The Early ON School Readiness Project: a preliminary report.

Abstract. The Early ON School Readiness Project is an emerging community-based model aimed at promoting the school readiness of 3- to 5-year-old children in a metropolitan area with a predominantly Latino (Mexican-American) population. Using an ecological approach, the multi-component program seeks to enhance school readiness opportunities for children at various levels. Key program components aim to improve community awareness, parent education, professional development for child care teachers, quality of child care environments, and transition to school. The model evolved through a community partnership initiated by the local government, involving nonprofit agencies and a university partnership. Child care environmental quality was measured by administration of the Early Childhood Environment Rating Scale-Revised Edition (ECERS-R; Harms, Clifford, & Cryer, 1998). To measure children's progress, the Developmental Indicators for the Assessment of Learning-Third Edition (DIAL-& Mardell-Czudnowski & Goldenberg, 1998) was administered in the fall and spring of two consecutive school years. A sample of children was screened to gain insight regarding the developmental status of children in the project compared to a matched sample of children not involved in the project. Preliminary findings show the progress of children in key developmental areas during the initial and second year of program implementation in selected child care centers. In the baseline year, standard scores of children at the comparison sites were unchanged from fall to spring in all of the developmental areas measured by the DIAL-3; scores at the intervention sites, however, were higher at a statistically significant level for two subtests and the composite score. During the second year, all subtest scores and the composite scores were higher at the intervention sites in the spring as compared to the fall. Although additional research is needed, preliminary results suggest the emerging model shows promise for increasing children's developmental skills and abilities associated with school readiness.

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Major paradigm shifts in national policy and priorities, along with increased accountability for schools, have brought the issue of school readiness to the forefront. As a result, calls for public investment in early education have led communities across the United States to become more active in developing programs to enhance the school readiness skills and abilities of all children (Shonkoff, 2004). Local policymakers have launched efforts to meld policy and programmatic arenas into cohesive frameworks of support for families with preschool-age children (Knitzer, 2002; Murphey & Burns, 2002; Weigel & Martin, 2006). Social and economic motivation to improve the quality of care and educational contexts for young children has remained high (Brauner, Gordic, & Zigler, 2004). Accordingly, many local governments have created policy and forged new alliances among community agencies and early childhood programs. Initiating new relationships among governmental entities and fostering community partnerships are strategies purported to hold promise for better child outcomes (Kagan & Neuman, 2003).

Technological advances in the neurosciences also have stirred interest in early learning and school readiness. Brain imaging research has provided insight into how the architecture of the brain develops and has underscored the importance of stimulating brain development early in a child's life. Technology has revealed that a child's brain undergoes a hierarchical maturation process, first establishing lower level skills as a foundation for the later acquisition of more complex skills. The optimal time to influence neural development is during early childhood, when neurons are making connections, or "synapses," at an amazing rate. Increasing evidence supports the theoretical perspective that brain development is influenced by both nature and nurture. While nature provides children with their biological and genetic characteristics, early experience can shape the expression of genes, thereby influencing the development of specific neural circuits. Clearly, the architecture of the brain is influenced by early experience and stimulation provided in children's physical and social environments. While poor-quality environments with insufficient stimulation can inhibit brain development, a stimulating environment promotes neural development and early learning, even when children are at risk for poor developmental outcomes (Bergen & Coscia, 2001; D'Arcangelo, 2003; Knudsen, Heckman, Cameron, & Shonkoff, 2006; Shonkoff & Phillips, 2000). Brain imaging technology has also provided an opportunity to examine the effects of socioeconomic status, race, and ethnicity on brain development. Although studies are limited, preliminary results suggest that racial disparities in cognitive development and school achievement may be mediated by socioeconomic status. Rather than being attributable to race or ethnicity, developmental and achievement differences appear to be associated with the negative effects of poverty on brain development (Noble, Tottenham, & Casey, 2005).

