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Few, if any, reliable and valid screening tools exist to identify language delay in young Spanish-English speaking dual-language learners (DLLs). The early communication indicator (ECI) is a brief, naturalistic measure of expressive communication development designed to inform intervention decision-making and progress monitoring for infants and toddlers at-risk for language delays. We assessed the accuracy of the ECI as a language-screening tool for DLLs from Latinx backgrounds by completing classification accuracy analysis on 39 participants who completed the ECI and a widely used standardized reference, the Preschool Language Scales, Fifth Edition-Spanish, (PLS-5 Spanish). Sensitivity of the ECI was high, but the specificity was low, resulting in low classification accuracy overall. Given the limitations of using standalone assessments as a reference for DLLs, a subset of participants (n = 22) completed additional parent-report measures related to identification of language delay. Combining the ECI with parent-report data, the specificity of the ECI remained high, and the sensitivity improved. Findings show preliminary support for the ECI as a language-screening tool, especially when combined with other information sources, and highlight the need for validated language assessment for DLLs from Latinx backgrounds.

Universal screening and progress monitoring are evidence-based practices in early intervention/early childhood special education (EI/ECSE). Individual Growth and Development Indicators (IGDIs) for infants/toddlers are measures that programs can use for universal screening, progress monitoring, intervention decision-making, and accountability. Prior to the COVID-19 pandemic, IGDIs were administered and scored exclusively in person by certified early educators. Because of COVID-19, EI/ECSE practitioners could no longer conduct in-person assessments. We report how two early intervention programs implemented IGDIs using remote protocols that included (a) preparation of parents for IGDI administration at home, (b) session observation by program staff using videoconferencing, and (c) remote coding of the child's performance by program staff when interacting with a parent/caregiver play partner using the standard toy set. The remote protocols are described, and uptake by the programs is compared before and during the pandemic. Equivalence of children's scores from in-person versus remote protocols is reported, as well as caregivers' and program staff's preferences. Implications for remote early childhood services are discussed.

One of the earliest indicators of autism spectrum disorder (ASD) is delay in language and social communication. Despite consensus on the benefits of earlier diagnosis and intervention, our understanding of the language growth of children with ASD during the first years of life remains limited. Therefore, this study compared communication growth patterns of infants and toddlers with ASD to growth benchmarks of a standardized language assessment. We conducted a retrospective analysis of growth on the Early Communication Indicator (ECI) of 23 infants and toddlers who received an ASD diagnosis in the future. At 42 months of age, children with ASD had significantly lower rates of gestures, single words, and multiple words, but significantly higher rates of nonword vocalizations. Children with ASD had significantly slower growth of single and multiple words, but their rate of vocalization growth was significantly greater than benchmark. Although more research is needed with larger samples, because the ECI was designed for practitioners to monitor children's response to intervention over time, these findings show promise for the ECI's use as a progress monitoring measure for young children with ASD. Limitations and the need for future research are discussed.

Measures of young children's social development are needed in the Multi-Tier System of Supports (MTSS) approach to early childhood. In 2004, we reported initial development of an observational measure of infants' and toddlers' social skills designed for early educators, the Early Social Indicator (ESI). Here, we report preliminary findings on the ESI's feasibility, sustainability, and sensitivity to growth in social engagement based on a large, multiyear sample of children in one early childhood program that agreed to pilot the measure. Results indicated that ESI use by program staff was sustained over a 5-year period. Program staff were reliable coding a range of children's positive and negative nonverbal and verbal social skills. However, staff were not reliable when coding the target of a child's social response when it was not the Adult play partner (i.e., the Peer, or Nondirected target). Results documented sensitivity to growth over time, dynamic patterns of change within and across key skills consistent with the typical course of social development, and moderation by children's home language and Individual Family Service Plan (IFSP) status. Implications are discussed.

