569744 research-article2015
AUT0010.1177/1362361315569744AutismSanders et al.
Original Article
The questions verbal children with autism spectrum disorder encounter in the inclusive preschool classroom
Autism 1–10 © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1362361315569744 aut.sagepub.com
Eric J Sanders1, Dwight W Irvin2, Katie Belardi3, Luke McCune2, Brian A Boyd3 and Samuel L Odom3
Abstract This study investigated questions adults asked to children with autism spectrum disorder in inclusive pre-kindergarten classrooms, and whether child (e.g. autism severity) and setting (i.e. adult-to-child ratio) characteristics were related to questions asked during center-time. Videos of verbal children with autism spectrum disorder (n = 42) were coded based on the following question categories adapted from the work of Massey et al.: management, low cognitive challenging, or cognitively challenging. Results indicated that management questions (mean = 19.97, standard deviation = 12.71) were asked more than less cognitively challenging questions (mean = 14.22, standard deviation = 8.98) and less cognitively challenging questions were asked more than cognitively challenging questions (mean = 10.00, standard deviation = 6.9). Children with higher language levels had a greater likelihood of receiving cognitively challenging questions (odds ratio = 1.025; p = 0.007). Cognitively challenging questions had a greater likelihood of being asked in classrooms with more adults relative to children (odds ratio = 1.176; p = 0.037). The findings present a first step in identifying the questions directed at preschoolers with autism spectrum disorder in inclusive classrooms. Keywords autism spectrum disorder, child characteristics, communication and language, preschool children, questions
Introduction Language input in early childhood classrooms is thought to be related to children’s social, literacy, language, and cognitive growth (Diamond et al., 2013). As such, the questions asked by adults in the classroom setting have received particular attention recently. A key focus has been on identifying the different types of questions asked in early childhood settings because they may be related to the development of linguistic complexity and foster the use of decontextualized language (De Rivera et al., 2005; Massey et al., 2008; Zucker et al., 2010). Little is known, however, about the types of questions specifically directed at preschool children with autism spectrum disorder (ASD). Recently, there has been an increase in the number of children with ASD entering inclusive classrooms (Technical Assistance and Dissemination Network, 2012). Research suggests that teachers in inclusive settings, in particular, may have difficulty differentiating their language, which includes questions, to meet the developmental needs of
children with versus without disabilities (Hestenes et al., 2004). Specific to children with ASD, there is evidence suggesting the amount of language these children are exposed to in preschool settings may be related to both child (e.g. cognitive abilities) (Dykstra et al., 2013; Irvin et al., 2013) and classroom (e.g. adult to child with ASD ratio) characteristics (Irvin et al., 2013). However, a systematic exploration of the questions children with ASD receive as well as the influence of child and classroom characteristics on these questions has not taken place. Therefore, the purpose of this study was to add to the 1Pacific
University, USA of Kansas, USA 3The University of North Carolina at Chapel Hill, USA 2University
Corresponding author: Eric J Sanders, School of Communication Sciences and Disorders, Pacific University, 2043 College Way, Forest Grove, OR 97116, USA. E-mail: [email protected]
2 knowledge base by (1) identifying the types of questions adults ask to children with ASD in inclusive settings and (2) examining whether certain within-child (i.e. autism severity, language, and cognitive ability) and classroom factors (i.e. adult-to-child ratio) impact the types of questions that are asked. This exploratory study solely focused on children who have the ability to verbally respond to a range of questions in inclusive classroom settings and may provide an important base for comparison to future studies of children with more limited expressive language.
Questions asked in preschool There are several reasons why adult questions in preschool classrooms are important. From a transactional perspective of child development (Sameroff and Chandler, 1975), the exchanges that result from the questions asked by adults may be related to the development of language and cognitive growth. For example, adults use question– answer exchanges to teach children novel language about objects, people, and events (Parnell and Amerman, 1983). Additionally, the context of question–answer exchanges provides cues that are often explicitly used for turn-taking sequences that draw children into a speaker’s role. This potentially provides an opportunity for the child to practice more complex language (de Rivera et al., 2005). Adult questions can be explored from a variety of perspectives. It is possible to examine questions in terms of their syntactic structure (De Villiers et al., 2008), pragmatic function (James and Seebach, 1982), or whether they advance conversation (De Rivera et al., 2005). While important, these perspectives do not permit examination of the questions’ cognitive load, which may influence children’s language growth and later academic success. One way to examine the cognitive load is to differentiate questions along lines of abstraction (e.g. Blank et al., 1978; Massey, 2004). Recently, coding schemes have been developed that categorize adult questions in terms of whether they exhibit high cognitive challenge or low cognitive challenge (Massey et al., 2008; McGinty et al., 2012). Questions of low cognitive challenge are typically related to perceptually present referents (e.g. “What is this?” and “Where is the car?”). Questions that possess greater cognitive challenge require more abstract reasoning such as recalling past events, making inferences, or perspective taking (e.g. “What did you do over the weekend?” and “How do you think he feels?”). The use of questions that share elements similar to cognitively challenging ones has been linked to positive outcomes among children who are typically developing. For example, a relationship has been shown between openended questions and longer responses from preschoolaged children (De Rivera et al., 2005). Additionally, adults in classroom settings have used inferential questions as a way to facilitate more advanced, abstract language skills in
