Children’s acquisition of early literacy skills: examining family contributions

Early Childhood Research Quarterly 17 (2002) 295–317

Children’s acquisition of early literacy skills: examining family contributions Kymberley K. Bennett a,∗ , Daniel J. Weigel b , Sally S. Martin c a

b

Department of Psychology and Human Development, Vanderbilt University, Box 512 Peabody, Nashville, TN 37203, USA Cooperative Extension University of Nevada, Reno, Mail Stop 140, Reno, NV 89557, USA c Department of Human Development and Family Studies, University of Nevada, Reno, Mail Stop 140, Reno, NV 89557, USA

Abstract A study of 143 families and their preschool-age children was undertaken to examine the relationship between the family environment and children’s language and literacy skills. This research was guided by three models hypothesized by Snow, Barnes, Chandler, Goodman, and Hemphill (1991) to explain the family’s contribution to children’s acquisition of language and literacy. The three theoretical models examined in this study were: Family as Educator, Resilient Family, and Parent–Child Care Partnership. Confirmatory factor analysis (CFA) and structural equation modeling were used to estimate latent constructs and structural models, respectively. Results showed that only the Family as Educator model was significantly related to child language and literacy outcomes (i.e., book-related knowledge, receptive language skills, and expressive language skills). Implications for future researchers and educational practice are discussed. © 2002 Published by Elsevier Science Inc. Keywords: Family as Educator; Resilient Family; Parent–Child Care Partnership

1. Introduction The processes underlying children’s acquisition of language and literacy have been a focus of research for many years. Much of this research aims not only to understand these processes, but also to improve children’s language-related competencies. Research of this nature ∗

Corresponding author. E-mail address: [email protected] (K.K. Bennett).

0885-2006/02/$ – see front matter © 2002 Published by Elsevier Science Inc. PII: S 0 8 8 5 - 2 0 0 6 ( 0 2 ) 0 0 1 6 6 - 7

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is important given the paramount role played by language and literacy in children’s academic development and achievement. For example, Werner and Smith (1992) found that literacy was one of the strongest predictors of children’s academic success. Walker, Greenwood, Hart, and Carta (1994) found that preschoolers’ language abilities predicted their reading achievements in grades one through three. Scarborough (1991) showed that expressive vocabulary skills during the preschool years predicted later reading skills in second grade. Weinberger (1996) also demonstrated that children’s literacy abilities at age 5 predicted their reading levels at age 7. Additionally, Dickinson and DeTemple (1998) found evidence that parents’ assessments of children’s language abilities at ages 3 and 4 were significantly related to teacher assessments of language and vocabulary skills in grades two and four. Given the important role played by language and literacy abilities in young children’s later academic competencies, the present study examines the relationships between the family environment and preschool children’s language and literacy skills. Although many studies investigating the developmental roots of children’s language and literacy skills have focused on children from low-income families (e.g., Lonigan & Whitehurst, 1998; Payne, Whitehurst, & Angell, 1994), we now understand that many home literacy environment-related processes also are important for preschool children from middle-income families. For example, research highlights the importance of parent–child book reading (e.g., Griffin & Morrison, 1997), parental expectations (e.g., Evans, 1998), family stressors (e.g., Entwise & Alexander, 1996), and emotionally healthy family environments (e.g., McMullen & Darling, 1996) in later academic achievements among children from middle-income families. Therefore, it is possible that all children, regardless of socioeconomic status, benefit from home literacy environments that foster their language and literacy skill development. Thus, the current study will investigate the role played by the family literacy environment among preschool-age children from middle-income families.

2. Young children’s emerging literacy skills Emergent literacy is the term used to describe young children’s developing literacy skills before formal schooling. Emergent literacy encompasses oral (i.e., expressive and receptive), reading, and writing skills that young children acquire (Teale & Sulzby, 1987). Teale (1987) states: By looking not merely at conventional manifestations of reading or writing, but considering also such manifestations as children’s rereading of familiar books before they are fully literate, 3-year-olds’ uses of environmental print, or writing with scribbles or random-appearing letters, and by examining literacy not merely from adult perspectives but also from the children’s viewpoints, we can see that emergent literacy learning occurs in virtually every young child in a literate society like ours. (p. 46)

The most important aspect of emergent literacy is that it is a process—one that continues and grows over time. Hence, children’s need to communicate, their curiosity, and their skills for making sense of the world drive them to gain many literacy-related skills long before they encounter formal reading and writing instruction in school (Morrow, 1989).

