al., 2004 ; Tager-Flusberg, 2004b ).

It will also be important in future translational language studies to evaluate the effects of contextual risk and resilience factors that are known to affect variations in language acquisition. Factors such as child gender, temperament, parenting style, and biological and social risk and resilience factors on children’s language functioning have been shown to affect children’s language performance in both typically developing and various at-risk groups but have been largely ignored in prior research in children with developmental language disorders ( Blacher, Kraemer, & Schalow, 2003 ; Dykens, 2003 ; Mervis & Robinson, 2005 ; Torr, 2003 ). A brief review of this literature is provided here for illustrative purposes.

In typical development, language acquisition usually emerges rapidly and follows a predictable sequence during early childhood. By the end of the preschool period, most typically developing children have mastered the basic components of speech and language development, including a rich, varied lexicon, diversity in semantic and morphosyntactic applications, and pragmatic skills ( Berko Gleason, 2005 ). Moreover, a large body of normative research suggests that there is marked similarity across different ethnic and language groups in the onset and mastery of these skills ( Berko Gleason, 2005 ; Tomasello & Bates, 2001 ).

However, individual differences in the style and rate of early language acquisition are well documented ( Fenson et al., 1994 ; Shore, 1995 ). Robust effects of biological and social contextual factors such as child gender, temperament, birthweight premature birth, caregiver interactive style, culture, and demographics on multiple specific aspects of language development have also been reported, which may account for some of this variation ( Bates et al., 1994 ; Goldfield & Snow, 2005 ; Hart & Risley, 1995 ; Landry et al., 1997 ; Massey, 1996 ; Morisset, Barnard, & Booth, 1995 ; Spiker et al., 2002 ).

Caregiving factors are especially critical to consider, as individual differences in early language acquisition have been strongly linked to both distal and proximal measures of the caregiving environment, such as parental education, maternal psychosocial adaptation, and parental interactive style, including the amount and quality of verbal input to the child ( Messer, 1994 ). For instance, low socioeconomic status is often linked with delayed language acquisition. Results of a large, home-based observational study showed that parents from low SES homes spoke significantly less to their young children than parents from middle-class homes ( Hart & Risley, 1995 ), suggesting that the effect of low SES on children’s language development is mediated by SES-related variations in parental verbal input to children. In other research, variations in caregiving have been linked to children’s language outcomes within low-income samples. For example, in a longitudinal study of African American preschoolers from low-income families, a global measure of maternal responsivity and support in the home environment predicted children’s language and early literacy skills ( Roberts, Jurgens, & Burchinal, 2005 ). Similarly, in another longitudinal study of mostly Caucasian low-income toddlers’ vocabulary development between 1 and 3 years of age ( Pan, Rowe, Singer, & Snow, 2005 ), maternal lexical input and maternal language and literacy skills exerted positive effects, whereas maternal depression exerted negative effects, on toddlers’ lexical outcomes. Moreover, extreme perturbations in the caregiving environment, such as child maltreatment, are strongly associated with delays in children’s lexical, syntactic, and pragmatic development during early childhood, even after controlling for general cognitive status ( Beeghly & Cicchetti, 1994 ; Coster, Gersten, Beeghly, & Cicchetti, 1989 ; Eigsti & Cicchetti, 2004 ).

At a more proximal level, specific variations in maternal verbal input and sensitivity or responsivity to children during mother–child interaction have been linked with the rate of children’s language development, in both typically developing and at-risk groups ( Dale, Greenberg, & Crnic, 1987 ; Dunham & Dunham, 1992 ). For instance, in multivariate longitudinal studies of children’s vocabulary development, Bornstein and colleagues ( Bornstein, 1998 ) showed that mothers’ spontaneous expressive vocabulary to their infants uniquely predicted infants’ comprehension at 20 months. Effects of variations in the socio-affective quality of parent–infant relationship on language outcomes have also been reported. In a meta-analytic review ( van Ijzendoorn, Dijkstra, & Bus, 1995 ), the quality of attachment between infant and parent was strongly associated with the infant’s language development. Similarly, in a study of medically high risk toddlers, additive effects of a secure mother–infant attachment relationship and home stimulation on children’s language competence (especially receptive skills) were observed ( Murray & Yingling, 2000 ).

Several investigators have suggested that variations in maternal interactive style and sensitivity may exert stronger effects on early linguistic development when children are at risk for language delay due to the presence of social or biological risk factors ( Baumwell, Tamis-LeMonda, & Bornstein, 1997 ; Beeghly & Cicchetti, 1994 ). For instance, in Landry’s programmatic longitudinal research on prematurely born infants with varying biological risk characteristics, maternal interactive style characterized by a high prevalence of maintaining (rather than redirecting) of the child’s focus of attention during dyadic interactive tasks was associated with longitudinal gains in children’s language, cognitive, and social functioning in both term and prematurely born children, with larger gains seen in the higher risk preterm groups (see Landry, Miller-Loncar, & Smith, 2002 , for a review). Similarly, in a large longitudinal study of the effects of child care on children’s outcomes, maternal sensitivity during mother–child interactions from infancy through 36 months mediated the effect of chronic maternal depressive symptoms on children’s cognitive and linguistic outcomes ( NICHD Early Child Care Research Network, 1999 ).

Although understudied, similar caregiving effects have been observed in language studies of children with a variety of developmental disabilities. For instance, in experimental intervention studies of children with language delays and with Down syndrome, Yoder, Hooshyar, Klee, and Shaffer (1996) showed that mothers’ responsive linguistic behaviors that were fine tuned to their infants’ language skills predicted gains in their children’s syntactic development. In another study ( Yoder & Warren, 1999 ), maternal verbal responsivity mediated the relationship between children’s prelinguistic intentional communication and later language skills. In a study of the early predictors of language in children with and without Down syndrome ( Yoder & Warren, 2004 ), parental verbal responsivity predicted children’s later productive language above and beyond etiology. Similarly, in a prospective study of hearing mothers and their deaf and hard-of-hearing children ( Pressman, Pipp-Siegel, Yoshinaga-Ito, & Deas, 1999 ), maternal affective sensitivity to toddlers during mother–child interaction was significantly, positively associated with children’s expressive language gain, even after controlling for maternal education, degree of child hearing loss, dyadic mode of communication, and other covariates.