Autism book-reading contexts with children who have language impairment (Van Kleeck et al., 2006) and who are typically developing (Wasik and Bond, 2001). These skills are presumably important for later literacy growth and achievement in the classroom. For these reasons, questions like these are commonly recommended in a variety of language and literacy interventions (e.g. Ruston and Schwanenflugel, 2010; Whitehurst and Lonigan, 1998). Few studies have specifically examined the cognitive challenge of questions asked in preschool classrooms. One recent study of teachers in classrooms serving at-risk children found that questions designed to manage behavior (e.g. “Can you give me that?”) or conversation (e.g. “What did you say?”) made up the near majority of the questions asked across contexts (45%; Massey et al., 2008). Questions with lower cognitive complexity were 23 percent of all questions asked, and questions with higher cognitive complexity were 33 percent of all questions asked. Of note is evidence indicating that teachers in inclusive classrooms ask children with and without disabilities a preponderance of questions that are intended to manage behavior and have less cognitive complexity as opposed to questions of higher cognitive complexity (Hestenes et al., 2004). Investigations of the questions addressed to preschoolers with ASD in preschool classrooms appear to be lacking. One exception is Burgess, Audet, and Harjusola-Webb (2013) who investigated the quantity and quality of the language directed at preschool children with ASD. During periods of high verbal interaction, approximately 27 percent of all utterances from classroom adults were yes/no questions and approximately 26 percent were open-ended questions. While these findings are important in that they describe the language richness of these preschool classrooms, this study does not provide specifics about the questions asked, particularly regarding their level of cognitive challenge.
Factors that may impact the questions directed at children with ASD Within-child factors such as the severity of ASD symptoms, language, and cognitive impairments may affect the types of questions asked to children with ASD. Warren et al. (2010) examined the natural language environment of the home for young children with ASD in comparison with children who are typically developing. The results indicated that increased language ability and decreased severity of autism, as reported by caregivers, were associated with the number of words (i.e. adult language) children experienced. In other words, children with better language skills and fewer symptoms of ASD received more language input from adults. Similarly, in the preschool classroom, there is evidence suggesting within-child factors affect language input. For example, researchers report that young children
3
Sanders et al. Table 1. Child assessment descriptives.
PLS-4 total (raw score) Mullen-VR (raw score) CARS (total score) Age (in months)
N
Minimum
Maximum
M
SD
41 42 42 42
19 22 19.5 37
129 50 42.5 63
84.22 39.43 28.80 50.07
26.19 8.59 5.42 7.66
SD: standard deviation; PLS-4: Preschool Language Scale, Fourth Edition; CARS: Childhood Autism Rating Scale; VR: visual reception.
with ASD experience fewer words from classroom adults if they have lower cognitive (Dykstra et al., 2013; Irvin et al., 2013) and language abilities (Dykstra et al., 2013). Taken together, these studies suggest a link between adult language, which encompasses questions asked, and certain child characteristics. Adult-to-child ratio is also a salient factor affecting the types of questions directed at children with ASD in classroom settings. For example, in inclusive preschool classrooms higher teacher-to-child ratios (e.g. more teachers per children in the classroom) are linked to higher quality teacher–child interactions, as evidenced by teacher practices such as using an appropriate tone of voice and responding to children in a positive manner (Hestenes et al., 2008). Specific to ASD, some authors have found in self-contained preschool classrooms that a lower adultto-child with ASD ratio results in less language being directed at children with this disorder (Irvin et al., 2013). As classroom adult-to-child ratio appears to be related to the type and quantity of the language children with disabilities experience, it is important to determine whether this relationship extends to the types of questions classroom adults ask in inclusive settings. To our knowledge, there is an absence of studies that employ fine-grained methods to examine the type of questions directed at children with ASD in inclusive preschool classrooms. The specific research questions in this study were as follows: (1) what types and quantity of questions do children with ASD receive from classroom adults in the preschool classroom, and (2) is there any association between specific child characteristics (i.e. autism severity, language, and cognitive ability) and classroom adultto-child ratio and questions classroom adults direct at preschoolers with ASD?
