Turn-taking and communication modes of students and staff in group activities at non-inclusive schools for students with intellectual disability

Abstract

Most students with intellectual and communicative disability who rely on augmentative and alternative communication (AAC) attend non-inclusive school settings. Little is known about turn-taking and the use of various communication modes in groups of students and staff in this context. Previous studies on single students with intellectual disability in various school settings have found that staff tend to dominate interactions and augmented communication modes are used more during structured than unstructured activities. The present study explored turn-taking contributions and communication modes in whole groups of students and staff in non-inclusive school settings in Sweden. Video observations of 33 students and 30 school staff were conducted in seven classrooms during one structured activity (circle time) and one unstructured activity (leisure time). Turn-taking contributions and communication modes were examined when comparing students and staff and when comparing the two activities. Findings revealed that staff dominated the interactions and augmented communication modes were used less during leisure time than circle time. Notably, aided augmented communication modes, particularly speech-output technologies, were used sparsely. Findings of this study highlight the importance of supporting staff members in applying partner strategies and incorporating augmented input, especially aided augmented input, across various group activities at school.

Keywords:

• Augmentative and alternative communication
• communication modes
• intellectual disability
• non-inclusive schools
• turn-taking contributions

Students with intellectual disability typically experience various communication challenges, ranging from delayed speech and language development to being dependent on the interpretation of their communication by others (Patel et al., 2020). These students’ communication abilities vary across activities, physical environments, and communicative partners. In addition, they tend to experience generalization difficulties. Therefore, it is important that the teaching of communication skills is incorporated into all activities, and with multiple partners, throughout the school day (Bouck & Maher, 2019).

Teachers and support staff can offer appropriate support by providing access to augmentative and alternative communication (AAC) and using partner strategies such as augmented input and responsive strategies. Such partner strategies facilitate all levels of communication skills and are thus beneficial for most students with intellectual disability (Biggs et al., 2018). When applying augmented input strategies, the school staff use AAC alongside natural speech in naturalistic interactions to demonstrate and encourage AAC use and facilitate receptive and expressive language development. Augmented input can involve the use of multiple modes of communication, which can be categorized as either unaided (i.e., communication expressed through a modality other than speech that does not rely on resources that are external to the individual, such as a communication board. Unaided AAC includes manual signs, gestures, and facial expressions) or aided (i.e., communication expressed through resources that are external to the person with complex communication needs, such as a communication board, cards, pictures that are exchanged, or a speech-output technology); Dada et al., 2020). Augmented input also aims to address the input-output asymmetry that often emerges when language input differs from the output mode (Smith & Grove, 2003).

Research has shown that staff members tend to dominate interactions with students who have intellectual and communicative disability by occupying many turns and mainly providing instructions or requests that do not necessitate active student responses (Andzik et al., 2016; Bunning et al., 2013). School staff who use responsive strategies are intentionally attentive and wait expectantly for the student to respond; they interpret and expand the student’s nonverbal and verbal expressions and communicate according to the attentional focus of the student (Broberg et al., 2012).

In recent decades, there has been a growing emphasis on inclusive settings for students with intellectual disability in education policies worldwide, resulting in an increased placement of students in mainstream classrooms. Nevertheless, relatively many students with intellectual disability are still educated in non-inclusive school settings worldwide (Buchner et al., 2021; Hanreddy & Östlund, 2020). In Sweden, students with intellectual disability usually attend non-inclusive school settings in self-contained classrooms or special schools. They follow a separate curriculum called the Compulsory School for Students with Intellectual Disability (CSSID) (Wilder & Lillvist, 2021). Only students with a diagnosed intellectual disability are eligible for CSSID. The CSSID curriculum is differentiated toward students with mild intellectual disability, where the syllabus focuses on academic subjects, while for students with more severe intellectual disability, the syllabus focuses on subjects of daily living. One of the daily living subjects is communication. When compared to mainstream schools, CSSID schools have more resources for providing adapted learning environments, and the staff/student ratio is high (Wilder & Klang, 2017). The classes in CSSID schools have small groups of students (approximately five to seven) and the school day involves both structured and unstructured activities (e.g., circle time and leisure time activities, as well as lessons, meal times, breaks, and transitions).

Circle time activity is a routine-based structured activity in which students and staff gather to focus on attendance, the calendar, the daily schedule, and the weather and season; and often sing together. The purpose of circle time is to provide opportunities to develop socialization skills, communication skills, and academic skills while fostering a sense of a classroom community. Circle time has been described as knowledge-disseminating and teacher-dominated because it follows a given structure (Östlund, 2015; Thunberg et al., 2011).

Leisure time activities in CSSID schools are, overall, unstructured (e.g., students themselves select play activities from those presented by staff members). Peer interactions are also encouraged. Student skills, interests, and staff approach influence communication during leisure time. Staff members can treat students as active and playful and worth encouraging to communicate, or mainly as recipients of care-oriented activities (Östlund, 2015).

