Proximal and Distal Features of Day Care Quality and Children's Development

Transcription

1 Early Childhood Research Quarterly, 8, (1993) Proximal and Distal Features of Day Care Quality and Children's Development Loraine Dunn University of Oklahoma Day care quality assessments can be categorized according to their proximity to children's actual experiences. Distal quality assessments describe experiences potentially available to children, but do not describe actual experiences. Distal quality assessments include structural variables, such as ratio, group size, caregiver characteristics, and global quality assessments such as the Early Childhood Environment Rating Scale (ECERS; Harms & Clifford, 1980). Proximal quality assessments describe the actual events experienced by children in day care settings. Proximal quality was defined by the National Association for the Education of Young Children's (NAEYC; Bredekamp, 1987) guidelines for developmentally appropriate practices and included caregiver goals, strategies, and guidance. The study examined (1) the efficacy of proximal and distal quality in predicting children's development after controlling for family factors, and (2) the validity of using the NAEYC guidelines as a measure of proximal quality. Correlations between the ECERS and proximal quality lent tentative support to the validity of the guidelines. Proximal and distal quality were equally effective in predicting children's development, each predicting two of six forms of development. Day care quality assessments can be categorized according to their proximity to children's actual experiences in the day care environment. Distal quality assessments describe experiences potentially available to children, but not Portions of this study were submitted to the Graduate Faculty of Purdue University as partial fulfillment of the requirements for a Doctor of Philosophy degree. An earlier version of this article was presented at the Biennial Meeting of the Society for Research in Child Development, April 1991, Seattle. Appreciation is expressed to Terry Buchanan, Linda Hestenes, Lora Andrada, Karen Fred, Yiping Wang, and Marikay Wilson for assistance in gathering, preparing, and coding the data, and to Michael Langenbach for criticizing the manuscript. Thanks also to Susan Kontos for assistance with this project. Correspondence and requests for reprints should be sent to Loraine Dunn, Instructional Leadership and Academic Curriculum, University of Oklahoma, College of Education, B20 Van Vleet Oval, Norman, OK Received July 9, 1991; Revision received July 27, 1992; Accepted November 25,

2 168 Dunn children's actual experiences. Proximal quality assessments, on the other hand, capture children's actual experiences in day care settings. Proximal and distal quality assessments represent differing levels of specificity in describing day care environments, and therefore differing levels of complexity, in explanatory research design. Distal forms of quality describe broad parameters of the environment and include structural assessments, such as ratio, group size, and caregiver training, as well as global assessments, such as the Early Childhood Environment Rating Scale (ECERS; Harms & Clifford, 1980). Distal measures of quality provide broad labels such as "large group size" or "average quality" for day care environments. Bronfenbrenner (1986) described such labels as "social address" models of research. He argued that more powerful models of research examine the processes that occur within social addresses. Proximal quality assessments, which describe specific, dynamic features of the environment (i.e., caregiver-child interaction), provide a window through which processes can be observed. By examining both proximal and distal features of day care quality, we can attend to both social addresses and processes in day care environments. Day Care Quality and Children's Development The available literature on day care quality sheds some light on the influences of distal quality on children's development. Children enrolled in programs with smaller group sizes tend to be more cooperative, compliant, and considerate, engage in more sophisticated social play, perform with more sophistication on measures of social competence, give fewer antisocial responses during social problem-solving tasks and make better academic progress (Clarke-Stewart & Gruber, 1984; Howes, 1988; Phillips, Scarr, & McCartney, 1987; Ruopp, Travers, Glantz, & Coelen, 1979; Whitebook, Howes, & Phillips, 1989). Large group sizes have been associated with more aimless wandering by children and lower levels of social adjustment (Howes, 1988; Ruopp et al., 1979). Low ratios (few children per caregiver) have been associated with higher levels of social competence, more sophisticated social play, higher levels of compliance and cooperation, and more advanced academic progress (Clarke-Stewart & Gruber, 1984; Howes, 1988; Howes & Olenick, 1986; Whitebook et al., 1989). Children experiencing high ratios have been observed to engage in more aimless wandering, more peer interaction, and exhibit less optimal social adjustment (Howes, 1988; Howes & Olenick, 1986; Whitebook et al., 1989). Higher levels of caregiver education (regardless of area of study) tend to be accompanied by higher levels of social competence in children (Clarke-Stewart & Gruber, 1984). When caregivers have education or training specifically related to children, the children in their care are more compliant and cooperative, and make higher scores on achievement tests (Howes & Olenick, 1986; Ruopp et al., 1979; Whitebook et al., 1989). On the other hand, higher levels of child-