Quality of Early Learning Environments

Evidence substantiates that learning environments play a key role in nurturing children's development and stimulating early learning. Consequently, there has been much interest in identifying specific contextual factors that might exert the greatest impact on children's attainment of school readiness skills and abilities. Large-scale, national studies have been instrumental in establishing a strong association between high-quality programs and better developmental outcomes in the cognitive and language domains, two areas considered foundational to academic success (Belsky, 2001; Fuller, Kagan, Loeb, & Chang, 2004; Peisner-Feinberg et al., 2000; Shonkoff & Phillips, 2000). The Cost, Quality, and Outcomes in Child Care Centers Longitudinal Study established the importance of high-quality child care to ensure children's school readiness and better long-term academic achievement (Peisner-Feinberg et al., 2000). The National Institute of Child Health and Human Development (NICHD) longitudinal studies have provided corroborating evidence that high-quality child care is a strong predictor of children's cognitive attainment, language performance, and school readiness skills but is not predictive of social ability. Moreover, the NICHD studies reported these predictions held true regardless of children's personal characteristics and family heritage (National Institute of Child Health and Human Development [NICHD] Early Child Care Research Network, 2002, 2003, 2004, 2005). The national study of Early Head Start programs also reported positive results for children's cognitive, language, social, and behavioral outcomes (Love et al., 2005). In Great Britain, the Effective Provision of Pre-school Education (EPPE) study provided strong evidence of a positive correlation between school readiness and preschool attendance (Sammons et al., 2004).

The enduring effects of high-quality programs regarding children's achievement are important to school success. Longitudinal studies indicate that children who attend high-quality preschool programs tend to gain cognitive advantages, such as higher achievement in math and reading, once they enter school. Moreover, children appear to maintain a higher performance across time compared to peers who do not attend high-quality programs (Gormley Jr., Gayer, Phillips, & Dawson, 2005; Magnuson, Meyers, Ruhm, & Waldfogel, 2004; Ou, 2005). Recent follow-up analyses of the NICHD Study of Early Child Care and Youth Development (SECCYD) reported a strong relationship between high-quality preschool experience and better vocabulary in the elementary grades. These findings further substantiate the association of high-quality child care with positive outcomes in children's language development (Belsky et al., 2007).

Inequities in access to high-quality care have been well-documented. One study reported that only 10 percent of child care centers studied were rated as excellent (NICHD Early Child Care Research Network, 2000). These findings corroborated earlier reports that raised concerns about accessibility of high-quality care and the general lack of research that would provide insight regarding the effects of low to mediocre child care (Belsky, 2001; Cost, Quality and Child Outcomes Study Team, 1995; Magnuson et al., 2004; Vandell, 2004). Less is known about the effects of poor to mediocre quality care or whether these environments can properly support the growth and development of children, especially those at risk of developmental delays (Buysse, Wesley, Bryant, & Gardner, 1999; Wolery, Brashers, & Neitzel, 2002). Mounting evidence suggests that large numbers of children experience substandard care that may be detrimental to their learning. Further, when care of lesser quality is center-based, children appear to be particularly at risk of developing persistent behavioral problems (Belsky et al., 2007).

Attending better quality early childhood programs may be especially critical for children who are economically disadvantaged and for those who are at risk for developmental delays (Peisner-Feinberg et al., 2001; Peisner-Feinberg et al., 2000; Pigott & Israel, 2005; Sammons et al., 2004). There is evidence that quality may exert a stronger influence on the outcomes of children in poverty compared to those in higher income families (Burchinal et al., 2000; Hubbs-Tait et al., 2002). Yet, low-income families are less likely to enroll their children in center-based educational settings. One explanation is that families in poverty often lack sufficient access to the high-quality centers that might improve educational support for children when family resources are meager. Inequitable access can widen the gap in school readiness experienced by poor children, who might benefit from high-quality educational experiences to stimulate cognitive and language development. Children who attend high-quality preschool programs may gain lasting advantages that improve their chances for success throughout their schooling, such as less retention and higher math and reading achievement (Hoff, 2003; Magnuson et al., 2004; Weigel & Martin, 2006). The link between high-quality learning environments and positive developmental outcomes for children has led to widespread calls for communities to take action and make investments in improving the quality of child care as a strategy to promote school readiness (Brauner et al., 2004; Pianta, 2007).

