Training and mentoring: Family child care providers’ use of linguistic inputs in conversations with children

Early Childhood Research Quarterly 28 (2013) 972–983

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Early Childhood Research Quarterly

Training and mentoring: Family child care providers’ use of linguistic inputs in conversations with children Carrie L. Ota a,∗ , Ann M. Berghout Austin b a b

Department of Child and Family Studies, Weber State University, Ogden, UT, USA Department of Family, Consumer, and Human Development, Utah State University, Logan, UT, USA

a r t i c l e

i n f o

Keywords: Professional development Family child care Linguistic inputs Mentoring Training

a b s t r a c t The purpose of this study was to examine the effectiveness of two professional development models in increasing family child care providers’ frequency of linguistic inputs in conversations with young children. The first professional development model consisted of a 10-h in-service training focused on supporting early language development. The second included the same 10-h in-service training program and mentoring. Providers and children at 48 family child care programs participated in this study. The family child care programs were randomly assigned to one of the two professional development models (i.e., training or training with mentoring) or to a control group. Audio recordings of the language environment were collected prior to the in-service training, at the completion of the in-service training, and at the completion of the mentoring. Hierarchical linear modeling was used to examine the average increase in the frequency of providers’ use of linguistic inputs over three observations, conducted before training, immediately at the end of training, and 6 weeks after training. Results indicate that both forms of professional development increased linguistically stimulating inputs as compared to the control group. The professional development model including mentoring support was related to greater increases in providers’ use of informational talk and teaching utterances over in-service training without mentoring. © 2013 Elsevier Inc. All rights reserved.

1. Introduction For a growing number of children in the United States, family or home-based child care provides an important context for language development. Over one and a half million children spend time in the care of a family child care provider each week (National Association of Child Care Resource and Referral Agencies [NACCRRA], 2010). Family child care (FCC) is used more often by low-income families (Johnson, 2005; Kontos, Howes, Shinn, & Galinsky, 1995; Layzer & Goodson, 2006; NICHD Early Child Care Research Network, 2004) and single parents (NICHD Early Child Care Research Network, 2004) than middle-income and two-parent families. FCC children tend to spend more hours in out-of-home care than center-based children because their parents often have longer work days (Austin, Blevins-Knabe, Ota, Rowe, & Lindauer, 2011). Several researchers (Austin, Godfrey, Larsen, Lindauer, & Norton, 1996; Kontos, Hsu, & Dunn, 1994; Raikes, Raikes, & Wilcox, 2005; Whitebook et al., 2004) have documented lower-quality activities in FCC, especially among providers having less education (Weaver, 2002). According to extant literature,

∗ Corresponding author. Tel.: +1 8016266959. E-mail address: [email protected] (C.L. Ota). 0885-2006/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ecresq.2013.04.001

family child care providers on average have significantly less education and training than center-based providers in the U.S. (Gable & Halliburton, 2003; Kontos et al., 1994; Kontos, 1992). For many children, FCC has the potential to serve as a significant context for learning language, and the quality of these early learning environments is often related to children’s language development (Clarke-Stewart, Vandell, Burchinal, O’Brien, & McCartney, 2002; Dickinson & Neuman, 2006; Hart & Risley, 1995; Lee, Lee, & Lee, 1997; Loeb, Fuller, Kagan, & Carrol, 2004; Logan, Piasta, Justice, Schatschneider, & Petrill, 2011; NICHD Early Child Care Research Network, 2004; Phillips & Morse, 2011). Higher-quality language stimulation provides a foundation for basic communication skills (Lee et al., 1997) that lead to emergent literacy skills and greater school readiness (Wasik, Bond, & Hindman, 2006). Likewise, higher scores on environmental rating scales have been linked with better receptive language vocabulary scores (Lee et al., 1997). 1.1. Language stimulation and linguistic inputs in FCC Early language abilities are largely dependent on the frequency and quality of adult–child language stimulation (Hart & Risley, 1995; Tamis-LeMonda, Bornstein, & Baumwell, 2001), whether at home or in child-care (Lee et al., 1997). To the best of our knowledge, very few studies have examined linguistic inputs in family child care programs. Most research on language stimulation and

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linguistic inputs was conducted with child care center caregivers and found that the quality and frequency of language stimulation are important indicators of the quality of child care language environments and a predictor of children’s language development (Dickinson & Tabors, 2001, 2002; Risley & Hart, 2006). Caregivers who engage in more linguistically stimulating interactions with children tend to have more talkative children (Girolametto & Weitzman, 2002) who score higher on child language measures (Lee et al., 1997). Caregivers use many different types of language stimulation strategies while talking to young children. When caregivers respond to children’s verbal communications, they encourage children to keep talking (Risley & Hart, 2006; Tomasello, ContiRamsden, & Ewert, 1990) by providing a cued framework for exchange that shows children when to speak and how to develop cohesiveness between the speaker and the listener (Cicognani & Zani, 1992; Copple & Bredekamp, 2009; Girolametto & Weitzman, 2002). Caregivers support children’s language growth when they use informational and referential talk (Dickinson, Darrow, & Tinubu, 2008; McCartney, 1984), express and describe emotions (McCoy & Raver, 2011; Eisenberg, Cumberland, & Spinrad, 1998), ask questions (Girolametto, Weitzman, van Lieshout, & Duff, 2000; Rasku-Puttonen, Lerkkanen, Poikkeus, & Siekkinen, 2012), and use teaching statements that expand children’s understanding through introducing vocabulary and providing new information (Dickinson et al., 2008; Early et al., 2005). These linguistic strategies are especially beneficial when caregivers provide inputs that are consistent with the current activity and conversation (Barnes, Gutfreund, Satterly, & Wells, 1983; McCabe & Peterson, 1991). Unfortunately, caregivers generally provide these types of linguistically stimulating inputs at a low rate, with only about 30% of total interactions considered to encourage language use in children (Turnbull, Anthony, Justice, & Bowles, 2009). Specifically, caregivers working with children in group settings frequently use directive inputs while talking to young children, such as “put the blocks back on the shelf” or “wash your hands for lunch,” which are not positively related to children’s language growth (Barnes et al., 1983; Girolametto et al., 2000). Family child care providers tend to provide less language stimulation for children ages 24–54 months than center-care caregivers (Dowsett, Huston, Imes, & Gennetian, 2008). These findings suggest a particular need to focus on ways to enhance the linguistic environment, including the frequency of provider linguistically stimulating inputs in family child care programs. 1.2. Quality of language environment and professional development Many states aim to improve the quality of family child care (Tout et al., 2010) and require family child care providers to attend annual in-service training such as group conferences and workshops (Ackerman, 2004; Merriam, Caffarella, & Baumgartner, 2007). One focus for increasing quality has been to improve verbal interactions between family child care providers and children in their care. Some studies have found that state-sponsored in-service training can increase the quality of family child care provider language interactions (Burchinal, Howes, & Kontos, 2002; Clarke-Stewart & Allhusen, 2005; Dickinson et al., 2008; Fukkink & Lont, 2007; Girolametto, Weitzman, & Greenberg, 2006; Kreader, Ferguson, & Lawrence, 2005; Wasik et al., 2006), while others have found formal education to be more influential (NICHD, 2005; Whitebook, 2003). These mixed results may be at least partially due to the variability in training strategies employed in state programs. The purpose of this study was to examine the effectiveness of two different state-sponsored training strategies with family child care providers, in-service only and in-service with on-site mentoring,