Despite evidence that frequent progress monitoring to identify children at-risk of delays and inform early intervention services improves child outcomes, this practice is rare in infant-toddler settings where children could benefit the most from early intervention. Using a descriptive research design within an Implementation Science framework, we evaluated how 10 community-based infant-toddler agencies implemented a standardized progress monitoring assessment using a web application to monitor children's growth and identify children at-risk for delay. An Implementation Index was developed to quantify implementation progress for each agency, which included their percent of tasks completed, and rate of task implementation over time. Staff turnover and high staff:child ratios were associated with low implementation of progress monitoring. The Implementation Index differentiated between agencies that otherwise demonstrated similar implementation rates. Implications for supporting progress monitoring and other evidence-based practices in community-based infant--toddler childcare settings are discussed.

While technology-based interventions enhance instruction and improve outcomes for students with disabilities, implementing and integrating technology in authentic learning environments continues to be a challenge. Based on the experiences of a variety of Stepping-Up Technology Implementation projects funded by the U.S. Department of Education, Office of Special Education Programs, this mixed-methods study explored the essential factors for the successful implementation of technology-based interventions in K-12 schools and early childhood programs. Based on the qualitative analysis of projects' implementation reports and responses to the follow-up questionnaire, four major themes emerged. The barriers and facilitators to technology implementation were reported across such areas as (a) developing and sustaining buy-in, (b) ensuring implementation fidelity to support the intervention, (c) research-to-practice dilemmas, and (d) data serving multiple purposes. The discussion and practical implications for supporting technology implementation are provided.

Data-driven decision making (DDDM) helps educators identify children not responding to intervention, individualize instruction, and monitor response to intervention in multitiered systems of support (MTSS). More prevalent in K-12 special education, MTSS practices are emerging in early childhood. In previous reports, we described the Making Online Decisions (MOD) web application to guide DDDM for educators serving families with infants and toddlers in Early Head Start home-visiting programs. Findings from randomized control trials indicated that children at risk for language delay achieved significantly larger growth on the Early Communication Indicator formative language measure if their home visitors used the MOD to guide DDDM, compared to children whose home visitors were self-guided in their DDDM. Here, we describe findings from a randomized control trial indicating that these superior MOD effects extend to children's language growth on standardized, norm-referenced language outcomes administered by assessors who were blind to condition and that parents' use of language promotion strategies at home mediated these effects. Implications and limitations are discussed.

The Early Communication Indicator (ECI) is a progress monitoring measure designed to support intervention decisions of the home visitors and early educators who serve infants and toddlers. The present study sought to add to the criterion validity claims of the ECI in a large sample of children using measures of language and preliteracy not previously investigated. Early Head Start service providers administered and scored ECIs quarterly for infants and toddlers in their caseload as part of standard services. In addition, a battery of language and early literacy criterion tests were administered by researchers when children were 12, 24, 36, and 48 months of age. Analyses of this longitudinal data then examined concurrent and predictive correlational patterns. Results indicated that children grew in communicative proficiency with age, and weak to moderately strong patterns of relationship emerged that differed by ECI scale, age, and criterion measure. The strongest positive patterns of relationships were between Single Words and Multiple Words and the criterion at older ages. Gestures and Vocalizations established a pattern of negative relationships to the criterion measures. Implications for research and practice are discussed.

Engaging, focusing, and persisting in the completion of tasks are among the skills needed for school success. Tracking whether a child is learning cognitive problem-solving skills is essential in knowing if they are acquiring skills important for development and school readiness; and if not, how they are responding to early intervention. Use of the Early Problem-Solving Indicator (EPSI) was documented by data for 2,614 children (6-42 months of age) collected by the early childhood staff from 45 programs. Results indicated that the EPSI was (a) scalable across programs, assessors, and assessment occasions, (b) reliable, (c) sensitive to growth over months of age, (d) comprised a dynamic continuum of skills within and across skills over time, and (e) moderated by children's disability status but not gender or home language. Implications for research and practice are discussed.