One of the most common diagnoses associated with highly unintelligible speech is intellectual disability (Binger et al., 2021). Students who do not use natural speech are more likely to be placed in non-inclusive school settings, whether or not they have access to well-functioning AAC systems (Erickson & Geist, 2016). Given that many students in non-inclusive settings have communication disability and rely on AAC, it is crucial to study their everyday interaction and communication modes in their naturally occurring environment in school.

Students with intellectual and communicative disability have been found to not always receive sufficient access to AAC or staff with appropriate AAC skills and knowledge in either inclusive or non-inclusive school settings (Andzik et al., 2016, 2017; Tönsing & Dada, 2016). Staff members often report a lack of time to plan and develop communication material, as well as to sufficient AAC education. In addition, they lack confidence in using augmented input, especially aided augmented input (Andzik et al., 2017; Tönsing & Dada, 2016). Moreover, it has been found that augmented communication modes are used less during unstructured activities, such as leisure time and meal times, than during structured activities, for example, pre-planned lessons and circle time (Andzik et al., 2016; Grove & McDougall, 1991).

Iacono et al. (2022) recently published a scoping review of AAC research conducted in non-inclusive school settings and found a relatively large body of research that incorporated AAC in this setting. The scoping review encompassed articles published worldwide from 2000 to 2020 that focused on AAC in school-aged students. A total of 141 articles were identified; however, they did not specifically focus on non-inclusive school settings for students with intellectual disability but rather looked at a broader group of students, including those without intellectual disability. In addition, the review identified only a few studies that explored naturalistic interaction under typical classroom conditions (i.e., most of the studies described interventions under ideal conditions).

Although several studies have explored aspects of naturalistic interaction in classrooms for students with intellectual disability, there is a paucity of research into multi-participant interaction of classroom activities that involve multiple students and staff. Andzik et al. (2016), Bunning et al. (2013), and Popich and Alant (1997) have all studied turn-taking in interactions involving students and staff in classrooms for students with intellectual disability and found that teachers dominated the interactions by taking many turns, asking many questions, and making frequent requests. This behavior was even more striking when the students did not use natural speech (Popich & Alant, 1997); however, Andzik et al. looked at students in mixed school settings, Bunning et al. focused on student-teacher dyads, and Popich and Alant focused only on teachers’ turn-taking.

Bruce and Vargas (2007) studied intentional communication acts of students with severe intellectual disability in self-contained classrooms and found students communicate more in preferred activities. Romski et al. (1989) found in their study that students in non-inclusive settings communicated more with adult partners at home than with school partners. The researchers proposed that this disparity could be attributed to the structured nature of school interactions, the focus on educational goals, and the teacher’s divided attention among all the students in the class. However, both the Bruce and Vargas study and the Romski et al. study focused on selected students in the classroom and did not examine school staff interactions.

Another way to explore everyday interaction, with more emphasis on AAC, is to examine participants’ use of various communication modes. Andzik et al. (2016) and Chung et al. (2012) considered students’ use of multiple communication modes in various activities throughout the day and found infrequent student use of AAC systems and that devices were not always in the students’ proximity. Instead, students primarily relied on facial expressions, gestures, and vocalizations, especially during unstructured activities. Then again, these studies focused on mixed or inclusive school settings and did not incorporate multi-participant interaction.

Carter (2003) studied the communicative spontaneity of students with intellectual disability in non-inclusive school settings. Non-symbolic communication modes (e.g., touch, gesture, pointing) and natural speech were the most spontaneous communication modes, while graphic and tangible symbols were used less spontaneously. Grove and McDougall (1991) explored students’ use of manual signs in two activities and found manual signs to be more used during teacher-directed activities than during free play activities.

Altogether, these findings bring some insights into the use of turn-taking and communication modes in everyday school settings for students with intellectual disability. Still, there is a paucity of research focusing on turn-taking contributions and communication modes in whole groups of students and staff in non-inclusive school settings. In particular, there has not been a focus on exploring these factors across everyday activities of ranging structure. Therefore, the present study aimed to explore turn-taking contributions and communication modes in whole groups of students and staff in typical group activities in non-inclusive school settings. The research questions were: How were turn-taking contributions and communication modes used in two everyday group activities at CSSID schools when (a) comparing students and staff and (b) when comparing two activities of ranging structure?

Method

This study was carried out within a larger project aiming to explore a communication partner intervention directed toward school staff at Compulsory Schools for Students with Intellectual Disability (CSSID). The intervention is called Communication Partner Intervention in an Augmented Learning Environment (ComPal). In the present study, data collected before the staff took part in the intervention was used and is the first study published within the project.

Participants

Principals of all CSSID schools (N = 25) listed on the webpage of one of the largest municipalities in Sweden were contacted by e-mail and telephone. Written information about the study was also disseminated at a communication conference in the same area. An additional school from a neighboring municipality expressed interest in participating in the study via their speech-language pathologist. The criteria for inclusion were based on class composition and class settings and were as follows: (a) the majority of the students in the class were described by the principals as having a communicative disability, (b) the circle time and leisure time activity were part of their daily routines, (c) it was possible to video record in the classroom, (d) at least one student in the class was between 6-to 9-years old (based on funding prerequisites), and (e) the school provided approval to take part in the partner communication intervention explored in the overall project.