Of course, the direction of effects in these studies is unclear, given that development is dynamic and transactional in nature ( Abbeduto & Murphy, 2004 ; Bates et al., 1982 ). Parents’ psychosocial well-being and interactive style with children are also affected by variations in the child’s own developmental and behavioral status. What is still unclear (and deserves further evaluation) is how children’s developmental and socioemotional behavioral characteristics affect others’ responsivity to them and how this transactional process may indirectly contribute to the quality of child’s language-learning environment over time ( Abbeduto & Murphy, 2004 ).

Gene–environment interactions in language disorders

Several investigators ( Abbeduto & Murphy, 2004 ; Hodapp, 1997 , 2004 ) have suggested that, because factors from multiple levels of influence affect the trajectory of children’s language development, gene–environment interaction effects on language outcomes in clinical groups are especially likely and should be evaluated. An effective way to study this would be to evaluate the ways in which children with different genetic disorders (e.g., Down syndrome, Williams syndrome, or autism)use language with others in social contexts, and how variations in children’s communicative style affect others’ responses to them over time. It is possible that the resulting specific child–environmental interchanges in different groups or subgroups could gradually affect the developmental trajectory of those children’s profile of language skills and alter their phenotypic manifestation of genetically based behavioral predispositions. Putatively, these indirect genetic effects could also affect children’s functioning in other domains (e.g., cognitive processes, socioemotional behavior).

Although intriguing, evaluating gene–environment interactions in translational language research (especially at an individual level) is likely to be complex and difficult. For instance, it remains to be determined which specific aspects of the child’s language and communicative behavior affect others, whether these effects persist over time, and whether these effects are specific to a single disorder or are generalizable to all children with similar profiles in other groups ( Hodapp, 2004 ).

Cumulative risk

Longitudinal research with at-risk groups of children has shown that the presence of multiple risk factors may be stronger predictors of children’s language and other developmental outcomes than single risk factors. In several studies of preterm birth, for instance, infants with lower gestational age and birth weight, along with additional comorbid biological risk factors (e.g., chronic lung disease, white matter brain injury) performed more poorly on tests of language ability than their lower risk counterparts ( Briscoe, Gathercole, & Marlow, 1998 ; Landry, Miller-Loncar, & Smith, 2002 ). Similarly, in a longitudinal study of the effect of prenatal cocaine exposure on low-income children’s language outcomes at 6 and 9.5 years of age ( Beeghly et al., 2006 ), children with both prenatal cocaine exposure and lower birth-weight had more compromised expressive language functioning than exposed children with higher birthweight or unexposed children.

Taken together, this literature confirms that biological and social contextual variables from multiple levels of influence can alter the trajectories of children’s language development, whether children are developing typically, atypically, or at risk for developmental problems. Therefore, investigators in future translational research on language development should measure and evaluate these contextual factors carefully. As Zigler (1971) contended, children with developmental delays or disabilities are children first, and thus investigators need to take an integrated, “whole-person” approach to their study.

Clinical Implications

Let us now return to the clinician’s predicament raised at the beginning of this paper. How can results from longitudinal cross-population research on early language development in at-risk and atypical groups be “translated” into more effective evidence-based clinical practice?

Translational research on early language development has many implications for clinical practice. A few compelling examples are provided here.

First, translational research on atypical language development to date has shown that there are striking individual differences in language acquisition and related cognitive and behavioral processes within different clinical groups and subgroups of children, as well as striking commonalities across conditions. The provision of further detailed information about these cross-population similarities and differences in language profiles and documentation of subtypes within populations would enhance clinicians’ ability to identify young children who are likely to develop clinically significant language-learning problems and would enhance clinicians’ understanding of the different levels of risk that may predispose very young children for persistent language impairment ( Thal et al., 2004 ). Moreover, this information would help clinicians individualize and customize existing programs and intervention strategies for different children and maximize their effectiveness ( Abbeduto & Murphy, 2004 ).

Second, further longitudinal evaluation of the unique trajectories of language development within and across different clinical groups would shed light on how profiles of abilities within or across clinical groups change or remain the same over time ( Lord et al., 2004 ). This research would also identify the specific contextual factors (biochemical, neurocortical, or environmental) that may be triggering these age-related changes ( Rice, 2004 ). This information would allow clinicians to anticipate accelerations and decelerations in specific skills in different subgroups at different ages, and tailor and fine-tune interventions for individual children at different levels of language functioning in developmentally appropriate ways.

Third, translational research documenting the specific cognitive and behavioral precursors of language development (e.g., joint attention, pretend play) in different clinical groups may assist clinicians in identifying more accurately and at earlier ages children who are at risk for persistent language problems ( Yoder & Warren, 2004 ), which would allow these children to receive intervention services as early as possible. Research suggests that intervention services are most effective when received during infancy and toddlerhood ( Guralnick, 1997 ; Leonard, 1998 ).

Fourth, the identification of specific biological and social risk factors that may support or derail children’s language development in different clinical populations would further assist clinicians in the early identification of children at risk for language problems and offer insights into the most effective interventions. Tomblin, Hardy, and Hein (1991) have suggested that information regarding children’s biological and family risk status could help clinicians identify those at greater risk for communicative impairments more clearly. For instance, in their retrospective study of the speech and language status of 662 children between 30 months and 5 years of age, a set of multiple risk factors comprising various family background and birth history variables predicted 55% of children with poor communication skills and 76% of those with normal communicative development ( Tomblin et al., 1991 ).