Programs serving infants and toddlers are expected to use child data to inform decisions about intervention services; however, few tools exist to support these efforts. The Making Online Decisions (MOD) system is an adaptive intervention that guides early educators' data-based intervention decision making for infants and toddlers at risk for language delay. Using a cluster randomized design to test the effect of the MOD, home visitors (HVs) were assigned to either use the MOD or not across 13 Early Head Start programs. Both groups used the Early Communication Indicator (ECI) for progress monitoring and a parent-mediated language promotion intervention. Children from both groups demonstrated significant growth in expressive communication. However, children whose HVs fully implemented the MOD grew significantly more than the group that did not use the MOD, even after statistically controlling for parent and HV variables. Implications for designing effective and usable systems to promote the use of data-based decision-making practices by infant-toddler service providers are discussed, as well as limitations of the current study.

Universal screening and progress monitoring measures are increasingly of interest to early interventionists who make decisions about the services provided to young children. A measure of infant-toddlers' growth in early movement, the "Early Movement Indicator" ("EMI"), was reported in 2002. However, the EMI has remained an experimental measure based on a small sample and not used broadly by practitioners in real-world programs. We addressed this limitation by advancing knowledge the EMIs scalability through a website and improved psychometrics in a large sample. Results indicated that the EMI was (a) scalable evidenced by a large volume of early childhood staff users in programs in five states with 628 children and 2,258 individual EMI assessments, (b) sensitive to growth over time, (c) comprised of a complex continuum of skill development, and (d) influenced by moderators (i.e., home language, Individual Family Service Plan [IFSP] status). Implications for research and practice are discussed.

For children with normal hearing (NH), early communication skills predict vocabulary, a precursor to grammar. Growth in early communication skills of infants with cochlear implants (CIs) was investigated using the Early Communication Indicator (ECI), a play-based observation measure. Multilevel linear growth modelling on data from six ECI sessions held at three-monthly intervals revealed significant growth overall, with a non-significant slower growth rate than that of children with NH (comparison age centred at 18 months). Analyses of gesture use and of nonword vocalisations revealed the CI group used significantly more of each, with more rapid growth. In contrast, the CI group used significantly fewer single words and multiword utterances, and with slower growth. Maternal education and time to achieve consistent CI use impacted significantly on growth for the CI sample. The results indicate that progression to vocabulary by young CI users can be supported by encouraging their use of prelinguistic communication.

Purpose: We sought to conduct a pilot investigation of the reliability and administration fidelity of a new play-based measure of social communication for infants and toddlers with an autism diagnosis. Method: Our team adapted an existing measure, the Early Communication Indicator (ECI), for use with young autistic children in clinical and research contexts. In this brief report, we detail our adaptation process including administration and scoring of the final adapted measure based on data from a two-phase pilot study with young autistic children (N = 17). Results: This adapted measure, the Early Communication Indicator-Autism (ECI-A), captured a range of scores for the ECI, Initiation of Joint Attention, and Directed Communication in pilot testing. Interrater reliability was moderate to strong across the scored behaviors. Finally, parents were able to administer the ECI-A with high fidelity with support from the research staff. Conclusions: This two-phase pilot study demonstrated promise for the ECI-A as a brief measure of social communication that can be administered by parents and reliably scored by trained staff with limited background in autism assessments. Validation of the ECI-A is presently underway. [ABSTRACT FROM AUTHOR]

Effectively scaling up evidence-based educational practices requires identification of barriers to the wide-scale implementation and maintenance of such practices at a distance from the original research and development team. The two studies reported here investigated the implementation of ClassWide Peer Tutoring (CWPT) in nine schools across five states. In Study 1, implementation was measured in terms of the percentage of teachers who completed the tasks required to conduct CWPT and the research protocol. Factors were identified that may have contributed to implementation variability across schools. In Study 2 we used "rate of implementation" as the implementation measure in an effort to assess the degree to which the factors identified in Study 1 affected implementation across a larger group of schools. Barriers were classified as Strong, Weak, or Non-Barriers. Implementation barriers included limited communication between practitioners and research staff, lack of support for CWPT from school and/or district leaders, and unexpected changes in school administrative responsibilities or staffing. Strategies for overcoming these barriers and the need for additional implementation research are discussed. (Contains 4 tables and 5 figures.)

