Classification of teachers’ interaction behaviors in early childhood classrooms

Early Childhood Research Quarterly, 15, No. 2, 247–268 (2000) ISSN: 0885-2006

© 2000 Elsevier Science Inc. All rights of reproduction in any form reserved.

Classification of Teachers’ Interaction Behaviors in Early Childhood Classrooms Rene´e E. L. de Kruif, R. A. McWilliam, and Stephanie Maher Ridley Frank Porter Graham Child Development Center University of North Carolina at Chapel Hill

Melissa B. Wakely Clinical Center for the Study of Development and Learning University of North Carolina at Chapel Hill This study investigated patterns of teachers’ interaction behaviors in early childhood classrooms. Sixty-three child care teachers were rated on their use of eight interaction behaviors taken from the Teaching Styles Rating Scale (McWilliam, Scarborough, Bagby, & Sweeney, 1998). Using cluster analysis techniques, we identified four homogenous interaction clusters. One cluster presented an average profile: The teachers in this group had average scores on all interaction behaviors compared to the other teachers in the study. The teachers in a second cluster were characterized by high ratings on elaborating and low ratings on redirecting behaviors. A third cluster consisted of teachers who where rated high on redirecting and low on all other behaviors, and the teachers in the fourth cluster received high ratings on nonelaborative behaviors. Cluster differences were found for teachers’ education; teachers’ sensitivity, as measured by the Caregiver Interaction Scale (Arnett, 1989); classroom quality, as measured by the Infant-Toddler Environment Rating Scale (Harms, Cryer, & Clifford, 1990) or the Early Childhood Environment Rating Scale-Revised (Harms, Clifford, & Cryer, 1998); group child engagement, as measured by the Engagement Check II (McWilliam, 1999); and center licensing level.

The quality of early childhood classrooms is, to a large extent, determined by the interactions that take place between teachers1 and the children in those classThis research was funded by the Office of Educational Research and Improvement, U. S. Department of Education (Grant No. R307F70099). The findings do not necessarily represent the policy of the Department and endorsement by the federal government should not be assumed. Direct all correspondence to: Rene´e E. L. de Kruif, Frank Porter Graham Child Development Center, University of North Carolina at Chapel Hill, CB#8180, Chapel Hill, NC 27599-8180; Phone: (919) 966-7155; E-mail: [email protected]

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rooms. Guidelines for developmentally appropriate practices outlined by the National Association for the Education of Young Children emphasize the importance of sensitive and responsive interactions that facilitate children’s play and guide children’s social-emotional development (Bredekamp, 1987; Bredekamp & Copple, 1997). Specifically, teacher-child interactions are considered to be developmentally appropriate when the teacher (a) responds quickly, directly, and warmly to children; (b) provides a variety of opportunities to participate in a two-way communication; and (c) identifies and elaborates on the feelings, interests, and activities of children (Bredekamp, 1987). As such, interactions between children and their teachers provide a powerful context for early learning and development. Much of the research investigating relationships between teacher-child interactions and child outcomes has focused on the warmth and sensitivity of interactions. Indeed, teachers who engage in sensitive and responsive interactions with children are more likely to develop nurturing relationships, which are essential to children’s security (Elicker & Fortner-Wood, 1995). Children who have a more secure relationship with their teacher are, in turn, more likely to explore their environment and, therefore, have more opportunities to learn. A number of studies have reported that children who have less directive, less harsh, and less detached teachers, experience more positive interactions, are more considerate and sociable (Phillips, McCartney, & Scarr, 1987), display higher levels of language development (Whitebook, Howes, & Phillips, 1990), and are observed to be more competent in cognitive activities (Howes & Stewart, 1987). Moreover, McMillen (1999) reported in a recent study that the relationship between environmental quality and mastery engagement is largely mediated by caregiver sensitivity. These findings highlight the role the caregiver plays in encouraging children to engage in sophisticated behaviors and verbal interactions with their environments. Although of critical importance, these findings do not provide much information about the nature and complexity of teacher-child interactions. In fact, researchers have only begun to investigate the specifics of teachers’ interaction behaviors (what teachers do and say to get children engaged) in early childhood classrooms, and how variations in these interaction behaviors are related to child behaviors and other outcomes in children. In the present study, we were interested in exploring whether teachers could be classified into subgroups based on their observed interaction behaviors with children in an early childhood classroom setting. Teaching young children is a complex activity and requires teachers to make many decisions about the appropriate ways to respond. It has been suggested that teachers’ behaviors fall on a continuum ranging from nondirective to directive with behaviors varying in intrusiveness between these two extremes (Bredekamp & Rosegrant, 1992). All behaviors on this continuum are appropriate at certain times and teachers should use the most appropriate interaction behavior for each situation. Nevertheless, recent studies have indicated that despite the desirability of using a range of behaviors, teachers actually behave in very predictable ways. For example, Enz and Christie (1994) found that teachers, indeed, shifted their roles depending on children’s play behaviors. When children argued over toys or displayed inappro-