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3. Family contribution to children’s language and literacy development Much research has demonstrated that the home environment serves as an important influence in the development of emergent literacy skills in young children (e.g., Beals & DeTemple, 1993; Dickinson & Tabors, 1991; Teale, 1987). The importance of the home environment is grounded in the fact that the home serves as a setting in which language and literacy is first encountered (Strickland & Taylor, 1989). Many conceptualizations of the home literacy environment have focused primarily on the occurrence or frequency of joint book reading between parent and child. This research demonstrates that joint book reading positively influences young children’s acquisition of language and literacy skills (e.g., Burgess, 1997; Lonigan et al., 1998; Payne et al., 1994; Senechal, LeFevre, Thomas, & Daley, 1998), as well as their motivations to read (e.g., Baker, Scher, & Mackler, 1997; Bus, 1994; Morrow, 1983), in both low- and middle-income families. In fact, Bus, van Ijzendoorn, and Pellegrini (1995) undertook a meta-analysis and concluded that the home environment, operationally defined as the frequency of joint book reading, had a positive effect on child literacy and language outcomes. The combined effect size of the studies analyzed was .59, demonstrating a medium to large effect size. Many investigators are now examining the home literacy environment in a more complex and comprehensive manner, focusing on variables in addition to the occurrence or frequency of parents and children reading together (e.g., Christian, Morrison, & Bryant, 1998; Evans, 1998; Griffin & Morrison, 1997; Leseman & de Jong, 1998). For example, Snow, Barnes, Chandler, Goodman, and Hemphill (1991) undertook a study to examine the family’s contribution to language and literacy development in a sample of school-age children. Their conceptualization of the family environment consisted of literacy-related activities and beliefs as well as family functioning-related variables such as routines, resources, and stresses, and the quality of relationships between family members and children’s teachers. The investigators sought to identify factors that distinguished high-achieving children from low-achieving children. They followed a sample of second, fourth, and sixth graders for 2 years, as well as their families and teachers. In their study, Snow et al. examined three theoretical models hypothesized to explain the family’s contribution to the acquisition of language and literacy: the Family as Educator, Resilient Family, and Parent–School Partnership models. 3.1. Family as Educator In the Family as Educator model, Snow et al. (1991) suggested that the family serves as an educating agent, positively affecting children’s language and literacy development. They examined five variables central to this model: (1) literacy environment of the home (e.g., number of books in home), (2) direct teaching (e.g., parents helping with homework), (3) creating opportunities to learn (e.g., exposing children to other people and activities), (4) parental education, and (5) parental expectations (e.g., how much schooling parents expect of their children). In addition to the research summarized above concerning joint book reading (e.g., Burgess, 1997; Senechal et al., 1998), much work supports relationships between these Family as Educator-type variables and language and literacy outcomes among young children from varying socioeconomic backgrounds. For example, Griffin and Morrison (1997) broadly measured

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the home literacy environment as magazine and newspaper subscriptions, library use, television viewing, and book reading, and found that it was positively related to middle-income kindergarten children’s receptive vocabulary skills, reading recognition skills, and mathematic skills. Results from a follow-up study conducted by Christian et al. (1998) showed that this conceptualization of the home literacy environment was positively related to kindergarteners’ reading achievement, verbal achievement, and alphabet recognition. Similar results have been reported by Evans (1998) and by Leseman and de Jong (1998). Research also supports the positive relationships between parental education and expectations and children’s language-related outcomes (e.g., Christian et al., 1998; Entwise & Alexander, 1996; Payne et al., 1994; Walker et al., 1994). Results from Snow et al. (1991) showed that the Family as Educator model significantly predicted children’s word recognition skills and vocabulary knowledge. The most powerful predictors of these child outcomes were the home literacy environment, parents’ education, and parents’ expectations. 3.2. Resilient Family In the Resilient Family model, Snow et al. (1991) hypothesized that the family can function as an insulating device against external stressors and pressures while still providing the time and attention deemed necessary for fostering the acquisition of language and literacy. In other words, the family provides an environment in which the child can become a gifted learner, thereby benefiting from formal instruction at school. Therefore, resiliency is more than an income issue—it refers to how the family functions, how it is organized, how well it manages its resources, and how it copes with the internal and external stresses that all families face. Three key variables identified as comprising this model were: (1) family organization (e.g., rules for behavior, predictability in scheduling events), (2) family emotional climate (e.g., children’s perceptions of their relationships with their parents, how punitive parents are), and (3) family stress (e.g., economic strain, demands on family members). Recent work has investigated the relationships between Resilient Family-type variables and child outcomes among young children from various backgrounds. Repeatedly, research has demonstrated that children from families with high levels of stress, poor emotional environments, and few resources perform at lower levels than their counterparts from “resilient” homes (e.g., Brody et al., 1994; Mantzicopoulos, 1997; Nicholson, 1999). For example, Strand (1999) found that preschool children who were eligible for free school meals, a variable used as a proxy for low family income, scored significantly lower than their middle-income counterparts on early literacy skills. In addition, Morrow (1983) examined family rules in relation to young children’s interest in reading; in the study, Morrow examined family rules in relation to television viewing. Results from the study revealed that children, regardless of socioeconomic class, who showed a high interest in reading were those who watched less than 2 hours of television per day, and those whose families enforced strict rules regarding television viewing. Dunst, Leet, and Trivette (1988) examined family resources among middle-income mothers with developmentally delayed preschoolers. Based on their results, they conclude the following: . . . mothers who reported inadequacies in family resources were less likely to see child-level educational and therapeutic needs as immediately important, and thus were not likely to indicate that they would invest the time and energy to carry out professionally prescribed treatments.

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Presumably, the mothers were more concerned about getting other family needs met, and were investing time and energy toward this end. (p. 113)

In discussing the relationships between family resources and stressors, and children’s acquisition of language and literacy, at both ends of the socioeconomic spectrum, Sonnenschein, Brody, and Munsterman (1996) write: . . . the development of literacy occurs within a larger social context. When parental psychological resources are depleted or when there is interpersonal rancor within the family, literacy development may be compromised. Although we can encourage parents to read to their children and take them to the library, they will probably be less likely to do so in the presence of financial or interpersonal stresses. (p. 16)

Results for the Resilient Family model, in the Snow et al. (1991) study, showed that it significantly predicted children’s writing skills and reading comprehension. The most powerful predictor of writing skills and reading comprehension was the family’s emotional climate. 3.2.1. Parent–School Partnership In the Parent–School Partnership model, Snow et al. (1991) suggested that parents who actively support schools’ efforts to teach their children are more successful in promoting their children’s language and literacy achievements. That is, families can contribute to language and literacy development by forming a partnership with their children’s schools. They identified five variables as relevant to the Parent–School Partnership model: (1) formal parent–school involvement (e.g., joining Parent–Teacher Associations), (2) frequency of contact with teachers, (3) homework help by parents, (4) nature of parent–child interaction during homework help (e.g., strained vs. encouraging), and (5) school attendance and punctuality. Although many studies exist supporting the importance of partnership in children’s academic achievement during the elementary years (e.g., Calfee, 1997; Macleod, 1996), little work has examined the role played by Parent–School Partnerships during the preschool years. We can look, however, to studies investigating the contributions of family reading intervention programs to preschool children’s language and literacy skills for support. These studies highlight the importance of home activities, in conjunction with school activities, in young children’s acquisition of language and literacy. For example, Lonigan and Whitehurst (1998) demonstrated that low-income preschool children involved in a dialogic reading intervention including home and school aspects outperformed their home- and school-only intervention counterparts, as well as the control group, on measures of expressive vocabulary. Similar results for reading skills and motivation were found by Morrow and Young (1997a, 1997b). On the topic of the importance of partnership in understanding children’s academic competencies, in both low- and middle-income families, Baker et al. (1996) write: . . . home–school partnerships can have a positive effect on literacy if families and teachers together develop ways of communicating and building meaningful curricula that extend the insular classroom community. The key elements of reciprocity and respect . . . must be locally interpreted and jointly constructed by parents and teachers. (p. 38)