Methods Participants Children. In all, 42 children who were part of a larger project evaluating the efficacy of preschool programs serving young children with ASD were included in this study. All participating children were enrolled in inclusive classrooms. The children were between the ages of 3–5 years (M = 50.12 months, standard deviation (SD) = 7.64) at the
time of study participation. Videos of children with ASD within center-time occurred within the first 3 months of the school year on a single day. The children had varying levels of ASD severity, as well as verbal and cognitive abilities (see Table 1). All measures were administered by trained staff who possessed or were in the process of obtaining a master’s or doctoral degree. All children in the study had a prior educational or community diagnosis of either ASD or developmental delay and met diagnostic criteria for ASD on the Autism Diagnostic Observation Schedule–Generic (ADOS-G; Lord et al., 2000). In addition, all children with ASD included in this study were verbal, and this was determined primarily based on the ADOS module they received. The ADOS is divided into four modules, and assessors determine the most appropriate module based on a child’s language abilities (e.g. children who receive Module 2 must have phrased speech). More children in this study received an ADOS Module 2 (n = 26; total score: M = 12, SD = 3.06) than a Module 1 (n = 8; total score: M = 19, SD = 2.73) or 3 (n = 8; total score: M = 15.63, SD = 4.14). However, a child who received Module 1 could be nonverbal; therefore, an additional criterion was established. Specifically, children administered Module 1 must have received a score of “0,” “1,” or “2” on item A1 Overall Level of Non-Echoed Language, indicating the child had at least five functional words. For this study, research-trained assessors administered 75 percent of the ADOS assessments; someone who was at least clinically trained and had established reliability with the research-trained assessor administered the remaining ADOS assessments. Classrooms. Children with ASD from a total of 29 inclusive preschool classrooms participated in this study, with an average of two children per classroom. The inclusive classrooms comprised two classroom types, either Learning Experiences: Alternative Program for Preschoolers and Parents (LEAP; Strain and Hoyson, 2000) or Businessas-usual (BAU; i.e. eclectic) programs. Dr Phil Strain established the LEAP model in 1981, and the prevailing theoretical/conceptual foundation for the model is applied behavior analysis. In LEAP, children who are typically developing learn peer-mediated methods aimed at improving the social interaction skills of children with ASD. The term BAU refers to classrooms in which teachers do not
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Autism
Table 2. Teacher and children demographics. Frequency Teacher demographics Race Ethnicity Gender Degree Children demographics Race Ethnicity Gender
White Black Non-Hispanic Hispanic Female Male Associates Bachelors Masters Above Masters
28 1 23 6 28 1 2 9 17 1
Asian Black White Non-Hispanic Hispanic Female Male
1 4 37 27 15 4 38
% 96.6 3.4 79.3 20.7 96.6 3.4 6.9 31.0 58.6 3.4 2.4 9.5 88.1 64.3 35.7 9.5 90.5
adhere to one theoretical/conceptual framework to guide their instructional practices (e.g. applied behavior analysis). Rather, teachers in these classrooms use a variety of intervention approaches from multiple instructional models. This eclectic model is the one typically used with children with ASD in public schools (Stahmer and Mandell, 2007), and the BAU classrooms included in this study conformed to this conceptualization (see Boyd et al., 2014, for an additional description of enrolled BAU classrooms). LEAP and BAU classrooms included in the study had to be operating in a public preschool. LEAP classrooms operate on a half-day schedule; thus, the duration of classroom instructional time for children was 2–3 h per day (M = 2.05 h). The instructional time for BAU classrooms ranged from 2 to 5 h (M = 2.78 h). The average number of children who are typically developing to children with ASD in LEAP (3:1) and BAU (4:1) classrooms was similar. It was not the purpose of this study to examine group differences; therefore, data were aggregated across both classroom types. Teachers. All lead teachers in these classrooms (n = 29) were certified to teach in their respective state and taught in a LEAP or BAU classroom for at least 2 years prior to study enrollment. Across both classroom types, lead teachers had an average of 10.78 years of experience in the classroom and 5.28 years of experience implementing their respective classroom treatment. Each LEAP and BAU classroom had one to two teachers as well as one to two teaching assistants. Teacher and child demographic information can be found in Table 2. Demographic data are presented on the lead teacher; however, it is important to clarify that we coded talk from any adult in the classroom
that was directed toward the focal children. We thought this was more reflective of the real-world experiences of children with ASD in classrooms. That is, they interact with a number of adults throughout the school day and not just the lead teacher. Unfortunately, demographic data were not systematically collected for classroom assistants or related service providers as part of the larger study.
Measures The Mullen Scales of Early Learning (Mullen, 1995) is a standardized, comprehensive assessment that measures gross motor, fine motor, visual reception (VR), and language abilities of children from birth through 68 months. The calculated VR subscale raw score was used in this study as a proxy for the child’s nonverbal cognitive abilities. For the current sample, the VR subscale was highly correlated with children’s total standard score (r = 0.85, p = 0.000) on the Mullen. Preschool Language Scale, Fourth Edition (PLS-4; Zimmerman et al., 2002) is a standardized measure used to assess language development, both receptive and expressive language ability, for children from birth through 6 years, 11 months. For the Mullen and PLS-4, raw scores were used because standard scores had floor effects and age equivalents scores were not available for all subscale or composite scores. Childhood Autism Rating Scale (CARS; Schopler et al., 1988) is a 15-item rating scale that is intended to differentiate children with ASD from peers who are typically developing and children with developmental delays. For each of the 15 items (e.g. relationship to people, listening response, verbal communication), an informant assigns a rating of 1 (normal for child’s chronological age), 2 (mildly abnormal for child’s chronological age), 3 (moderately abnormal for child’s chronological age), or 4 (severely abnormal for child’s chronological age). Thus, the total CARS score may range from 15 to 60. A total score greater than or equal to 30 is interpreted to suggest the child shows at least a moderate degree of ASD symptom severity. The instrument has more than acceptable reliability (i.e. an alpha of 0.94). Total scores were used in data analysis for this study. Research staff administered this assessment and had to meet the following reliability criteria: be within ±0.5 on 12 of 15 items (equal to an 80% reliability criterion) and within ±3 on the total score. Prior to the collection of any data, this study was approved by the Institutional Review Board at the University of North Carolina at Chapel Hill.