Learning and Latino Children

Latino children constitute the largest child minority population in the United States. According to the U.S. Census, Latinos are the largest and fastest growing minority group in the United States, with a growth rate exceeding that of the nation. However, for some Latino children, high poverty rates and other risk factors threaten their chances for academic success (Morse, 2003; National Center for Education Statistics, 2005; United States Census Bureau, 2006). Studies have reported that children from low-income, minority families enter school less prepared and lacking the fundamental skills to succeed (Lee & Burkam, 2002; McLanahan, 2005). While growing numbers of children in the United States are enrolling in preschool programs, disparities still exist (Pianta, 2007). Children from advantaged homes are enrolled in early childhood programs at a higher rate than children from disadvantaged homes, resulting in a school readiness gap (Magnuson et al., 2004). Latino children, less likely to be enrolled in early childhood programs compared to other children, are often caught in the school readiness gap. Recruiting Latino families into early childhood programs and improving the quality of programs attended by Latino children are among two strategies that could help close the gap (Collins & Ribeiro, 2004; Magnuson & Waldfogel, 2005; Morse, 2003). Unfortunately, even if efforts to close the gap are successful, Latino children and their families may still face potential barriers. For example, despite the rapidly increasing Latino population in the United States, the number of bilingual and Latino early childhood professionals in the field is insufficient to meet the rising need. Inadequate preparation for teaching in culturally and linguistically diverse early childhood classrooms is also detrimental to children's success. Failure to address differences in culture and language can hamper home-school communication, limit parental participation, and make relationships between teachers and Latino families cumbersome (Buysse, Castro, West, & Skinner, 2005; Collins & Ribeiro, 2004).

Considerable attention has been focused on reducing risk factors for minority children and identifying ways to improve their chances for success in school. Variations in child care quality and accessibility may limit minority children's educational opportunities and result in poor achievement once these children enter school (Pianta, 2007). Experts have stressed that serious action is needed toward upgrading the quality of child care systems, especially those serving racial and ethnic minorities in the United States. It is critical to identify ways to help parents succeed as the first teachers of their children, especially when parents may face barriers to achieving their own literacy (Cassidy et al., 2004).

Research suggests certain program characteristics and practices may be advantageous in preparing Latino children for school. For instance, providing a culturally responsive program with appropriate levels of family support can help Latino preschoolers improve their school readiness skills and abilities (Gormley Jr. et al., 2005; Ryan, 2005). Relationships with Latino parents may be enhanced when early childhood professionals receive staff development aimed at improving cultural competence and sensitivity (Collins & Ribeiro, 2004). Programs characterized as comprehensive, using multiple strategies and components, appear to better prepare Latino children for success in school, compared to programs with less comprehensive approaches (Buysse et al., 2005; Pigott & Israel, 2005; Ryan, 2005). These strategies are recommended to help bridge the cultures of home and school to better ensure the school readiness of Latino children.

Purpose

The purpose of this study was exploratory in nature and intended to examine the efforts of an emerging city-wide program aimed at improving the school readiness of young children in a predominantly Latino (Mexican American) population. We are reporting preliminary data collected during the baseline and one subsequent year as the new program emerged. Consequently, the purposes for this study were twofold: 1) to gain insight into the overall quality of the child care center environments experienced by children in the Early ON School Readiness Project, and 2) to sample the developmental progress of children enrolled in the program.

Method

Participants

The participants were children, ages 3-5, from predominantly Mexican American families whose average income was approximately $20,000. Acculturation questions revealed that the majority of the families preferred to speak English at home and reported their children's first language as English. The parental age range most frequently reported was from 20 to 29 years, with the highest educational attainment reported as high school. The children were enrolled in child care centers located across San Antonio, Texas, a large metropolitan city in the southwestern United States. The population served by each center included children whose families qualified for a level of subsidized care assistance.