These sentiments are echoed by Cairney (1997) and Elicker, Noppe, Noppe, and FortnerWood (1997). Results from Snow et al. (1991) showed that the Parent–School Partnership model

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significantly predicted children’s word recognition, vocabulary knowledge, writing skills, and reading comprehension. Across the four child outcomes examined, formal parent–school involvement was the most significant predictor. 4. Purpose of study Although Snow et al. (1991) studied the contributions of these models to language and literacy skill development among elementary school children, no study of which we are aware has examined the Snow et al. models’ possible contributions among younger children. In addition, while the authors’ efforts concentrated on children from low-income families, research cited above (e.g., Baker et al., 1996) points to the possible importance of these theoretical models in explaining literacy and language acquisition among preschool children from middle-income families, as well. Therefore, the present study was undertaken to examine relationships between the Family as Educator, Resilient Family, and Parent–School Partnership models and language and literacy skills among preschool children from middle-income families. 5. Method 5.1. Procedures Preschool-age children and their families were recruited through licensed child care centers in an urban county in a western state. Child care centers were randomly selected from a list of all licensed facilities, excluding home providers, in the county in which the study was conducted. The researchers contacted directors of the randomly selected child care centers to request consent for participation. Of the 80 directors contacted, a total of 30 (37.5%) gave consent for their centers to participate in the study. The majority of participating child care centers was private-for-profit (76.7%), while 16.7% were religiously affiliated, and 6.6% were community-based, not-for-profit. Once permission was granted by these 30 participating directors, researchers contacted child care teachers with classrooms for 3- and 4-year-old children. Forty-seven teachers, from 47 classrooms, agreed to participate. Teachers then distributed flyers inviting families to participate in the study to the parents of the children in their classrooms. Interested parents either directly contacted researchers or returned slips to their children’s teachers. Once direct contact was made with parents, data collection interview times were scheduled. Most interviews took place in family homes, though a few were conducted in university offices and child care centers. At the beginning of the interview, the goals and procedures of the study were explained to parents and they signed informed consent forms. During the interview, the researcher provided parents with self-administered questionnaires. While parents completed their questionnaires, the researcher assessed children’s language and literacy skills. Most interviews were completed within 1 hour. Families were assured their participation was completely voluntary and that all responses would be kept strictly confidential. Families were paid $20 for their participation.

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5.2. Participants The sample consisted of 143 families.1 Data were collected from parents who were the primary caregivers, 134 (93.7%) mothers and 9 fathers (6.3%), and from their children, 76 girls (53.1%) and 67 boys (46.9%). The average age of participating parents was 33.9 years, with ages ranging from 20 to 46 years. The average age of the children was 50.9 months (approximately 4 and one-quarter years), with ages ranging from 36 months (3 years) to 70 months (approximately 6 years).2 Children in this sample started child care at an average age of 19.9 months, with ages ranging from 1 to 54 months, and spent an average of 30.6 hours per week in child care, with hours ranging from 5 to 50. Finally, the average annual family income was in the $40,000–$49,999 range, with responses ranging from “less than $9,999” to “more than $60,000.” A vast majority (88.1%) of the participating parents was Caucasian, while 3.5% of the participants were of Hispanic decent, 2.1% reported their ethnic background as “other,” 1.4% were African-American, 1.4% were Asian-American or Pacific Islander, 1.4% were multi-ethnic or multi-racial, .7% were Native American, Alaskan Native, or Aleut, and 1.4% failed to report their ethnic background. Most parents were married or living with partners (77.6%). A majority of participating parents was employed either full-time (65.7%) or part-time (18.9%), while 7.0% were full-time homemakers, 2.8% were full-time students, 2.1% were part-time students, and less than 1% were unemployed. Although there was a range of educational attainment, overall, the sample of participating parents consisted of a well educated group: 9.8% had completed high school or earned a GED, 42.0% had completed high school and some college, 18.9% had completed a 4-year college degree, and 28.0% had completed a graduate degree. Finally, most families (95.8%) reported English as their native language. 5.3. Measures The self-administered questionnaire completed by parents was comprised of several standardized scales as well as measures created specifically for this study by the authors. See Table 1 for means, standard deviations, and coefficient alphas. Several of the variables comprising Snow et al.’s (1991) Family as Educator, Resilient Family, and Parent–School Partnership models were not appropriate for preschool children or their parents (e.g., homework help by parents). Therefore, variables more developmentally appropriate, as well as meaningful, for this sample were measured. In addition, because the focus of this study is on preschool children and their families, we will use the term Parent–Child Care Partnership rather than Snow et al.’s original Parent–School Partnership model because it better represents the interactions between this sample of parents and their children’s child care providers. 5.3.1. Family as Educator variables Parents were given a measure of literacy-related activities developed by the authors. This 7-item scale measures how often parents and children engage in emergent literacy activities such as reading aloud, reciting rhymes, telling stories, drawing pictures, and playing games. Parents indicated their engagement in these activities along a 5-point Likert scale (1 = hardly