Nine schools were eligible to participate in the study. Informed consent was obtained from staff members and the students’ caregivers, who also received pictorial support to inform and ask for assent from the students. Two schools were excluded from the study as a limited number of participants consented to participate in the study, resulting in a total of seven participating schools.

In all, 63 participants, comprised of students (n = 33) and school staff (n = 30) from seven schools (one class from each school), consented to participate in the study. Each class consisted of 3-7 students and 3-5 school staff. Student characteristics are shown in Tables 1 and 2, and staff characteristics in Table 3.

Table 1. Student Characteristics Provided by Caregivers

Characteristics	Total (n = 33)
Age
Mean (years;months)	8;8
Range	6;0–12;10
SD	1.78
Sex (n)
Female	12
Male	20
Not reported	1
Curriculum^a
Students with mild to moderate intellectual disability	5
Students with severe intellectual disability	25
Not reported	3
Additional diagnosis
Autism spectrum disorder	18
Chromosomal conditions	10
Epilepsy	3
Cerebral Palsy	1
Other diagnosis^b	7
Language at home
Exclusively Swedish	16
Exclusively other languages	9
Swedish and another language	7
Not reported	2

Note: ^aEnrollment based on a social, pedagogical, medical, and psychological investigation. ^bDysarthria, ataxia, dyspraxia, ADHD, hydrocephalus, or cleft lip and palate.

Table 2. Student Communication Characteristics (n = 33) Reported by Staff Members Using the CSI-CY Inventory

Subsections and items from the CSI-CY inventory	Number of Don’t know ratings	Number of Not applicable ratings	Scale grading 1–6^a
			Total (n)	Mdn	Range	SD
Receptive language
Comprehending the meaning of single spoken words	1	0	32	5	2–5	.90
Comprehending the meaning of 2–3 spoken word phrases	1	0	32	5	2–5	1.15
Comprehending the meaning of spoken sentences	1	0	32	4	1–5	1.29
Comprehending the meaning of a spoken narrative	5	0	28	3	1–5	1.56
Expressive language
Using single spoken words to communicate (includes word approximations)	0	0	33	4	1–5	1.70
Combining spoken words into 2–3 word phrases	0	0	33	2	1–5	1.71
Using sentences with appropriate syntax in spoken communication	0	0	33	1	1–5	1.45
Combining sentences to convey a cohesive topic in spoken communication	0	0	33	1	1–5	1.40
AAC: Receptive strategies
Comprehending 3-dimensional objects/representations used to communicate	1	12	20	5	1–5	1.43
Comprehending the meaning of drawings and photographs used to communicate	1	0	32	4	1–5	1.37
Comprehending the meaning of manual sign language	5	5	23	4	1–5	1.49
Comprehending the meaning of AAC signs/symbols	3	0	30	5	1–5	1.36
AAC: Expressive strategies
Using 3-dimensional objects/representations to communicate	0	17	16	7	1–5	1.83
Using drawings, pictures, or photographs to communicate	1	9	23	5	1–5	1.90
Using manual sign language to communicate	0	7	26	2	1–5	1.62
Using single AAC signs/symbols to communicate	0	5	28	3	1–5	1.71

Note: ^a1: (Complete limitation), 2: (Severe limitation), 3: (Moderate limitation), 4: (Mild limitation), 5: (No limitation), 6: (Skills above average peer).

Table 3. Self-reported Staff Characteristics

Characteristics	Teachers (n = 11)	Support staff (n = 17)	Personal assistants^a (n = 2)	Total (n = 30)
Age
Mean (years;months)	44;0	37;2	27;7	39;0
SD	11.49	11.67	0.58	12.03
Sex
Female	100% (11)	88% (15)	50% (1)	90% (27)
Male	0% (0)	12% (2)	50% (1)	10% (3)
Education
University	91% (10)	59% (10)	50% (1)	70% (21)
Post-secondary	0% (0)	12% (2)	0% (0)	7% (2)
Secondary	0% (0)	18% (3)	50% (1)	13% (4)
Not reported	9% (1)	12% (2)	0% (0)	10% (3)
Experience in working with students with intellectual disability
Mean (years;months)	3;3	3;3	0;3	3;2
SD	2.93	4.20	0.21	3.71
AAC: Education
Manual signs	55% (6)	24% (4)	50% (1)	37% (11)
Picture-based AAC	9% (1)	12% (2)	0% (0)	13% (4)
Specific AAC software/app/device	18% (2)	6% (1)	0% (0)	10% (3)
General AAC education	45% (5)	18% (3)	0% (0)	27% (8)
None	18% (2)	41% (7)	50% (1)	33% (10)
AAC: Practical experience
Manual signs	55% (6)	41% (7)	50% (1)	47% (14)
Picture-based AAC	82% (9)	59% (10)	50% (1)	67% (20)
AAC devices used in the classroom	36% (4)	0% (0)	0% (0)	13% (4)
Student-specific AAC systems	18% (2)	12% (2)	0% (0)	13% (4)
None	9% (1)	18% (3)	50% (1)	17% (5)

Note: ^aEmployed by assistance provider, not by the school.