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in increasing the quantity of FCC providers’ language interactions with children. While the required amount of training varies (NACCRRA, 2010), state licensing requirements for annual in-service training for family child care providers are usually met through individual workshop sessions on various topics (Burchinal, Cryer, Clifford, & Howes, 2002). There are a limited number of studies that focus on standalone in-service trainings for family child care providers and even fewer focusing on improving the quantity of linguistic inputs among these providers. Family child care providers appear to have the lowest rates of formal education, in-service training, and outside support (such as technical assistance and mentoring) (Dowsett et al., 2008; Fuligni, Howes, Lara-Cinisomo, & Karoly, 2009). On the positive side, research has shown that in-service training on supporting early language and literacy development can have favorable outcomes (Dickinson & Caswell, 2007; Girolametto et al., 2006; Wasik et al., 2006). The goal of many in-service training programs is to change the behavior of family child care providers and maintain that change over time. Although training developed to meet the needs of adult learners has been linked to change in caregiver beliefs and attitudes, in many cases it is not successful in changing behavior (Joyce & Showers, 2002). Others have found that training does influence caregiver behaviors, but positive behaviors diminish over time (Ota, DiCarlo, Burts, Laird, & Gioe, 2006; Pence, Justice, & Wiggins, 2008). These findings indicate that in-service training alone may not be enough to change caregiver practices long term (beyond a few months) even though it incorporates good pedagogical practices for adults (Honig & Martin, 2009). In-service training combined with on-site mentoring may increase change in caregiver behaviors (Bryant et al., 2009; Norris, 2001; Maxwell, Feild, & Clifford, 2005; McCabe & Cochran, 2008; see also Dickinson et al., 2008). Mentoring, defined as individualized on-site guided support (Bellm, Whitebook, & Hnatiuk, 1997; Pavia, Nissen, Hawkins, Monroe, & Filimon-Demyen, 2003), has been shown to improve the quality of caregiver-child interactions. Mentoring support coupled with training can have a significant impact on caregiver behaviors leading to better experiences for children (Bryant et al., 2009; Downer, Kraft-Sayre & Pianta, 2009; Downer, Locasale-Crouch, Hamre, & Pianta, 2009; Girolametto et al., 2006; Jackson et al., 2006; Koh & Neuman, 2009; McCabe & Cochran, 2008; Landry, Anthony, Swank, & Monseque-Baily, 2009; Landry, Swank, Smith, Assel, & Gunnewig, 2006; Wasik et al., 2006). Specifically, studies have found that mentoring supports increased quality in FCC programs (Bryant et al., 2009; McCabe & Cochran, 2008) and increased positive caregiver-child interactions such as expansion and extension of children’s verbal language in center caregivers (Girolametto et al., 2006; Jackson et al., 2006). To the best of our knowledge, there are no studies that aim to increase the frequency of family child care providers’ linguistic inputs with the children in their care through a focus on an in-service training and mentoring intervention. The present study addresses this gap. 1.3. Research questions This study investigated family child care providers’ linguistic inputs with children before and after participation in two different professional development models (10-h in-service training and 10h in-service training with 12 weeks of on-site mentoring support), as compared to a control group. The specific research questions were as follows: (1) Is there a significant difference in the frequency of family child care provider linguistic inputs after provider participation in a 10-h training program as compared to a control group?; (2) Is there a significant difference in the frequency of family child care provider linguistic inputs after provider participation in a 10-h training program combined with on-site mentoring as compared to

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Table 1 Child characteristics by treatment group. Characteristic Ethnicity Caucasian Latino African American Other Family income <$25,000 $25,000–50,000 $50,000–75,000 >$75,000

Table 2 Program and provider characteristics by treatment group.