Regarding the development of effective treatment programs, results from intervention research documenting the efficacy of different types of parental verbal responsivity on children’s language outcomes could be incorporated into ongoing parenting programs to maximize their effectiveness ( Yoder & Warren, 1999 , 2004 ). More generally, reduction of the overall level of risk for individual children and their families and provision of social support at multiple levels may do much to facilitate positive child developmental outcomes ( Dunst, 2000 ; Tronick & Beeghly, 1999 ). For instance, results from intervention research spanning nearly three decades ( Olds, 2006 ) have shown that general and specific prenatal and infancy preventive interventions for low-income families provided by home visiting nurses can significantly improve parental care and are associated with better infant and emotional outcomes, particularly for families at greater risk.

Fifth and finally, longitudinal translational research on the efficacy of different intervention programs could provide valuable information to clinicians regarding the relative efficacy of different types of intervention programs on parenting and child language outcomes in different clinical groups, whether these effects vary for children at different ages, and whether different approaches are needed for families from different socioeconomic and cultural backgrounds. Such research could also shed light on how specific intervention parameters (intensity, duration, comprehensiveness of service) may affect parental adaptation, parenting, and children’s language outcomes in different clinical groups (see, e.g., Hauser-Cram, Warfield, Shonkoff, & Krauss, 2001 ; Warfield, Hauser-Cram, Krauss, & Upshur, 2000 ).

Acknowledgments

Partial support during the writing of this paper was provided by NIH Grant RO1HD044068. I am grateful to Dante Cicchetti for his thoughtful feedback on a prior version of this paper.