The Program

Emergence of Program. The Early ON program was launched as part of a community development initiative to achieve broad, systemic change through activities designed to strengthen families and improve the future workforce. Similar to other community-based early childhood projects, the Early ON program can be described as emergent rather than explicit and preplanned. Emergent programs often evolve through community partnerships and are informed by empowered stakeholders who know the needs and culture of the community (Buysse, Wesley, & Skinner, 1999; Hurd, Lerner, & Barton, 1999; Kaplan & Larkin, 2004). In this case, the local government initiated a community-university partnership consisting of nonprofit community agencies, school districts, and the University of Texas at San Antonio. The community agencies and one of the school districts were contracted to facilitate implementation of the program in child care centers selected for participation in the program. The key role of the University of Texas at San Antonio was to conduct formative research to examine the process of program development and summative research studies to examine the impact of the emerging program. Monthly meetings of the community-university partnership served as a forum for consensus building as a common set of program strategies evolved. From the collaborative vision and effort of the community-university partnership, a comprehensive, multi-component model program, the Early ON School Readiness Project, emerged.

Key Intervention Strategies. Based on an ecological approach, the program consisted of strategies aimed at layers of contexts: community, home, child care, and the next school setting, kindergarten. Five key intervention strategies emerged: 1) Community Awareness--A media campaign was launched with public service announcements to encourage parents to be the first teachers of their children. Brochures with school readiness guidelines for parents in both English and Spanish were distributed. 2) Parent Education--In Year 1, monthly sessions on school readiness topics were held at child care centers. In Year 2, the community agencies agreed upon a common set of topics and content for the sessions. 3) Teacher Professional Development--In Year 1, individual community agencies made decisions about the content and number of sessions. Teachers received professional development typical of most community-based programs. In Year 2, the agencies decided to provide five half-day workshops on literacy development to all teachers in the project. 4) Child Care Quality--In Year 1, Early ON community agencies provided technical assistance to improve the overall environment and teaching practices at centers. In Year 2, the community agencies gave increased emphasis on ensuring that all centers had materials to promote literacy development. 5) Transition to School--Child care teachers met with kindergarten teachers at the neighborhood elementary school several times a year to become acquainted and to plan a smooth transition process.

Study Design

The sites for the study were child care centers selected to participate in the Early ON School Readiness Project. As is typical of most communities, the centers varied in type from federally funded Head Start, nonprofit, and faith-based centers to proprietary child care facilities. During the first year of the project, the authors collected data to establish a baseline for subsequent years. This preliminary examination focused on two aspects of the program. First, we examined child care center quality at the beginning and end of each school year, using a descriptive approach. Second, we assessed the progress of children, using a quasi-experimental pretest, posttest comparison group design. A new cohort of children was examined each year.

Procedures

Center Quality. To measure the overall quality of the child care environments, we administered the Early Childhood Environment Rating Scale-Revised Edition (ECERS-R; Harms et al., 1998), widely used in early childhood research to measure global quality of child care centers. The ECERS-R yields a total score and seven subscale scores: Space and Furnishings, Personal Care Routines, Language-Reasoning, Activities, Interaction, Program Structure, and Parents and Staff. Rating scores on the ECERS-R range from 1.0 to 7.0, with 1.0 being considered "inadequate" and 7.0 considered to be "excellent." Research staff and university students were trained as raters to administer the ECERS-R. Raters received three hours of intensive training from a research coordinator with a master's degree in education who followed recommended training protocols, including item-by-item discussions and practice coding with the ECERS-R videotaped training. According to the ECERS-R authors, interrater internal consistency coefficients range from 0.71 to 0.88 for the subscales and 0.92 for the total environment score. Therefore, an interrater reliability of 80 percent agreement among pairs of raters was established before data collection began in the child care centers. The procedure for establishing interrater reliability consisted of paired raters administering the ECERS-R in child care classrooms, simultaneously. Ratings that were identical were counted as an agreement. If raters failed to achieve 80 percent agreement, they discussed disparities and attempted to establish the required level of interrater reliability in another set of observations.

The ECERS-R scale was administered at each center during the fall and spring. Interview items were addressed to center personnel and two hours of observation at the center was necessary to complete observational items. ECERS-R was administered in the morning hours to ensure that most of the children would be present and engaged in program activities. However, Buell and Cassidy (2001) have urged consideration of the Complex Dynamical Systems Theory, also known as the Chaos Theory, when evaluating child care centers, to account for subtle changes and fluctuations in program quality across time. Following their recommendation, we avoided the single "snapshot" approach and endeavored to administer the ECERS-R at least twice at each center, averaging the scores to obtain a mean. In Year 1, there were 17 centers, and in Year 2 the project had doubled to 34 centers in the program, necessitating a higher number of observations for the ECERS-R assessment.