Control (n = 32)

TO (n = 32)

TM (n = 32)

26 (81.2) 3 (09.4) 0 (0.0) 3 (09.4)

25 (78.1) 5 (15.6) 1 (03.1) 1 (03.1)

27 (84.4) 3 (09.4) 2 (06.3) 0 (0.0)

2 (06.3) 17 (53.1) 10 (31.3) 3 (09.4)

0 (0.0) 18 (56.3) 11 (34.4) 3 (09.4)

3 (09.4) 14 (43.8) 14 (43.8) 1 (03.1)

Note: Percentages for Individual Treatment Groups are shown in parentheses. TO, Training Only; TM, Training plus Mentoring.

a control group?; (3) Is one model (training or training plus mentoring) associated with a greater increase in the frequency of provider linguistically stimulating inputs in family child care programs? 2. Method

Characteristic Program Type Family Home Family Group Average Enrollmenta Provider Ethnicity Caucasian Latino African American Other Provider education High school College degree Graduate degree Missing Provider experience <5 year 5–15 years >15 years

Control (n = 16)

TO (n = 16)

TM (n = 16)

8 (50.0) 8 (50.0) 11 (91.7)

8 (50.0) 8 (50.0) 9 (75.0)

7 (56.0) 9 (72.0) 11 (88.0)

11 (68.8) 3 (18.8) 1 (06.3) 1 (06.3)

8 (50.0) 5 (31.3) 2 (12.5) 1 (06.2)

10 (62.5) 4 (25.0) 2 (12.5) 0 (0.0)

9 (56.3) 3 (18.8) 2 (12.5) 2 (12.5)

7 (43.8) 6 (37.5) 2 (12.5) 1 (06.3)

8 (50.0) 5 (31.3) 3 (18.8) 0 (0.0)

4 (25.0) 5 (31.3) 7 (43.8)

2 (12.5) 8 (50.0) 6 (37.5)

8 (50.0) 4 (25.0) 4 (25.0)

Note: Percentages for Individual Treatment Groups are shown in parentheses. TO, Training Only; TM, Training plus Mentoring. a Percentage based on average licensed capacity.

2.1. Selection and assignment Family child care programs were selected by using a statewide database to obtain a listing of all licensed family child care programs in the targeted regions. Recruitment efforts included the use of postcards sent by mail and phone calls made to licensed providers. Postcards were sent to 800 providers and announced an opportunity for English-speaking providers to volunteer in a research study on verbal language in FCC. Researchers made phone contact with 240 family child care programs (30% of the 800 total programs) during recruitment. Of these, 50 (20%) met the criteria and agreed to participate with 190 (80%) not interested in participating or not meeting study criteria. Study criteria required that programs be licensed by the state, have more than four full-time children attending between the ages of 2- and 4-years-old, and be willing to participate in all the activities associated with both professional development models. As contact was made with potential providers, they were assigned sequentially from a random starting point to one of the three groups. Of the 50 initial participating programs, two programs withdrew – one from the training group and one from the control group – leaving the final sample with 16 programs in each of the treatment groups and representing an overall attrition rate for the entire study of 4%. Four children from each program were randomly selected to wear audio recorders provided they met the following qualifications: their parents had given signed informed consent; they attended the family child care program a minimum of 30 h a week; they were between 2- and 4-years-old; they were native English speakers; they had no diagnosed cognitive or linguistic delays. The average age across groups was 3 years 6 months (3 years 5 months for control; 3 years 6 months for training only; 3 years 7 months for training plus mentoring). To limit provider bias in purposely changing behaviors specifically for children wearing recorders, researchers selected more children to wear audio recorders than would be used for coding and mock recorders were provided for the remaining children in the program. Of the four children wearing real recorders, two children from each program were selected for coding, balancing child age and gender across the groups; in each age group, there were 16 boys and 16 girls. The selected children were 81% Caucasian, 12% Latino; 3% African American, and 4% other. Family income was mostly middle class, with 5% earning less than $25,000, 51% earning $25,000–50,000, 37% earning $50,000–75,000, and 7% earning more than $75,000. See Table 1 for demographics by treatment group. Using one-way ANOVA for

child age and Chi-square for ethnicity and family income, there were no significant differences found across treatment groups (pvalue range, .37–.74). 2.2. Participants For this study, four of the larger regions of a Western state were selected based on their large numbers of family child care programs, ranging from 144 to 238. Family child care refers to child care provided by unrelated adult caregivers to children, often of different ages, in the caregiver’s own home (NACCRRA, 2010). The specific definition, licensing requirements, and regulations for family child care programs vary by state. Of the 48 programs participating; 23 were licensed as family home child care (up to 8 children) and 25 were licensed as family group child care (up to 16 children at a time with at least 2 providers). The mean number of children enrolled, including part-time and full-time enrollments, across programs was 10.71, range 6–22. All of the participating programs cared for children 0–5 years of age; with 40 programs providing before and afterschool care for primary-age children. See Table 2 for further details. Providers also reported non-study related trainings attended during this period. The average number of non-study related training hours received by participants was similar across experimental groups (control, M = 10.00; Training Only, M = 9.22; Training plus Mentoring, M = 9.06). Using Chi-square (program type, ethnicity, education) and one-way ANOVAs (enrollment, years of experience, non-study related training hours), there were no significant differences found between treatment groups for program or provider characteristics (p-value range, .26–.65). 2.3. Intervention The three study groups are identified as follows: Group 1: (Control) this group maintained “business as usual,” which could include other in-service trainings that caregivers might attend as part of their normal professional development outside of this study; Group 2: (Training only: TO) providers in the TO group received professional development in the form of the prescribed training for this study (i.e., 10-h training in language development and verbal interactions through the curriculum, First Steps: Supporting Early Language Development [Educational Productions, 1995]); Group 3:

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(Training plus Mentoring: TM) Providers in the TM group received professional development in the form of the prescribed training for this study (i.e., 10-h training in language development and verbal interactions through the First Steps: Supporting Early Language Development [Educational Productions, 1995]). Additionally, the TM group received six on-site mentoring visits, made every other week for 12 weeks, and weekly phone calls initiated by the mentor.

2.4. Training procedures Provider training for TO and TM groups consisted of four, 150-min sessions over a 6-week period. Providers in each region received training delivered by one of four early care and education specialists employed to deliver trainings. Providers were required to attend all four training sessions, arrive on time, and stay for the full duration of each session. The trainers for both TO and TM groups made follow-up contact with providers via phone or face-to-face in the following training to answer questions and clarify content.

2.4.1. Training curriculum The training intervention curriculum, developed by Educational Productions (1995), consisted of group training for providers in overall language development and how adults can support this development through linguistic interactions. The first session focused on the topic of language development, the importance of adult responses to young children, and the necessity of appreciating each child’s unique path in language development. The remaining three training sessions (150 min each) centered on talking with young children (i.e., identifying, understanding, and incorporating language in interactions with children; using specific strategies in conversations) and building conversations (i.e., understanding the opportunities conversation provides to children and techniques to facilitate conversation; turn-taking and following the child’s lead). Each training class could accommodate 20 providers.