3 Proximal and Distal Day Care Quality 169 related education and/or training have been related to lower levels of independence and social competence (Clarke-Stewart & Gruber, 1984). The most commonly used global quality assessment, the ECERS (Harms & Clifford, 1980), has also been associated with children's development. Higher levels of ECERS quality have been associated with more considerate, sociable, and task-oriented behaviors in children (Phillips et al., 1987). A limited amount of information is available on how proximal features of day care quality influence children's development. The research conducted to date indicates that positive, attentive caregiver interactions with children are associated with positive child outcomes in all developmental domains (McBride & Rubenstein, 1990; McCartney, 1984; Phillips et al., 1987; Rubenstein & Howes, 1979). In addition, the environment created by the caregiver through planned activities is also related to children's development (Clarke-Stewart & Gruber, 1984; Vandell, Henderson, & Wilson, 1988; Vandell & Powers, 1983). Developmentally Appropriate Practices Current wisdom argues that proximal quality assessments, such as those previously outlined, are the best way to capture the essence of quality variation effects on children's development (Belsky, Steinberg, & Walker, 1982). The measurement of proximal quality features is dependent upon identifying and isolating variables that should influence children's development. In order to do this, theoretical notions about how development is facilitated must be examined. Cognitive developmental theory argues that development occurs as children actively participate in the environment. Being a theory of development though, cognitive developmental theory does not describe how active participation with the environment can be facilitated. A theory of practice is needed for this task. A theory of practice should take an active posture by describing desired behaviors and practices. It should provide a specific description of the context(s) in which optimal development is most likely to occur (Fein & Schwartz, 1982). The closest approximation to a theory of practice currently available in early childhood education is the National Association for the Education of Young Children's (NAEYC; Bredekamp, 1987) guidelines for developmentally appropriate practice. Drawing from the tenets of cognitive developmental theory, NAEYC delineates specific classroom practices believed to facilitate heathly child development. Thus, the developmentally appropriate practice guidelines can be seen as a potential theory of practice useful for guiding the selection of proximal features of day care quality. Two recent studies support the use of NAEYC's developmentally appropriate practice guidelines as a theory of practice. Children in more developmentally appropriate classrooms exhibited lower levels of stress (e.g., hair twisting, finger drumming; Butts, Hart, Charlesworth, & Kirk, 1990), more

4 170 Dunn creativity, and more prosocial behavior (Hirsh-Pasek, Hyson, & Rescorla, 1990) than children in less appropriate classrooms. Because both studies measured developmentally appropriate in a global fashion, additional examination of the guidelines is needed to identify the specific practices that may serve as proximal quality features. The sections of the NAEYC guidelines most closely tied to cognitive developmental theory and most similar to variables included in the extant proximal day care quality literature are those describing appropriate practices for adult-child interaction and curriculum. Three components of developmentally appropriate practice fall under the rubric of adult-child interaction and curriculum: (1) caregiver's curriculum goals; (2) caregiver's strategies in preparing the environment and interacting with children; and (3) the nature of caregiver's guidance of children's social-emotional development. Curriculum goals may reveal the appropriateness of caregiver's curriculum beliefs and curriculum plans. Strategies refer to the caregiver's facilitation of learning through the preparation of the environment and caregiver-child interaction. Caregiver's guidance of children includes both positive guidance techniques, such as praise, and the establishment of parameters or limits for child behavior. These three components of developmentally appropriate practice describe situations children actually experience in day care environments and so represent proximal quality variables. The primary goal of this study was to examine proximal and distal forms of quality and their relationships to children's social and cognitive development. It was hypothesized that proximal quality (processes) would be effective in predicting children's development after variance from distal quality (social address) had been controlled. The second goal of this study was to examine the validity of using NAEYC's developmentally appropriate practice guidelines as a measure of proximal day care quality. To address this issue, associations between proximal and distal quality variables were examined. The two study goals also provided an initial test of the validity of using the developmentally appropriate practice guidelines as a theory of practice. METHOD Sample The sample consisted of 30 day care classrooms in 24 centers and the head teachers from each classroom. The classrooms were recruited from community centers in an eight-county region of north-central Indiana. All of the 47 licensed centers in this area were contacted and invited to participate. To ensure quality variability, no more than 2 classrooms from any center were observed. Twenty-four or of the centers agreed to participate in the study. Eight of the participating centers were nonprofit ad 16 were for profit.

5 Proximal and Distal Day Care Quality 171 Table 1. Descriptive Statistics for Day Care Quality and Child Outcomes Distal Quality M M Item Score SD Range Group Size Ratio l: :9-1:20 Caregiver Educ. a Caregiver Center Exp. a Caregiver Field Exp. a Caregiver Age a ECERS (37-259) Proximal Quality Goals (28-168) Strategies Play Space variety Divergent/Elaborative Guidance Praise/Nurture/Redirect Clear Limits Total Limits Child Outcomes CBI-Social ( ) PBQ (0-6O) Social Play CBI-Intelligence ( ) PSI (0-64) Cognitive Play Note. Numbers in parentheses represent possible ranges. a Measured in years. Of the 6 centers from which a second classroom was drawn, 2 were nonprofit and 4 were for-profit centers. A nonsignificant chi-square test indicated that there was no difference in auspice between participating and nonparticipating centers. Information obtained from the directors during recruitment and compared via t tests indicated the participating and nonparticipating centers were similar in terms of center size, number of teachers employed, training of staff, and staff turnover. Centers participating in the study employed fewer aides than centers not participating, t(40)=2.29, p<.05. Average turnover rates for centers in the sample were for teachers, for aides, and 8070 for directors. Average group size and ratio in the participating cla~ssrooms are reported in Table 1.