All students had intellectual disability as determined by their enrollment in CSSID schools, and the majority (n = 26) had at least one additional diagnosis. Two students were described as having personalized AAC systems provided by speech-language pathologists at the habilitation center, but these were reported as not being currently used in school.

Staff members were aged 23–61 years and had one month to 17 years of experience working with students with intellectual disability in school settings.

Setting

Two everyday group activities were video recorded in each class: one structured activity (circle time) and one unstructured activity (leisure time). Both activities took place in the classroom, and whole groups of students and staff members participated. Both activities in all seven schools had a high staff/student ratio. During the circle time activity, there were two to six staff and three -seven students (on average, 0.57 more students than staff). During the leisure time activity, there were three – six staff and three–seven students (on average, 0.14 more students than staff).

If a student or staff member who usually took part in the activity had declined to participate in the study, that individual was relocated to another room during the data collection. Participating staff were instructed to be attentive to whether any student expressed discomfort during the video observations, which would immediately be terminated; however, this did not occur.

Materials and measures

Background information on students and staff members was collected through study-specific forms. Information on the students’ communication characteristics was gathered using selected parts of the Communication Supports Inventory – Students & Youth (CSI-CY) (Rowland et al., 2012). In psychometric testing, Rowland et al. found the inter-observer agreement to range from 64% to 87% in the subsections from which the selected items derive and 64% to 94% in the inventory as a whole.

Materials for collecting video observational data included seven iPads¹ of various models mounted on suction cup brackets. A computer running Windows 10 with the software Reflector² (Version 3.2.0) was used to duplicate the screens of all iPads on the computer, enabling the researcher to be in another room during the observations. Before the data analysis, all video angles of each activity were synchronized and trimmed to the activity’s start and end using Camtasia³ (version 2020.0.16).

The video observations were analyzed with the video observation software The Observer XT⁴ (version 14.2.1127), using a coding scheme developed for this study, comprising turn-taking contributions and communication modes (see Table 4). Statistical analyses were performed using SPSS Statistics (Version 26).

Table 4. Coding Scheme

Code	Description
Turn-taking contributions
Expressive contributions (Communication mode code required)
Initiation	Introducing a new topic or directing to a new partner (either student or staff) using a mode defined by communication mode codes.
Response	Reacting to someone else’s (either student or staff) intentional or non-intentional move using a mode defined by communication mode codes.
Non-expressive contributions (Communication mode codes not applicable)
Attentive	Orienting toward or looking at the communication partner/object in focus of an interaction/activity.
Distracted	Not oriented toward or looking at the communication partner/object in focus of an interaction/activity. Include all staff-to-staff interactions.
Other contributions (Communication mode codes not applicable)
Alone	Physically located at a distance from another person and not oriented toward or looking at the communication partner/object in focus of the activity.
Not visible	Not seen in the video.
Communication modes (Coded within expressive contribution durations)
Unaided modes
Speech	Verbal communication interpreted as words.
Vocalization (students only)	Verbal communication not interpreted as words.
Physical manipulation	Using own body to manipulate the partner or objects used in activity.
Pointing	Pointing at a person or object, using a finger or hand/arm gesture. Does not include pointing to highlight/activate aided modes.
Singing	Voice or physical movements indicating involvement in a song, a chant, or music.
Challenging behavior (students only)	Screaming, hitting, throwing things, biting.
Unaided augmented modes
Manual signs/iconic gestures	Using movements of the hands to express semantic meaning. Includes both sign language and iconic gestures, i.e., gestures that can be interpreted as a word.
Aided augmented modes
Picture symbols	Graphic representations, highlighted through pointing, showing or handing over to the partner.
Speech-output technologies	Using a device that provide speech output.
Other modes	Modes not included in above codes, clarified with notes.

Research design

A cross-sectional exploratory design was used to study interaction in whole groups of students with intellectual and communicative disability and their school staff. Video observations were carried out during circle time activity and leisure time activities. Comparisons were made between students and staff and between the two activities regarding turn-taking contributions and communication modes. Cross-sectional designs enable different groups to be compared and to present patterns on a group level (Cohen et al., 2018) and were thus considered appropriate for addressing the objective of the present study. Ethical approval was obtained from the Swedish Ethical Review Authority (Reference number 2019-03994).

Researchers

All four authors were involved in all phases of the study. The first author collected and analyzed all study data. Regular meetings were held between the authors to collaboratively discuss the coding scheme’s content and structure, including the analysis. During the development phase of the coding scheme, the first author, a doctoral student, tested the coding scheme on videos of interactions that were unrelated to the study. An independent doctoral student (not an author) conducted inter-coder reliability assessments.