Children's Progress. The Developmental Indicators for the Assessment of Learning-Third Edition (DIAL-3) (Mardell-Czudnowski & Goldenberg, 1998) was administered to children at the child care centers in the study during the fall and spring of each school year. The DIAL-3 provides subtest scores in the development categories of Motor (gross and fine motor development), Concepts (knowledge of such basic concepts as counting and colors), and Language (use of receptive and expressive language), as well as an Overall Composite score. Each of the standard scores and the overall composite score has a mean of 100 and an SD of 15. The DIAL-3 can be team- or individually administered, and each of the three content areas has up to 10 questions (there are basals and cutoffs, and the test requires approximately 15 minutes to administer). According to the publisher, the DIAL-3 has internal consistency coefficients that range from 0.66-0.87. Results from concurrent validity studies suggest that scores from this test can be considered an adequate measure of early childhood development across the constructs represented.

To gain insight into the developmental progress of children, a sample of approximately one-quarter of the children in the intervention sites was selected for administration of a developmental assessment each year of the study. Each year, the investigators used a judgment sample of children thought to be representative of four geographic quadrants of the city. Children from 10 child care centers in Year 1 and 11 child care centers in Year 2 were assessed. Four matched comparison sites were selected from child care centers not involved in the intervention program. These sites were located in each of the four quadrants of the city and matched on major characteristics of intervention centers in those areas. The DIAL-3 was administered during the baseline year of the project at the intervention sites and comparison sites. The test was again administered during the second year of the project at the intervention sites. Tests were administered during the fall and spring of each school year, during the morning hours so as not to take place immediately before or after nap time.

University students participated in data collection by administering the DIAL-3. Prior to on-site data collection, students were provided with three hours of intensive training that conformed to training procedures recommended in the test manual. Staff members with master's degrees administered the test and answered questions posed by the students. Students also practiced using a DIAL-3 training video and administered the test to one another. A team administration of the DIAL-3 was used at the child care centers so that university students could be supervised by research staff. As members of the team, students had an opportunity to observe and work alongside staff members. To ensure accuracy of administration and scoring, students could ask any questions that might have arisen during test administration.

Analysis

Analysis was conducted using the SPSS statistical analysis package. Analysis of the quality of the child care environments was conducted by generating descriptive statistics, mean and standard deviations for each subscale, and the total for the ECERS-R instrument to compare fall and spring scores each year. To analyze children's progress, descriptive statistics, including the mean and standard deviations, were calculated using standard scores of the intervention group and the comparison group of children at the fall pretest and the spring posttest. A two-tailed hypothesis test was conducted for the intervention group and the comparison group each year to determine whether children made progress from fall to spring each year, as increases are expected for typically developing children. A second two-tailed hypothesis test was conducted to compare results for the intervention and comparison group children each year. Sample sizes varied slightly for each test, due to missing data. Using criteria recommended by Cohen (1988), an estimate of effect size (partial 112) was calculated to assess the degree to which study variables were related.

Results

This section provides information about the quality of the child care centers involved in the project as measured by ECERS-R, developmental progress within the comparison and intervention sites by year, and between the comparison and intervention sites by year.

Quality of Environments

Table 1 shows that on the seven attributes measured by the ECERS-R, the centers on average changed very little. According to the authors of the ECERS-R, the scores found in Table 1 show that the centers involved in this project are "good" but not "excellent." A recent examination of the psychometric properties of the ECERS-R suggests that the overall score is most indicative of the quality of the child care environment. The factor analysis investigations conducted revealed redundancy among items, resulting in subgroups similar to the overall score (Perlman, Zellman, & Le, 2004). Results, presented in Table 1, corroborate the Perlman et al. findings. Specifically, the subtest scores and the overall scores are relatively similar within semesters.