6 172 Dunn Caregivers. All but 3 of the caregivers were white. As seen in Table 1, their mean level of education was quite high. Nineteen of the caregivers reported some education beyond high school, a percentage of the total similar to that found in the National Child Care Staffing Study (NCCSS; Whitebook et al., 1989). Of those 19 caregivers, 15 reported college-level work in a child-related major. Only 6 of those 15 caregivers reported majoring in early childhood education/child development. When asked how much training they had specifically related to child care, early childhood education, or child development, the average caregiver response was junior college/technical school training or an associate's degree. As reported in Table 1, the mean level of caregiver experience in the field of day care was quite high and the range of experience was quite broad. Caregiver's mean level of experience in their current centers was somewhat lower. Children. One boy and 1 girl (N=60) from each participating classroom were randomly selected. Eligibility requirements for children focused on normal development, age (36-60 months), and day care history. The goal was to obtain children who attended day care full-time (at least 25 hours per week) and who had been enrolled in the target centers at least 6 months. In the few cases where it was not possible to recruit 1 boy and 1 girl due to lack of eligible children, 2 children of one sex were randomly selected. This sampling procedure resulted in 34 (57070) girls and 26 (43 7o) boys with a mean age of months (SD = 6.71). The majority of the children were white; 6 were black. Mean length of time children had been enrolled in the target centers was 1.25 years (SD=0.89). Children's mean age of entry into day care was months (SD = 15.59). Family Characteristics. Parent information was returned by 57 of the 60 families (95 70). The majority of the parents in the sample (77.207o) were married. Mean age for mothers was (SD = 4.50) and (SD = 4.71) for fathers. Educational attainment averaged 13.4 years (SD= 1.97) for mothers and years (SD = 2.57) for fathers. The average family income ranged between $29,000 and $34,999. Mean socioeconomic status level for the sample fell in Category IV of the Hollingshead (1976) Four-Factor Index of Social Status: medium business, minor professional, and technical workers. Instruments: Independent Variables Child and Family Characteristics. Because family background characteristics are known to interact with day care quality and children's development, family background information was obtained from each child's parent via parent questionnaires. Parents were asked to provide information on child age, day care history, parental age, marital status, education, occupation and income. Parental occupation and education were used to

7 Proximal and Distal Day Care Quality 173 compute a Hollingshead (1976) Four-Factor Index of Social Status. Maternal stress was assessed through a 13-item questionnaire on role overload addressing feelings about work and family life. The questionnaire, developed by Reilly (1982), contains only negative items that are rated on a 5-point Likert scale. Higher scores on the scale indicate lower levels of stress. Reilly reported an internal consistency of.88 (Cronbach's alpha). Internal consistency for this sample was.92 (Cronbach's alpha); mean level of maternal stress in this sample was moderate (M= 32.84, SD = 10.54). Distal Day Care Quality. Distal day care quality variables were measured through direct observations, interviews, and questionnaires. The participating caregivers responded to questionnaire items regarding their age, level of education, training, and experience. The caregivers were interviewed to obtain information on group size and caregiver-child ratio. This information was verified by direct observation (the highest figures recorded were used for analyses). Classrooms in profit and nonprofit centers were similar on all of these variables except ratio. More favorable ratios were observed in nonprofit centers, t(28)= 3.56, p <.01. Each classroom was also observed to provide an overall assessment of the day care environment using the ECERS (Harms & Clifford, 1980). The ECERS assesses multiple aspects of the day care environment through items on the following subscales: Personal Care, Creative Activities, Language/ Reasoning Activities, Furnishings/Display, Fine/Gross Motor Activities, Social Development and Adult Facilities/Opportunities. Good interrater reliability and internal consistency have been previously established on this instrument (~=.93 and.83, respectively; Harms & Clifford, 1980). For this study, an interrater reliability level of was established before data collection was begun. Interrater reliability was checked after every 10th center observation and averaged throughout the course of the study. Internal consistency for the ECERS with this sample was.95 (Cronbach's alpha). The ECERS required a 2-hour observation of the classroom after which the observer rated each of the 37 scale items on a 7-point Likert scale. Items scores were summed to create subscale scores and subscale scores were summed to create a total score. The mean ECERS score for the sample is shown in Table 1. ECERS scores did not differ as a function of center auspice. Proximal Day Care Quality. Proximal day care quality was assessed through the three components of developmentally appropriate practices identified before: caregiver curriculum goals, caregiver strategies, and guidance of social-emotional development. According to NAEYC, curriculum goals are appropriate when (1) experiences meet children's needs in all developmental areas (cognitive, social, emotional, physical), (2) individual needs are considered, and (3) the environment is conducive to the development of positive self-esteem and positive attitudes toward learning. Average