Procedures

Data collection

Data were gathered through video observations, with each activity being observed once at each school. The video equipment was positioned to enable participants to move freely within the classroom while ensuring their capture on video. The researcher monitored the screens from a separate room during the observations to avoid disrupting the natural interactions that occurred in the classroom.

The duration of the recordings varied between 14–30 min (M = 19 min 54 s, SD = 5 min 42 s) during the circle time activity and between 21–43 min (M = 31 min 35 s, SD = 7 min 53 s) during the leisure time activity, after synchronizing and trimming the videos into the onset and end of the activities.

Data analysis

The selection of analysis units from the video recordings was based on the aim of the study, to explore interactions in whole groups of students and staff in the context of everyday school activities. Since there were many participants, a high staff/student ratio, and multiple ongoing interactions in the activities, all participants had the option to engage or disengage in interaction with each other. Thus, simultaneous observations of multiple participants within the same video sections were used in the analysis.

The selection criteria for video sections differed between the two activities. The circle time activity involved all participants throughout the whole activity, enabling the same video sections to be analyzed for all participants. Leisure time instead entailed shifting the involvement of participants at varying time points. For example, students and staff occasionally left the classroom to visit the restroom or take a break. This made it necessary for individual selections of video sections to be analyzed. In addition, as the circle time activity followed a pre-planned and given structure that included waiting for given turns, it was considered necessary to analyze a longer time than the leisure time activity to achieve individual data saturation. Consequently, a total of six min of the circle time activity were analyzed for all participants, split into three two-min intervals, at the beginning, the middle, and the end of the activity, to cover potential fluctuations in interaction over time. Video sections in the leisure time activity were selected in one four-min interval for each participant based on involvement in activities with others. For this, a priority order was followed for selection: The participant was either (a) engaged in an activity involving one or multiple other persons; (b) physically close to another person but not engaged in the same activity; or (c) not involved in, or close to another person, but present in the video. When several video sections met the highest priority, the section in which the most augmented communication modes were used was selected. In summary, each participant was coded individually, often within the same video sections as other participants, with lengths of 6 min during circle time and 4 min during leisure time activity. A total of 336 individual observation min were generated during circle time activity (total number of participants was 56: 30 students and 26 staff) and a total of 244 min during leisure time (total number of participants was 61: 30 students and 31 staff). Each participant and school was assigned a pseudonym before analysis.

The coding scheme comprised turn-taking contributions and communication modes, see Table 4. The selection of codes was informed by previous studies conducted by Andzik et al. (2016), Bunning et al. (2013), Chung et al. (2012), Pennington et al. (2009), Thunberg et al. (2011), and Wilder (2008). A turn-taking contribution was defined as expressive and non-expressive contributions made by participants in ongoing classroom interactions and comprised the codes initiation, response, attentive, and distracted. Additional two other turn-taking contributions were used when the participants were alone or not visible on the video.

Communication modes were defined as the means by which a participant demonstrated a communication expression. Unaided modes referred to means of communication that did not comprise augmentation by external aids or gestures with semantic meaning. These communication modes were speech, vocalizations, physical manipulation, pointing, singing, and challenging behavior. Unaided augmented modes comprised the code manual signs/iconic gestures and were defined as modes that did not include external aids but were augmented by manual signs or gestures with conventional semantic meaning (e.g., nodding to indicate ‘yes’). Aided augmented modes were defined as means of communication built on external aids and comprised the codes picture symbols and speech-output technologies.

Turn-taking contributions were coded using continuous recording within the selected intervals, with mutually exclusive and collectively exhaustive state behaviors. In other words, one turn-taking contribution had to be activated at all times throughout the selected intervals. The duration of expressive contributions (initiations and responses) served as intervals for coding communication modes. Within these intervals, communication modes were coded using partial interval recording, meaning that the modes used at any point of each initiative and response were coded as present. Multiple communication modes could be coded at present within the same expressive contribution.

Non-parametric statistical tests—the Mann-Whitney U test for comparisons of students and staff and the Wilcoxon signed-rank test for comparisons of the activities—were used because the majority of variables of interest were not normally distributed (the Shapiro-Wilk test for normality was conducted).

One standardized value of each participant in each of the two activities was used in the statistical analysis. In turn-taking contributions, the codings were transformed into an average rate per minute by dividing each participant’s total frequency of each code in each activity by the number of observed min (i.e., either 6 or 4 min, depending on the activity). Durations coded as not visible were excluded from the statistical analysis. In communication modes, the codings were transformed into a percentage of intervals in which the mode was present by dividing each participant’s total frequency of each mode by the total individual frequency of expressive contributions in each activity.

Reliability

Videos collected in a pilot data collection at a CSSID school during circle time activity were used to establish the first author’s intra-coder reliability before proceeding to code study data. The first author coded two min of the pilot data video twice, using all turn-taking contribution codes. Cohen’s Kappa resulted in κ = .91 in frequency (Jansen et al., 2003), indicating almost perfect levels of agreement across the two codings performed by the same coder (Landis & Koch, 1977).