2.4.2. Trainers In each of the four regions, trainings were administered by an early care and education specialist working in that region. All specialists were female, had a 4-year degree in an early childhood related field, and all had experience as a center child care caregiver, program administrator, and child care provider mentor. The trainers were registered with the state and held several training certifications such as the Program for Infant and Toddler Caregivers (PITC). Each trainer was familiar with the First Steps training curriculum, and each received the trainer’s manual which included training resources, activities, lecture notes, discussions, and DVD video clips for interactive skills practice. The trainers attended a 2-h orientation with the researcher to discuss the training expectations related to this research project; however, at no time were the purpose of the study or the research questions shared with the trainers. Trainers were encouraged to be responsive to the individual interests of the group and meet their learning needs in discussion, but were asked to address each main point in the curriculum and to use all of the activities on the training agenda for each session. To support implementation fidelity of this training across all regions, one session for each trainer was audio-recorded. After listening to the recordings, the researcher certified that the training activities were aligned with the curriculum, that the trainer covered the topics assigned for the session, and that the session was the designated length. Additionally, individual phone calls were made to each trainer following each of the four sessions to see if there were any questions, problems, or concerns from the recent training.

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2.5. Mentoring procedures Mentoring for the TM group included both off-site and onsite components. Mentors provided six consultative visits over 12-weeks. Mentor visits consisted of modeling; discussion of current individual issues, concerns, and goals; and direct feedback on recommended practices. The mean visit duration across all mentors and family child care programs was 75 min (range, 65–99). A large portion of the mentoring was provided in the family child care setting during everyday activities and routines. Off-site, mentors contacted providers by phone weekly and were available for providers to call or email during business hours. Mentor initiated phone calls were used to follow-up on the previous visit. Providerinitiated phone call and email content were determined by the individual provider and served to provide emotional and informational support. All communications were logged by the mentor in a computer database. 2.5.1. Mentors Each of the four mentors had previous child care and mentoring experience and an understanding of recommended practices in child care. The on-site mentors were employees of the state Office of Child Care. Three held early childhood related 4-year degrees, and all had experience as a center- or family-care provider, trainer, and mentor. All on-site mentors were trained to address six elements (see Riley & Roach, 2006) as they worked with providers: (1) build a training relationship, (2) shape promising practices, (3) generalize effective practices, (4) provide conceptual labels, (5) link practices with research-based knowledge, and (6) encourage caregiver’s self-exploration. The mentors were familiar with the training and concepts taught, however, they were not made aware of the specific linguistic inputs being measured to avoid “teaching to the test.” Additionally, researchers wanted any changes found that related to mentoring to be more generalizable to mentoring as a whole and not to the teaching of a limited set of inputs. To monitor consistency in mentoring, two mentoring visits were randomly selected and recorded for each mentor. Researchers reviewed these audio recordings for fidelity including length of visit, overall climate, and mentor professionalism. Providers completed mentoring satisfaction surveys at the end of the study. Surveys focused on content, length, and general feelings about the mentoring experience. 2.6. Data collection Provider linguistic inputs were assessed during free-choice time. That activity period was selected because it is one of the most commonly occurring activity periods in a preschool child’s day. A majority of their time is spent in free-choice activities (Fuligni, Howes, Huang, Hong, & Lara-Cinisomo, 2012). Providers tend to use less directive inputs during free choice activities (Girolametto et al., 2000; O’Brien & Bi, 1995) and child conversations with caregivers are often minimal (Dickinson, 2001) which creates a need to focus on increasing linguistically stimulating inputs during this time. The baseline recording was conducted two weeks prior to intervention. The second recording was collected approximately six weeks after baseline when the training courses had been completed. The mean time in days from baseline to the second recording for each group was 41 for control group, 42 for TO group, and 41 for TM group. The third recording providing an intervention posttest for all three groups was collected 12 weeks after baseline when the mentoring program was complete. The mean elapsed time by group in days from second to third recording was 41 for control, 40 for TO, and 41 for TM. For each data collection time point, the same data collections procedures were followed.

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The LENA (LENA Foundation, Boulder, CO), an automatic speech recording and analysis tool, was used to record child and provider conversations. In addition to recording child and provider speech, the software that accompanied the LENA gave actual frequencies of child turns during the recording period. The LENA system reliability for adult speech and child vocalizations is found in the literature to range from .65 to .92 (Xu, Yapanel, & Gray, 2009; Zimmerman et al., 2009). A minimum of 30 min of free-choice time was recorded, although the total recording time varied for each program depending on the length of the free-choice time at each program. Programs that had fewer than 30 min of free-choice were asked to extend their free-choice to meet the 30 min minimum. All programs complied with this request. 2.7. Linguistic inputs code system Each child’s recording was at least 30 min long. The first 10 min of each recording were skipped to provide time for children to transition into play activities. Then 15-min segments (minutes 10–25) were coded. The coding system used in this study was modified from Polyzoi (1997) and Salerni, Suttora, and D’Odorico (2007). Codes contained the following categories: (1) frequency of child turns, (2) frequency of provider linguistic inputs (informational talk, question inputs, expressive utterances, directives, and teaching utterances by the caregiver), and (3) conversational cohesiveness for the provider. A child’s turn was defined as a child’s verbal contribution seeking or continuing an interaction with a provider. Informational talk was defined as inputs that described a child’s action, behavior, or exploration or provided an answer to a child’s question by providing specific information (i.e., “I see you put the red one on top.”; “This tower has three blocks and this one has seven blocks”; “You are making groups by color.”). Question inputs were defined as provider open or closed-ended inquiries where a response was anticipated from the child (i.e., “Can you find a square block?”; “Why do you think this tower fell?”). Expressive utterances were defined as an expression or recognition of emotions (i.e., “Wow! You are very excited.”; “I enjoyed your story.”; “You really like being the chef.”). Directives were defined as an input that requested or required the child to take action (i.e., “Please hang up your coat.”; “Come sit down for lunch.”). Teaching utterances were defined as inputs that provided teaching or coaching or gave quality feedback to a child (i.e., When a child is struggling with using scissors, a provider provides helpful suggestions such as, “If you put your thumb in the smaller hole and fingers in the larger hole, cutting may be easier.”). The inputs included linguistically stimulating inputs related to positive outcomes for young children (i.e., expressive utterances, questions, information talk, teaching utterances) as well as less-stimulating linguistic inputs (i.e., directives) that, according to several researchers, are commonly used by providers. Cohesiveness was described as the number of contingent responses where the provider’s input in a conversation maintained the topic of the child’s turn. Each provider input was only coded as one linguistic input type (i.e., information talk or question input). If the provider’s input was a response to a child’s turn, the response was also coded for contingency. Inter-rater reliability (IRR) between the graduate student and the researcher was assessed on a randomly selected 22% of all recordings (64 recordings; 960 min). Prior to using the coding system, the graduate student was trained to 90% agreement with the researcher using five 10-min recordings that were not part of this study. Coders were blind to treatment group participation during coding. IRR was calculated using two methods. First, a simple percentage rate of agreement was calculated with the overall percent agreement for the linguistic inputs being 91%, response contingency 94%, and child turns 87%. Second, two-way, absolute agreement intraclass correlations (ICC) were calculated to assess