8 174 Dunn quality scores for all proximal quality variables are listed in Table 1. Proximal quality scores were similar in profit and nonprofit centers. Curriculum Goals. Based on these guidelines, the Educational Attitude Scale, teacher form (EAS, Rescorla, Hyson, Hirsh-Pasek, & Cone, 1990) was chosen to assess caregivers' curriculum goals. The EAS was designed to assess the beliefs of early childhood staff regarding the importance of academic experiences for young children. It also contains items regarding caregiver beliefs about children's social, emotional, and cognitive abilities, thereby tapping caregiver's goals for all areas of children's development. Items on the scale refer to specific activities occurring in early childhood environments, so it is assumed that the attitudes or beliefs reflected by caregivers through the EAS correspond to the curriculum goals caregivers rely on to plan classroom activities. Supporting this assumption, Rescorla et al. (1990) found positive relationships between caregivers' and directors' EAS scores and the developmentally appropriate ratings of their programs. The teacher form of the scale contains 28 items rated on a 6-point Likert scale from strongly disagree (1) to strongly agree (6). A high score on the scale is construed to represent developmentally inappropriate curriculum goals. Rescorla et al. (1990) reported the following reliabilities: split-half,.95, test-retest,.82, and internal consistency,.91 on the parent form of the EAS. The internal consistency of the 28-item EAS used here was.82 (Cronbach's alpha) indicating total scores could be used reliably in subsequent analyses. As seen in Table 1, the curriculum goals of caregivers in this sampole were moderately appropriate. Caregiver Strategies. The second form of proximal day care quality assessed was caregiver strategies. NAEYC (Bredekamp, 1987) defines caregiver strategies in two basic ways. One is the manner in which the caregiver prepares the environment for play and the other is the manner in which the caregiver interacts with the children during the day. An appropriately prepared environment is one that encourages active exploration and interaction with materials, peers, and caregivers rather than one in which children are expected to be passive and concentrate on adult-directed activities. Appropriate caregiver interaction with children is represented by facilitation of children's activities through the asking of divergent questions, offering suggestions, encouraging and helping children elaborate on their activities. A content analysis was used to assess the caregiver's preparation of the environment. An evaluation scheme developed by Kritchevsky (1967) and used by Getz and Berndt (1982) determined the complexity and variety of the environment. During play time an observer identified all possible play units available (materials or equipment available for play). The play units were coded for complexity as described by Kritchevsky into simple, complex, or super units, and weights were assigned to each unit: simple (1), complex (4), super (8). The weights reflect the number of children that each

9 Proximal and Distal Day Care Quality 175 unit can accommodate. The weighted frequencies for each play unit were summed and then divided by the number of children present to create a score for play spaces available per child. This number represents the potential number of play choices available to a child at any given time. Kritchevsky recommended that a minimum of 2.5 play spaces per child be available at all times. Getz and Berndt found considerably lower levels typically available in the day care centers they studied. Similarly, the typical number of play spaces available per child in this sample was quite low (see Table 1). The play environment was also evaluated for variety, that is, how many different types of activities were available. It is possible for a classroom to have an adequate number of play spaces available, but to have little variety. For example, an environment offering choices of riding, climbing, painting, and pretending has a higher variety than an environment offering choices of only riding and climbing. Each play unit was classified for the primary type of activity it invited as described by Kritchevsky (1967). A variety score was created by summing the number of different types of activities available. Mean variety for this sample was 4.90 (SD = 1.88, range = 1-8). Interrater reliability of 93% for the content analysis was established before data collection was begun. Reliability checks conducted at 10-classroom intervals indicated interrater reliability averaged 98% throughout the course of the study. The second aspect of caregiver strategies, caregiver interaction with children, was assessed through two behaviors chosen for their emphasis in the NAEYC document and their relevance to cognitive developmental theory. They were caregiver's divergent questioning of children and caregiver's facilitation or elaboration of children's learning. During a 2-hour observation period, an observer used an audiotape recorder to describe interactions (using direct quotes) among the caregiver and children. An event agreement rate of 89% was established before data collection was begun. Reliability checks conducted after approximately every 10 classrooms observed indicated the event agreement rate averaged 86% throughout the course of data collection. The audio recordings were transcribed and coded for the variables of interest: divergent questioning and facilitation of learning. The divergent questions addressed to children by the caregiver during the observation period were identified. Facilitation of play was assessed by identifying those interactions that involved elaborated exchanges (as defined by Dunst, 1986) between caregiver and child. The divergent and elaborative interactions were summed to create a single score. Both percent agreement and a correlation coefficient were computed to determine interrater reliability for divergent/elaborative interactions. Before coding data from the study, two coders were trained to an interrater agreement level of 94% (r = 1.00). Interrater agreement was checked after