For inter-coder reliability (ICR), a second coder coded 20% of the study data using the turn-taking contribution codes with the same procedure as the first author. Videos included in the study but not used in the ICR analysis were used for training. The ICR analysis resulted in a Cohen’s Kappa of κ = .71 in frequency (Jansen et al., 2003) and κ = .81 in code agreement using a listwise deletion Cohen’s Kappa (De Raadt et al., 2019). Both Kappa values indicate substantial levels of agreement across coders (Landis & Koch, 1977).

Results

Following the aims of the study, the results section is divided into two parts: Turn-taking contributions and communication modes (a) when comparing students and staff and (b) when comparing two activities of ranging structure.

Turn-taking contributions and communication modes: comparing students and staff

Turn-taking contributions of both students and staff are presented using the median, range, and standard deviation in Table 5. Staff used significantly more initiations than students in both activities (circle time, U = 143, z = 4.1, p < .001; leisure time, U = 311.5, z = 2.22, p = .027). Staff also used responses more than students in both activities, but only significantly more during the circle time activity, U = 260, z = 2.1, p = .032. Students, on the other hand, used the non-expressive contributions more than staff, but only during the circle time activity (attentive, U = 210, z = 3.0, p = .003; distracted, U = 30.5, z = 5.9, p < .001).

Table 5. Student and Staff Turn-Taking Contributions in Rate per Minute

Contribution	Circle time						Leisure time
	Students (n = 30)			Staff (n = 26)			Students (n = 31)			Staff (n = 30)
	Mdn	Range	SD	Mdn	Range	SD	Mdn	Range	SD	Mdn	Range	SD
Expressive contributions
Initiation	1.33	0.0–4.3	1.10	2.42^a	0.5–8.7	2.47	3.00^b	0.0–10.5	2.14	4.63^a	0.0–10	2.77
Response	1.83	0.2–6.3	1.45	2.42^a	0.5–5.3	1.41	1.75	0.0–5.0	1.60	2.63	0.0–6.5	1.71
Non-expressive contributions
Attentive	3.67^a	1.5–5.2	0.94	2.92	0.0–4.2	1.23	3.50	1.0–6.0	1.32	3.50	0.5–6.0	1.53
Distracted	2.67^ab	1.2–4.8	1.01	0.17	0.0–2.3	0.72	1.00	0.0–3.0	1.05	1.50^b	0.3–3.5	0.79
Alone	0.0	0.0–0.2	0.03	0.0	0.0–0.0	0.00	0.25^ab	0.0–2.3	0.67	0.0	0.0–2.0	0.38

Note: ^aSignificantly higher rate per minute than the other group in the same activity (p < .05).

^b Significantly higher rate per minute than during the other activity in the same group (p < .05).

Communication modes of both students and staff are presented using median, range, and standard deviation in Table 6. Physical manipulation was the only mode that students used significantly more than the staff, but only during leisure time activity, U = 320, z = 2.3, p = .019. Picture symbols were also used more by students than staff in both activities, but no statistical analysis could be performed due to the overall limited use. Staff used speech, pointing, and manual signs/iconic gestures more frequently than the students in both activities (Circle time; speech, U = 211.5, z = 2.9, p = .003; pointing, U = 232, z = 2.7, p < .008; manual signs/iconic gestures, U = 176.5, z = 3.5, p < .001. Leisure time; speech, U = 121.5, z = 4.9, p < .001; pointing, U = 310, z = 2.1, p = .037; manual signs/iconic gestures, U = 233.5, z = 3.5, p = .001). Students and staff used speech-output technologies to a similar degree across both activities; namely, they did not use them during leisure time and used them sparsely during circle time. Another similarity between students and staff across activities was that when staff used manual signs/iconic gestures more (circle time activity), the students also used manual signs/iconic gestures more.

Table 6. Student and Staff Communication Modes in Percentages of Expressive Contributions

Communication mode	Circle time						Leisure time
	Students (n = 30)			Staff (n = 26)			Students (n = 31)			Staff (n = 30)
	Mdn	Range	SD	Mdn	Range	SD	Mdn	Range	SD	Mdn	Range	SD
Non-augmented modes
Speech	21.8	0–82.8	28.85	54.8^a	4.8–98.6	27.29	18.2	0-100	27.74	79.9^ab	0–100	26.86
Vocalization	14.1	0–73.1	20.12				18.2	0–89.3	21.12
Physical manipulation	30.9	0–100	30.67	38.8	4.8–74.0	16.58	72.7^ab	0–100	31.55	52.9	0–95.5	29.27
Pointing	0	0–19.2	5.12	6.0^a	0–21.4	5.93	0	0–50.0	11.99	8.2^a	0–48.9	12.00
Singing	0^b	0–65.0	14.64	17.7^ab	0–41.2	11.99	0	0–25.8	4.63	0	0–100	19.43
Challenging behavior	0	0–13.3	3.49				0	0–16.7	3.55
Unaided augmented modes
Manual signs/iconic gestures	10.0^b	0–76.9	21.69	40.0^ab	3.6–100	22.87	0	0–30.3	7.65	9.8^a	0–100	21.76
Aided augmented modes
Picture symbols	5.4^b	0–50.0	16.16	5.1^b	0–25.5	8.52	0	0–75.0	16.00	0	0–13.8	3.86
Speech-output technologies	0^b	0–16.7	4.36	0	0–2.1	0.42	0	0	0.00	0	0	0.00
Other modes^c	0	0–3.9	0.93	0	0–3.6	0.74	0	0–3.2	0.76	0	0–5.1	0.94

Note: ^aSignificantly higher percentage than in the other group in the same activity (p < .05).