• Abbeduto L, Hagerman RJ. Language and communication in fragile X syndrome. Mental Retardation and Developmental Disabilities Research Reviews. 1997; 3 :313–322. [ Google Scholar ]
• Abbeduto L, Murphy MM. Language, social cognition, maladaptive behavior, and communication in Down syndrome and fragile X syndrome. In: Rice ML, Warren SF, editors. Developmental language disorders: From phenotypes to etiologies. Mahwah, NJ: Erlbaum; 2004. pp. 77–97. [ Google Scholar ]
• American Academy of Pediatrics Committee on Children with Disabilities. Developmental surveillance and screening of infants and young children. Pediatrics. 2001; 108 :192–196. [ PubMed ] [ Google Scholar ]
• American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4. Washington, DC: Author; 1994. [ Google Scholar ]
• Baron-Cohen S. Autism and symbolic play. British Journal of Developmental Psychology. 1987; 5 :139–148. [ Google Scholar ]
• Baron-Cohen S. Mindblindness: An essay on autism and theory of mind. Cambridge, MA: MIT Press; 1995. [ Google Scholar ]
• Baron-Cohen S, Allen J, Gillberg C. Can autism be detected at 18 months? The needle, the haystack, and the CHAT. British Journal of Psychiatry. 1992; 161 :839–843. [ PubMed ] [ Google Scholar ]
• Bates E. Explaining and interpreting deficits in language development across clinical groups: Where do we go from here? Brain and Language. 2003; 88 :248–253. [ PubMed ] [ Google Scholar ]
• Bates E, Bretherton I, Beeghly M, McNew S. Social bases of language development: A reassessment. In: Reese H, Lipsitt L, editors. Advances in child development and behavior. Vol. 16. New York: Academic Press; 1982. pp. 7–75. [ PubMed ] [ Google Scholar ]
• Bates E, Bretherton I, Snyder L. From first words to grammar: Individual differences and dissociable mechanisms. New York: Cambridge University Press; 1988. [ Google Scholar ]
• Bates E, Marchman V, Thal DJ, Fenson L, Dale PS, Reznick JS, et al. Developmental and stylistic variation in the composition of early vocabulary. Journal of Child Language. 1994; 21 :85–124. [ PubMed ] [ Google Scholar ]
• Baumwell L, Tamis-LeMonda CS, Bornstein MH. Maternal verbal sensitivity and child language comprehension. Infant Behavior and Development. 1997; 20 :247–258. [ Google Scholar ]
• Beeghly M. Emergence of symbolic play: Perspectives from typical and atypical development. In: Burack J, Hodapp R, Zigler E, editors. Handbook of mental retardation and development. New York: Cambridge University Press; 1997. pp. 240–289. [ Google Scholar ]
• Beeghly M, Cicchetti D. Child maltreatment, attachment, and the self system: Emergence of an internal state lexicon in toddlers at high social risk. Development and Psychopathology. 1994; 6 :5–30. [ PubMed ] [ Google Scholar ]
• Beeghly M, Cicchetti D. Talking about self and other: Emergence of an internal state lexicon in young children with Down syndrome. Development and Psychopathology. 1997; 9 :729–748. [ PubMed ] [ Google Scholar ]
• Beeghly M, Martin B, Rose-Jacobs R, Cabral H, Heeren T, Augustyn M, et al. Prenatal cocaine exposure and children’s language functioning at 6 and 9.5 years: Moderating effects of child age, birth-weight, and gender. Journal of Pediatric Psychology. 2006; 31 :98–115. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Beeghly M, Perry BW, Cicchetti D. Structural and affective dimensions of play development in young children with Down syndrome. International Journal of Behavioral Development. 1989; 12 :257–277. [ Google Scholar ]
• Beeghly M, Weiss-Perry B, Cicchetti D. Beyond sensorimotor functioning: Early communicative and play development of children with Down syndrome. In: Cicchetti D, Beeghly M, editors. Children with Down syndrome: A developmental perspective. New York: Cambridge University Press; 1990. pp. 329–368. [ Google Scholar ]
• Bellugi U, Wang PP, Jernigan TL. Williams syndrome: An unusual neuropsychological profile. In: Broman SH, Grafman J, editors. Atypical cognitive deficits in developmental disorders. Hillsdale, NJ: Erlbaum; 1994. pp. 23–56. [ Google Scholar ]
• Berko Gleason J. The development of language. 6. Boston: Allyn & Bacon; 2005. [ Google Scholar ]
• Billingsley-Marshall RL, Simos PG, Papanicolaou AC. Reliability and validity of functional neuroimaging techniques for identifying language— Critical areas in children and adults. Developmental Neuropsychology. 2004; 26 :541–563. [ PubMed ] [ Google Scholar ]
• Bishop DVM. Grammatical errors in specific language impairment: Competence or performance limitations. Applied Psycholinguistics. 1994; 15 :507–550. [ Google Scholar ]
• Bishop DVM, Chan J, Adams C, Hartley J, Weir F. Conversational responsiveness in specific language impairment: Evidence of disproportionate pragmatic difficulties in a subset of children. Development and Psychopathology. 2000; 12 :177–199. [ PubMed ] [ Google Scholar ]
• Blacher J, Kraemer B, Schalow M. Asperger syndrome and high functioning autism: Research concerns and emerging foci. Current Opinion in Psychiatry. 2003; 16 :535–542. [ Google Scholar ]
• Bornstein M. Sources of child vocabulary competence: A multivariate model. Journal of Child Language. 1998; 25 :367–393. [ PubMed ] [ Google Scholar ]
• Briscoe J, Gathercole SE, Marlow N. Short-term memory and language outcomes after extreme prematurity at birth. Journal of Speech, Language, and Hearing Research. 1998; 41 :654–666. [ PubMed ] [ Google Scholar ]
• Carpenter PA, Just MA, Keller T, Cherkassky V, Roth JK, Minshew N. Dynamic cortical systems subserving cognition: fMRI studies with typical and atypical individuals. In: McClelland JL, Siegler R, editors. Mechanisms of cognitive development: Behavioral and neural perspectives. Mahwah, NJ: Erlbaum; 2001. pp. 353–383. [ Google Scholar ]
• Catts HW. The relationship between speech–language impairments and reading disabilities. Journal of Speech and Hearing Research. 1993; 36 :948–958. [ PubMed ] [ Google Scholar ]
• Chapman RS. Language and communication in individuals with Down syndrome. In: Abbeduto L, editor. International review of research in mental retardation. Vol. 27. New York: Academic Press; 2003. pp. 1–34. [ Google Scholar ]
• Chapman RS, Hesketh L. Language, cognition, and short-term memory in individuals with Down syndrome. Down Syndrome: Research and Practice. 2001; 7 :1–7. [ PubMed ] [ Google Scholar ]