10 176 Dunn coding every 10th transcript and documented an average agreement level of (r =.93) throughout the course of the study. Guidance. The final component of proximal day care quality examined was caregiver's guidance of children's social-emotional development. Bredekamp (1987) defined guidance of social-emotional development as caregiver facilitation of children's self-control through positive guidance techniques. The previously described audio recording of caregivers' interactions with children was used to obtain a frequency count of caregivers' guidance techniques. The following behaviors identified in Stremmel and Powell's (D.R. Powell, personal communication, September, 1989) adaptation of Prescott and Jones's (1967) work was used for this purpose: (1) caregiver gives praise or encouragement; (2) caregiver provides nurturance, comfort, help, or affection; (3) caregiver redirects behavior or suggests alternate activity. Frequencies of these behaviors were summed to create a total score. Reliability for observation of guidance was established at (r=.99) before coding actual data and averaged (r--.98) over the course of the study. A second measure of guidance was caregiver's setting of limits for children. Limits were assessed by obtaining a frequency count from the audio transcripts of the following situations: (1) caregiver gives directive and child complies immediately; (2) caregiver gives directive and follows up until child complies; (3) caregiver gives directive but does not follow up until child complies; (4) caregiver threatens action on which he or she cannot follow up (i.e., "Stop that or Santa Claus won't come to your house"). The first two categories refer to clear limits, whereas the second two categories refer to unclear limits. The total frequency of clear limits was summed and divided by the sum of both clear and unclear limits to create a proportion score for limits. In addition, a score for the total number of limits set by caregivers was computed by summing the frequency of clear and unclear limits. Reliability for limit setting was established at (r = 1.00) before coding of data began and averaged (r--.99) over the course of the study. Descriptive statistics for all quality variables are presented in Table 1. Instruments: Dependent Variables Social Development. CBI Sociability. Dependent measures assessing child outcomes consistent with the expectations of cognitive developmental theory were chosen for this study. Two static and one process measure of children's social development were obtained. The first static measure was the Classroom Behavior Inventory-Preschool Form (CBI; Schaefer & Edgerton, 1978). The CBI is a 60-item teacher rating scale on which children are rated from not at all like (1) to very much like (5) scale. The Sociability subtest consists

11 Proximal and Distal Day Care Quality 177 of 30 items from six subscales assessing Extroversion-Introversion, Considerateness-Hostility, and Independence-Dependence. The mean internal consistency of these subscales is.84 (Cronbach's alpha). The mean interrater reliability (Spearman-Brown corrected) is.66 (Schaefer & Edgerton, 1978). Higher scores on the scale indicate children display more considerateness, extroversion, and independence. Internal consistency for this sample was.79 (Cronbach's alpha). PBQ. The second static assessment of children's social development was the Preschool Behavior Questionnaire (PBQ; Behar & Stringfield, 1974), a modification of Rutter's (1967) Children's Behavior Questionnaire that measures social deviance. Higher scores indicate more deviant behavior. The PBQ contains 30 items describing problem behaviors. Caregivers must determine whether each item doesn't apply (scored 0), applies sometimes (scored 1), or certainly applies (scored 2) to the target child. Behar and Stringfield reported test-retest reliability of the PBQ as.87 and interrater reliability as.84. Internal consistency for this sample was.89 (Cronbach's alpha). Social Play. The process measure of children's social development was obtained via the Howes' (1980) Peer Play Scale. During four 10-min sessions, the target child's behavior was observed for 5 s and then coded for 5 s resulting in a total of 20 min of actual observation time. The categories observed were solitary, parallel, parallel with mutual regard, simple social, and reciprocal-complementary play. Weights were assigned to the frequency scores as directed by Howes (1980). The weighted frequencies were summed and divided by the total number of play behaviors observed to create a weighted average for complexity of social play. Howes (1980) reported interobserver reliability ranging from.87 to.93 and test-retest reliability over a 4-week period of.91. For this study, interrater reliability of 97 7o was established prior to data collection. During data collection, reliability checks were conducted after one third and two thirds of the data had been collected and documented the average agreement level as 97 7o throughout data collection. Cognitive Development. CBI Intelligence. Children's cognitive development was also measured through static and process measures. The Intellectual subscale of the CBI (Schaefer & Edgerton, 1978), contained in the remaining 30 items of the scale, was one of the static assessments. The 30 items contain subscales relating to task orientation versus distractibility, creativity/curiosity versus apathy and verbal intelligence. Higher scores on the Intelligence subscale indicate more task orientation, creativity, and verbal intelligence. Internal consistency of the CBI Intelligence subscale for this sample was.89 (Cronbach's alpha).