^b Significantly higher percentage than in the other activity in the same group (p < .05).

^c Slamming hand on the table, lip flutter.

Turn-taking contributions and communication modes: comparing activities

When comparing the two activities, students initiated significantly fewer interactions during the circle time activity, z = 3.91, p < .001, and showed significantly higher rates of distraction than during leisure time. They were also more alone during leisure time, z = 3.70, p < .001, than during circle time. Students consistently demonstrated a high rate of attentive contributions in both activities, while responses were consistently used at a mid-range rate.

In staff comparisons, the contrasts between the two activities were not as pronounced as observed in students. Attentive contributions were consistently used at a high rate across the two activities, responses at a mid-range rate, and alone at a low rate; however, in contrast to the students, the staff were significantly more distracted during the leisure time activity than during the circle time activity, z = 3.2, p = .002. A large proportion of the staff’s distracted behavior occurred when they were engaged in conversations with each other or engaged in planning activities that did not involve the students. No significant differences were found in staff initiations in the two activities, but as the circle time leader accounted for a substantial portion of the initiations, the median of the two activities had a wide range (circle time, 2.42; leisure time, 4.63).

When comparing the communication modes in the two activities, the students used all of the augmented communication modes more during the circle time activity than during the leisure time activity (manual signs/iconic gestures, z = 3.42, p = .001; picture symbols, z = 2.27, p = .023; speech-output technologies, z = 2.20, p = .028). During the leisure time activity, the students used physical manipulation significantly more during the circle time activity, z = 2.68, p = .007. Students’ median percentage of speech, vocalizations, pointing, challenging behavior, and other modes were similar in the two activities, relatively high in speech (circle time, 21.8%; leisure time, 18.2%) and vocalizations (circle time, 14.1%; leisure time, 18.2%), and sparse in pointing, challenging behavior, and other modes (slamming a hand on the table, lip flutter).

Similar to the students, the staff also demonstrated higher rates of augmented communication modes during the circle time activity compared to the leisure time activity, significantly higher in manual signs/iconic gestures, z = 3.94, p < .001, and picture symbols, z = 2.42, p = .016. Statistical analysis could not be performed for speech-output technologies, as the staff did not use this mode during the leisure time activity and to a low percentage in circle time activity. During the leisure time activity, the staff instead used speech more frequently than during the circle time activity, z = 2.73, p = .006. Staff median percentage of physical manipulation, pointing, and other modes were similar in the two activities, relatively high in physical manipulation (circle time, 38.8%; leisure time, 52.9%) and relatively low in pointing (circle time, 6.0%; leisure time, 8.2%) and other modes that were hardly used at all in any of the activities.

Discussion

Overall, the study’s findings revealed several significant differences in turn-taking contributions and communication modes when comparing students and staff as well as when comparing circle time activity and leisure time activity.

Comparisons of students and staff

The first research question aimed to explore student and staff comparisons of turn-taking contributions and communication modes during both activities. Findings revealed an uneven turn-taking distribution of students and staff with frequent staff initiations, and responses during circle time, in concordance with earlier research on turn-taking in school settings (Andzik et al., 2016; Bunning et al., 2013; Popich & Alant, 1997). This finding indicates a need for staff members to adapt their interaction patterns, such as waiting expectantly for the students to respond and communicate according to the attentional focus of the students (Broberg et al., 2012). Packaged partner interventions that include such strategies have shown positive effects on several pragmatic skills in students, including turn-taking (Biggs et al., 2018).

A notable difference was observed between students and staff regarding their use of speech in both activities. This finding was expected as intellectual disability is one of the most common diagnoses associated with highly unintelligible speech (Binger et al., 2021), and students tend to be placed in non-inclusive settings when they lack natural speech (Erickson & Geist, 2016). Additionally, the staff also used pointing and manual signs/iconic gestures more than the students in both activities. The lower student use of pointing could be related to limited motor skills or the presence of autism spectrum disorder. Individuals with autism spectrum disorder have been recognized as having specific difficulties in using pointing gestures to share experiences with other people but not in using pointing to make requests (Baron-Cohen, 1989). In speech and pointing, the student use was similar in the two activities, suggesting that their limited ability to use these modes was relatively stable.