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Table 1 Means, standard deviations, and coefficient alphas Variables

Mean

Standard deviation

Coefficient alpha

Family as Educator model Literacy-related activities PRBI Parents’ reading enjoyment Minutes reading to child Frequency child sees parents writing Parents’ education

26.3 167.7 4.1 2.6 4.0 4.6

3.9 11.2 1.0 .9 1.5 1.0

.73 .87

Resilient Family model FRQ FRS Frequency of hassles Intensity of hassles

53.7 127.2 54.9 43.0

7.3 14.5 8.9 9.7

.77 .94 .84 .89

Parent–Child Care Partnership model Parental involvement Frequency of contact Confidence in interactions with teacher Effectiveness in interactions with teacher Satisfaction in interactions with teacher

18.5 20.5 2.6 2.5 2.3

4.0 11.6 .5 .5 .5

.77 .70

Child outcomes CELT Writing skills AC EC

5.0 5.7 40.1 39.1

2.5 2.6 4.0 5.6

Note: Blank cells under the “coefficient alpha” column were analyzed as single-item indicators, were dichotomously scored, or were the summed composite of two variables and thus did not yield coefficient alpha values.

ever to 5 = two or more times a day). Possible scores on this scale range from 7 to 35, with higher values indicating increased engagement in emergent literacy activities. Developmentally appropriate Parental Reading Beliefs were assessed using the parental reading belief inventory (PRBI; DeBaryshe & Binder, 1994). The PRBI is a 39-item measure that assesses the extent to which parents agree or disagree with a number of developmentally appropriate and inappropriate reading beliefs on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). For example, developmentally appropriate beliefs include, “My child learns lessons and morals from the stories we read” and “When we read, I want my child to ask questions about the book.” Examples of developmentally inappropriate beliefs include, “My child is too young to learn about reading” and “Parents should teach children how to read before they start school.” Possible scores on the PRBI range from 39 to 195; the higher the values, the greater the respondents’ developmentally appropriate beliefs. Three single-item indicators of literacy practices were asked of parents: how much they enjoy reading (1 = not at all to 5 = a great deal), how many minutes per day parents spend reading to their children (1 = no minutes to 4 = more than 20 minutes), and how often children see their parents writing on a weekly basis (1 = never to 6 = more than once a day). Parents also were asked their level of education (1 = less than 9th grade to 6 = graduate work).

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5.3.2. Resilient Family variables Family routines were measured using the Family Routines Questionnaire (FRQ; Boyce, Jensen, James, & Peacock, 1983; Jensen, James, Boyce, & Harnett, 1983). The FRQ is a 17-item scale that measures engagement in a number of family practices, such as “Family checks in or out with each other when someone leaves or comes home” and “Family eats at the same time at night.” Responses are made along a 4-point continuum (1 = almost never to 4 = everyday). Scores on this scale can range from 17 to 68, with higher values reflecting a higher number of routines within the family. Family resources were assessed using the Dunst and Leet (1987) Family Resource Scale (FRS). The FRS is a 30-item scale designed to assess the adequacy of a number of family resources. Parents were asked to report the adequacy of such basic necessities as “Food for two meals a day” and “Heat for your house or apartment” as well as the adequacy of social resources (e.g., “Time to be with spouse or close friend” and “Someone to talk to”) and the family’s ability to engage in entertainment activities (e.g., “Toys for children” and “Travel/vacation”). Responses were made along a 5-point scale (1 = not at all adequate to 5 = almost always adequate); possible scores on the FRS range from 30 to 150, with higher scores indicating higher levels of resources. Family hassles were measured with the Parenting Daily Hassles Scale (PDH; Crnic & Booth, 1991; Crnic & Greenberg, 1990). The PDH consists of two 20-item subscales, the “Frequency Scale,” a measure of how often a number of minor hassles occur within the family, and the “Intensity Scale,” a measure of parents’ perceptions of the severity of those hassles. Scores on both subscales range from 20 to 100, with higher scores reflecting higher numbers and intensities of hassles, respectively. The “Frequency Scale” asked parents to rate how often hassles such as “Continually cleaning up messes of toys or food” and “The kids are hard to manage in public (grocery store, shopping center, restaurant)” occur along a 5-point scale (1 = never to 5 = constantly). The “Intensity Scale” asked parents to then rate these 20 hassles again in terms of their severity along a 5-point continuum (1 = none to 5 = huge). 5.3.3. Parent–Child Care Partnership variables Parents also completed a number of measures to assess their attitudes toward, and involvement with, their children’s child care teachers and centers. To measure parental involvement with the child care centers, the authors adapted a scale from the Hopkins Survey of School and Family Connections (Becker & Epstein, 1982; Epstein & Becker, 1982). This 12-point scale asked parents to indicate how often they helped the child care center in a variety of ways. Helping behaviors included assisting teachers in the classroom or on a field trip, participating in discussions or parent–teacher meetings, and volunteering time in the classroom. Responses were made along a 3-point scale (1 = never to 3 = very often). Possible scores ranged from 12 to 36, with higher scores indicating a greater number of helping behaviors. The frequency of contact with child care centers was assessed using a scale from the Hopkins Survey of School and Family Connections (Becker & Epstein, 1982; Epstein & Becker, 1982). Parents were asked to indicate the number of times, from 0 to 10, during the preceding 6 months the child care center did the following things: sent a memo or notice home, talked to you before or after school, sent you a handwritten note, called you on the telephone, asked for a meeting with you, and invited you to a workshop at school. Possible scores on this scale