• Charman T. The relationship between joint attention and pretend play in autism. Development and Psychopathology. 1997; 9 :1–16. [ PubMed ] [ Google Scholar ]
• Charman T, Baron-Cohen S, Swettenham J, Baird G, Cox A, Drew A. Testing joint attention, imitation, and play as precursors to language and theory of mind. Cognitive Development. 2000; 15 :481–498. [ Google Scholar ]
• Charman T, Drew A, Baird C, Baird G. Measuring early language development in preschool children with autism spectrum disorder using the MacArthur Communicative Development Inventory (Infant Form) Journal of Child Language. 2003; 30 :213–236. [ PubMed ] [ Google Scholar ]
• Cicchetti D. The emergence of developmental psychopathology. Child Development. 1984; 55 :1–7. [ PubMed ] [ Google Scholar ]
• Cicchetti D, Beeghly M. An organizational approach to the study of Down syndrome: Contributions to an integrative theory of development. In: Cicchetti D, Beeghly M, editors. Down syndrome: A developmental perspective. New York: Cambridge University Press; 1990. pp. 29–62. [ Google Scholar ]
• Cicchetti D, Beeghly M, Carlson V, Coster W, Gersten M, Rieder C, et al. Development and psychopathology: Lessons from the study of maltreated children. In: Keating DP, Rosen H, editors. Constructivist perspectives on developmental psychopathology and atypical development. The Jean Piaget symposium series. Hillsdale, NJ: Erlbaum; 1991. pp. 69–102. [ Google Scholar ]
• Cicchetti D, Beeghly M, Weiss-Perry B. Symbolic development in children with Down syndrome and in children with autism: An organizational, developmental psychopathology perspective. In: Slade A, Wolf DP, editors. Children at play: Clinical and Developmental approaches to meaning and representation. New York: Oxford University Press; 1994. pp. 206–237. [ Google Scholar ]
• Cielinski KL, Vaughn BE, Seifer R, Contreras J. Relations among sustained engagement during play, quality of play, and mother–child interaction in samples of children with Down syndrome and normally developing toddlers. Infant Behavior and Development. 1995; 18 :163–176. [ Google Scholar ]
• Clahsen H, Almazan M. Syntax and morphology in Williams syndrome. Cognition. 1998; 68 :167–198. [ PubMed ] [ Google Scholar ]
• Cohen NJ, Davine M, Horodezky N, Lipsett L, Isaacson L. Unsuspected language impairment in psychiatrically disturbed children: Prevalence and language and behavioral characteristics. Journal of the American Academy of Child and Adolescent Psychiatry. 1993; 32 :1103. [ PubMed ] [ Google Scholar ]
• Conti-Ramsden G, Botting N, Faragher B. Psycholinguistic markers for specific language impairment (SLI) Journal of Child Psychology and Psychiatry. 2001; 42 :741–748. [ PubMed ] [ Google Scholar ]
• Coster W, Gersten M, Beeghly M, Cicchetti D. Communicative functioning in maltreated toddlers. Developmental Psychology. 1989; 25 :1020–1029. [ Google Scholar ]
• Dale P, Greenberg M, Crnic KA. The multiple determinants of symbolic development: Evidence from preterm children. New Directions for Child Development. 1987; 36 :69–86. [ PubMed ] [ Google Scholar ]
• Dale PS, Price TS, Bishop DVM, Plomin R. Outcomes of early language delay: I. Predicting persistent and transient language difficulties at 3 and 4 years. Journal of Speech, Language, and Hearing Research. 2003; 46 :544–560. [ PubMed ] [ Google Scholar ]
• Dawson G, Castelloe P. Autism. In: Walker DE, Roberts MC, editors. Handbook of child clinical psychology. 2. New York: Wiley; 1992. pp. 375–397. [ Google Scholar ]
• Dionne G, Dale PS, Boivin M, Plomin R. Genetic evidence for bidirectional effects of early lexical and grammatical development. Child Development. 2003; 74 :394–412. [ PubMed ] [ Google Scholar ]
• Dunham P, Dunham F. Lexical development during middle infancy: A mutually driven infant–caregiver process. Developmental Psychology. 1992; 28 :414–420. [ Google Scholar ]
• Dunst CJ. Revisiting “rethinking early intervention. Topics in Early Childhood Special Education. 2000; 20 :95–104. [ Google Scholar ]
• Dykens E, Hodapp R, Finucane BM, editors. Genetics and mental retardation syndromes: A new look at behavior and interventions. Baltimore, MD: Paul Brookes; 2000. [ Google Scholar ]
• Dykens EM. The Williams syndrome behavioral phenotype: The “whole person” is missing. Current Opinion in Psychiatry. 2003; 16 :523–528. [ Google Scholar ]
• Eigsti IM, Cicchetti D. The impact of child maltreatment on expressive syntax at 60 months. Developmental Science. 2004; 7 :88–102. [ PubMed ] [ Google Scholar ]
• Elman JL, Bates EA, Johnson MH, Karmiloff-Smith A, Parisi D, Plunkett K. Rethinking innateness: A connectionist perspective on development. Cambridge, MA: MIT Press; 1996. [ Google Scholar ]
• Feldman HM. Evaluation and management of language and speech disorders in preschool children. Pediatrics in Review. 2005; 26 :131–141. [ PubMed ] [ Google Scholar ]
• Fenson L, Dale PS, Reznick JS, Bates E, Thal DJ, Pethick SJ. Variability in early communicative development. Monographs of the Society for Research in Child Development. 1994; 59 (5) Series no 242. [ PubMed ] [ Google Scholar ]
• Fowler AE. Language abilities in children with Down syndrome: Evidence for a specific syntactic delay. In: Cicchetti D, Beeghly M, editors. Children with Down syndrome: A developmental perspective. New York: Cambridge University Press; 1990. pp. 302–328. [ Google Scholar ]
• Goldfield BA, Snow CE. Individual differences: Implications for the study of language acquisition. In: Berko Gleason J, editor. The development of language. 6. Boston: Allyn & Bacon; 2005. [ Google Scholar ]
• Grizzle KL, Simms MD. Early language development and language learning disabilities. Pediatrics in Review. 2005; 26 :274–283. [ PubMed ] [ Google Scholar ]
• Guralnick MJ. The effectiveness of early intervention. Baltimore, MD: Paul Brookes; 1997. [ Google Scholar ]
• Happe F. Autism: An introduction to psychological theory. Cambridge, MA: Harvard University Press; 1995. [ Google Scholar ]
• Happe F, Frith U. The neuropsychology of autism. Brain. 1996; 119 :1377–1400. [ PubMed ] [ Google Scholar ]
• Hart B, Risley TR. Meaningful differences in the everyday experience of young American children. Baltimore, MD: Brookes; 1995. [ Google Scholar ]