Procedures Children and classroom adults were videotaped during 30 min of center-time. In preschool classrooms, centertime can be conceptualized as the free time or space during which children are provided an opportunity to engage with
5
Sanders et al. Table 3. Percentage of inter-observer agreement versus disagreement for individual codes. Coder 1
Coder 2
M
Maximum
Minimum
M
Maximum
Minimum
Management Less cognitively challenging Cognitively challenging More cognitively challenging
89% 92% 93% 93%
93% 96% 97% 99%
81% 81% 83% 82%
91% 91% 95% 94%
96% 94% 98% 96%
84% 87% 92% 92%
adults and/or peers in designated areas containing academic and/or play materials. Center-time was selected because it was one of the few classroom activities that occurred consistently across classroom types (i.e. LEAP and BAU classrooms). The types of center activities available to children in this study included large blocks/manipulatives, pre-academic areas such as reading storybooks and computer time, and sensory motor activities such as art and large motor activities. For this study, no instructions were provided to adults other than to continue with their normal classroom routines and activities. The PROCODER software program (Tapp and Walden, 2000) was used to code each 10-s interval of the approximately 30-min video samples for adult questions. This typically resulted in 179 intervals (range: 129–192, M = 176, SD = 13.68) per observation. Each 10-s interval was coded for the presence or absence of each question type. Given that only four types of questions were being coded (see section “Coding scheme”), it was not necessary for coders to view videos multiple times in order to make coding decisions. Coding scheme. The coding scheme comprised categories and codes adapted from Massey et al.’s (2008) teacher questions coding scheme. Partial interval coding was used to code the questions that were either directed solely at the focal child or to a group that included the focal child (e.g. during circle time). The question classification for this study included the following categories: (1) management, (2) less cognitively challenging, (3) cognitively challenging, and (4) more cognitively challenging. More cognitively challenging questions were subsequently combined with the cognitively challenging category for data analysis purposes because they occurred infrequently and they were related to each other conceptually (see Appendix 1 for categories and examples of adult questions). Inter-rater reliability. All videos were independently coded by two primary coders, one of whom held a PhD in speechlanguage pathology and the other was pursuing a PhD in speech-language pathology. Across the two coders, 20 percent of their videos were subsequently coded by a secondary rater (the second author of this study) for reliability purposes. Raters first had to reach at least an average of 80 percent agreement per code as well as overall
agreement on the coding scheme across three consecutive non-study training videos. Coders had to maintain at least a mean 80 percent reliability criterion for each code as well as overall agreement throughout coding project videos. See Table 3 for complete reliability results.
Data analysis Research Question 1. What types and amounts of questions do children with ASD receive from adults in the preschool classroom? Descriptive statistics were used to identify the types and amounts of questions children with ASD experience in the classroom. In addition, chi-square analysis was employed to determine whether there were differences between types of questions asked. Research Question 2. How do child characteristics (i.e. autism severity, language, and cognitive ability) and adult-to-child ratio affect the questions adults direct at preschoolers with ASD? To answer this question, we first examined the intraclass correlations (ICCs) to assess whether a multilevel model was necessary (Snijders and Bosker, 2012). The multilevel structure was such that each child had multiple 10-s observations and each classroom contained several children. We opted to use a three-level model (see Table 4) to preserve the original structure of the data, ensure ample power to detect effects, and because there was a substantial amount of variance explained at Level 2 (i.e. children) and Level 3 (i.e. the classroom). Using PROC GLIMMIX (SAS Institute Inc, 2010), we estimated a mixed binomial logit model for each question type, predicting the odds of children receiving a particular question based on their raw PLS-4 total score, raw Mullen-VR score, CARS total score, and the ratio of adults to children. Classroom type (i.e. LEAP or BAU) was included as a covariate because we found that children in BAU classrooms were more likely to be asked cognitively challenging questions than those in LEAP classrooms (χ2(1) = 14.579; p = 0.0001). Classroom type did not affect the likelihood of management (χ2(1) = 1.802; p = 0.1794)
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Autism
Table 4. Intra-class correlations.
Management Less cognitively challenging Cognitively challenging
Level 1 (observation)
Level 2 (child)
Level 3 (classroom)
0.0365 0.0388 0.0405
0.1910 0.3712 0.4693
0.7724 0.5900 0.4902
Table 5. Questions by child characteristics, adult-child ratio, and classroom type. Management β (SE)
Less cognitively challenging p
Odds β (SE) ratios
p
Cognitively challenging Odds β (SE) ratios
p
Odds ratios
−2.202 (0.458)
AUT0010.1177/1362361315569744AutismSanders et al.