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ranged from 0 to 60, with higher scores reflecting greater contact between child care centers and caregivers. Finally, three items from Hughes (1995) asked parents to indicate how confident they felt after interactions with teachers (confident interactions), how effective they felt they were in dealing with concerns raised by teachers (effective interactions), and how satisfied they believed teachers were after their interactions (satisfied interactions). Parents responded to these questions on 3-point scales (1 = not confident, not effective, and not satisfied, respectively to 3 = very confident, very effective, and very satisfied, respectively). These items were analyzed as single-item indicators. 5.3.4. Child outcomes Four literacy and language outcomes were assessed: children’s book knowledge, writing skills, receptive language skills, and expressive language skills. Children’s book knowledge was assessed using the Child’s Emergent Literacy Task (CELT; Abt Associates Inc., 1991), a 17-item measure. For example, children were asked to point to the front of a book, indicate in which direction we read, point to a letter, point to a word, and identify a period and its function within a sentence. Children were given 1 point if they provided the correct answer to a question, and 0 points if they provided an incorrect response; therefore, possible scores on this scale range from 0 to 17. Children’s writing skills were also measured using the CELT. Two questions comprised this writing scale; children were asked to write their names (1 = no attempt to write their names to 5 = writing their names correctly) and their ages (1 = no attempt to write their ages to 5 = writing their ages correctly). Possible scores ranged from 2 to 10. Receptive and expressive language skills were measured using the “auditory comprehension” (AC) and “expressive communication” (EC) subscales of the Preschool Language Scale-3 (PLS-3; Zimmerman, Steiner, & Pond, 1992), respectively. AC, the receptive language subscale, serves as a measure of how well children understand verbal language. For example, one item asks children to identify pictures of a caterpillar, a doctor, groceries, and a triangle. In addition, understanding of quantity concepts is tested by asking children to look at a picture and count fish in an aquarium, as well as count strawberries on a plate. EC, the expressive language subscale, serves as a measure of how well children express their thoughts verbally. For example, understanding of analogies is assessed by asking children to complete a sentence such as, “A lady bug is little. An elephant is . . . .” Also, children’s use of regular and irregular forms of past tense verbs is measured by asking children to repeat sentences such as, “Jesse ran fast and won the race.” Each subscale is comprised of 48 items and includes criteria against which to rate responses as either correct or incorrect. Scores for both subscales are summations of the correct and incorrect responses (i.e., 1 point for correct responses, 0 points for incorrect responses) and thus range from 0 to 48; higher scores on both subscales indicate greater facility in the respective skill area. 5.4. Method of analysis Confirmatory factor analysis (CFA) was used to create latent constructs representing the three theoretical models hypothesized by Snow et al. (1991). CFA involves an a priori specification

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of a factor structure among a set of variables, then compares this structure to the existing data for disconfirmation (Maruyama, 1998). Structural equation modeling was used to examine the relationships between the Snow et al. theoretical models and the literacy and language outcome variables, i.e., the structural models. All measurement and structural models for this study were estimated using the computer program “AMOS,” version 4.0 (Arbuckle & Wothke, 1999). All these models used maximum likelihood estimation (MLE), the default estimation method in “AMOS.” The MLE procedure estimates means and intercepts for item non-responses, allowing use of the entire sample in the analyses.

6. Results CFA was used to create measurement models of the three theoretical models (i.e., latent constructs), Family as Educator, Resilient Family, and Parent–Child Care Partnership, proposed by Snow et al. (1991). Care was taken to insure that variables similar to those used by Snow et al. were included in each measurement model. Although the variables in the measurement models do not exactly match ones used by Snow et al., appropriate measures for preschool children, as opposed to elementary school children, were included.3 Analyses followed a two-step process: first, measurement models of latent constructs, the three Snow et al. theoretical models, were tested, and second, individual structural models for CELT, Writing, AC, and EC were tested. 6.1. Measurement models Measurement models of the three Snow et al. (1991) latent constructs were tested simultaneously. Results showed: χ 2 (87) = 148.53, p = .000; χ 2 /df ratio = 1.71; normed fit index (NFI; Bentler & Bonett, 1980) = .98; incremental fit index (IFI; Bollen, 1989) = .99; comparative fit index (CFI; Bentler, 1990) = .99; and the root square error of estimation (RMSEA) = .07. These fit indices reflect adequate model fit as the following guidelines have been offered: Carmines and McIver (1981) and Byrne (1989) suggest that χ 2 /df ratios 2.0 and below reflect good model fit; Maruyama (1998) suggests that optimal levels of the NFI, IFI, and CFI approximate .90; and, Jaccard and Wan (1996) suggest that RMSEA values of .08 and below reflect good model fit. Results also showed that factor loadings were stable when all measurement models were estimated simultaneously, as opposed to individually; that is, relative weights of the indicator variables did not vary when all measurement models were estimated simultaneously. Table 2 reports the estimated loadings for all latent constructs on their respective indicator variables; all loadings are significant at the .001 level. We can examine the strength of the associations between latent constructs and indicator variables in order to conclude which indicator(s) is most important to each latent construct. Therefore, within the Family as Educator latent construct, the highest loadings are for the literacy-related activities and developmentally appropriate reading beliefs indicator variables. This suggests that of the indicators included within this latent construct, literacy-related activities and parent reading beliefs are the most important components of the Family as Educator model. Likewise, Table 2 shows that the frequency and intensity of daily hassles are most important to the Resilient Family model, as are the measures of parents’

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Table 2 Confirmatory factor analysis results for latent constructs Latent constructs and indicator variables Family as Educator model Literacy-related activities PRBI Parents’ reading enjoyment Minutes reading to child Frequency child sees parents writing Parents’ education Resilient Family model FRQ FRS Frequency of hassles Intensity of hassles Parent–Child Care Partnership model Parental involvement Frequency of contact Confidence in interactions with teacher Effectiveness in interactions with teacher Satisfaction in interactions with teacher ∗∗∗