• Hauser-Cram P, Warfield ME, Shonkoff JP, Krauss MW. Children with disabilities: A longitudinal study of child development and parent well-being. Monographs of the Society for Research in Child Development. 2001; 66 :1–131. [ PubMed ] [ Google Scholar ]
• Hodapp RM. Direct and indirect behavioral effects of different genetic disorders on mental retardation. American Journal on Mental Retardation. 1997; 102 :67–80. [ PubMed ] [ Google Scholar ]
• Hodapp RM. Studying interactions, reactions, and perceptions: Can genetic disorders serve as behavioral proxies? Journal of Autism and Developmental Disorders. 2004; 34 :29–34. [ PubMed ] [ Google Scholar ]
• Joseph RM. Neuropsychological frameworks for understanding autism. International Review of Psychiatry. 1999; 11 :309–325. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Karmiloff-Smith A. Development itself is the key to understanding developmental disorders. In: Tomasello M, Bates E, editors. Language development: The essential readings. Malden, MA: Blackwell; 2001. pp. 331–350. [ Google Scholar ]
• Karmiloff-Smith A, Thomas M. What can developmental disorders tell us about the neurocomputational constraints that shape development? The case of Williams syndrome. Development and Psychopathology. 2003; 15 :969–990. [ PubMed ] [ Google Scholar ]
• Kennedy MD, Sheridan MK, Radlinsky SH, Beeghly M. Play–language relationships in young children with development delays: Implications on assessment. Journal of Speech and Hearing Research. 1991; 34 :112–122. [ PubMed ] [ Google Scholar ]
• Laing E, Butterworth G, Ansari D, Gsodl M, Longhi E, Panagiotaki G, et al. Atypical development of language and social communication in toddlers with Williams syndrome. Developmental Science. 2002; 5 :233–246. [ Google Scholar ]
• Landry SH, Miller-Loncar CL, Smith KE. Individual differences in the development of social communication competency in very low birthweight children. In: Molfese DL, Molfese VJ, editors. Developmental variations in learning: Applications to social, executive function, language, and reading skills. Mahwah, NJ: Erlbaum; 2002. pp. 81–112. [ Google Scholar ]
• Landry SH, Smith KE, Miller-Loncar CL, Swank PR. Predicting cognitive–language and social growth curves from early maternal behaviors in children at varying degrees of biological risk. Developmental Psychology. 1997; 33 :1040–1053. [ PubMed ] [ Google Scholar ]
• Law J, Boyle J, Harris F, Harkness A, Nye C. Prevalence and natural history of primary speech and language delay: A systematic review of the literature. Journal of Langauge and Communication Disorders. 2000; 35 :165–188. [ PubMed ] [ Google Scholar ]
• Leonard L. Children with specific language impairment. Cambridge, MA: MIT Press; 1998. [ Google Scholar ]
• Lord C, Paul R. Language and communication in autism. In: Cohen DJ, Volkmar FR, editors. Handbook of autism and pervasive developmental disorders. 2. New York: Wiley; 1997. [ Google Scholar ]
• Lord C, Risi S, Pickles A. Trajectory of language development in autistic spectrum disorders. In: Rice ML, Warren SF, editors. Developmental language disorders: From phenotypes to etiologies. Mahwah, NJ: Erlbaum; 2004. pp. 7–29. [ Google Scholar ]
• Lord C, Rutter M. Autism and pervasive development disorders. In: Taylor E, editor. Child and adolescent psychiatry: Modern approaches. 3. Oxford: Blackwell; 1994. pp. 569–593. [ Google Scholar ]
• Luthar SS, Cicchetti D, Becker B. The construct of resilience: A critical evaluation and guidelines for future work. Child Development. 2000; 71 :543–562. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Marchman VA, Saccuman C, Wulfeck B. Productive use of the English past tense in children with focal brain injury and specific language impairment. Brain and Language. 2003; 88 :202–214. [ PubMed ] [ Google Scholar ]
• Massey AE. Cultural effects on language: Implications for assessing African American children. In: Kamhi A, Pollock K, editors. Communication development and disorders in African American children: Research, assessment, and intervention. Baltimore, MD: Paul Brookes; 1996. pp. 285–306. [ Google Scholar ]
• McCardle P, Cooper J, Freund L. Language and genetics: Needs and opportunities. Applied Psycholinguistics. 2005; 26 :129–135. [ Google Scholar ]
• Mervis CB. Williams syndrome: 15 years of psychological research. Developmental Neuropsychology. 2003; 23 :1–12. [ PubMed ] [ Google Scholar ]
• Mervis CB, Klein-Tasman B. Methodological issues in group matching designs: Alpha levels for control variable comparisons and measurement characteristics of control and target variables. Journal of Autism and Developmental Disorders. 2004; 34 :7–17. [ PubMed ] [ Google Scholar ]
• Mervis CB, Morris CA, Klein-Tasman B, Bertrand J, Kwitny S, Abbelbaum LG, et al. Attentional characteristics of infants and toddlers with Williams syndrome during triadic interactions. Developmental Neuropsychology. 2003; 23 :243–268. [ PubMed ] [ Google Scholar ]
• Mervis CB, Robinson BF. Expressive vocabulary ability of toddlers with Williams syndrome or Down syndrome: A comparison. Developmental Neuropsychology. 2000; 17 :111–126. [ PubMed ] [ Google Scholar ]
• Mervis CB, Robinson BF. Designing measures for profiling and genotype/phenotype studies of individuals with genetic syndromes or developmental language disorders. Applied Psycholinguistics. 2005; 26 :41–64. [ Google Scholar ]
• Messer DJ. The development of communication: From social interaction to language. Chicester: Wiley; 1994. [ Google Scholar ]
• Miller J. The developmental asynchrony of language development in children with Down syndrome. In: Nadel L, editor. The psychobiology of Down syndrome. Cambridge, MA: MIT Press; 1990. [ Google Scholar ]
• Morisset CE, Barnard KE, Booth CL. Toddlers’ language development: Sex differences within social risk. Developmental Psychology. 1995; 31 :851–865. [ Google Scholar ]
• Morris CA. Genotype-phenotype correlations: Lessons from Williams syndrome research. In: Rice ML, Warren SF, editors. Developmental language disorders: From phenotypes to etiologies. Mahwah, NJ: Erlbaum; 2004. pp. 355–369. [ Google Scholar ]
• Muller RA. Neurocognitive studies of language impairments: The bottom-up approach. Applied Psycholinguistics. 2005; 26 :65–78. [ Google Scholar ]