12 178 Dunn PSI. The Preschool Inventory-Revised Edition (PSI; Caldwell, 1970), an individually administered achievement test, was the second static measure of children's cognitive development. The PSI contains 64 items and requires about 20 min to administer. The total number of correct responses was tallied for use as the dependent measure. Although percentile scores based on age norms are available, the raw scores were not converted to percentile scores because percentile scores do not represent interval-level data (Popham & Sirotnik, 1973). Because the raw PSI scores were highly correlated with children's age (r =.65, p <.001), children's age was covaried in all analyses using the PSI score. Split-half reliability for the PSI was assessed as.92 (Spearman-Brown corrected) and.91 (Kuder-Richardson 20; Caldwell, 1970). Cognitive Play. Complexity of children's cognitive play was assessed with a combination of Smilansky's (1968) Cognitive Play Scale and Howes and Stewart's (1987) Play with Objects Scale. Four 10-min observations of each child's play behavior made in tandem with the social play observations were coded into the following categories: no cognitive play, functional play without objects, functional play with passive use of objects, functional play with active use of objects, constructive play, and dramatic play. As suggested by Howes and Stewart, these frequencies were then weighted (from 0-5), summed, and divided by the total number of play behaviors observed to create a total score for average complexity of cognitive play. As with social play, interrater reliability was established at before data collection began and was checked twice during the data-collection period. Average interrater agreement over the course of the study was 97o70. Descriptive statistics for all child outcomes measures are reported in Table 1. Procedure Two eligible children from each participating classroom were randomly selected, their parents contacted, and the study explained. All parents contacted agreed to participate. At least three visits were made to each classroom. During the first visit an observer administered the ECERS (Harms & Clifford, 1980), recorded the number of children and adults in the classroom, interviewed the caregiver regarding distal quality variables, and distributed questionnaires for caregivers and parents. A second observer, blind to the ECERS rating, made the narrative recording during this visit. Another observer, blind to ECERS quality and the narrative recording, made a second visit to observe the children's play and conduct the content analysis of the classroom. The caregiver and parent questionnaires were collected at this time. An independent experimenter visited the classrooms to administer the PSI to the children during the final visit.

13 Proximal and Distal Day Care Quality 179 Table 2. Intercorrelations Among Distal Quality Variables Caregiver Child Exp. Exp. Group Education Major Training a Center Field Size Ratio Child Major.50* Training a.72**.32 Center Exp Field Exp Group Size Ratio ECERS '.29*.16 Note. n = 30. a Training Scoring: 0=none, 1 = High School courses, 2 = Jr. College/Technical School courses or CDA training, 3 = Associate's degree, 4 = Bachelor's degree, 5 = Master's degree, 6 = Doctoral degree. * p<.05. ** p<.001. RES UL TS Desriptive Statistics Quality and Child Outcome Intercorrelations. Three sets of data analyses were performed to address the research questions. The first set of analyses explored intercorrelations among proximal and distal quality variables as well as correlations among the child outcome measures. Given the position advanced by some scholars that good program characteristics tend to cooccur (Hayes, Palmer, & Zaslow, 1990; Phillips & Howes, 1987), surprisingly few correlations were found among the various quality variables. As seen in Table 2, there were few significant intercorrelations among distal quality variables. Caregivers with higher levels of education, in general, were more likely to have formal or informal training specifically related to children and were more likely to have college-level work in a child-related area. Classrooms with higher ECERS quality tended to have larger group sizes and be led by teachers with more experience in the field. As seen in Table 3 (p. 180), there were four significant relationships between distal and proximal quality variables. Larger group sizes and higher ECERS quality scores were associated with more variety in classroom activities. Caregivers in classrooms rated as higher on ECERS quality were more likely to engage in divergent/elaborative interactions with children and to set fewer limits for children. These associations point to areas of overlap in quality features addressed by the ECERS and the proximal quality variables. The relationships among the proximal quality variables are documented in Table 4 (p. 181). Higher levels of classroom variety were associated with