β

b

Critical ratio

1.00 3.31 .17 .21 .28 .18

.66 .77 .46 .57 .47 .48

6.70∗∗∗ 4.58∗∗∗ 5.52∗∗∗ 4.67∗∗∗ 4.75∗∗∗

1.00 1.87 −2.00 −2.12

.48 .46 −.81 −.81

3.84∗∗∗ −5.00∗∗∗ −4.98∗∗∗

1.00 2.14 .15 .11 .14

.64 .48 .70 .58 .74

4.60∗∗∗ 6.07∗∗∗ 5.32∗∗∗ 6.26∗∗∗

p < .001.

confidence and satisfaction after discussions with teachers for the Parent–Child Care Partnership model. 6.2. Structural models Results4 for the first structural model, the contributions of the theoretical models (i.e., Family as Educator, Resilient Family, and Parent–Child Care Partnership) to CELT scores, are depicted graphically in Fig. 1. Because the child outcomes included in the structural models are likely to be positively correlated with children’s ages, all structural models tested included child age as a control variable; such a step controlled for the possible confounds of children’s ages on the language/literacy outcomes studied.5 Results for the first structural model showed an acceptable fit to the model (see Table 3 for goodness-of-fit indices for all structural models tested). As shown in Fig. 1, results from this structural model revealed that only the Family as Educator model was significantly related to CELT scores (β = .40, p < .01). Results for the second structural model, the contributions of the theoretical models to writing skills, are shown in Fig. 2. Results indicated an adequate fit for the structural model (see Table 3) though none of the theoretical models was significantly related to children’s writing skills. Results for the third structural model, the contributions of the three theoretical models to AC, are shown in Fig. 3. Results also reflect an adequate fit for the structural model (see Table 3). Consistent with Fig. 1, only the Family as Educator model was significantly associated with AC (β = .41, p < .01). Results for the final structural model, the contributions of the theoretical models to EC, are shown in Fig. 4. Again, results reflect an adequate fit for the structural model (see Table 3). Consistent with Figs. 1 and 3 only the Family as Educator model was significantly associated with EC (β = .36, p < .01).

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Fig. 1. Structural equation model examining contributions of family environment to child’s emergent literacy task (CELT) scores controlling for children’s ages. Standardized path coefficients reported. ∗∗ p < .01, ∗∗∗ p < .001.

After estimating the above structural models, exploratory structural models, controlling for family annual income in addition to children’s ages, were examined. Although most families in the study could be considered “middle-income,” we wanted to examine whether variations in family income, however small in the current sample, affected the structural models outlined above. Results showed that the path magnitudes, as well as significance levels, did not change across the four structural models. The fit indices for the CELT, Writing, AC, and EC structural models were comparable: χ 2 (123) = 257.07, p = .000, NFI = .97, IFI = .98, CFI = .98, RMSEA = .09; χ 2 (123) = 253.54, p = .000, NFI = .97, IFI = .98, CFI = .98, RMSEA = .09; χ 2 (123) = 254.77, p = .000, NFI = .97, IFI = .98, CFI = .98, RMSEA = .09; and, χ 2 (123) = 262.99, p = .000, NFI = .97, IFI = .98, CFI = .98, RMSEA = .09, respectively. Akaike information index (AIC) values (see Heck & Thomas, 2000) also were less for structural models controlling only for children’s ages, as opposed to structural models controlling

Table 3 Fit indices for structural models examining contributions to child literacy outcomes Model

χ2

df

p-value

χ 2 /df ratio

NFI

IFI

CFI

RMSEA

Squared multiple correlation

CELT Writing skills AC EC

183.81 173.65 178.61 184.39

111 111 111 111

0.000 0.000 0.000 0.000

1.66 1.56 1.61 1.66

.98 .98 .98 .98

.99 .99 .99 .99

.99 .99 .99 .99

.07 .06 .06 .07

.26 .19 .37 .35

Note: NFI: normed fit index; IFI: incremental fit index; CFI: comparative fit index; RMSEA: root mean square error of approximation.

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Fig. 2. Structural equation model examining contributions of family environment to writing skills controlling for children’s ages. Standardized path coefficients reported. ∗∗ p < .01, ∗∗∗ p < .001.

for income in addition to children’s ages (301.81 vs. 389.07, 291.64 vs. 385.54, 296.61 vs. 386.77, 302.39 vs. 394.99, respectively). Finally, chi-square change values for CELT, Writing, AC, and EC were non-significant: χ 2 (22) = 73.26, n.s.; χ 2 (22) = 79.89, n.s.; χ 2 (22) = 76.16, n.s.; and, χ 2 (22) = 78.6, n.s., respectively. Because adding annual family income as a control variable did not alter the results of the structural models presented above, only the structural models depicted in Figs. 1–4 will be discussed.

Fig. 3. Structural equation model examining contributions of family environment to auditory comprehension (AC) controlling for children’s ages. Standardized path coefficients reported. ∗∗ p < .01, ∗∗∗ p < .001.

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Fig. 4. Structural equation model examining contributions of family environment to expressive communication (EC) controlling for children’s ages. Standardized path coefficients reported. ∗∗ p < .01, ∗∗∗ p < .001.