Original Article
The questions verbal children with autism spectrum disorder encounter in the inclusive preschool classroom
Autism 1–10 © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1362361315569744 aut.sagepub.com
Eric J Sanders1, Dwight W Irvin2, Katie Belardi3, Luke McCune2, Brian A Boyd3 and Samuel L Odom3
Abstract This study investigated questions adults asked to children with autism spectrum disorder in inclusive pre-kindergarten classrooms, and whether child (e.g. autism severity) and setting (i.e. adult-to-child ratio) characteristics were related to questions asked during center-time. Videos of verbal children with autism spectrum disorder (n = 42) were coded based on the following question categories adapted from the work of Massey et al.: management, low cognitive challenging, or cognitively challenging. Results indicated that management questions (mean = 19.97, standard deviation = 12.71) were asked more than less cognitively challenging questions (mean = 14.22, standard deviation = 8.98) and less cognitively challenging questions were asked more than cognitively challenging questions (mean = 10.00, standard deviation = 6.9). Children with higher language levels had a greater likelihood of receiving cognitively challenging questions (odds ratio = 1.025; p = 0.007). Cognitively challenging questions had a greater likelihood of being asked in classrooms with more adults relative to children (odds ratio = 1.176; p = 0.037). The findings present a first step in identifying the questions directed at preschoolers with autism spectrum disorder in inclusive classrooms. Keywords autism spectrum disorder, child characteristics, communication and language, preschool children, questions
Introduction Language input in early childhood classrooms is thought to be related to children’s social, literacy, language, and cognitive growth (Diamond et al., 2013). As such, the questions asked by adults in the classroom setting have received particular attention recently. A key focus has been on identifying the different types of questions asked in early childhood settings because they may be related to the development of linguistic complexity and foster the use of decontextualized language (De Rivera et al., 2005; Massey et al., 2008; Zucker et al., 2010). Little is known, however, about the types of questions specifically directed at preschool children with autism spectrum disorder (ASD). Recently, there has been an increase in the number of children with ASD entering inclusive classrooms (Technical Assistance and Dissemination Network, 2012). Research suggests that teachers in inclusive settings, in particular, may have difficulty differentiating their language, which includes questions, to meet the developmental needs of
children with versus without disabilities (Hestenes et al., 2004). Specific to children with ASD, there is evidence suggesting the amount of language these children are exposed to in preschool settings may be related to both child (e.g. cognitive abilities) (Dykstra et al., 2013; Irvin et al., 2013) and classroom (e.g. adult to child with ASD ratio) characteristics (Irvin et al., 2013). However, a systematic exploration of the questions children with ASD receive as well as the influence of child and classroom characteristics on these questions has not taken place. Therefore, the purpose of this study was to add to the 1Pacific
University, USA of Kansas, USA 3The University of North Carolina at Chapel Hill, USA 2University
Corresponding author: Eric J Sanders, School of Communication Sciences and Disorders, Pacific University, 2043 College Way, Forest Grove, OR 97116, USA. E-mail: [email protected]
2 knowledge base by (1) identifying the types of questions adults ask to children with ASD in inclusive settings and (2) examining whether certain within-child (i.e. autism severity, language, and cognitive ability) and classroom factors (i.e. adult-to-child ratio) impact the types of questions that are asked. This exploratory study solely focused on children who have the ability to verbally respond to a range of questions in inclusive classroom settings and may provide an important base for comparison to future studies of children with more limited expressive language.
Questions asked in preschool There are several reasons why adult questions in preschool classrooms are important. From a transactional perspective of child development (Sameroff and Chandler, 1975), the exchanges that result from the questions asked by adults may be related to the development of language and cognitive growth. For example, adults use question– answer exchanges to teach children novel language about objects, people, and events (Parnell and Amerman, 1983). Additionally, the context of question–answer exchanges provides cues that are often explicitly used for turn-taking sequences that draw children into a speaker’s role. This potentially provides an opportunity for the child to practice more complex language (de Rivera et al., 2005). Adult questions can be explored from a variety of perspectives. It is possible to examine questions in terms of their syntactic structure (De Villiers et al., 2008), pragmatic function (James and Seebach, 1982), or whether they advance conversation (De Rivera et al., 2005). While important, these perspectives do not permit examination of the questions’ cognitive load, which may influence children’s language growth and later academic success. One way to examine the cognitive load is to differentiate questions along lines of abstraction (e.g. Blank et al., 1978; Massey, 2004). Recently, coding schemes have been developed that categorize adult questions in terms of whether they exhibit high cognitive challenge or low cognitive challenge (Massey et al., 2008; McGinty et al., 2012). Questions of low cognitive challenge are typically related to perceptually present referents (e.g. “What is this?” and “Where is the car?”). Questions that possess greater cognitive challenge require more abstract reasoning such as recalling past events, making inferences, or perspective taking (e.g. “What did you do over the weekend?” and “How do you think he feels?”). The use of questions that share elements similar to cognitively challenging ones has been linked to positive outcomes among children who are typically developing. For example, a relationship has been shown between openended questions and longer responses from preschoolaged children (De Rivera et al., 2005). Additionally, adults in classroom settings have used inferential questions as a way to facilitate more advanced, abstract language skills in