14 180 Dunn Table 3. Correlations Between Distal and Proximal Quality Variables Proximal Quality Distal Play Clear Total Quality Goals Space Variety DE g PNR b Limits Limits Caregiver Educ Child Major Training Center Exp , Field Exp Group Size ** Ratio ECERS *.66*** ** Note. n = 30. a DE = divergent/elaborative interactions, interactions. * p<.05. ** p<.01. *** p<.001. b PNR = praise/nuturance/redirection more play spaces per child and with a higher incidence of caregiver divergent/ elaborative interactions. Caregivers who engaged in higher levels of divergent/elaborative interactions also displayed a higher incidence of praise/ nuturance/redirection and a lower level of limit setting. Next, intercorrelations among the child outcome variables were examined. As seen in Table 5 the three caregiver rating measures were highly correlated. This suggests the presence of shared method variance among both the CBI subscales and the PBQ. In addition, when children's age was covaried, higher PSI scores were associated with caregiver ratings of children's intelligence on the CBI.' Quality and Children's Development. The second set of analyses were descriptive statistics on the proximal and distal quality variables, child/family background characteristics and child outcomes. Correlations were computed between ECERS quality scores and family background characteristics to identify the presence of center selectivity factors in the sample, a strategy previously used in the Bermuda day care study (Phillilps et al., 1987). Correlations between the ECERS and parental age, marital status, income, SES, ' Because of the significant intercorrelations among child outcome measures, a principal components analysis was performed to identify a composite measure or measures of children's development. The analysis produced two interpretable components: (1) social competence consisting of PBQ scores, CBI Sociability and CBI Intelligence scores, and (2) play/achievement consisting of PSI scores and mean level of social and cognitive play. Only one correlation was found between the two composite outcome measures and quality: social competence and caregiver's experience in the center (r =.25, p<.05). Because the composite outcomes identified by the principal components analysis yielded less information about day care quality and children's development than the individual outcome measures, the individual outcome measures were used for the purposes of this study.

15 Proximal and Distal Day Care Quality 181 Table 4. lntercorrelations Among Proximal Quality Variables Play Clear Goals Space Variety DE a PNR ~ Limits Play Space.04 Variety.05.45"* DE a *.27 PNR b * Clear Limits Total Limits * Note. n = 30. a DE = divergent/elaborative interactions. interactions. * p<.05. ** p<.01. b PNR = praise/nuturance/redirection Table 5. Correlations Among Child Outcome Measures CBI Social CBI Sociability PBQ Play Intelligence PSI ~ PBQ -.69** Social Play CBI-Intelligence.76** -.57*.12 PSI a * Cognitive Play Note. n = 60. a Partial correlation coefficients controlling for age. * p<.01. ** p<.001. and stress were nonsignificant. Children's race was correlated with ECERS quality (r=.39, p<.01), indicating this variable was operating as a center selectivity factor. Black children were more likely to be enrolled in higher quality centers. This finding is buttressed by relationships between race and profit status of the center, X2(1, N= 60)= 13.33, p <.001, and between race and income (r =.42, p<.01). Black children were more likely to attend nonprofit centers and to come from families with lower incomes. Thus, race and income were confounded. Race was not correlated with the Hollingshead (1976) assessment of SES. Although the Hollingshead Index does not directly measure income, it was correlated with income in this sample (r=.50, p<.001). This pattern of correlations indicates that income and SES are most likely the underlying factors influencing families' child care choices. Therefore, income, rather than race, was used as a statistical control for center selectivity in later analyses. Correlations between proximal and distal forms of quality and children's development were examined to determine the utility of further analyses. As seen in Table 6 (p. 182), distal quality variables were related to both childrens'

16 182 Dunn Table 6. Correlations Between Day Care Quality and Children's Development Social Development Cognitive Development CBI Social CBI Cognitive Distal Quality Sociability PBQ Play Intelligence PSI a Play Caregiver Educ. b Child Major * I 1 Training Center Exp. b -.30" * Field Exp. b Caregiver Age Group Size Ratio "* ECERS ** Goals Strategies Play Space Variety Diverg/Elab , Guidance Praise/Nuture/Redirect , Clear Limits Total Limits * ,12.01 a Partial correlation coefficients controlling for age. * p<.05. ** p<.01. b Measured in years. social and cognitive development. Proximal quality was related to children's social development but not to children's cognitive development. Pearson product-moment correlations were also computed between child and family background characteristics and child outcomes (see Table 7). Consistent with findings from other studies (Kontos & Dunn, 1989; Kontos & Fiene, 1987), family characteristics were more efficacious in predicting children's cognitive development (10 significant correlations of 24) than social development (1 significant correlation of 24). These relationships documenting the power of family background characteristics in predicting children's development suggest the need to include family characteristics in later analysis. Predicting Children's Development. The third set of analyses were a series of hierarchical multiple regression analyses (one series for each dependent variable) designed to test the hypotheses regarding the efficacy of the proximal quality measures in predicting child development outcomes. A four-step process was used to uncover predictors of children's cognitive and social development. The first step in each series was simultaneous entry of any child and family characteristics (i.e., child age, day care history, SES, and parental age and education), excluding the center selectivity factor, that