Early childhood is an opportune time to begin teaching STEM, and preschool education provides the opportunity. How children experience and respond to STEM in community‐based preschools is our focus. Using the CIRCLE classroom observation system, we examined how frequently and in what contexts preschool teachers provided STEM learning opportunities, and how children responded using quantitative–descriptive methods. Data were collected in 39 low‐socioeconomic status (SES), community‐based preschool classrooms on a stratified sample of 117 children that included mono‐English speaking children, dual language learners, and children with a diagnosed disability. Results indicated that children were exposed to nonacademic content 71% of the observed time. In contrast, STEM instruction occurred only 7% of the time, or about 6 min of our 90 min observation on a given day. When teachers provided STEM content, the probability that children were academically engaged was 0.57 compared with only 0.08 during nonacademic content. There were no statistically significant differences in STEM academic content received between girls and boys, children with versus without an Individualized Education Program (IEP), and English‐only speakers versus dual language learners. However, dual language learners were significantly less engaged during STEM than English‐only speakers. Implications are discussed. [ABSTRACT FROM AUTHOR]

Speech and language development are early indicators of overall analytical and learning ability in children. The preschool classroom is a rich language environment for monitoring and ensuring growth in young children by measuring their vocal interactions with teachers and classmates. Early childhood researchers are naturally interested in analyzing naturalistic vs controlled lab recordings to measure both quality and quantity of such interactions. Unfortunately, present-day speech technologies are not capable of addressing the wide dynamic scenario of early childhood classroom settings. Due to the diversity of acoustic events/conditions in such daylong audio streams, automated speaker diarization technology would need to be advanced to address this challenging domain for segmenting audio as well as information extraction. This study investigates alternate deep learning-based lightweight, knowledge-distilled, diarization solutions for segmenting classroom interactions of 3–5 years old children with teachers. In this context, the focus on speech-type diarization which classifies speech segments as being either from adults or children partitioned across multiple classrooms. Our lightest CNN model achieves a best F1-score of ∼76.0% on data from two classrooms, based on dev and test sets of each classroom. It is utilized with automatic speech recognition-based re-segmentation modules to perform child-adult diarization. Additionally, F1-scores are obtained for individual segments with corresponding speaker tags (e.g., adult vs child), which provide knowledge for educators on child engagement through naturalistic communications. The study demonstrates the prospects of addressing educational assessment needs through communication audio stream analysis, while maintaining both security and privacy of all children and adults. The resulting child communication metrics have been used for broad-based feedback for teachers with the help of visualizations. [ABSTRACT FROM AUTHOR]

Families in rural or remote areas have limited access to evidence-based intervention for their children with autism. Using web-based training and telemedicine technology, the current study investigated the feasibility of training seven parents to implement Applied Behavior Analysis (ABA) strategies with their children with autism. In this exploratory formative evaluation, parents increased their knowledge of ABA strategies and concepts by an average of 39 percentage points, and improved their implementation of ABA strategies with their children by an average of 41 percentage points. A total of 9,052 driving miles were saved across the four families. Implications for families living in remote areas, improvements in the training program, and future research directions are discussed.

Measurement in early childhood is an increasingly large-scale endeavor addressing purposes of accountability, program improvement, child outcomes, and intervention decision making for individual children. The Early Communication Indicator (ECI) is a measure relevant to intervention decision making for infants and toddlers, including response to intervention approaches. The widespread use of the ECI is growing in multiple programs and states. Local program staff members collect ECI data and, with their program directors, manage their own system of ECI measurement. Program-level implementations represent independent ECI measurement replications, and the success of each potentially influences the quality of data produced and, ultimately, the validity of the inferences made thereof. The purpose of this research was to examine program-level influences on child-level ECI total communication growth and 36-month outcomes in a large sample of children, including those with individual family service plans served by multiple Early Head Start programs in two states. Results indicated variation in programs' sociodemographic composition, ECI implementation quality, ECI total communication growth, and 36-month outcomes. Program-level sociodemographic composition was found not to be an influence on ECI growth or 36-month outcomes, whereas state location and implementation quality were. Implications are discussed. (Contains 6 notes, 7 tables, and 3 figures.)