7. Discussion The goal of this study was to examine associations between the three theoretical models, Family as Educator, Resilient Family, and Parent–Child Care Partnership (Snow et al., 1991), and emergent literacy skills among middle-income preschool children. Results from this study showed that the Family as Educator model was significantly associated with preschool children’s book-related knowledge and receptive and expressive language skills. Results did not, however, show the Resilient Family and Parent–Child Care Partnership models as significantly related to preschool children’s emergent literacy skills. Although these results lend support to Snow et al.’s (1991) contention that the family environment significantly affects children’s language and literacy outcomes, this study only provides support for the relationship between the Family as Educator model and outcomes. This model encompasses parental reading beliefs, literacy activities, joint book reading, and parental education. The variables comprising the Family as Educator model can be seen as a cluster of parental beliefs and practices that afford children an opportunity to learn through observation and exploration. Furthermore, many of these beliefs and practices have been found to be related to preschool children’s language and literacy skills. For example, joint book reading has been associated repeatedly with child literacy outcomes (e.g., Bus et al., 1995; Senechal et al., 1998). More comprehensive conceptualizations of the home literacy environment, including literacy-related activities and beliefs, also have been linked to children’s acquisition of language and literacy (Evans, 1998; Griffin & Morrison, 1997). Commenting on the importance of the home literacy environment, Snow, Burns, and Griffin (1998) write, “Thus, a preschooler whose home environment provides fewer opportunities for acquiring knowledge and skills pertaining to books and reading is at somewhat higher risk for reading difficulties than a child whose home affords a richer literacy environment” (p. 11).

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Although the Family as Educator model represents parental beliefs and practices affording learning opportunities to children, the other two models, Resilient Family and Parent–Child Care Partnership, seem to encompass concepts that reflect contextual variables that may affect children’s language and literacy skills. In this study, these two models were not significantly related to preschool children’s language and literacy skills. Our results indicate that protective factors representing the Resilient Family model were not related to outcomes among the preschool children studied as previously reported by Snow et al. (1991) among low-income elementary school children. Although some work has documented the importance of resiliency-type variables among middle-income families (e.g., Morrow, 1983; McMullen & Darling, 1996), we did not find them to be significant in this study. Low-income families, such as those studied by Snow et al., may be faced with strains and social inequalities that make it difficult for parents to foster children’s emerging literacy skills. Therefore, it is possible that protective factors characteristic of the Resilient Family model, such as family resources, routines, and stressors, are not as critical for middle-income children, like those in this study, as they are for low-income children. Additionally, although Snow et al. (1991) reported significant associations between their Parent–School Partnership model and writing skills and reading comprehension among elementary school children, no such relationships between our Parent–Child Care Partnership model and child outcomes were found in this study. In attempting to explain this difference, it is important to first remind the reader that in this study the variables comprising our Parent–Child Care Partnership model were different from those used by Snow et al. in their Parent–School Partnership model. While Snow et al.’s variables focused on parent involvement in homework and insuring that children attended school, our variables, chosen to be more appropriate for preschool children, focused on parents’ relationships and contact with child care teachers. For example, although most preschools do follow some degree of developmentally focused curricula, out-of-school work required by children is infrequent. Therefore, future research on the parent–child care connection might include other appropriate indicators, such as parental agreement with centers’ educational practices or teachers’ perceptions of the Parent–School Partnership. In attempting to explain the differing results between our study and Snow et al.’s (1991), it is possible that the processes, or family dynamics, that foster language and literacy skills differ between elementary and preschool-age children. Parents’ and children’s interactions around literacy and learning activities before formal schooling are often very parent-dependent; parents often direct the types of learning opportunities their children engage in, as well as when and how these opportunities take place. For example, the importance of parent-initiated, literacy-related activities, such library use and book reading, in preschool children’s acquisition of language and literacy is supported by our results, as well as by others (e.g., Christian et al., 1998; Griffin & Morrison, 1997). In addition, parents can often choose the types of child care in which they enroll their children (e.g., structured academic, developmental, Montessori, etc.). On the other hand, interactions between children and parents after a child begins to read may be less a function of parent direction and more a function of a child’s school activities (e.g., homework). Parents may find themselves reacting to the demands of their children’s schools, and to their children’s own interests. Therefore, parents of preschoolers and elementary school children may view their partnerships with their children’s schools, as well as their relationships with their children, very differently.

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Finally, it is noteworthy that the Family as Educator, Resilient Family, and Parent–Child Care Partnership latent constructs were highly intercorrelated across the four structural models tested. The highest correlation was between the Family as Educator and Resilient Family latent constructs (p < .001). The high association between these constructs implies that families characterized by high resources and routines, as well as few daily stressors, are those also likely to afford their children opportunities to learn through parental beliefs and practices. The positive correlation between the Family as Educator model and the Parent–Child Care Partnership construct also implies that parents who are actively involved in their children’s schooling are also likely to encourage learning through the home environment. Therefore, even though there are conceptual distinctions among the Family as Educator, Resilient Family, and Parent–Child Care Partnership models, they may be part of a general, overarching family orientation to early childhood learning and development. Several limitations of the present study also warrant consideration. First, the results are based on cross-sectional data. Even though directional assumptions were made in the structural equation modeling procedures in accordance with past research (i.e., Snow et al., 1991), readers are reminded that the relationships found represent only covariations among variables. Therefore, an implication for future research is the need for longitudinal studies to confirm the structural models reported here. A second limitation of the present study is that the results are based on a relatively small sample of middle-income families and should be interpreted cautiously. It also is noteworthy that the variables examined in this study were different from many of those in the Snow et al. (1991) study. This decision to measure different variables from Snow et al. was made to insure that participating parents perceived the measures as relevant and meaningful, as well as developmentally appropriate, for their preschool children. However, it is possible that this study did not replicate all of the findings of the Snow et al. study as a result of the different, albeit developmentally appropriate, constructs measured. Finally, all home environment variables were assessed through self-report measures. The use of self-report measures does not allow for confirmation of parental responses. It is possible that parents responded to questions in a socially-desirable manner. Future research should therefore address this issue by collecting objective data on the home environment (e.g., observer ratings of the home environment) in addition to self-report measures to allow for confirmation of self-reported, literacy-related activities and beliefs. 7.1. Implications for practice Results from this study suggest several implications for researchers and educational practitioners. First, these results support the utility of using comprehensive, multi-faceted measures of the home literacy environment. Although much research has supported the importance of joint book reading in children’s language and literacy development (e.g., Bus et al., 1995; Senechal et al., 1998), future research should further explore how other, more comprehensive literacy constructs, including parental education, parental reading habits, parental reading beliefs, and parental writing skills, affect young children’s language and literacy outcomes. Such research endeavors also should explore how these processes operate for low-income families in addition to middle-income families.