Autism book-reading contexts with children who have language impairment (Van Kleeck et al., 2006) and who are typically developing (Wasik and Bond, 2001). These skills are presumably important for later literacy growth and achievement in the classroom. For these reasons, questions like these are commonly recommended in a variety of language and literacy interventions (e.g. Ruston and Schwanenflugel, 2010; Whitehurst and Lonigan, 1998). Few studies have specifically examined the cognitive challenge of questions asked in preschool classrooms. One recent study of teachers in classrooms serving at-risk children found that questions designed to manage behavior (e.g. “Can you give me that?”) or conversation (e.g. “What did you say?”) made up the near majority of the questions asked across contexts (45%; Massey et al., 2008). Questions with lower cognitive complexity were 23 percent of all questions asked, and questions with higher cognitive complexity were 33 percent of all questions asked. Of note is evidence indicating that teachers in inclusive classrooms ask children with and without disabilities a preponderance of questions that are intended to manage behavior and have less cognitive complexity as opposed to questions of higher cognitive complexity (Hestenes et al., 2004). Investigations of the questions addressed to preschoolers with ASD in preschool classrooms appear to be lacking. One exception is Burgess, Audet, and Harjusola-Webb (2013) who investigated the quantity and quality of the language directed at preschool children with ASD. During periods of high verbal interaction, approximately 27 percent of all utterances from classroom adults were yes/no questions and approximately 26 percent were open-ended questions. While these findings are important in that they describe the language richness of these preschool classrooms, this study does not provide specifics about the questions asked, particularly regarding their level of cognitive challenge.
Factors that may impact the questions directed at children with ASD Within-child factors such as the severity of ASD symptoms, language, and cognitive impairments may affect the types of questions asked to children with ASD. Warren et al. (2010) examined the natural language environment of the home for young children with ASD in comparison with children who are typically developing. The results indicated that increased language ability and decreased severity of autism, as reported by caregivers, were associated with the number of words (i.e. adult language) children experienced. In other words, children with better language skills and fewer symptoms of ASD received more language input from adults. Similarly, in the preschool classroom, there is evidence suggesting within-child factors affect language input. For example, researchers report that young children
3
Sanders et al. Table 1. Child assessment descriptives.
PLS-4 total (raw score) Mullen-VR (raw score) CARS (total score) Age (in months)
N
Minimum
Maximum
M
SD
41 42 42 42
19 22 19.5 37
129 50 42.5 63
84.22 39.43 28.80 50.07
26.19 8.59 5.42 7.66
SD: standard deviation; PLS-4: Preschool Language Scale, Fourth Edition; CARS: Childhood Autism Rating Scale; VR: visual reception.
with ASD experience fewer words from classroom adults if they have lower cognitive (Dykstra et al., 2013; Irvin et al., 2013) and language abilities (Dykstra et al., 2013). Taken together, these studies suggest a link between adult language, which encompasses questions asked, and certain child characteristics. Adult-to-child ratio is also a salient factor affecting the types of questions directed at children with ASD in classroom settings. For example, in inclusive preschool classrooms higher teacher-to-child ratios (e.g. more teachers per children in the classroom) are linked to higher quality teacher–child interactions, as evidenced by teacher practices such as using an appropriate tone of voice and responding to children in a positive manner (Hestenes et al., 2008). Specific to ASD, some authors have found in self-contained preschool classrooms that a lower adultto-child with ASD ratio results in less language being directed at children with this disorder (Irvin et al., 2013). As classroom adult-to-child ratio appears to be related to the type and quantity of the language children with disabilities experience, it is important to determine whether this relationship extends to the types of questions classroom adults ask in inclusive settings. To our knowledge, there is an absence of studies that employ fine-grained methods to examine the type of questions directed at children with ASD in inclusive preschool classrooms. The specific research questions in this study were as follows: (1) what types and quantity of questions do children with ASD receive from classroom adults in the preschool classroom, and (2) is there any association between specific child characteristics (i.e. autism severity, language, and cognitive ability) and classroom adultto-child ratio and questions classroom adults direct at preschoolers with ASD?