Developmental Progress Within Sites

During the baseline year, standard scores on the DIAL-3 were not different ([alpha] = .05) at the comparison sites from fall to spring (see Table 2). Average scores on the Motor subtest were almost one standard deviation above the mean (approximately 112 for both semesters), while scores on the Concepts and Language subtests were slightly lower than the mean. Average Motor and Language subtest scores, as well as the average Overall Composite score, were higher in the spring as compared to the fall at the intervention sites for the baseline year. Again, average scores on the Motor subtest were higher than average in the spring, with the average motor subtest score for students at the intervention sites approximately one standard deviation above the mean (114.8). Average Concepts and Language subtest scores, as well as the average Overall Composite scores, increased from fall to spring during the second year of the program. While scores on the Motor subtest were again above the mean, no statistically significant difference existed between the two semesters.

For year one at the intervention sites, effect sizes (partial [[eta].sup.2]) for the Motor, Language, and Overall Composite scores meet Cohen's criterion for a "small" effect size (.010) (Cohen, 1988). Cohen suggested that effect sizes in naturalistic studies are typically small, as they are affected by multiple influences. However, the effect sizes estimated for this study are similar to those seen in the Study of Early Child Care, a longitudinal study of over 1,000 children also conducted in a naturalistic setting (NICHD Early Child Care Network, 2002). The effect size for the Language scores during year two at the intervention sites also meets this criterion. During year one, differences between the Concepts, Language, and Overall scores between the intervention and comparison sites also resulted in a "small" effect size.

Developmental Progress Between Comparison and Intervention Sites

Scores also were compared between the comparison sites and intervention for the spring semesters of the baseline year and year two. Table 3 shows that scores at the intervention sites were significantly higher on the Language subtest than those at comparison sites during the baseline year; however, the Motor, Concepts, and Overall Scores were not found to be different. The effect sizes for the Language (partial [[eta].sup.2] = 0.026) and Concepts (partial [[eta].sup.2] = 0.011) scores can be considered "small." Year two scores at the intervention sites were not significantly different from scores at comparison sites.

Discussion

Consistent with the findings of the NICHD Early Child Care Research Network (2000) and other studies of community-based child care, the centers in this study fell into the mid-range of quality as measured by the ECERS-R. The centers were "good" but not "excellent" in quality. Although improving the overall quality of the child care center sites was one of the goals of the project, the center environments began the study in the "good" category and were at the same level at the conclusion of the study. This finding suggests that changing the quality of the centers may take more time, effort, and resources than those brought to bear in the initial two years of the project.

In examining the child outcomes measured by the DIAL-3, increases in standard scores from fall to spring suggest that the approaches and elements of the Early ON School Readiness intervention are promising. Especially promising are the scores from the DIAL-3 Language subtest (this subtest measures both expressive and receptive language skills as well as phonemic awareness). Scores on the Language subtest were not only higher at intervention sites than at the comparison sites at posttest the first year of the project, but also increased from years one and two of the project at the intervention sites. As phonemic awareness is an important predictor of reading ability (International Reading Association, 1998), further research on the methods and outcomes of the Early ON intervention is warranted. These findings, however, are particularly noteworthy, since the children in the study were predominantly Latino from low-income families. Previous studies have found that minority and economically disadvantaged children are at greater risk of lacking fundamental school readiness skills upon school entry (Lee & Burkam, 2002; McLanahan, 2005).

The fact that the scores on the Motor subtest (this subtest measures such skills as catching, jumping, hopping, skipping, building with blocks, cutting, copying shapes and letters, and writing) were consistently higher than the national average would seem to indicate that children at these centers have the growth and physical development needed for learning. The Motor subtest scores are approximately one standard deviation above scores on the other (Language and Concepts) subtests. The children's environments may offer a multitude of opportunities for them to improve their fine and gross motor skills but lack the academic stimulation that is necessary for them to develop cognitive skills on par with their motor skills.