17 Proximal and Distal Day Care Quality 183 Table 7. Correlations Between Child and Family Background Characteristics and Children's Development Social Development Cognitive Development CBI Social CBI Cognitive Sociability PBQ Play Intelligence PSI a Play Child Characteristics Child age Sex Race * -.01 Age of entry *.08 Time in center Family Characteristics Maternal age * -.01 Paternal age * -.09 Marital status * Maternal Educ. b *.43* -.02 Paternal Educ. b **.03 Income * -.09 SES *.48***.05 Stress a Partial correlation coefficients controlling for age. * p<.05. ** p<.01. *** p<.00. b Measured in years. correlated with the dependent variable. The second step was entry of the center selectivity factor, income. The third step was simultaneous entry of the distal quality predictors of the dependent variable identified from the correlation analyses. The fourth step was entry of the proximal quality predictors also identified from the correlation analyses. At each step, the increase in R 2 was calculated and an Ftest applied to determine the significance of the R ~ change. Thus, the hierarchical regression described the efficacy of distal and proximal quality in explaining variance in children's social and cognitive development after the variance due to age and family background was taken into account. Hierarchical multiple regression equations were computed for the CBI Sociability subscale, the PBQ, social play, and the CBI Intelligence subscale. Hierarchical multiple regression equations were not calculated for cognitive play or the PSI because therejwere no significant correlations between these measures of development and any of the quality variables. The results of the regression analyses are presented in Table 8 (p. 184). Looking first at CBI Sociability scores, income was not a significant predictor of children's social development. Distal quality in the form of caregiver's experience in the center was a weak but effective negative predictor.

18 ee "~.... ~.. o S o. ~ o o ~. ~ 8-"'~;~. ~, - :... o. " ~ -~,~$.~- ~ ""~ e., := = 8.~..o.~ 8 ~.~ ~ o.,., #_ I=,< o ~0 ~J.o s o d U~.= v 8 o:,,4 0 v ~Q o ~Q 184

19 Proximal and Distal Day Care Quality 185 Children were rated as more sociable when their caregivers had less experience in the center. Regarding children's social adjustment as measured by the PBQ, parent's marital status was a significant predictor of this form of children's development. Children were rated as better socially adjusted when their parents were married. Neither the addition of income nor distal quality in the form of ratio improved the model. The simultaneous entry of variety and total limits significantly improved the predictive power of the model indicating proximal quality was a significant influence on children's social adjustment. Children in classrooms with more limits and more variety were rated as less well adjusted. The average level of children's social play was not predicted by income but was predicted by proximal quality in the form of total limits. More complex social play was seen in classrooms where more limits were set. Note, however, from Table 1, that the average level of social play was quite low (though typical of preschool-age children), parallel with mutual regard. Regarding cognitive development, the results of the hierarchical regression analyses indicated neither child/family background nor center selectivity predicted children's cognitive development as assessed by the CBI Intelligence subscale. The distal quality variables (child major, caregiver's center experience, ECERS) entered simultaneously in the third step of the equation, did significantly increase the prediction of children's development after the effects of child/family variables and center selectivity had been removed. Children in classrooms with higher ECERS quality and whose caregivers had a child-related major and little experience in the center made higher CBI Intelligence scores. Interaction Effects In order to obtain further information about the findings reported here, the potential presence of interaction effects between family background characteristics and day care quality were explored. Literature documenting relationships between family characteristics and quality (Howes & Stewart, 1987) suggest this strategy may be more effective in predicting children's development than either family or quality characteristics alone. Indeed, Kontos (1990) found that the interaction of paternal education and family day care quality predicted children's cognitive and language development. To isolate potential family by quality interaction effects, the zero-order correlations among children's development, child and family characteristics, and proximal and distal quality were examined to identify independent variables that had been useful in predicting each assessment of children's development. As seen in Tables 6 and 7, only children's CBI Intelligence and PBQ scores correlated with both family and quality variables. The strongest family and quality correlates of these two child outcomes were chosen for inclusion in the interaction analyses. For CBI Intelligence scores,

20 186 Dunn 70~ 60~ 0 CBI- Intell 50~ 40 Y Nonchild Major Child Major 0 Low SES O High SES Figure 1. Child-major and SES interaction. the interaction term consisted of family SES and caregiver's child-related major. The interaction term for children's PBQ scores consisted of parents' marital status and classroom variety. The marital status by variety interaction did not predict children's social adjustment when regressed directly on their PBQ scores or when entered as Step 5 (after proximal quality) of the hierarchical regression equation described in Table 8. The SES by child-related major interaction did significantly predict a substantial portion of the variance in children's scores on the CBI Intelligence subscale. This was true both when the interaction term was regressed directly on children's CBI Intelligence scores, R2=.43, F(1, 27)=20.43, p<.001, and when the interaction term was entered as Step 5 of the regression equation (after proximal quality) described in Table 8, R 2 change=.11, Fine=5.66, p<.01. Children from higher SES families whose caregivers had a child-related major scored higher on the CBI-Intelligence subscale than children of lower SES parents (see Figure 1). No child in the high SES group had a caregiver without a child-related major. Recall that only caregivers with college-level work were included in the childrelated major variable. Consequently, the interaction does not speak to the development of children whose caregivers had no college-level training.