• Mundy P, Sigman M, Kasari C. A longitudinal study of joint attention and language development in autistic children. Journal of Autism and Developmental Disorders. 1990; 20 :115–128. [ PubMed ] [ Google Scholar ]
• Mundy P, Sigman MD, Kasari C. The theory of mind and joint-attention deficits in autism. In: Baron-Cohen S, Tager-Flusberg H, Cohen DJ, editors. Understanding other minds: Perspectives from autism. Oxford: Oxford University Press; 1993. [ Google Scholar ]
• Mundy P, Sigman MD, Kasari C. Joint attention, developmental level, and symptom presentation in autism. Development and Psychopathology. 1994; 6 :389–401. [ Google Scholar ]
• Murray AD, Yingling JL. Competence in language at 24 months: Relations with attachment security and home stimulation. Journal of Genetic Psychology. 2000; 161 :133–140. [ PubMed ] [ Google Scholar ]
• Nelson CA, Bloom FE, Cameron JL, Amaral D, Dahl RE, Pine D. An integrative, multi-disciplinary approach to the study of brain–behavior relations in the context of typical and atypical development. Development and Psychopathology. 2002; 14 :499–520. [ PubMed ] [ Google Scholar ]
• Newschaffer CJ, Falb MD, Gurney JG. National autism prevalence trends from United States special education data. Pediatrics. 2005; 115 :277–282. [ PubMed ] [ Google Scholar ]
• NICHD Early Child Care Reseach Network. Chronicity of maternal depressive symptoms, maternal sensitivity, and child functioning at 36 months. Developmental Psychology. 1999; 35 :1297–1310. [ PubMed ] [ Google Scholar ]
• Olds DL. The nurse-based partnership: An evidence-based preventive intervention. Infant Mental Health Journal. 2006; 27 :5–25. [ PubMed ] [ Google Scholar ]
• Pan BA, Rowe ML, Singer JD, Snow CE. Maternal correlates of growth in toddler vocabulary production in low-income families. Child Development. 2005; 76 :763–782. [ PubMed ] [ Google Scholar ]
• Paul R. Clinical implications of the natural history of slow expressive language development. American Journal of Speech–Language Pathology. 1996; 5 :5–21. [ Google Scholar ]
• Phillips C. Electrophysiology in the study of developmental language impairments: Prospects and challenges for a top-down approach. Applied Psycholinguistics. 2005; 26 :79–96. [ Google Scholar ]
• Phillips W, Baron-Cohen S, Rutter M. The role of eye contact in goal detection: Evidence from normal infants and children with autism or mental handicap. Development and Psychopathology. 1992; 4 :375–383. [ Google Scholar ]
• Pressman LJ, Pipp-Siegel S, Yoshinaga-Ito C, Deas A. Maternal sensitivity predicts language gain in preschool children who are deaf or hard of hearing. Journal of Deaf Studies and Deaf Education. 1999; 4 :294–304. [ PubMed ] [ Google Scholar ]
• Ramey CT, Campbell FA, Ramey SL. Early intervention: Successful pathways to improving intellectual development. Developmental Neuropsychology. 1999; 16 :385–392. [ Google Scholar ]
• Reilly J, Klima ES, Bellugi U. Once more with feeling: Affect and language in atypical populations. Development and Psychopathology. 1991; 2 :367–391. [ Google Scholar ]
• Reilly J, Losh M, Bellugi U, Wulfeck B. “Frog, where are you?” Narratives in children with specific language impairment, early focal brain injury, and Williams syndrome. Brain and Language. 2004; 88 :229–247. [ PubMed ] [ Google Scholar ]
• Rescorla L. Language and reading outcomes at age 9 in late-talking toddlers. Journal of Speech and Hearing Research. 2002; 45 :360–371. [ PubMed ] [ Google Scholar ]
• Rice ML. A unified model of specific and general language delay: Grammatical tense as a clinical marker of unexpected variation. In: Levy Y, Schaeffer J, editors. Language competence across populations: Toward a definition of specific language impairment. Mahwah, NJ: Erlbaum; 2003. pp. 63–95. [ Google Scholar ]
• Rice ML. Growth models of developmental language disorders. In: Rice ML, Warren SF, editors. Developmental language disorders: From phenotypes to etiologies. Mahwah, NJ: Erlbaum; 2004. pp. 207–240. [ Google Scholar ]
• Rice ML, Hadley PA, Alexander A. Social biases toward children with speech and language impairments: A correlative causal model of language limitations. Applied Psycholinguistics. 1993; 14 :443–471. [ Google Scholar ]
• Rice ML, Warren SF. Developmental language disorders: From phenotypes to etiologies. Mahwah, NJ: Erlbaum; 2004. [ Google Scholar ]
• Rice ML, Warren SF. Developmental language disorders: From phenotypes to etiologies. Mahwah, NJ: Erlbaum; 2005a. [ Google Scholar ]
• Rice ML, Warren SF. Moving toward a unified effort to understand the nature and causes of language disorders. Applied Psycholinguistics. 2005b; 26 :3–6. [ Google Scholar ]
• Rice ML, Warren SF, Betz SK. Language symptoms of developmental language disorders: An overview of autism, Down syndrome, fragile X, specific language impairment, and Williams syndrome. Applied Psycholinguistics. 2005; 26 :7–27. [ Google Scholar ]
• Rice ML, Wexler K, Marquis J, Hershberger S. Acquisition of irregular past tense by children with SLI. Journal of Speech, Language, and Hearing Research. 2000; 43 :1126–1145. [ PubMed ] [ Google Scholar ]
• Roberts J, Jurgens J, Burchinal MR. The role of home literacy practices in preschool children’s language and emergent literacy skills. Journal of Speech, Language, and Hearing Research. 2005; 48 :345–359. [ PubMed ] [ Google Scholar ]
• Robinson BF, Mervis CB, Robinson BW. The roles of verbal short-term memory and working memory in the acquisition of grammar by children with Williams syndrome. Developmental Neuropsychology. 2003; 23 :12–31. [ PubMed ] [ Google Scholar ]
• Roeyers H, VanOost P, Bothuyne S. Immediate imitation and joint attention in young children with autism. Development and Psychopathology. 1998; 10 :441–450. [ PubMed ] [ Google Scholar ]
• Rozien NJ. Down syndrome. In: Batshaw ML, editor. Children with disabilities. Baltimore, MD: Paul Brookes; 1997. pp. 361–376. [ Google Scholar ]
• Sameroff AJ, Fiese BH. Transactional regulation and early intervention. In: Meisels SJ, Shonkoff JP, editors. Handbook of early childhood intervention. New York: Cambridge University Press; 1990. pp. 119–149. [ Google Scholar ]
• Shore CM. Individual differences in language development. Thousand Oaks, CA: Sage; 1995. [ Google Scholar ]
• Sigman M. What are the core deficits in autism? In: Broman SH, Grafman J, editors. Atypical cognitive deficits in developmental disorders. Hillsdale, NJ: Erlbaum; 1994. pp. 139–158. [ Google Scholar ]