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priate behavior, teachers tended to be more directive than responsive. These researchers also reported, however, that teachers tended to prefer one role over another and used their preferred role more frequently. This was especially true for the novice teachers in the study. Similarly, de Kruif, Zulli, McWilliam, Scarborough, and Sloper (1999) used a qualitative analysis to examine the interaction behaviors of 10 child care teachers and found that teachers’ interactions with children occurred in a highly predictable fashion. Teachers could be classified into one of three categories [i.e., directive-responsive (DR), directive-nonresponsive (DNR), or nondirective-responsive (NDR)] based on their observed interactions with children in a classroom setting. Further analysis revealed that teachers’ interaction styles were related to the amount of time children spent interacting with adults, peers, or materials in a developmentally and contextually appropriate manner at different levels of competence. These findings emphasize the importance of a more rigorous investigation of teachers’ interaction behaviors with children in their classrooms and motivated the investigation described here. The impact of adult interaction behaviors on child outcomes has been studied most intensely in the mother-child dyad. In recent years, researchers in this field have debated the merits of the use of responsive (i.e., typically defined as elaborating or expanding on the child’s behavior) and directive (i.e., generally defined as directing or controlling child behavior) interaction styles with young children with and without disabilities. Whereas the constructivist approach to adult-child interactions generally emphasizes high levels of adult responsiveness and low levels of directiveness, studies investigating the relationship between adult responsive interactions versus directive interactions and child outcomes, especially with children who have special needs, have provided mixed results. One explanation for these results may be the fact that responsiveness and directiveness have been erroneously conceptualized as two ends of a single continuum assuming that interactions cannot be both responsive and directive. An alternative conceptualization of interaction behaviors is to consider responsiveness and directiveness as separate continua (McWilliam, 1997). Support for this position comes from several studies in which researchers found no relationships between directiveness and responsiveness. For instance, Crawley and Spiker (1983) investigated the relationship between maternal directiveness and sensitivity in a correlational study of eighteen 2-year-old children with Down syndrome. Mothers were grouped based on their levels of sensitivity and were then examined for their levels of directiveness. Each group, regardless of sensitivity, included mothers who were highly directive in interactions with their children. The researchers concluded that directiveness and responsiveness were not necessarily mutually exclusive interaction styles, but that mothers could be directive and responsive at the same time. Likewise, Marfo (1992) examined the interaction behaviors of 25 mothers and their developmentally delayed toddlers and preschoolers. The results indicated two intercorrelated groups of variables. One group consisted of variables such as warmth, sensitivity, responsivity, elaborativeness, and wait time, whereas a second group consisted of directiveness, pacing, and intrusiveness. Of these three

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latter variables, only intrusiveness was (negatively) related to the variables in the first group, suggesting that directiveness did not necessarily prevent mothers from being warm, sensitive, elaborative, and responsive. Other researchers in the adult-child interaction literature have reported similar results (e.g., Marfo & Kysela, 1988; Tannock, 1988). Finally, McWilliam, Scarborough, and Kim (1999) most recently investigated how child engagement differed as a function of adult interactions and found that interaction behaviors that were responsive without providing direction and those that were directive without responding to children did not influence engagement. A second explanation for the conflicting results regarding the effectiveness of adults’ responsive and directive interaction styles with young children might be related to the way researchers have defined the two constructs. Directiveness generally has a negative connotation because it is often equated with intrusiveness. Directiveness, however, is a complex construct, consisting of a range of behaviors. For instance, Marfo (1991) identified four classes of directives: response control, topic control, turn-taking control, and inhibiting control. Similarly, McCathren, Yoder, and Warren (1995) suggested that teachers issue directives in three ways: follow-ins (following the child’s lead), redirectives (initiating a new topic), and introductions (given to a nonengaged child). More important, McCathren et al. (1995) found that follow-in directives were positively related, and redirectives were negatively related, to children’s language development. Like directiveness, responsiveness has also been defined in different ways. Pine (1992), for example, classified adult responses to children into no response, unrelated response, and appropriate response. Other researchers have included adults’ elaborations, acknowledgments, and praise of the child to indicate responsiveness (e.g., Marfo, 1992; McWilliam & Bailey, 1992). The variety of definitions reported across studies does not necessarily mean that one or the other is incorrect. It seems to be possible, however, that different combinations of responsive and directive interaction behaviors may lead to a variety of child outcomes. This, in turn, raises a number of questions, such as how much directiveness and how much responsiveness is developmentally appropriate? Can teachers be classified in meaningful groups based on their interaction behaviors? Is there a particular teaching style that is more effective with a particular group of children? How do these subgroups relate, for example, to children’s outcomes and to environmental quality of the classroom. The current study had three purposes. First, we were interested in examining whether there were patterns of interaction behaviors among child care teachers, in essence, to assess whether groups of teachers could be characterized by different patterns of scores on eight interaction behaviors with infants and toddlers in their classroom. Directive interaction behaviors included in this study were redirecting, introducing, following, and informing. Responsive interaction behaviors were elaborating, acknowledging, praising, and affect. Second, we investigated whether group membership was related to traditional measures of child care quality and group child engagement. Finally, we examined the groups of teachers to determine whether demographic variables, such as teacher’s age, race, and experience, explained group membership.

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METHODS Participants Participants in this study were 63 teachers working in child care centers in central North Carolina. Teachers were selected through the following procedure. A list of all licensed child care centers (not family day care homes) in four counties in central North Carolina was obtained from the state child care regulatory agency. Centers were initially selected from this list based on two criteria: center size (i.e., serving more than 30 children) and age range (i.e., serving children through 5 years of age or older). In addition, equal numbers of child care centers were selected from two different licensing levels, A and AA. The difference in licensing reflects differences in program features, such as space requirements, curriculum requirements, adult-child ratio, and provisions for parents, with AA being the higher level. Although we did not collect data on these variables, it can be assumed that the cost of child care and staff salaries are higher at AA centers. From the list of centers that met these criteria, a random selection of child care center directors was contacted and informed about the study. Information packets describing the nature of the study were sent out to directors who expressed interest in participating. The final sample of 17 child care centers consisted of those centers whose directors consented to participate. Next, classrooms were selected from these child care centers based on the age of the children served. The target age for the children in this study was 12 to 36 months of age. Although all children participating in the study were initially in toddler classrooms, some children made a transition into a preschool classroom before data collection started. Consequently, 50 toddler classrooms and 13 preschool classrooms were included in the sample. No more than six and no fewer than two classrooms were selected from any one of the centers. The maximum group size of the individual classrooms ranged from 5 to 24 children (M ⫽ 12.29, SD ⫽ 4.48), and the number of adults in these classrooms ranged from one to three (M ⫽ 1.86, SD ⫽ 0.50). The adult-child ratio ranged from 2.50 to 13.00 (M ⫽ 6.69, SD ⫽ 2.35) children per adult. Center directors identified the lead teacher in each of the classrooms included in the study. Sixty-three lead teachers, all women, consented to participate in the study. Nine teachers left their centers before completing the background questionnaire, and one teacher declined to provide any background information. Table 1 provides demographic information about the teachers in the study. Instrumentation Classification Variables Classification of the teachers was based on eight variables taken from the Teaching Styles Rating Scale (TSRS; McWilliam, Scarborough, Bagby, & Sweeney, 1998). The TSRS is an observational instrument designed to capture the quality of specific interaction behaviors and affective characteristics of early childhood teachers (McWilliam, Zulli, de Kruif, 1998).