Methods Participants Children. In all, 42 children who were part of a larger project evaluating the efficacy of preschool programs serving young children with ASD were included in this study. All participating children were enrolled in inclusive classrooms. The children were between the ages of 3–5 years (M = 50.12 months, standard deviation (SD) = 7.64) at the
time of study participation. Videos of children with ASD within center-time occurred within the first 3 months of the school year on a single day. The children had varying levels of ASD severity, as well as verbal and cognitive abilities (see Table 1). All measures were administered by trained staff who possessed or were in the process of obtaining a master’s or doctoral degree. All children in the study had a prior educational or community diagnosis of either ASD or developmental delay and met diagnostic criteria for ASD on the Autism Diagnostic Observation Schedule–Generic (ADOS-G; Lord et al., 2000). In addition, all children with ASD included in this study were verbal, and this was determined primarily based on the ADOS module they received. The ADOS is divided into four modules, and assessors determine the most appropriate module based on a child’s language abilities (e.g. children who receive Module 2 must have phrased speech). More children in this study received an ADOS Module 2 (n = 26; total score: M = 12, SD = 3.06) than a Module 1 (n = 8; total score: M = 19, SD = 2.73) or 3 (n = 8; total score: M = 15.63, SD = 4.14). However, a child who received Module 1 could be nonverbal; therefore, an additional criterion was established. Specifically, children administered Module 1 must have received a score of “0,” “1,” or “2” on item A1 Overall Level of Non-Echoed Language, indicating the child had at least five functional words. For this study, research-trained assessors administered 75 percent of the ADOS assessments; someone who was at least clinically trained and had established reliability with the research-trained assessor administered the remaining ADOS assessments. Classrooms. Children with ASD from a total of 29 inclusive preschool classrooms participated in this study, with an average of two children per classroom. The inclusive classrooms comprised two classroom types, either Learning Experiences: Alternative Program for Preschoolers and Parents (LEAP; Strain and Hoyson, 2000) or Businessas-usual (BAU; i.e. eclectic) programs. Dr Phil Strain established the LEAP model in 1981, and the prevailing theoretical/conceptual foundation for the model is applied behavior analysis. In LEAP, children who are typically developing learn peer-mediated methods aimed at improving the social interaction skills of children with ASD. The term BAU refers to classrooms in which teachers do not
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Table 2. Teacher and children demographics. Frequency Teacher demographics Race Ethnicity Gender Degree Children demographics Race Ethnicity Gender
White Black Non-Hispanic Hispanic Female Male Associates Bachelors Masters Above Masters
28 1 23 6 28 1 2 9 17 1
Asian Black White Non-Hispanic Hispanic Female Male
1 4 37 27 15 4 38
% 96.6 3.4 79.3 20.7 96.6 3.4 6.9 31.0 58.6 3.4 2.4 9.5 88.1 64.3 35.7 9.5 90.5
adhere to one theoretical/conceptual framework to guide their instructional practices (e.g. applied behavior analysis). Rather, teachers in these classrooms use a variety of intervention approaches from multiple instructional models. This eclectic model is the one typically used with children with ASD in public schools (Stahmer and Mandell, 2007), and the BAU classrooms included in this study conformed to this conceptualization (see Boyd et al., 2014, for an additional description of enrolled BAU classrooms). LEAP and BAU classrooms included in the study had to be operating in a public preschool. LEAP classrooms operate on a half-day schedule; thus, the duration of classroom instructional time for children was 2–3 h per day (M = 2.05 h). The instructional time for BAU classrooms ranged from 2 to 5 h (M = 2.78 h). The average number of children who are typically developing to children with ASD in LEAP (3:1) and BAU (4:1) classrooms was similar. It was not the purpose of this study to examine group differences; therefore, data were aggregated across both classroom types. Teachers. All lead teachers in these classrooms (n = 29) were certified to teach in their respective state and taught in a LEAP or BAU classroom for at least 2 years prior to study enrollment. Across both classroom types, lead teachers had an average of 10.78 years of experience in the classroom and 5.28 years of experience implementing their respective classroom treatment. Each LEAP and BAU classroom had one to two teachers as well as one to two teaching assistants. Teacher and child demographic information can be found in Table 2. Demographic data are presented on the lead teacher; however, it is important to clarify that we coded talk from any adult in the classroom
that was directed toward the focal children. We thought this was more reflective of the real-world experiences of children with ASD in classrooms. That is, they interact with a number of adults throughout the school day and not just the lead teacher. Unfortunately, demographic data were not systematically collected for classroom assistants or related service providers as part of the larger study.
Measures The Mullen Scales of Early Learning (Mullen, 1995) is a standardized, comprehensive assessment that measures gross motor, fine motor, visual reception (VR), and language abilities of children from birth through 68 months. The calculated VR subscale raw score was used in this study as a proxy for the child’s nonverbal cognitive abilities. For the current sample, the VR subscale was highly correlated with children’s total standard score (r = 0.85, p = 0.000) on the Mullen. Preschool Language Scale, Fourth Edition (PLS-4; Zimmerman et al., 2002) is a standardized measure used to assess language development, both receptive and expressive language ability, for children from birth through 6 years, 11 months. For the Mullen and PLS-4, raw scores were used because standard scores had floor effects and age equivalents scores were not available for all subscale or composite scores. Childhood Autism Rating Scale (CARS; Schopler et al., 1988) is a 15-item rating scale that is intended to differentiate children with ASD from peers who are typically developing and children with developmental delays. For each of the 15 items (e.g. relationship to people, listening response, verbal communication), an informant assigns a rating of 1 (normal for child’s chronological age), 2 (mildly abnormal for child’s chronological age), 3 (moderately abnormal for child’s chronological age), or 4 (severely abnormal for child’s chronological age). Thus, the total CARS score may range from 15 to 60. A total score greater than or equal to 30 is interpreted to suggest the child shows at least a moderate degree of ASD symptom severity. The instrument has more than acceptable reliability (i.e. an alpha of 0.94). Total scores were used in data analysis for this study. Research staff administered this assessment and had to meet the following reliability criteria: be within ±0.5 on 12 of 15 items (equal to an 80% reliability criterion) and within ±3 on the total score. Prior to the collection of any data, this study was approved by the Institutional Review Board at the University of North Carolina at Chapel Hill.