• Sigman M. Improvement in cognitive and language skills from preschool to adolescence in autism. Journal of Autism and Developmental Disorders. 2005; 35 :15–23. [ PubMed ] [ Google Scholar ]
• Singer NG, Bellugi U, Bates E, Jones W, Rossen M. Contrasting profiles of language development in children with Williams and Down syndromes, Project in cognitive and neural development technical report. La Jolla, CA: University of California, San Diego; 1994. [ Google Scholar ]
• Smith SD, Morris CA. Planning studies of etiology. Applied Psycholinguistics. 2005; 26 :97–110. [ Google Scholar ]
• Spiker D, Boyce GC, Boyce LK. Parent–child interactions when young children have disabilities. International Review of Research in Mental Retardation. 2002; 25 :35–70. [ Google Scholar ]
• Spinath F, Price T, Dale PS, Plomin R. The genetic and environmental origins of language disability and ability. Child Development. 2004; 75 :445–454. [ PubMed ] [ Google Scholar ]
• Stone WL, Ousley OY, Yoder PJ, Hogan KL, Hepburn SL. Nonverbal communication in two- and three-year-old children with autism. Journal of Autism and Developmental Disorders. 1997; 27 :677–696. [ PubMed ] [ Google Scholar ]
• Tager-Flusberg H. Do autism and specific language impairment represent overlapping language disorders? In: Rice ML, Warren SF, editors. Developmental language disorders: From phenotypes to etiologies. Mahwah, NJ: Erlbaum; 2004a. pp. 31–52. [ Google Scholar ]
• Tager-Flusberg H. Strategies for conducting research on language in autism. Journal of Autism and Developmental Disorders. 2004b; 34 :75–80. [ PubMed ] [ Google Scholar ]
• Tallal P, Benasich AA. Developmental language learning impairments. Development and Psychopathology. 2002; 14 :559–579. [ PubMed ] [ Google Scholar ]
• Tallal P, Merzenich MM, Miller S, Jenkins W. Language learning impairments: Integrating basic science, technology, and remediation. Experimental Brain Research. 1998; 123 :210–219. [ PubMed ] [ Google Scholar ]
• Thal D, Katich J. Predicaments in early identification of specific language impairment: Does the early bird always catch the worm? In: Cole KN, Dale PS, Thal DJ, editors. Assessment of communication and language. Vol. 6. Baltimore, MD: Paul Brookes; 1996. pp. 1–28. [ Google Scholar ]
• Thal D, Reilly J, Seibert L, Jeffries R, Fenson J. Language development in children at risk for language impairment: Cross-population comparisons. Brain and Language. 2004; 88 :167–179. [ PubMed ] [ Google Scholar ]
• Thelen E, Bates E. Connectionism and dynamic systems: Are they really different? Developmental Science. 2003; 6 :378–391. [ Google Scholar ]
• Thorpe K, Rutter M, Greenwood R. Twins as a natural experiment to study causes of mild language delay. II. Family interaction risk factors. Journal of Child Psychology and Psychiatry. 2003; 44 :342–355. [ PubMed ] [ Google Scholar ]
• Tomasello M, Bates E. Language development: The essential readings. Malden, MA: Blackwell; 2001. [ Google Scholar ]
• Tomblin JB, Hardy JC, Hein HA. Predicting poor communication status in preschool children using risk factors present at birth. Journal of Speech and Hearing Research. 1991; 34 :1096–1105. [ PubMed ] [ Google Scholar ]
• Tomblin JB, Smith E, Zhang X. Epidemiology of specific language impairment: Prenatal and perinatal risk factors. Journal of Communication Disorders. 1997; 30 :325–344. [ PubMed ] [ Google Scholar ]
• Tomblin JB, Zhang X, Weiss A, Catts HW, Weismer SE. Dimensions of individual differences in communication skills among primary grade children. In: Rice ML, Warren SF, editors. Developmental language disorders: From phenotypes to etiologies. Mahwah, NJ: Erlbuam; 2004. pp. 53–76. [ Google Scholar ]
• Torr J. Personality disorder in intellectual disability. Current Opinion in Psychiatry. 2003; 15 :517–521. [ Google Scholar ]
• Tronick EZ, Beeghly M. Prenatal cocaine exposure, child development, and the compromising effects of cumulative risk. Clinics in Perinatology. 1999; 26 :151–171. [ PubMed ] [ Google Scholar ]
• Van Ijzendoorn MH, Dijkstra J, Bus AG. Attachment, intelligence, and language: A meta-analysis. Social Development. 1995; 4 :115–128. [ Google Scholar ]
• Warfield ME, Hauser-Cram P, Krauss MW, Upshur CC. The effect of early intervention services on maternal well-being. Early Education and Development. 2000; 11 :499–517. [ Google Scholar ]
• Weckerly J, Wulfeck B, Reilly J. The development of morphosyntactic ability in atypical populations: The acquisition of tag questions in children with early focal lesions and children with specific language impairment. Brain and Language. 2003; 88 :190–121. [ PubMed ] [ Google Scholar ]
• Wulfeck B, Bates E, Krupa-Kwiatkowski M, Saltzman D. Grammaticality sensitivity in children with early focal brain injury and children with specific language impairment. Brain and Language. 2004; 88 :215–228. [ PubMed ] [ Google Scholar ]
• Yirmiya N, Pilowsky T, Solomonica-Levy D, Shulman C. Gaze behavior and theory of mind abilities in individuals with autism, Down syndrome, and mental retardation of unknown etiology. Journal of Autism and Developmental Disorders. 1999; 29 :333–341. [ PubMed ] [ Google Scholar ]
• Yoder PJ, Hooshyar N, Klee T, Shaffer M. Comparisons of the types of child utterances mothers expand with children with language delays and with Down syndrome. Journal of Intellectual Disability Research. 1996; 40 :557–567. [ PubMed ] [ Google Scholar ]
• Yoder PJ, Warren SF. Maternal responsivity mediates the relationship between prelinguistic intentional communication and later language. Journal of Early Intervention. 1999; 22 :126–136. [ Google Scholar ]
• Yoder PJ, Warren SF. Early predictors of language in children with and without Down syndrome. American Journal on Mental Retardation. 2004; 109 :285–300. [ PubMed ] [ Google Scholar ]
• Zigler E. The retarded child as a whole person. In: Adams HE, Boardman WK, editors. Advances in experimental clinical psychology. Oxford: Pergamon Press; 1971. pp. 47–121. [ Google Scholar ]
• Zukowski A. Investigating knowledge of complex syntax: Insights from experimental studies of Williams syndrome. In: Rice ML, Warren SF, editors. Developmental language disorders: From phenotypes to etiologies. Mahwah, NJ: Erlbaum; 2004. [ Google Scholar ]