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Teachers’ Demographic Information n

Women Age

63 32.89 (range 19.89–55.25)

Ethnicity White African American Hispanic Other Highest level of formal educationa 12th grade/GED Associate’s degree Bachelor’s degree Years of child care experiencea 0–5 6–10 11–15 16 or more

32 30 1 1 35 10 8 18 16 13 6

Note: a Ten respondents did not provide information.

Interaction behaviors are measured through seven discrete items: redirecting, introducing, elaborating, following, informing, acknowledging, and praising (see Table 2). Each of these behaviors is rated on a 7-point Likert scale with four anchors: 1 ⫽ never, 3 ⫽ occasionally, 5 ⫽ often, and 7 ⫽ most of the time. Affective characteristics are measured through 13 items. These items include ratings of, for example, teacher’s activity level, visual involvement, responsiveTable 2. TSRS variable Redirects

Introduces Elaborates Follows Informs Acknowledges Praises

Definitions of Variables on the Teaching Styles Rating Scale Definition The teacher gets the children to do something different from what they are doing. Stops children (i.e., Don’t . . ., Stop . . .). (Does not include natural classroom transitions). The teacher gives the child who is not engaged or who is new to an activity something to do. The teacher provides information to expand on children’s engagement, without eliciting behavior. The teacher elicits responses (verbal or behavioral) related to what children are already doing. The teacher provides nonelaborative information, tells stories, sings. The teacher acknowledges children without elaborating on what they are doing and without helping them (includes imitation). The teacher praises children enthusiastically. Conveys pleasure or admiration for the child, the child’s behavior, or the child’s product.

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ness, child-directedness, consistency of interactions, and tone. Each item is rated on a 5-point Likert scale with three anchors asking for the frequency or the quality of the behavior. For example 1 ⫽ exerts no energy to meet children’s needs, 3 ⫽ exerts some energy to meet children’s needs, and 5 ⫽ exerts much energy to meet children’s needs. Cronbach’s alpha was used to determine internal consistency of these affect items, ␣ ⫽ 0.89, indicating that these items can be combined into an overall affect score. To obtain an overall affect score (ranging from 1 to 5), the 13 affect items were averaged. Variables used in the cluster analysis consisted of all seven interaction behaviors and the overall affect score. Validation Variables A number of variables were used to explore the validity of our classification solution. These variables were taken from the teachers’ demographic questionnaire, the Caregiver Interaction Scale (CIS, Arnett, 1989), the Infant-Toddler Environmental Rating Scale (ITERS; Harms, Cryer, & Clifford, 1990) or the Early Childhood Environmental Rating Scale Revised (ECERS-R; Harms, Clifford, & Cryer, 1998), and the Engagement Check II (McWilliam, 1999). The CIS is a widely used scale that measures teachers’ behavior in a child care setting. The scale consists of 26 items that are rated by a trained observer on a 1 to 4 Likert scale, indicating the extent to which the teacher engages in a particular behavior (1 ⫽ not at all, 2 ⫽ somewhat, 3 ⫽ quite a bit, and 4 ⫽ very much). Analysis of previous data (Arnett, 1989) resulted in four factors assessing the child care teacher’s sensitivity, harshness, detachment, and permissiveness. The sensitivity factor reflects developmentally appropriate interactions, enthusiasm, and warmth. The detachment factor refers to the degree to which the caregiver is uninvolved or uninterested in children. The harshness factor includes items regarding hostile and excessively critical behavior toward children, and the permissiveness factor contains items referring to the tolerance of misbehavior. Only the sensitivity and detachment subscales (which were negatively correlated with each other at r ⫽ ⫺0.62) were used in this study for ease of interpretation and because they were judged to be most closely related to the TSRS affect score. To obtain an overall sensitivity score, the detachment score was reversed and added to the sensitivity score. This total score was then divided by the number of items involved in the detachment and sensitivity scale. Interrater agreement on the CIS before the start of actual data collection ranged from 81% to 100% (M ⫽ 95%). This criterion was evaluated through classroom observations during which the rater and a staff member with significant expertise in using the CIS completed the scale simultaneously. Ratings on the CIS were moderately to highly related to scores on the TSRS. In addition, ratings on the CIS have been associated with child care provider education and training, as well as child attachment security and language development (Arnett, 1989; Whitebook, Howes, & Phillips, 1990). The CIS was, therefore, judged to be an adequate instrument for external validity analysis. The ITERS and its equivalent for classrooms containing preschoolers age 30 months or older, the ECERS-R, were used to assess global quality of the individual classrooms. These instruments involve an assessment of space and