the degree of agreement in the frequencies the coders provided for provider linguistic inputs, provider response contingency, and child turns. Intraclass correlations are the recommended statistic for assessing IRR for interval and nominal data (Hallgren, 2012; McGraw & Wong, 1996) such as frequency counts. The ICC for the linguistic inputs was .91, response contingency was .95, and child turns was .90, indicating excellent reliability (Cicchetti, 1994; Hallgren, 2012). 2.8. Data analysis Because of the nested nature of the data set, Hierarchical Linear Modeling (HLM) was applied to take into account dependencies by estimating variance associated with groups (i.e., programs), differences in average responses (intercepts), and group differences in association (slopes) between predictors and linguistic inputs (e.g., group difference between treatments). The specific technique used for this analysis was Poisson HLM regression (Raudenbush & Bryk, 2002; Raudenbush, Bryk, Cheong, Congdon, & du Toit, 2004) using HLM 6.08. Poisson is typically the most applicable distribution when data counts reveal relatively small frequencies. A three-level HLM was employed to estimate initial frequencies of input strategies (intercept) and linear change (slope) across three observations through treatment, as well as to test associations between these estimates and characteristics of children and providers. The Level-1 model denotes behavior changes over time. Level-2 coefficients describe the behavior difference across children within programs as a function of demographic variables. At Level-3, the parameters describe provider differences among the three groups. First-level units were provider input strategies measured at three separate time points in relation to the treatments being employed. Second-level units were the 96 children from 48 family child care programs participating in one of the three third-level treatment groups. 3. Results Means across groups for each input type showed similar frequencies in the 15-min observation prior to treatment. Teaching utterances (range, .44–.75) and expressive utterances (range, 2.81–4.25) had the lowest mean frequency across groups. Providers used questions (range, 13.81–19.75) and directives (range, 12.00–15.75) most frequently. Contingent responses were more frequent (range, 9.25–14.75), compared to noncontingent responses (range, .13–.74). The mean frequency for child conversational turns was 15 (range, 12.00–17.75). One-way ANOVA was used to test mean differences across treatment groups for each individual linguistic input, response contingency, and child turns at baseline. There were no significant differences (p-value range, .33–.76). Overall, means for each linguistic input, except for directives, and contingent responses increased for TO and TM after in-service training. Six weeks after training, the TO group showed a drop in means for information talk, expressive utterances, directives, teaching utterances, contingent responses, and child turns. Excluding directives, the TM means showed a continued increase in all linguistic inputs, contingent responses, and child turns six weeks after in-service training. For individual linguistic input mean frequencies at each observation point, see Figs. 1–3. Prior to testing the three research questions, a null model was run. Initially, only one predictor, time, was entered in Level-1 as a fixed effect based on the assumption that provider linguistic inputs would change over the time points. Table 3 presents the results from this null model which indicates the average change in frequency of each input across time. The results show the provider’s use of specific linguistic inputs not only had grand means, in terms

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Fig. 2. Mean frequencies of directives, expressive utterances, and teaching utterances for the three treatment groups across observations.

The positive slope values indicate that overall behaviors increased over time with information talk, questions, expressive utterances, and teaching utterances. Each had significant slope increases over the three observation times. Except for the slope for

Fig. 1. Mean frequencies of information talk, questions, directives, contingent responses and child turns for the three treatment groups across observations.

of start points, significantly different from zero but also the slope, in terms of change over time, was significantly different from zero. The expounded coefficients represent the average number of times the provider used that specific input. In this case, the average expected counts were 7.85 units for information talk, 14.73 units for questions, 2.77 units for expressive utterances, 13.54 units for directives, and .34 units for teaching utterances.

Fig. 3. Mean frequencies for non-contingent responses for the three treatment groups across observations.

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Table 3 Null Model Poisson HLM regression coefficients and variance components for linguistic inputs.

Fixed effects Intercept Slope Random error components Intercept all cases Slope all cases Intercept all groups Slope all groups

Information talk 

Questions 

Expressive utterance 

Directives 

Teaching utterance 

2.06* (7.83) .41* (.05)

2.69* (.13) .23* (.05)

1.02* (.16) .37* (.07)

2.61* (.15) .06 (.06)

−1.09* (.25) .82* (.09)

.09* .02* 1.17* .21*

.04 .01 1.06* .22*

.03 .01 1.78* .35*

.10* .02* .79* .10*

1.55 .18 8.18* 1.46*

Note:  stands for coefficient. Standard error of each coefficient was provided in the parenthesis. * p < .05.

