Improving children’s kindergarten readiness and narrowing the achievement gap among preschool children have received much attention throughout the world (Barton & Coley, 2010). There are at least two strategies to accomplish these twin goals.

Using Funding Streams to Promote School Readiness

Governments at different levels provide funds for early care and education. The logic behind this strategy is the well-established role of early childhood education in preparing children for school (Ackerman & Barnett, 2006). Barnett (2007) argues that high-quality programs produce substantial gains in child development that generate long-term benefits to society far in excess of their costs. Different funding streams for early care and education have different priorities. Some aim to provide low-cost child care so that parents can work. Others aim to improve the quality of learning and development of children. The relationship between these programs or funding streams and children’s gains in learning outcomes is largely unclear (Burchinal, Vandergrift, Pianta, & Mashburn, 2010). This uncertainty is a serious challenge, given that many governments budget substantial amount of funding for early care and education.

Florida in the United States is one of the few states that are experimenting with the combination of multiple funding streams (with different goals) to create a universal approach to preschool education which is open to all 4-year-old children. In Palm Beach County, four funding streams are used. One is Head Start, a well-known federally funded program, which provides services to children from low-income families. Voluntary Prekindergarten (VPK)is a free public pre-K program funded by the State of Florida that prepares early learners for success in kindergarten and beyond.School Readiness is the other state-funded program that offers qualified parents financial assistance for child care through a variety of services. And finally, Quality Countsis a comprehensive voluntary early care and education improvement system, funded locally by Children’s Services Council of Palm Beach County. We examined data collected by Children’s Services Council to explore the interactive effects of funding streams on children’s gains in early learning outcomes in the present study.

Using Classroom Practices to Promote School Readiness

Some researchers consider teachers’ classroom practices as important as their education, as Early et al. (2007) stated that “teachers’ education tends to be correlated with … important predictors of classroom quality, making it difficult to tease them apart” (p. 560). Early care and education classroom quality has been linked to children’s academic gains (Early et al., 2007). A meta-analysis indicated that “for all ages, … children in higher-quality early care and education programs tended to have modestly higher academic and language outcomes and better social skills, controlling for background characteristics” (Burchinal et al., 2009, p. 3).

The present study joins the effort in establishing a credible link between classroom practices of early care and education practitioners and early developmental outcomes of children. More precise measurements and more sensitive models are needed in the context of early childhood research (Raver et al., 2012). In response, we consider the application of both refined measurement instruments and advanced statistical techniques as critical in gauging the strength of the link between classroom practices and learning outcomes.

We examined children’s learning outcomes in early care and education programs and their relationships to two constructs, classroom practices and funding streams.

1. To what extent are funding streams interactively associated with children’s early cognitive outcomes when analyzed with and without classroom practices of early care and education practitioners?

2. To what extent are classroom practices of early care and education practitioners associated with early cognitive outcomes of children when analyzed with and without interactive funding streams?

We used a survey-based randomized pretest-posttest design to collect data (N = 1494 preschoolers from 387 classrooms). A universal list of all school- and center-based programs (classrooms) was obtained across Palm Beach County funded by Quality Counts, Head Start, VPK, and School Readiness. Many classrooms received support from more than one funding stream. We used a stratified random sampling procedure (classrooms and children) to produce proportional sub-groups of children in different program types (school- and center-based) and funding streams. Selected children were administered measures of early cognitive skills in a pretest (fall) and posttest (spring) manner. Three child assessment instruments were administered. The Peabody Picture Vocabulary Test (3rd ed.) (PPVT-III) was employed to test children’s language abilities (Dunn & Dunn, 1997). The Woodcock-Johnson Psycho-Educational Battery (3rd ed.) (WJ-III) and its Spanish version were employed to test children’s mathematics abilities (Woodcock & Johnson, 1989). The Test of Preschool Early Literacy (TOPEL) and its Spanish version were employed to assess children’s print knowledge (Lonigan, Wagner, Torgesen, & Rashotte, 2007). Children who spoke Spanish were tested in either English or Spanish, depending on a child’s primary language (as designated by the child’s teacher). Assessments were conducted one-on-one in a child’s classroom, and were scheduled to avoid meal, nap, and outdoor play times. Teachers of selected children were observed during this period of time, and their classroom practices were scored with the CLASS instrument (Pianta, La Paro, & Hamre, 2007). As an observational system that assesses preschool classroom practices, CLASS measured the interactions between children and adults. Funding streams data were obtained from the Palm Beach County Children’s Services Council. Finally, we collected data on children’s background and program types. We employed a 2-level HLM model as our primary statistical technique (Raudenbush & Bryk, 2002). The model aimed to evaluate children’s learning outcomes in relation to classroom practices and funding streams, with control for child background (gender, age, race-ethnicity, home language, and special education status) at the child level and program type (school- versus center-based) at the classroom (teacher) level. The level-1 model was similar to analysis of covariance (ANCOVA) to measure children’s gains in early cognitive outcomes with control over child characteristics, and the level-2 model examined children’s gains with classroom practices and funding streams with control over program type. A full information maximum likelihood estimation method allowed us to use all available data except those missing on dependent variables.

Using a stratified random sample of classrooms and children, we examined the relationship of early cognitive outcomes (receptive vocabulary, mathematics skills, and emergent literacy) of children to funding streams (i.e., funding sources) at various administrative levels and classroom practices of early care and education practitioners in a survey-based pretest-posttest design. Results of hierarchical linear modeling (HLM) identified the robust effects of classroom organization on emergent literacy even after control over funding streams. After control for classroom practices, three interactive funding patterns emerged. A stimulating interactive funding pattern can be identified by a statistically significant positive interaction effect between two funding streams and one or two statistically significant negative main effects (in smaller absolute values). A stimulating pattern indicated that a combination of certain funding streams was effective in promoting emergent literacy. An interfering interactive funding pattern can be identified by a statistically significant negative interaction effect between two funding streams and one or two statistically significant positive main effects (smaller than the absolute value of the interaction effect). An interfering pattern indicated that a combination of certain funding streams undermined both mathematics skills and emergent literacy. A replacing interactive funding pattern can be identified by the absence of a statistically significant interaction effect and the presence of one or two statistically significant negative main effects. We use the term of “replacing” to indicate that, instead of the interaction effect, there are negative main effects. A replacing pattern indicated that individual funding streams operating alone might not be adequate to help falling-behind children.

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