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furnishings, personal care routines, activities and interactions, and program structure as well as provisions for parents and staff. The ITERS consists of 35 items, and the ECERS-R consists of 43 items. Both instruments use a 7-point scale with descriptors for 1 ⫽ adequate, 3 ⫽ minimal, 5 ⫽ good, and 7 ⫽ excellent. It is recommended that a trained observer spend at least 2 hr in the classroom to complete either of these scales. Previous studies have indicated that for each scale a single total score comprised of the child-related items can provide a reliable and valid index of classroom quality (Peisner-Feinberg & Burchinal, 1997; Phillipsen, Burchinal, Howes, & Cryer, 1997; Scarr, Eisenberg, & Deater-Deckard, 1994). Good interrater agreement and internal consistency have been reported for the ITERS and ECERS-R. For this study, an interrater agreement level of at least 82% on the ITERS and 84% on the ECERS-R was established before the start of data collection. Again, this was evaluated through classroom observations during which the observer and a staff member with significant expertise in using the ITERS or ECERS-R completed the scale simultaneously. Both scales have been widely used in early childhood research and have been found to be associated with positive and sensitive teacher-child interactions (Dunn, 1993; Peisner-Feinberg & Burchinal, 1997). In the present study, it was hypothesized that teachers with different patterns of interaction behaviors might also differ in their scores on a quality measure. In addition to the overall environmental quality score, both the ITERS and ECERS-R provide space to record group size and adult-child ratio. Both scores have been used as quality indicators in addition to the overall score obtained by using the scale. Group size and adult-child ratios were, therefore, used as additional external validity measures. Finally, the Engagement Check II (McWilliam, 1999), a modification of the Planned Activity Check (Risley & Cataldo, 1973), was used to measure group engagement. This procedure is used to determine the percentage of children engaged during activities. With this measure, engagement was defined as attention to or active participation in classroom activities as reflected by visual fixation, manipulation, vocalization, approach, or affect. Furthermore, engagement included only behavior that was both developmentally and contextually appropriate (i.e., appropriate to the activity being conducted). The Engagement Check II was completed by counting the number of children visible in one pass and then counting the number of nonengaged children in a second pass. The percentage of children engaged equals the number of children visible minus the number of children nonengaged, divided by the number of children visible, and multiplied by 100. In this study, observations were made at three different times for a duration of 15 min each, using 15-s intervals. The session score consisted of the average of the 60 observations made in a 15-min session. The average score of three sessions was used as an overall group engagement score. Interrater agreement was calculated by taking the lowest overall group engagement score between two observers and dividing it by the highest overall group engagement score between two observers. Observers were trained until an interrater agreement of 85% was reached. To avoid observer drift during actual data collection, a total of 45 observation sessions (25%) were coded by a second observer. The mean interrater percentage agreement for group engagement was 98% (94 –100%).

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Procedure Four observers were trained to use the TSRS, the ITERS, the ECERS-R, and the CIS. Each classroom received a visit in which the ITERS or ECERS-R (depending on the age of the children), the TSRS, and the CIS were completed. Throughout the morning, the observer recorded notes and scored items on the ITERS or ECERS-R. At three different times during the morning (at 8:00, 9:00, and 10:00 a.m.) the observer also spent 15 min making notes about the lead teacher’s interaction behaviors with the children as described on the TSRS. At the end of the morning, observers carefully read each item on the TSRS and circled the number that best described the teacher’s interactions during the observed time. Finally, each observer completed the CIS for the lead teacher in the room. Teacher demographics questionnaires were distributed after this visit, and they were returned to the research staff via mail. All data were recorded by using standardized scoring forms. An independent observer was trained to gather group engagement data by using the Engagement Check II during a subsequent visit to the classroom. Each classroom was observed for a total of 45 min across three 15-min sessions. A stopwatch signaled the observer, equipped with a single earphone, to code group engagement at the end of each 15-s interval. All data were recorded by hand on a standard coding form. A minimum of 10 min of coding was required to record session data. The session was discarded if less than 10 min of coding was completed. All three observations occurred on the same day in a given classroom (with only two exceptions). As was the case with all observations throughout the study, the three Engagement Check II sessions were conducted during naturally occurring activities in an indoor setting (i.e., the researchers did not manipulate the classroom activities). Classrooms were observed only when the primary caregiver (i.e., not a substitute) was present. During interrater agreement checks, the second observer’s earphone was plugged into a Y-jack on the first observer’s stopwatch, allowing both observers to hear the coding cues at the same time. Data Analysis Cluster analysis was the main statistical technique used in this study. Cluster analytic techniques provide a way to identify homogenous subgroups within a heterogeneous sample. Although not grounded in mathematical theory and commonly viewed as descriptive, clustering methods are heuristic (Everitt, 1993; Morris et al., 1998) and have been widely used in research on children’s language (Feagans & Appelbaum, 1986), behavior (Dykman & Ackerman, 1993; McKinney & Speece, 1986), achievement (Meece & Holt, 1993), memory (Swanson, Cochran, & Ewers, 1990), and reading (Lyon & Watson, 1981; Morris et al., 1998). Given our contention that early childhood teachers vary in their interaction behaviors with children, cluster analysis appeared to be the most appropriate method for exploring the nature of their interaction profiles. A variety of procedures suggested by other researchers were used to determine internal validity of the clusters (see Hooper & Willis, 1989; Morris, Blashfield, & Satz, 1981).

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Finally, external validity of the clusters was examined. Because we were specifically interested in finding out which groups differed from each other, as opposed to finding out whether there was an overall difference among the clusters on each variable, we bypassed the omnibus F-test and proceeded directly with pair wise comparisons between groups (see Keselman et al., 1998). Cohen’s d, a standardized effect size, was used to determine the magnitude of the differences between groups. Cohen’s d is computed by dividing the difference between two group means by the average standard deviation of the two groups. The noteworthiness of the differences between groups was determined individually for each dependent variable.