Table 4 Full model Poisson HLM regression (comparisons between Control vs. TO and Control vs. TM): coefficients and Odds Ratios. Fixed effects

DV intercept TO TM DV slope TO TM

Information talk

Expressive utterance

Directives



OR

Questions 

OR



OR



OR

Teaching utterance 

OR

−.22 (.28) −.65+ (.33)

.80 .52

−.33 (.36) −.58 (.36)

.72 .56

−.36 (.48) −.89* (.49)

.70 .41

−.27 (.30) −.18 (.43)

.76 .83

.15 −1.24*

1.16 .29

.50* (.13) .75* (.12)

1.66 2.12

.45* (.13) .61* (.13)

1.58 1.85

.60* (.19) .81* (.19)

1.83 2.24

.11 (.11) .02 (.14)

1.11 1.02

.57+ 1.06*

1.76 2.88

Note:  stands for coefficient whereas OR stands for Odds Ratio – the control group is the reference group. Standard error of each coefficient was provided in the parenthesis. TO, Training Only; TM, Training plus Mentoring. + p < .10. * p < .05.

directive inputs which was non-significant Exp() = 1.06, p = .320 in terms of change over time, the other behaviors (information talk, questions, expressive utterances, and teaching utterances) significantly changed over three time points Exp() from 1.26 to 2.27, p < .001. The variance components or random effects for the null model are reported in Table 3. The variance components show that there is significant amount of variance in behavior changes not explained by time alone indicating there is a need to further identify variables that may explain this variance. Intraclass correlations (ICCs) estimated from the null model provide the proportion of variance in outcomes attributable to differences between the treatment groups. At the provider level, ICCs ranged from .83 for questions −.85 for teaching utterances with significant Chi-square tests. These values indicate adequate variance between treatment groups.

The Level-3 predictor is experimental group membership (treatment versus non-treatment) to explain the contextual differences between providers. Three outcome variables, contingent responses, non-contingent responses, and child turns, did not converge, after more than 2000 iterations, in the hypothesized full model in hierarchical linear modeling. These variables were excluded from the HLM analyses. Except for the domain of information talk, there were significant mean differences across domains of behaviors in terms of provider linguistic inputs. When compared to the control group, the TM group had significantly lower frequencies at the starting point in expressive utterances Exp() = .41, p = .034 and teaching utterances Exp() = .29, p = .001 (see Table 4). In addition, TO had significantly higher frequencies than TM in the beginning in the domain of teaching utterances Exp() = 4.04, p = .006 (see Table 5). Research questions one and two addressed the differences in providers’ use of linguistic inputs after participation in in-service training with or without mentoring. Comparing the slopes to the control group, both TO and TM had significantly higher odds of increasing inputs over time for information talk, questions, expressive utterances, and teaching utterances. The average slope of the control group across time was not significantly different from zero

3.1. Professional development models compared to control group The Level-1 predictor is time (i.e., each of the three observation times) capturing the frequency of linguistic inputs use by providers over time. Level-2 did not have a predictor to portray variations and differential patterns of provider linguistic inputs across children.

Table 5 Full model Poisson HLM regression (comparisons between TM vs. TO and TM vs. Control): coefficients and Odds Ratios. Fixed effects

Information talk 

DV intercept TO Control DV slope TO Control

Questions OR



OR

Expressive utterance

Directives



OR



OR

Teaching utterance 

OR

.43 (.27) .65+ (.33)

1.54 1.92

.24 (.36) .58+ (.36)

1.28 1.78

.53 (.39) .89* (.42)

1.70 2.43

−.09 (.39) .18 (.43)

.91 1.20

1.40* (.48) 1.24* (.34)

4.04 3.47

−.24* (.09) −.75* (.13)

.78 .47

−.16 (.12) −.61* (.12)

.85 .54

−.21 (.15) −.81* (.23)

.82 .45

.09 (.15) −.02 (.14)

1.09 .98

−.49* (.19) −1.06* (.33)

.61 .35

Note:  stands for coefficient whereas OR stands for Odds Ratio – TM is the reference group. Standard error of each coefficient was provided in the parenthesis. TO, Training Only; TM, Training plus Mentoring. + p < .10. * p < .05.

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Table 6 Full model Poisson HLM regression: error variance components. Random effects

Information talk

Questions

Expressive utterance

Directives

Teaching utterance

Intercept all cases Slope all cases Intercept all groups Slope all groups R2

.09* .02* 1.04* .08* .619 (61.9%)

.03 .01+ .97* .13* .409 (40.9%)

.03 .01 1.61* .21* .400 (4.0%)

.10* .02* .77* .10* .00 (0.0%)

1.55 .18 7.63* 1.28* .123 (12.3%)

Note: R2 are computed only for the between-providers variance (i.e., level 3) using the formula (10NULL − 10FULL )/10NULL . + p < .10. * p < .05.