A unique strength of the Early ON School Readiness Project has been the grassroots effort of community agencies working toward the common goals of the program. Each community agency has brought a wealth of conventional wisdom, community experience, and specialized services to the children and families served by the Early ON School Readiness Project. Ideas spawned through collaboration of community partners have been tried within clusters consisting of selected child care centers and elementary schools. As the project progressed, stakeholders and researchers continued to make solid progress toward a program model with codified strategies and procedures that can be replicated in other sites, locally and beyond. While the collaboration of community agencies has provided many benefits, it has taken time for community partners to move toward consensus regarding the specific program strategies to use in promoting school readiness. Discussions between community partners during the first two years of the program have helped to frame the evaluation of program strategies and build consensus surrounding programmatic strategies chosen.

Limitations of the Study

This study was intended to be exploratory and developmental in nature. As commonly reported by developers and researchers of other community-based approaches to early care and intervention (e.g., Buysse, Wesley, & Skinner, 1999), this study had several limitations readers should consider when generalizing study findings to other populations. Children sampled for progress were not selected at random. Instead, the sampling method did employ judgment and an attempt to represent a roughly geographically representative sample.

The investigators faced limitations regarding the extent of guidance they could exert to encourage consistent implementation of the Early ON program strategies at the child care centers. As noted in the introduction of this article, researchers worked through representatives of the partner community agencies to encourage full implementation of program strategies and were not able to work directly with centers. Implementation of the program strategies was somewhat inconsistent across sites and across the time period of the study as the program emerged through consensus building of the community partners. Moreover, broadly aimed community awareness strategies could not be strictly controlled. Consequently, parents at both the intervention sites and the comparison sites may have experienced some exposure to the media campaign. These limitations may have exerted an impact on the extent to which score gains can be attributed to the Early ON School Readiness Project.

Implications and Future Research

The results of this study contribute to a better understanding of the impact of child care typically available in community settings that falls within the middle range of quality. Preliminary data suggest that communities may be able to boost the development and school readiness skills of children enrolled in "good" quality centers with an emergent program approach. That is, strategies that emerge from community partnerships and are aimed at key program components, such as teacher training and parent education, might be effective. While it was beyond the scope of this preliminary examination, future studies could help to determine whether specific strategies in the multi-component program were responsible for greater developmental gains by children at the intervention sites and to what degree. Information of this kind could help streamline program strategies for greater efficiency and better results.

Community development approaches can be challenging to implement, especially when the community is diverse. However, studies suggest that such grassroots efforts might yield positive results for children. Community agencies with a long history of working with minority families, in collaboration with university partners who can inform the emergent program process with evidence-based research, may be successful in identifying program strategies that can have a positive impact on the school readiness of minority children (Buysse, Wesley, Bryant et al., 1999; Buysse et al., 2005).

Once the Early ON School Readiness Project is better established and program strategies are consistently implemented, it will be possible to conduct more rigorous types of research designs to gain greater insight into the effectiveness and, ultimately, the efficacy of the program. The preliminary data reported in this study suggests the program may be beneficial to children. However, future empirical research using experimental design and randomized trials will be needed to fully establish the effectiveness of the new program. Future research also can be aimed toward streamlining a model for building community alliances and developing programs that are informed by research and tempered with local wisdom and experience.

Acknowledgments

This study was funded, in part, by the Department of Community Initiatives of the City of San Antonio, Texas. The authors wish to acknowledge the contributions of Dennis Campa, Director of the Department of Community Initiatives, for his vision and leadership in establishing this community-university partnership.

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Suzanne M. Winter

Raymond Zurcher

Arthur Hernandez

Zenong Yin

The University of Texas at San Antonio

Table 1
Mean ECERS-R Scores at Intervention Sites

                                Year 1

                          Fall           Spring
Section Scores        Mean   (SD)    Mean   (SD)

Space/furnishings     4.9    (1.3)   4.7    (1.3)
Personal care         4.9    (1.8)   5.3    (1.4)
Language/reasoning    4.7    (1.3)   5.0    (1.5)
Activities            4.5    (1.3)   4.4    (1.2)
Interaction           5.3    (1.7)   5.7    (1.7)
Program structure     4.9    (1.9)   5.3    (1.6)
Parents and staff     5.3    (1.3)   5.2    (1.1)
Total                 4.9    (1.3)   5.0    (1.1)
No. of observations       40             64