RESULTS Clustering Methods Because the clustering variables taken from the TSRS were on different scales, all TSRS variables were first standardized, based on overall group scores (M ⫽ 0, SD ⫽ 1.00). Two frequently reported clustering techniques were used to identify clusters of teachers’ interaction behaviors and to determine stability across methods: The hierarchical agglomerative method was selected to ascertain initial cluster solutions, and the k-means method was used to evaluate these initial solutions (Fletcher, Francis, & Harris, 1988). In this study, (a) the amount of variance each cluster accounted for at each step of the clustering process, (b) statistical tests of separation among all clusters, and (c) statistical tests of separation between just-joint clusters in hierarchical chaining indicated five potential solutions ranging from three to eight clusters. Scatter plots, line plots of cluster profiles, and univariate statistics for each cluster were visually inspected to analyze changes in the cluster profiles when the number of clusters was increased or decreased. The three-, four-, and five-cluster solutions were determined to be potential solutions, but the k-means iterative clustering method resulted in four interpretable clusters of teachers’ interaction behaviors. To facilitate interpretation of the four clusters, cluster profiles (standardized means for each variable) were plotted as shown in Figure 1. Table 3 presents raw means and standard deviations of each of the interaction behaviors by cluster. Cluster Descriptions Cluster 1 This group consisted of 24 teachers and was the largest of the four clusters. The teachers in this cluster received average ratings across all TSRS classification variables compared to the other participating teachers (see Table 3 and Figure 1). Statistically, this means that there were few deviations from the mean on each clustering variable. Practically, this means that the teachers in this group engaged in each of the interaction behaviors on the TSRS some of the time. They sometimes redirected the children; sometimes introduced nonengaged children to new activities, elaborated, and followed the children’s interests; and

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Figure 1. Profiles of the four teacher clusters based on their scores on the Teaching Styles Rating Scale.

sometimes informed, acknowledged, and praised children. Finally, their rating on the affect variable was moderately high. The teachers in this group included an approximately equal number of White and African American teachers. An equal number of teachers worked at A and AA centers. According to self-reports of the highest level of education, 11 (61%) of the teachers in this group had high school degrees, 6 teachers (33%) had associate’s degrees, and 1 had a 4-year college degree. Six teachers did not provide information about their educational background. For hermeneutic purposes, we have labeled these teachers average. Cluster 2 The teachers in this cluster (n ⫽ 11) could be discriminated from those in other clusters mainly by their extremely low ratings on redirects and extremely high ratings on elaborates, follows, praises, and affect (see Table 3 and Figure 1). They introduced nonengaged children to new activities and praised children for their efforts more than average, but unique to this group of teachers were their high ratings on elaborates and follows, in combination with average ratings on providing information and merely acknowledging. These ratings indi-

258 Table 3.

de Kruif et al. Raw Means on Variables From the Teaching Styles Rating Scale for Four Teacher Clusters Teacher Clusters Cluster 1 (Average) (n ⴝ 24)

TSRS variables Redirects Introduces Elaborates Follows Informs Acknowledges Praises Affect

Cluster 2 (Elaborative) (n ⴝ 11)

Cluster 3 (Controlling) (n ⴝ 18)

Cluster 4 (Nonelaborative) (n ⴝ 10)

M

SD

M

SD

M

SD

M

SD

4.08 2.50 3.04 3.63 3.29 3.04 3.08 3.77

1.10 .78 1.27 1.41 .81 .81 .83 .34

3.55 4.45 4.82 5.27 3.45 3.36 4.45 4.45

.93 1.21 1.25 1.68 1.13 1.29 .93 .31

5.67 1.89 1.83 2.89 2.61 2.50 2.28 2.99

.97 .58 .71 1.08 .85 .71 .57 .43

4.80 4.20 3.10 3.80 4.00 4.90 4.20 4.03

1.23 .92 .57 1.48 1.33 .99 .63 .44

Note: All variables were standardized by group. Real means are presented to improve interpretability. Values that deviate at least a standard deviation of .5 from the standardized group mean are in boldface. The first 7 variables were rated on a 7-point Likert scale with the following anchors: 1 ⫽ never, 3 ⫽ occasionally, 5 ⫽ often, and 7 ⫽ most of the time. The affect variable was rated on a 5-point Likert scale.

cate that the teachers in this cluster mainly spent their time expanding on children’s activities and using these activities to elicit responses related to what the children were already doing. In addition, these teachers had the highest rating on the affect variable. Six teachers in this group were White, and five teachers were African American. Nine of the 11 teachers worked in an AA-licensed center. Five teachers had high school degrees, one teacher (10%) had an associate’s degree, and four teachers (40%) had college degrees. Educational information was not available for one teacher in this group. We have labeled these teachers elaborative. Cluster 3 The teachers in this cluster (n ⫽ 18) had extreme ratings on all clustering variables (see Table 3 and Figure 1). Unlike any of the other groups, these teachers were rated very highly on redirecting, which indicates that they often tried to stop children’s behavior to have them do something else instead. In addition, they were rated as very low on all other variables. Although these teachers spent much time stopping children’s behavior, they rarely introduced children to new activities, rarely elaborated on children’s activities or interests, only occasionally asked children to do something related to what they were already doing, rarely provided information to the children (e.g., which centers were open, what the next activity would be), and rarely acknowledged or praised children for their efforts. Their affect rating was medium high. Whereas redirecting can be used for classroom management, teachers’ constant redirecting of children, combined with the extremely low ratings on almost all of the other interaction behaviors, prompted us to label the teachers in this cluster as controlling. Eight teachers were White, and 10 teachers were African American. Sev-