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These data also suggest the utility of reading intervention programs for educational practitioners. Because parental beliefs and activities that afforded preschool children opportunities to learn were most important within this study, intervention programs focusing on teaching parents developmentally appropriate ways to foster language and literacy skills in preschool children seem promising. Already, many researchers have demonstrated the positive effect interventions can have upon children’s language and literacy outcomes (e.g., Arnold, Lonigan, Whitehurst, & Epstein, 1994; Burger & Landerholm, 1991; Cronan, Walen, & Cruz, 1994; Morrow & Young, 1997a, 1997b; Neuman, 1996; Whitehurst et al., 1994a, 1994b). For example, Reese and Cox (1999) taught parents to read to their children in a “describer style” (i.e., describing and labeling pictures). Results showed that children read to in this manner showed the greatest overall improvement in vocabulary and print skills. Findings suggest that intervention programs guided by empirical research can enhance young children’s emergent literacy.

8. Conclusion Results from this study suggest that parental literacy-related beliefs and activities that afford children opportunities to learn are important in preschool children’s acquisition of language and literacy skills. Given that children are exposed to words and language when reading books with their parents, these results are not surprising. It also is likely that parents who are well-educated, as many of the ones sampled in this study, can better provide a literacy-enriched home environment, positively affecting their children’s language and literacy skills. Similarly, it may be that parents who are themselves articulate provide a family environment that fosters the same in their children; these parents may serve as models of verbal behavior to their young children. We also speculate that preschool-age children from low-income families may reap achievement-related benefits from family protective factors, as suggested by Snow et al.’s (1991) Resilient Family model, to an extent that children from middle-income families may not. We suggest that such protective factors can compensate for early disadvantages encountered by low-income children that may not often be experienced to the same degree by their middle-income counterparts. Finally, we did not replicate findings reported by Snow et al. concerning their Parent–School Partnership model. It is possible that the Snow et al. results were not replicated on account of the different conceptualizations of “partnership” at the elementary and preschool levels. While Snow et al.’s model focused on parental involvement with homework and parent–child interactions around homework, different variables were chosen for our Parent–Child Care Partnership model to be more meaningful for the sample of preschool children and their parents. In conclusion, results from this study support the link between the home literacy environment and young children’s acquisition of emergent literacy skills among middle-income families. Our study supports the relationship between parents’ literacy-related beliefs and activities, affording opportunities to learn, and preschool children’s language and literacy competencies. Results suggest that literacy-related variables such as joint book reading, parents’ attitudes toward, and interests in, reading books, and parental education may strongly impact

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young children’s language outcomes. These results represent a first step toward clarifying the processes underlying the development of young children’s language and literacy skills. Given the paramount role played by language and literacy in children’s future academic development and achievement, these findings are vital for researchers and educators alike. Notes 1. Data for this project were collected from 151 families. Eight families were excluded from the data analyses for normality purposes because children’s scores on the literacy/language outcomes were identified as outliners. 2. Although the researchers specifically targeted 3- and 4-year-old children through their child care teachers and parents for participation in the study, data were collected from a few children older than the desired age. These older children were students in mixed-aged classrooms. In other words, the older children in the study attended classrooms that also included the desired age range of 3- and 4-year-old children. All children included in the study attended licensed child care centers in the county. 3. A correlation matrix with all variables included in the structural models tested is available from the first author upon request. 4. Prior to estimating the structural models, child outcome variables were examined for normality. After excluding outlying cases (see footnote 1), the ratios between the variables’ kurtosis values and standard errors, and the ratios between skewness values and standard errors, were examined. The optimal levels for these ratios, signifying normality, are between −2.0 and 2.0 (SPSS, 1997). Results for the CELT showed the kurtosis ratio was −1.20 and the skewness ratio was −.40. Results for the Writing measure showed the kurtosis ratio was −2.50 and the skewness ratio was .80. Results for AC showed the kurtosis ratio was −1.40 and the skewness ratio was −1.90. Finally, results for EC showed the kurtosis ratio was 3.10 and the skewness ratio was −1.60. Because the kurtosis ratios for Writing and EC fall outside the optimal range, a log transformation for Writing, and a squared transformation for EC, was done. After these transformations, the kurtosis ratios for Writing and EC were 2.10 and −2.20, respectively. Although these ratios fall slightly outside the optimal range, MLE is robust to variations in normality (Bijleveld, Mooijaart, van der Kamp, & van der Kloot, 1998; Jaccard & Wan, 1996). Results from structural models with transformed Writing and EC scores [χ 2 (111) = 178.34, p = .000, NFI = .98, IFI = .99, CFI = .99, RMSEA = .06 and χ 2 (111) = 184.23, p = .000, NFI = .98, IFI = .99, CFI = .99, RMSEA = .07, respectively] were not appreciably different from models with non-transformed scores. Therefore, the non-transformed Writing and EC scores will be used in subsequent analyses. 5. Although Snow et al. (1991) included parent education as a variable in the Family as Educator model, we explored the possibility that education might be related to all three models, rather than just to the Family as Educator model. Hence, we re-estimated the structural models using parent education as a control variable (rather than including it as an indicator of the Family as Educator latent construct). We found that parent education was not significantly related to any of the child outcomes. Furthermore, education was

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significantly related to the Family as Educator latent construct, but not to the Resilient Family or Parent–Child Care Partnership latent constructs. Model fit indices also revealed poor fits to the re-estimated structural models. Based on these results, we chose to include parent education as an indicator of the Family as Educator latent construct as opposed to a control variable across structural models.

Acknowledgments The study was supported by a Nevada Agriculture Experiment Station Grant.

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