except for asking questions Exp() = .83, p = .042. On the other hand, while the average slope of TO for directives Exp() = 1.11, p = 167 was not significantly different from the control group, information talk Exp() = 1.66, p = .003, questions Exp() = 1.58, p = .003, and expressive utterance Exp() = 1.83, p = .001 were significantly different. Additionally, the average slope of TM for directives Exp() = 1.02, p = 167 was not significantly different from the control group, however, information talk Exp() = 2.12, p = .000, questions Exp() = 1.85, p = .000, and expressive utterance Exp() = 2.24, p = .001, and teaching utterances Exp() = 2.88, p = .003 were significantly different (see Table 4). In sum, these results show that family child care providers in the control group did not change their frequency of using linguistic inputs across the three time points with the exception of question inputs, which increased over the course of the study. Both TO and TM participants showed an increase in all linguistic inputs except directives over the three time points and thus were more likely than the controls to increase their use of information talk, questions, expressive utterances, and teaching utterances. 3.2. Training only model compared to training with mentoring support Research question three considered the differences between the two professional development models. The average slope of TM was significantly different from zero for all strategies, Exp() from 1.52 to 3.43, p level all less than .001 level, except for directives Exp() = 1.03, p = .798. Moreover, TO had significantly lower frequency increases than TM in information talk Exp() = .78, p = .009 and teaching utterances Exp() = .61, p = .014 (see Table 5 for details). These results show that the family child care providers participating in in-service training with mentoring increased their use of information talk and teaching utterances significantly more than those receiving in-service training only. Except for the directive inputs, the two predictors (i.e., time and group) had decreased the residual variance of provider-level averages by approximately 62% for information talk, 41% for questions, 40% for expressive utterances, and 12% for teaching utterances (see Table 6). The proportion of variance explained by the treatment group was moderate; noting the observed change in the frequency of linguistic inputs used by the providers was explained by the specific professional development model. 4. Discussion This study contributes new knowledge to an under-studied area in the child care literature: the importance of structuring in-service training programs with an on-site mentoring component for family child care providers to increase the probability of desired training results. As stated earlier, according to some studies, child care quality in FCC is lower than that in center care, while children attending FCC spend longer days in out-of-home care because their parents tend to work longer hours (Austin et al., 2011). Thus, it is particularly relevant to investigate the ways that recommended practices,

measured in this study by linguistic inputs, might be enhanced for FCC providers. In this study, providers’ use of linguistically stimulating inputs increased following both training only (TO) and training plus mentoring (TM) models, but the increases were greater with the training and on-site mentoring model. This difference could be because on-site mentoring is a more personal strategy that offers the provider an opportunity to discuss individual concerns with a supportive and knowledgeable professional. The mentors had professional training in child development and experience in early care and education so their insights likely served to enhance their mentee’s professional understanding and development. Significantly, the mentors were allowed to provide assistance on all topics, but even with this general approach to mentoring, specific linguistic inputs still showed related gains with TM. 4.1. Training increased the frequency of linguistic inputs The first research question asked whether there was a significant difference in family child care provider linguistic inputs after participating in 10-h training compared to a control group. The results of this study indicate that family child care providers’ use of specific linguistic inputs increased following participation in in-service training. Participating providers increased their use of information talk, questions, and expressive and teaching utterances over providers in the control group. However, this study emphasizes the ongoing issue of retention of training advantages because the means show slight decreases in expressive utterances, teaching utterances and information talk six weeks following the training. In this regard, our findings are similar to those of Honig and Martin (2009) who looked at retention of in-service training, turn-taking and use of Socratic (open-ended) questions for providers in centerbased child care. Thus, retention of training benefits appears to be an ongoing issue in the child care provider training literature both for center and family child care providers. 4.2. Training plus mentoring increased the frequency of linguistic inputs Research question two asked whether a significant difference was present in family child care provider linguistic inputs after provider participation in a 10-h training program combined with on-site mentoring as compared to a control group. Research question three asked which professional development model (training or training plus mentoring) was associated with the greatest increase in the frequency that providers used linguistically stimulating inputs in family child care programs. Both treatment groups had increases in information talk, questions, expressive utterances, and teaching utterances, with the TM group showing a greater increase in the frequency of these strategies by observation three. Similar to other work (Bryant et al., 2009), when provided with mentoring support in addition to attending in-service training, family child care providers used information talk, questions, and teaching utterances more frequently than those not participating in this specific professional development opportunity. Center

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caregivers also seem to benefit from on-site mentoring (Black, Molseed, & Sayler, 2003). It appears that training and individualized one-on-one mentoring, as opposed to training only, can support providers in using specific linguistic inputs more often during free choice time, but it cannot be said with confidence that mentoring itself is related to the differences found. It does seem that mentoring might lead to better retention of training concepts because it allows the provider to discuss individual circumstances privately, ask questions, and request clarifications. It is possible that this iterative process operationalizes the concepts discussed during group trainings. Given the unique characteristics of the family child care industry, on-site mentoring may be particularly important for this population. Family child care providers often have less education and training (Weaver, 2002), work longer hours (Austin et al., 2011), have lower incomes than center caregivers or workers in other industries with comparable skills (Helburn, Morris, & Modigliani, 2002), and have limited support (Dowsett et al., 2008; Fuligni et al., 2009). FCC providers often offer extended hours of care for families with varying work schedules. This could make it challenging for providers to attend in-service trainings. Additionally, because of the relative isolation of the FCC provider, it is possible that they will be more receptive and ready for mentoring support. 4.3. Addressing specific linguistic inputs Questions, consistent with other study findings (e.g., Turnbull et al., 2009), had the highest occurrence at baseline and notable increases after in-service training for both TO and TM participants. Using questions seems to be a fairly typical form of linguistic input with children. It may be more natural for providers to increase their use of questions, compared with other types of inputs, when the importance of asking questions is expressed to them through group-training sessions. It is important to note that the type of question was not a focus of this study. According to extant research, Socratic questions provide more benefits for children’s language growth than closed test-like questions, however, the aim of this study was to look at changes in the frequency of multiple linguistic inputs and the types of questions providers used in this study is unknown. Linguistically stimulating inputs, like practicing information talk and teaching utterances, appear to increase more when family child care providers are supported with additional mentoring, but it is unknown whether specific types of questions or other, untested linguistic strategies, would respond to training plus mentoring. Previous research on in-service training has found that center caregivers apply portions of trainings in their classroom rather than implementing all strategies globally across activities (Girolametto, Weitzman, & Greenberg, 2003). Providers may need additional training and mentoring to implement some behaviors and practice these across activities within the program. While child turns and provider contingent responses could not be included in the inferential analyses of this study, it is important to note that the mean frequencies over the three observations show similar patterns to the other inputs. It appears that providers who received training plus mentoring responded with increased contingency while the children in their programs were taking more verbal turns in the conversations over time. Looking at provider contingency and child turns with a larger sample may help provide a better picture of these changes with and without mentoring support. It was anticipated that, as providers implemented increased frequencies of linguistically stimulating inputs, the frequency of directives would decrease significantly. However, a decrease was not found in this study. The use of directives stayed fairly consistent across time regardless of professional development participation.