The purpose of this research was to replicate and extend some of the findings of Hart and Risley using automatic speech processing instead of human transcription of language samples. The long-term goal of this work is to make the current approach to speech processing possible by researchers and clinicians working on a daily basis with families and young children. Twelve hour-long, digital audio recordings were obtained repeatedly in the homes of middle to upper SES families for a sample of typically developing infants and toddlers (N = 30). These recordings were processed automatically using a measurement framework based on the work of Hart and Risley. Like Hart and Risley, the current findings indicated vast differences in individual children's home language environments (i.e., adult word count), children's vocalizations, and conversational turns. Automated processing compared favorably to the original Hart and Risley estimates that were based on transcription. Adding to Hart and Risley's findings were new descriptions of patterns of daily talk and relationships to widely used outcome measures, among others. Implications for research and practice are discussed. (Contains 1 table and 3 figures.)

We investigated Early Head Start home visitors' use of evidence-based practices and the effectiveness of a web-based system to support these practices. Home visitors learned to use 3 evidence-based practices: (a) frequent assessment of children's early communication for screening and progress monitoring, (b) 2 home-based language promoting interventions, and (c) data-based decision making in the use of the language promoting intervention strategies. We randomly assigned 1 group of home visitors to use an online data collection system and receive training in data-based intervention decision making and in the evidenced-based language interventions. The other home visitors had access to these tools and trainings, but in addition, they had web-based support (Making Online Decisions; MOD) linked to the children's expressive communication data. We found that the expressive communication of children served by home visitors who used the MOD grew significantly more than children whose home visitors did not have MOD support. Home visitors who used the MOD reported high satisfaction with its use. Future research and implications for early intervention and home visiting practices are discussed. (Contains 2 figures.)

We investigated Early Head Start home visitors' use of evidence-based practices and the efficacy of a web-based system to support these practices. Home visitors learned to use 3 evidence-based practices: (a) frequent assessment of children's early communication for screening and progress monitoring, (b) 2 home-based language-promoting interventions, and (c) data-based decision making in the use of the language-promoting intervention strategies. Two conditions were compared in a randomized control trial. Condition A involved the use of an online data collection system, training in data-based intervention decision making, and training in the evidenced-based language interventions. Condition B was the same as A plus additional web-based support (MOD: Making Online Decisions) linked to the children's expressive communication data. Results indicated that the expressive communication of children receiving MOD support grew significantly more than for children whose home visitors did not receive MOD support. Home visitors in both groups increased their monitoring of children in need of intervention. The dosage of the MOD intervention that children received varied within the group, and MOD home visitors reported high levels of implementation fidelity and satisfaction with the MOD system. Future research and implications for early intervention and home-visiting practices are discussed. (Contains 2 figures, 7 tables and 1 note.)

The Early Communication Indicator (ECI) is a measure relevant to intervention decision making and progress monitoring for infants and toddlers. With increasing recognition of the importance of quality early childhood education and intervention for all children, measurement plays an important role in documenting children's progress and outcomes of early educational experiences. Screening and progress-monitoring measures used in a response-to-intervention approach require age-based benchmarks for decision-making support. The goal of this study was to create a normative sample of ECI data referenced to children served by Early Head Start, including children with Individualized Family Service Plans (IFSPs). In a large sample of children (N = 5,883), program staff in 27 Early Head Start programs in two states collected ECI data from 2002 to 2007. Results indicated that children's ECI total communication growth was conditional on IFSP status but not on gender or home language (English versus Spanish). Children's patterns of communication on the ECI key skill elements (i.e., gestures, vocalizations, single words, and multiple words) were also conditional on IFSP status. Children with IFSPs had (a) later ages of onset for vocalizations, single words, and multiple words; (b) generally slower growth over time; and (c) significantly lower mean levels in the most advanced key skill: multiple words at 36 months of age. Implications for early childhood researchers and service providers are discussed. (Contains 6 notes, 6 tables, and 3 figures.)