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enteen of the 18 teachers (94%) worked in A-licensed child care centers. Selfreports indicated that 12 (86%) teachers had high school degrees and 2 teachers (14%) had an associate’s degree. This information was not available for four teachers. Cluster 4 The teachers in this cluster (n ⫽ 10) could be distinguished from other teachers by their high ratings on nonelaborative interaction behaviors, in combination with average ratings on redirecting and elaborative interaction behaviors (see Table 3 and Figure 1). Similar to the teachers in the average group, these teachers sometimes redirected children to different activities, sometimes elaborated on children’s behaviors, and sometimes used children’s activities to elicit responses. They differed from the average group in the high ratings they received on introducing children to new activities, providing information, acknowledging children’s responses without elaborating on what they were doing, and praising children’s efforts. In addition, their affect rating was above average. This group of teachers consisted of 5 African American and 4 White teachers. One teacher was from some “other” ethnic background. Four teachers in this group (50%) had a high school degree, 1 teacher had an associate’s degree, 3 teachers (38%) had a college degree, and 2 teachers did not report this information. We labeled these teachers nonelaborative. Internal Validity Three methods that have been suggested in the classification literature were used for establishing internal validity of the clusters (see Fletcher et al., 1988). First the k-means four-cluster iterative solution was compared to the hierarchical four cluster solution as a test for cluster stability. Fifty-nine percent of the teachers remained in the same cluster across clustering techniques, indicating reasonable internal validity. Second, the k-means clustering method was rerun using a two-thirds random sample (n ⫽ 42) of the data set. The solution revealed that 69% of the teachers remained in the same cluster. Finally, canonical variates were computed to discriminate among the clusters. A plot of the first two canonical variates indicated four fairly well-separated clusters. External Validity The external validity in this study was addressed by comparing the four clusters on three independent observational measures: the CIS, the ITERS or ECERS-R, and the Engagement Check II. The Tukey/Kramer procedure (for unequal group sizes) and Cohen’s d were used to interpret the magnitude of differences among groups. Cohen’s d indicates the percentage of a pooled standard deviation. Only noteworthy differences are reported. We determined noteworthiness (e.g., whether small, moderate, or large differences) among clusters by examining effect sizes, scaling, and sample size. The results of the test of significance are also reported, but they should be interpreted only in the context of the effect size estimate (Wilkinson and the Task Force on Statistical Inference, 1999). As shown in Table 4, teachers in the elaborative group (Cluster 2) were more

12.04 (4.18) 6.48 (2.10) 89.11 (6.21)

Group Size

33.58 (7.07) 7.80 (4.89)

11.73 (6.48) 5.85 (2.72) 91.86 (4.29)

4.05 (.70)

3.37 (.35)

Cluster 2 (Elaborative) M (SD)

31.02 (7.84) 7.61 (3.81)

13.33 (4.23) 7.72 (2.52) 81.29 (8.32)

2.81 (.37)

2.35 (.32)

Cluster 3 (Controlling) M (SD)

32.80 (11.97) 8.07 (6.90)

11.60 (3.17) 6.25 (3.17) 91.86 (4.04)

4.03 (.79)

3.12 (.44)

Cluster 4 (Nonelaborative) M (SD)

No noteworthy differences

1 vs. 3, Q(4, 53) ⫽ 5.31*, d ⫽ 1.08 2 vs. 3, Q(4, 53) ⫽ 5.98*, d ⫽ 1.67 3 vs. 4, Q(4, 53) ⫽ 5.81*, d ⫽ 1.71 No noteworthy differences

No noteworthy differences

1 vs. 2, Q(4, 59) ⫽ ⫺5.85*, d ⫽ 1.52b 1 vs. 3, Q(4, 59) ⫽ 5.50*, d ⫽ 1.08 2 vs. 3, Q(4, 59) ⫽ 10.04*, d ⫽ 2.99 3 vs. 4, Q(4, 59) ⫽ ⫺7.37*, d ⫽ 2.02 1 vs. 3, Q(4, 59) ⫽ 4.92*, d ⫽ 1.26 2 vs. 3, Q(4, 59) ⫽ 6.95*, d ⫽ 2.32 3 vs. 4, Q(4, 59) ⫽ ⫺6.65*, d ⫽ 2.13 No noteworthy differences

Comparisonsa

Items on the CIS were rated on a 1 to 4 scale; scores on the ITERS and ECERS-R were rated on a 1 to 7 scale; scores on group size and adult-child ratio indicate number of children; scores on the Engagement Check II are reported in percentage of time; teacher’s age and experience are reported in years. a Numbers in parenthesis indicate number of groups compared and degrees of freedom used to calculate Q (Tukey/Kramer for unequal group sizes). b d ⫽ Cohen’s measure of effect size (approximately representing % of 1 SD). * p ⬍ .05.

Note:

Teacher’s Experience

Teacher’s Age

Engagement Check II

33.86 (7.63) 10.45 (5.95)

3.52 (.76)

ITERS/ECERS-R

Adult-Child Ratio

2.81 (.39)

CIS—sensdet.

Cluster 1 (Average) M (SD)

Teacher Clusters

Mean Scores, Standard Deviations, and Pairwise Comparisons Between Clusters on Variables Used for External Validity

Variables

Table 4.

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sensitive than the teachers in the average group (Cluster 1) and the teachers in the controlling group (Cluster 3). Teachers in the controlling group (Cluster 3) were less sensitive than teachers in the average group (Cluster 1) and teachers in the nonelaborative group (Cluster 4). Two of these comparisons (i.e., elaborative vs. controlling teachers and nonelaborative vs. controlling teachers) had large effect sizes (d ⬎ 2.00). A moderate difference in sensitivity was found between the average and the elaborative teachers and between the average and controlling teachers (d ⬎ 1.00). Differences among groups were also found for teachers’ scores on classroom environmental quality as measured by the ITERS or ECERS-R. Controlling teachers were in classrooms with lower quality scores compared to the classrooms of the teachers in any of the other groups. Effect sizes ranged from moderate (d ⬎ 1.00) to large (d ⬎ 2.00). No noteworthy differences were found among the environmental quality scores of the remaining three groups. For descriptive purposes, we examined cluster means on the ITERS and ECERS-R subscales. It appeared that the classrooms of the teachers in the controlling group had scores reflecting inadequate care for five of the six subscales (i.e., personal care, language, activities, interactions, and program structure). None of the other groups had such low scores on any of the ITERS or ECERS-R subscales. No noteworthy group differences were found for group size and adult-child ratio. Finally, fewer children in classrooms with controlling teachers were observed to be engaged at appropriate levels (as measured with the Engagement Check II) than in classrooms with teachers in any of the other clusters (all moderate effect sizes, d ⬎ 1.00). For descriptive purposes, clusters were also compared on variables such as teachers’ ages, teachers’ races, years of experience working with children, highest level of education obtained, and licensing level of the day care center where the teachers were working. No differences among groups were found for teachers’ ages, years of experience, or races (see Tables 4 and 5). We found a small difference in teachers’ education, ␹2 (6, n ⫽ 53) ⫽ 13.09, p ⫽ .04, Cramer’s V ⫽ 0.35, and a moderate difference in licensing level, ␹2 (3, n ⫽ 63) ⫽ 22.18, p ⫽ .001, Cramer’s V ⫽ 0.59. Cramer’s V is a magnitude of effect size estimate ranging from ⫺1.0 to 1.0. Inspection of the means indicated that 82% of the elaborative teachers and 80% of the nonelaborative teachers were working in AA-licensed day care centers compared to 50% of the average teachers and 6% of the controlling teachers. Information about teacher’s education was available for 53 of the 63 teachers. Inspection of the means indicated that elaborative teachers reported relatively high levels of education, whereas controlling teachers reported relatively low levels of education (see Table 5).