Procedures Children and classroom adults were videotaped during 30 min of center-time. In preschool classrooms, centertime can be conceptualized as the free time or space during which children are provided an opportunity to engage with
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Sanders et al. Table 3. Percentage of inter-observer agreement versus disagreement for individual codes. Coder 1
Coder 2
M
Maximum
Minimum
M
Maximum
Minimum
Management Less cognitively challenging Cognitively challenging More cognitively challenging
89% 92% 93% 93%
93% 96% 97% 99%
81% 81% 83% 82%
91% 91% 95% 94%
96% 94% 98% 96%
84% 87% 92% 92%
adults and/or peers in designated areas containing academic and/or play materials. Center-time was selected because it was one of the few classroom activities that occurred consistently across classroom types (i.e. LEAP and BAU classrooms). The types of center activities available to children in this study included large blocks/manipulatives, pre-academic areas such as reading storybooks and computer time, and sensory motor activities such as art and large motor activities. For this study, no instructions were provided to adults other than to continue with their normal classroom routines and activities. The PROCODER software program (Tapp and Walden, 2000) was used to code each 10-s interval of the approximately 30-min video samples for adult questions. This typically resulted in 179 intervals (range: 129–192, M = 176, SD = 13.68) per observation. Each 10-s interval was coded for the presence or absence of each question type. Given that only four types of questions were being coded (see section “Coding scheme”), it was not necessary for coders to view videos multiple times in order to make coding decisions. Coding scheme. The coding scheme comprised categories and codes adapted from Massey et al.’s (2008) teacher questions coding scheme. Partial interval coding was used to code the questions that were either directed solely at the focal child or to a group that included the focal child (e.g. during circle time). The question classification for this study included the following categories: (1) management, (2) less cognitively challenging, (3) cognitively challenging, and (4) more cognitively challenging. More cognitively challenging questions were subsequently combined with the cognitively challenging category for data analysis purposes because they occurred infrequently and they were related to each other conceptually (see Appendix 1 for categories and examples of adult questions). Inter-rater reliability. All videos were independently coded by two primary coders, one of whom held a PhD in speechlanguage pathology and the other was pursuing a PhD in speech-language pathology. Across the two coders, 20 percent of their videos were subsequently coded by a secondary rater (the second author of this study) for reliability purposes. Raters first had to reach at least an average of 80 percent agreement per code as well as overall
agreement on the coding scheme across three consecutive non-study training videos. Coders had to maintain at least a mean 80 percent reliability criterion for each code as well as overall agreement throughout coding project videos. See Table 3 for complete reliability results.
Data analysis Research Question 1. What types and amounts of questions do children with ASD receive from adults in the preschool classroom? Descriptive statistics were used to identify the types and amounts of questions children with ASD experience in the classroom. In addition, chi-square analysis was employed to determine whether there were differences between types of questions asked. Research Question 2. How do child characteristics (i.e. autism severity, language, and cognitive ability) and adult-to-child ratio affect the questions adults direct at preschoolers with ASD? To answer this question, we first examined the intraclass correlations (ICCs) to assess whether a multilevel model was necessary (Snijders and Bosker, 2012). The multilevel structure was such that each child had multiple 10-s observations and each classroom contained several children. We opted to use a three-level model (see Table 4) to preserve the original structure of the data, ensure ample power to detect effects, and because there was a substantial amount of variance explained at Level 2 (i.e. children) and Level 3 (i.e. the classroom). Using PROC GLIMMIX (SAS Institute Inc, 2010), we estimated a mixed binomial logit model for each question type, predicting the odds of children receiving a particular question based on their raw PLS-4 total score, raw Mullen-VR score, CARS total score, and the ratio of adults to children. Classroom type (i.e. LEAP or BAU) was included as a covariate because we found that children in BAU classrooms were more likely to be asked cognitively challenging questions than those in LEAP classrooms (χ2(1) = 14.579; p = 0.0001). Classroom type did not affect the likelihood of management (χ2(1) = 1.802; p = 0.1794)
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Table 4. Intra-class correlations.
Management Less cognitively challenging Cognitively challenging
Level 1 (observation)
Level 2 (child)
Level 3 (classroom)
0.0365 0.0388 0.0405
0.1910 0.3712 0.4693
0.7724 0.5900 0.4902
Table 5. Questions by child characteristics, adult-child ratio, and classroom type. Management β (SE)
Less cognitively challenging p
Odds β (SE) ratios
p
Cognitively challenging Odds β (SE) ratios
p
Odds ratios
−2.202 (0.458)