                                  Year 2

                          Fall           Spring
Section Scores        Mean   (SD)    Mean   (SD)

Space/furnishings     5.1    (1.1)   5.3    (1.1)
Personal care         5.0    (1.6)   5.5    (1.5)
Language/reasoning    5.0    (1.8)   5.2    (1.6)
Activities            4.5    (1.5)   4.9    (1.4)
Interaction           5.3    (1.8)   5.8    (1.5)
Program structure     5.2    (1.7)   5.7    (1.6)
Parents and staff     4.9    (1.5)   5.3    (1.2)
Total                 4.9    (1.3)   5.3    (1.2)
No. of observations       55             81

Note: Scores on the ECERS-R range from 1.0 (inadequate) to 7.0
(excellent).

Table 2
DIAL-3 Scores at Comparison Site and Intervention Sites

                                   Fall             Spring
Comparison Sites, Year 1
                               Mean     (SD)    Mean     (SD)

  Motor                        112.6   (13.2)   112.2   (11.6)
  Concepts                      96.7   (13.0)    95.8   (13.7)
  Language                      95.1   (13.8)    95.4   (14.0)
  Overall Composite            101.6   (13.5)   101.6   (12.7)

                                    Fall            Spring
Intervention Sites, Year 1
                               Mean     (SD)    Mean     (SD)

  Motor                        109.2   (14.9)   114.8   (16.0)
  Concepts                      97.0   (13.9)    99.4   (13.5)
  Language                      96.3   (14.1)   101.7   (16.0)
  Overall Composite            100.6   (14.0)   106.0   (16.1)

                                    Fall            Spring
Intervention Sites, Year 2
                               Mean     (SD)    Mean     (SD)

  Motor                        109.0   (15.9)   111.0   (16.4)
  Concepts                      95.8   (13.2)    98.4   (14.1)
  Language                      94.6   (14.7)    98.6   (14.2)
  Overall Composite            100.2   (15.1)   103.1   (15.5)

Comparison Sites, Year 1
                                  t      Partial [[eta].sup.2]

  Motor                         0.15            .000
  Concepts                      0.31            .001
  Language                     -0.08            .000
  Overall Composite            -0.03            .000

Intervention Sites, Year 1
                                  t      Partial [[eta].sup.2]

  Motor                        -3.04 *          .031
  Concepts                     -1.43            .007
  Language                     -3.03 *          .031
  Overall Composite            -3.03 *          .031

Intervention Sites, Year 2
                                  t      Partial [[eta].sup.2]

  Motor                        -1.36            .004
  Concepts                     -2.05 *          .009
  Language                     -2.96 *          .019
  Overall Composite            -2.04 *          .009

* p > .05

Note: The DIAL-3 standardization sample had a Mean of 100 and an
SD of 15.

Table 3
Posttest DIAL-3 Scores of Comparison and Intervention Sites

                     Comparison       Intervention
Year 1                  Sites            Sites

                    Mean     (SD)    Mean     (SD)

Motor               112.2   (11.6)   114.8   (16.0)
Concepts             95.8   (13.7)    99.4   (13.5)
Language             95.4   (14.0)   101.7   (16.0)
Overall composite   101.6   (12.7)   106.0   (16.1)
Sample size               32              127

                     Comparison       Intervention
Year 2                  Sites            Sites

                    Mean     (SD)    Mean     (SD)

Motor               112.2   (11.6)   111.0   (16.4)
Concepts             95.8   (13.7)    98.4   (14.1)
Language             95.4   (14.0)    98.6   (14.2)
Overall composite   101.6   (12.7)   103.1   (15.5)
Sample size               32              207

Year 1
                       t       Partial [[eta].sup.2]

Motor               -0.869             .005
Concepts            -1.330             .011
Language            -2.029 *           .026
Overall composite   -1.412             .013
Sample size

Year 2
                         t     Partial [[eta].sup.2]

Motor                0.373             .000
Concepts            -0.955             .004
Language            -1.134             .006
Overall composite   -0.502             .001
Sample size

* p < .05