It seems from these results that directives are not influenced by the professional development models used nor do they necessarily decrease in frequency as other inputs increase. Directives may be an expression of philosophies of management or indicative of providers’ sense of responsibility to maintain the group routine. The lack of change could be that the providers’ directives are a necessary part of routines (i.e., washing hands, toileting routines). Each provider has their own philosophy for caring for children that may contribute more to how often directives are used outweighing gains provided by additional training or mentoring. While family child care providers who received mentoring support demonstrated significant increases in two specific linguistic inputs above those with in-service training only, it is still unclear whether these increases in frequencies could have been reached with additional in-service training hours as opposed to more-expensive, on-site mentoring support. Research on in-service training as professional development has mixed findings (Honig & Martin, 2009; Whitebook, 2003), but findings are more consistent for professional development that includes specific feedback and individual mentoring for providers (Cain, Rudd, & Saxon, 2007; Dickinson & Caswell, 2007; Pianta, Mashburn, Downer, Hamre, & Justice, 2008; Powell, Diamond, Burchinal, & Koehler, 2010) rather than more global, group-oriented training methods. In this study, the intention was to determine the success of mentoring that focused on concepts taught during in-service training, while allowing opportunities to focus on other issues as well. Several studies investigating the impact of mentoring on caregiver practices focus on providing specific feedback and modeling for caregivers on the discrete skills being measured, suggesting that mentoring may show more benefits when discrete skills are targeted specifically (Pianta et al., 2008; Powell et al., 2010). An alternate explanation is that discrete skills can be taught in a shorter time frame in an in-service setting and with individual support. To understand how more comprehensive concepts and broader practices are implemented, training and mentoring may need to be delivered over longer time periods. 4.4. Summary Overall, this study extends current knowledge of professional development for family child care providers related to linguistic inputs. These findings indicate that in-service training on supporting children’s language development is related to an increase in providers’ use of linguistically stimulating inputs. Greater gains were seen when professional development included in-service training and on-site mentoring. In this case, providers used the linguistic inputs of informational talk, and teaching utterances more frequently when they were supported by a mentor than if they received in-service training only. 4.5. Limitations The findings from this study provide support for professional development in the form of in-service training and mentoring as a way to increase providers’ use of linguistically stimulating input. While these findings are encouraging, there are several limitations that need to be noted. Providers were randomly assigned to treatment or control groups. However, each provider in the study volunteered to participate and only 20% of the contacted providers met the criteria and agreed to participate. Consideration should be made for the possibility that providers who volunteered for this study are different than those who were not interested in participating. It is possible that providers who volunteered are more open to the idea of training and mentoring or are already seeking ways to improve which could have contributed to their change in behavior. This sampling

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method leads to possible lack of external validity for these study results. The study sample is primarily mid-income and Caucasian. Previous research has shown that early language interactions vary with income and also between ethnic groups (Farkas & Beron, 2004). Therefore, findings from this study are limited to a narrow population and future research is needed to examine training and mentoring with diverse populations including income levels and ethnicities. It is also important to note that this study did not include a delayed follow-up observation. While the final observation was six weeks after the training was complete, this is a relatively short period of time. In this study, a slight decline in means from observation two to three was observed. This finding is consistent with previous research findings where behavior changes after in-service training only declined over time (Honig & Martin, 2009). It is likely with this study that family child care providers in the TO group who showed an increased use of linguistic inputs may have shown a continued decline or complete regression if observed 6 months after the intervention ended. A decline might also be seen for the family child care providers in the TM group, although research has shown that behavior change after mentoring may be maintained up to 6 months after intervention (Bryant et al., 2009). In either case, an extended follow-up would have allowed researchers to look at long-term outcomes of each professional development model. Research has shown that differences in child care environments are related to experiences and outcomes for children. Specifically for this study, the overall quality of the programs and language environments were not measured. These FCC programs likely varied considerably in the quality of the language environment provided. This information would have allowed a richer look at changes in providers’ linguistic inputs and the language experiences of the children. The data collected for this study focused on free-choice activities in family child care. This is a specific time in children’s daily experience in FCC that has rich language opportunities. However, the language strategies used by family child care providers and language spoken by the children are likely very different while in large group activities, lunch, or structured small-group activities. Caution should be used when extending the results beyond the free-choice setting. An additional limitation of this study is the absence of a treatment that included only mentoring or one-on-one provider support. A mentoring-only approach provides individualized training for providers, either according to a particular mentoring curriculum or according to the individual circumstances and issues faced by each provider. Having a group that received only professional development in the form of mentoring would allow comparisons to be made in the absence of the in-service training. To examine mentoring as an isolated treatment would have provided better estimates of the two different forms of professional development and the combination of the two as it related to increases in desired behaviors.

4.6. Implications As states continue to develop and implement professional development systems, consideration should be given to combining in-service training and on-site mentoring. Opportunities for providers to participate in training and receive ongoing support could assist providers as they work toward meeting state standards for quality child care while enhancing their skills. States that recognize the potential added benefit of personal mentoring in addition to required in-service training could find a more desirable outcome – progress toward or meeting quality standards.

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4.7. Future directions There are two notable directions for future research that are apparent from these study findings. First, an examination of the contribution of mentoring as a standalone treatment is necessary. This format may have value for community and state agencies as there are many providers who cannot or do not participate in professional development in the form of in-service training. Understanding professional development through mentoring aside from other professional development could reveal ways to reach new provider populations (i.e., those in rural areas, those providing extended care, those with transportation limitations). Another area for future research is to examine whether professional development in the form of in-service training spread out over a longer duration, where trainers provide feedback and facilitate discussions related to curriculum content and current practices, would create a similar context to mentoring. This study’s on-site mentoring consisted of feedback and reflection through discussion. Adding these components to in-service training should be examined further. This format would provide a clearer understanding of the mentoring contribution and then allow for the incorporation of the most successful components in the most cost effective way.

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