DISCUSSION The results of the present study demonstrated that early childhood teachers could be empirically classified into distinct and internally homogeneous clusters or groups based on the ratings they received on eight observed interaction behaviors.

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de Kruif et al. Table 5.

Teachers’ Demographic Information by Cluster Teacher Clusters

Variables Race White African American Other Highest level of formal Educationa,* 12th grade/GED Associate’s Degree College Degree Licensing level** A AA

Cluster 1 Cluster 2 Cluster 3 Cluster 4 (Average) (Elaborative) (Controlling) (Nonelaborative) (n ⴝ 24) (n ⴝ 11) (n ⴝ 18) (n ⴝ 10) 11 12 1

6 5 —

10 8 —

4 5 1

13 6 1

5 1 4

12 2 —

5 1 3

12 12

2 9

17 1

2 8

Note: a Ten teachers did not provide this information. * p ⬍ .05, Cramer’s V ⫽ .35, ** p ⬍ .01, Cramer’s V ⫽ .59.

All teachers were assigned by a cluster analysis procedure into one of four groups. Differences were found among the four groups on measures of teachers’ sensitivity, classroom environmental quality, and group child engagement. In addition, teachers’ levels of education and the licensing level of their child care center explained part of the differences in interaction behaviors in this sample of teachers, whereas teachers’ age, race, and experience, as well as group size and adult-child ratio did not. The four-group solution in this study is consistent with theory and research. Similar to the findings in the adult-child interaction literature, our findings indicated that adults manifest a wide range of interaction behaviors. The patterns of interaction behaviors we found provided additional empirical evidence for the contention that directive interaction behaviors do not preclude the use of responsive interaction behaviors. Like other researchers (e.g., Crawley & Spiker, 1983; Marfo, 1991; McCathren et al., 1995; Pine, 1992), we demonstrated that conceptualizing directiveness and responsiveness as multivariate constructs, existing on separate continua, rather than univariate constructs on one continuum, is helpful in unraveling some of the conflicting results reported in the adult-child interaction literature. Although associations between and among different types of responsive and directive interaction behaviors and children’s developmental outcomes have been investigated, these studies have typically used a univariate framework. The study reported here is the first to take a multivariate look at patterns of relationships among a number of directive and responsive teacher-child interaction behaviors. The teacher groups identified in the present study showed some resemblance to the groups identified by de Kruif et al. (1999). Using qualitative analysis to

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investigate the nuances of teachers’ responsive and directive interaction behaviors, these researchers found that teachers could be classified into three groups: DR, DNR, and NDR. The interaction behaviors of DR teachers typically consisted of asking why and how questions, eliciting behaviors based on the children’s interests and responses, and using a variety of interaction strategies, such as modeling, time delay, and prompts that provided assistance without intruding on the child and the activity. This pattern of interaction behaviors most closely resembled the teachers we identified as elaborators in the present study, who could be discriminated from other teachers mostly by their high score on elaborating behaviors and their less frequent use of redirective interaction behaviors. In contrast, DNR teachers often stopped and redirected children’s behaviors and asked test-like questions, rather than elaborating on the children’s engagement, modeling, prompting with materials, or offering children clues to encourage them to respond. This interaction pattern is quite similar to the controlling teachers in the present study. Unlike the controlling teachers, however, who did not engage in many other interaction behaviors than redirecting and stopping the children from what they were doing, the DNR teachers in the qualitative study by de Kruif et al. (1999) did attempt to elicit responses from the children. The NDR teachers in the qualitative analysis displayed some interaction behaviors similar to those of the nonelaborative teachers in the present study. Although very responsive, the NDR teachers rarely attempted to elicit specific behavioral and verbal responses that would guide children to be engaged in more elaborate ways. When they did ask children to do something, it was designed to help the children make choices or engage in conversations and was rarely followed by an attempt to elicit more detailed responses. Interaction strategies included offering children alternatives (introducing new activities, letting them choose between colors, etc.), asking what and where questions, describing their activities, acknowledging responses without prompting for more information, and providing the children with information. The identification of a fourth group in the present study is new. Apart from the methodological differences, one explanation might be that the teachers in the present study were quite different from those in the qualitative study. The groups in the qualitative study were based on observations of a small group of 10 teachers. All teachers worked at a university-supported, high-quality child care center, and all had at least a 2- or 4-year degree. The groups studied in the present study, however, were based on observations of 63 teachers working at 18 different child care centers of varying quality across four different counties in a midAtlantic state. In addition, teachers varied widely in their educational level. The terminology from the qualitative study might have led us to characterize this fourth group as nondirective-nonresponsive because no one interaction predominated. Average, however, is more accurate because the teachers were not lacking in directiveness and responsiveness. Differences among two or more groups were found in teachers’ sensitivity, environmental quality of their classrooms, and group engagement. Differences and nondifferences in sensitivity were expected. Not all groups differed on sensitivity because this single characteristic of teachers does not adequately reflect