Progress monitoring and data-based intervention decision making have become key components of providing evidence-based early childhood special education services. Unfortunately, there is a lack of tools to support early childhood service providers' decision-making efforts. The authors describe a Web-based system that guides service providers through a decision-making process informed by child performance on Infant and Toddler IGDIs (Individual Growth and Development Indicators), the provider's professional judgment, and information from the child's primary caregiver. Using a case example, the authors describe how a service provider integrates the system into an existing service delivery model. Finally, they describe barriers and potential solutions to implementation within the context of a traditional early childhood service delivery model and implications for policy and practice. (Contains 5 figures.)

Few evidence-based instructional practices achieve large-scale use, often remaining only in the schools directly involved in their development. Research on scaling up effective educational practice often lacks sensitive measures of the practice's implementation and the required research protocol. This article describes how we used rate of implementation as a sensitive measure to help identify barriers to implementation of class-wide peer tutoring (CWPT). Using communication technologies and a learning management system, we monitored the rate of CWPT implementation and its research protocol across nine schools in five states. Rate of implementation was defined as the number of weeks in which a school successfully completed the 12 implementation tasks required to reach full implementation. We discuss factors related to the variation in implementation rate (30-50 weeks) between schools, and implications of this measurement strategy for research on instructional practices and the technology used to facilitate scalability research.

The authors developed and evaluated an online foster parent training system designed specifically for low-bandwidth Internet connections and individuals with limited Internet/computer experience. After preliminary onsite evaluations, a 2-week field test was conducted to evaluate the following dimensions: foster parents' pre- to post-test scores on two training modules; user satisfaction ratings; foster parent dropout rate; and amount of communication between participants and researchers. Foster parents made statistically significant pre-/post-test gains in both content areas (Pre-test M[1] = 46.6%, Post-test M[1] = 86.4; Pre-test M[2] = 46.6%, Post-test M[2] = 92.6%), both foster parents and social workers gave the system high ratings on all satisfaction survey items, and the foster parent dropout rate was 27%. Future research and implications for the foster care system are discussed. (Contains 3 figures and 4 tables.)

The purpose of this paper is to describe the role of computer and information technology in scaling up research-validated instructional strategies like ClassWide Peer Tutoring (CWPT). Recently, implementation software, the CWPT Learning Management System, web and e-mail communications, and interactive multimedia resources have been developed to support teachers' and schools' use of CWPT. Preliminary findings suggest that this technology improves access and use of CWPT, and that when local school factors of implementation are in place, improvement in student academic scores replicate past CWPT results. Results suggest that the initial and ongoing professional development, the strength of local school leadership, and a building faculty's ability to work with information technology are key elements to widespread implementation and accelerated student learning. The implications of such are discussed.

The usability of classroom interventions plays a significant role in the likelihood that they will reach wide scale use. The current report describes the usability testing of a software application designed for ClassWide Peer Tutoring (CWPT), a research-based classroom intervention. Initially, CWPT teachers rated the usability of the software and indicated how they used it in their classrooms. Then, teachers were observed completing seven common activities with the software. The following usability data were collected during the activities: how many teachers requested help and reported problems, what part of the software caused problems and prompted requests for help, and the time to complete activities. A part of the software was considered "difficult to use" if 40% or more teachers requested help with it or reported problems. After identifying the difficult-to-use parts of the software, the nature of the problem and how to correct it was assessed by reviewing teachers' specific questions and problems. Findings suggest that the software's usability ratings were much higher than its observed usability. The implications of usability evaluations beyond subjective ratings are discussed in terms of how to improve the scalability of educational interventions and technology. (Contains 1 table and 7 figures.)

We compared online study guides to pen-and-paper study guides in terms of academic performance, the amount of time instructors spent grading study guides, and student preferences. Students in 3 sections of a child psychology course used online study guides (n = 46), and students in 3 other sections used pen-and-paper study guides (n = 64). Instructors spent 14.3 hr during the semester grading the pen-and-paper study guides and no time grading the online study guides. Students who used the online study guides reported higher satisfaction than the students who used pen-and-paper study guides. Our results suggest that integrating online study guides saved labor costs and increased student satisfaction while maintaining student performance.