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the complexity of adult-child interactions. Whereas sensitivity might differentiate some teacher types, interaction behaviors alone (i.e., TSRS scores) differentiate other groups. Differences among groups on the environmental quality of their classrooms were not as distinct as expected. Controlling teachers had significantly lower scores on their classroom quality measure than did the teachers in the other groups, who did not differ from each other on this measure. The lack of differences among the other clusters might have occurred because of the limited range of quality scores obtained with this sample of teachers. A closer investigation of the quality scores indicated that the quality of care provided by the teachers in this sample was mediocre (M ⫽ 3.49, SD ⫽ 0.81), suggesting that the children were attending child care centers that met their basic needs, but provided few opportunities for learning activities, individual attention, or language stimulation (Cost, Quality, and Child Outcomes Study Teach, 1995). Replicating this study with teachers who have a wider variety of scores on the quality measure may provide more information about the relationship between teachers’ interaction behaviors and the quality of the child care classroom. Another possible explanation is that the ITERS and ECERS-R predominantly rate the structural features (materials, setting, etc.) of early childhood classrooms and include few items related to teacher-child interaction. Differences in group child engagement provided some evidence for the relationship between teachers’ interaction behaviors and what children do in the classroom. Fewer children in classrooms of controlling teachers were actively engaged compared to any of the other classrooms. This finding is consistent with the findings in the qualitative study by de Kruif et al. (1999). Directive-nonresponsive teachers (who we compare to the controlling teachers in this study) engaged in brief, task-directed interactions with numerous children, in which they attempted to control the children’s activities. Children often had to wait for additional materials or instruction and tended to lose interest quickly, which led them to abandon the activity. Furthermore, children who were already previously engaged became nonengaged when teachers tried to take control over the activity or tried to redirect them to a teacher-directed activity. Teachers in the four groups also differed on teachers’ level of education and the licensing level of their child care center. Teachers who used more redirective and less elaborative behaviors tended to be less sensitive and tended to have less education. These results are consistent with the results from other studies (Arnett, 1989; Howes, 1997; Howes, Smith, & Galinsky, 1995; Whitebook et al., 1990). For example, Arnett (1989) reported that caregivers with more education had less authoritarian child rearing styles and were more knowledgeable about child development. Teachers with more training received more positive ratings in observations and were less punitive and detached with children. Similarly, Howes et al. (1995) reported that changes in regulations regarding training of child care providers improved the quality of teacher-child interactions. Teachers with more training were more sensitive, although not necessarily more involved. No group differences were found for teachers’ age, teachers’ race, teachers’ experience with children, group size, or adult-child ratio. Whereas the finding that

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experience alone is not a good predictor of effective caregiving is not new (see Howes, 1983; Kontos & Fiene, 1987), group-size, adult-child ratio, and race have previously been found to be related to teachers’ sensitivity and use of directive interaction behaviors. For example, Ruopp, Travers, Glantz, and Coelen (1979) reported that in classrooms with lower adult-child ratios teachers were less likely to spend time managing and controlling activities and more likely to be involved in center-related activities or to be engaged with other staff members. Whitebook et al. (1990) found that classrooms with lower adult-child ratios tended to have teachers who were more sensitive, less harsh, and less detached in their interactions with the children in their care. In contrast, our findings suggest that what teachers do when interacting with children does not necessarily depend on group size or adult-child ratio. In summary, this study has shown an initial grouping of child care teachers with regard to their interaction behaviors with young children. The finding that controlling teachers were essentially different from the other three types of teachers has implications for both research and practice. Further research is needed to understand the unique elements of “directive” teaching (see McCathren et al., 1995). The findings from this study suggest that, in practice, differences within nondirective teaching styles are not as salient as the difference between directiveness and nondirectiveness. Consequently, personnel preparation, practice guidelines, supervision, and teaching itself should focus on the avoidance of overly controlling teaching behaviors. The results of the study should be interpreted with caution until further cross-validation can take place. We acknowledge the following limitations to the study. First, seven of the TSRS scores were obtained by ratings on single items, whereas the affect score was based on 13 items. This means that the affect score was more stable than the others were. Second, this study was part of a larger study. As a result, there were only a few instruments available to use for external validity checks of the four groups. Third, teachers’ interaction behaviors and children’s engagement behaviors were observed on separate days, raising the question whether activities and, therefore, teachers’ interaction behaviors and children’s engagement behaviors were the same across days. Although classroom schedules were similar on these days, thereby increasing the likelihood that similar activities occurred on these days, we do not have detailed evidence that this was true. Fourth, adult-child interaction behaviors are transactional (Sameroff & Fiese, 1990). Teachers’ interactions with children are influenced by the child’s characteristics, such as temperament, age, and cognitive ability, and vice versa. Although we collected information on such child characteristics, only a maximum of four children were selected in each classroom, which is not a representative sample for each classroom. The results of this study suggest the following implications for practice, personnel development, and research. 1. Use the TSRS for observing teachers and classifying them. Use the data to plan training (see the next two implications). 2. Provide training in sensitivity to average and controlling teachers.

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3. Train teachers to be less redirective and more elaborative to increase the overall quality of the environment and to increase the percentage of children engaged. 4. When classrooms receive low environment-quality score, examine the teaching style of the teacher. Aim to correct problems in the teacher’s teaching style as well as in other environmental aspects. 5. Continue research to test the following typology: (a) elaborative, or directiveresponsive; (b) controlling, or directive-nonresponsive; (c) nonelaborative, or nondirective-responsive; and (d) average, or nondirective-nonresponsive teachers. Acknowledgments: We thank the participating teachers, parents, and children. Thanks also to Katherine Harville, Kelly Maxwell, Brad McMillen, Melissa Raspa, Don Trull, and Paul Wegner.

NOTES 1. Teachers is used to refer to caregivers working with young children. Similarly, teaching is used to refer to the variety of interactions caregivers have with children. The terms are not meant to restrict who is considered a teacher, nor what interactions are considered teaching.

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