In contrast, the student use of manual signs/iconic gestures correlated with the increased use by staff members. This relationship has been reported in previous studies of manual sign use, in which individuals with intellectual disability were more likely to use manual signs when staff used them (Grove & McDougall, 1991; Rombouts et al., 2019). Students who can successfully use manual signs/iconic gestures are, therefore, less susceptible to the input-output asymmetry described in previous research (Smith & Grove, 2003) when the staff uses manual signs/iconic gestures as augmented input; however, students with limited fine motor skills, memory restrictions, or transitory processing difficulties may not efficiently use or comprehend manual signs/iconic gestures (Beukelman & Light, 2020). For these students, aided augmented input is of great importance. As the findings in the study revealed limited use of aided augmented communication modes by both students and staff, they have clear potential to increase this use. In international studies, school staff working in both inclusive and non-inclusive settings have reported that they have undergone insufficient AAC education and lack confidence in using augmented input, particularly aided augmented input (Chung et al., 2012; Tönsing & Dada, 2016). Staff in the present study reported having low levels of AAC education; a third had not undergone any AAC education and only a few had training in aided augmented communication modes, as presented in Table 3. Thus, insufficient AAC education and low staff confidence may influence the low use of aided augmented communication modes in the present study.

Comparisons of activities

The second research question aimed to explore comparisons of the circle time and leisure time activity regarding turn-taking contributions and communication modes made by students and staff. The findings showed differences in the two activities in student initiations and distracted behavior of both students and staff. Students initiated more during the leisure time than during the circle time activity. This finding was not unexpected, as circle time is a structured and teacher-dominated activity that may not always necessitate expressive contributions from the students (Östlund, 2015; Thunberg et al., 2011). More surprising was the differences in distracted behavior in the two activities; students were more distracted during the circle time activity, and the staff was more distracted during the leisure time activity. This finding could be attributed to the structured nature of circle time, which aligns with staff goals and agendas, while leisure time activity follows a student outline and agenda. Previous studies have suggested that the structured nature of school interactions, the emphasis on educational goals, and teachers’ divided attention contribute to lower rates of student communication in school settings compared to home settings (Romski et al., 1989). It is plausible that these factors have a similar impact on communication rates in school activities of ranging structure, as circle time is more structured, is teacher-led, and has more emphasis on educational goals than leisure time activity. In addition, students with intellectual and communicative disability have been found to communicate more in the context of preferred activities (Bruce & Vargas, 2007).

Staff members may also adopt various approaches to the goals of leisure time activity. Earlier studies in Swedish CSSID schools showed that staff had two approaches to their own roles: either mainly performing care-oriented functions without interacting or viewing activities as opportunities to develop communicative skills (Östlund, 2015). Staff with the first approach might be more prone to being distracted during leisure time activities. One additional factor observed in the present study is that staff members talked to each other more during the leisure time activity (coded as distracted). For example, they spoke about planning and preparations and discussed how to pair students with staff during the following lesson or how to divide students into sub-groups depending on their daily functioning and mood. Some staff members also produced material for upcoming lessons or material for communication while sitting close to the students and interacting with them occasionally. This observation aligns with the existing research highlighting that staff lacks time to plan and organize material and develop content for communication (Andzik et al., 2017; Tönsing & Dada, 2016).

Both students and staff used augmented communication modes more frequently during the circle time activity than during the leisure time activity, consistent with earlier research (Andzik et al., 2016; Chung et al., 2012; Grove & McDougall, 1991). Beukelman and Light (2020) propose that it is easier to become familiar with the vocabulary and have access to aided AAC in activities with similar content daily, such as the pre-planned and reoccurring sub-activities in the circle time activity. This was reflected in the present study, where manual signs, picture symbols, and speech-output technologies were used in songs, schedules, and when going through the calendar, weather, and attendance during circle time. Carter (2003) found that student communicative spontaneity was lower in graphic and tangible symbols than in non-symbolic symbols such as touch. Applied to this study’s findings, it is likely that the lower student use of augmented communication modes during leisure time is associated with higher spontaneity levels. Fear of communication aid damage and not having free use of the hands have also been suggested to decrease the use of augmented communication modes during unstructured activities (Andzik et al., 2016; Grove & McDougall, 1991; Tönsing & Dada, 2016). In the present study, students and staff often had their hands occupied with toys or games, and picture symbols and speech-output technologies were rarely in close proximity and were thus not used much during leisure time activity.

Implications for practice

Staff working in non-inclusive school settings for students with intellectual disability face the task of supporting the various communication needs of multiple students in different activities throughout the day. This cross-sectional study sheds light on students’ and staff’s turn-taking contributions and the use of various communication modes in group interactions during everyday school activities in such settings. Staff who work in this context need to recognize their collective and individual role in turn-taking and their use of communication modes to efficiently adapt their communication style to meet the needs of the students. Previous research has mainly studied single students or staff members, while multi-participant interaction in group activities is part of the reality in typical school days in most settings. As the observed staff tended to dominate the multi-participant interactions, also seen in previous research on single participants, the application of various partner strategies, such as waiting expectantly for the students to respond and communicate according to the attentional focus of the students, would likely reduce the potential for students to adopt passive roles.

Manual signs/iconic gestures was the most used augmented mode in this study, and when the staff increased their use, so did the students. This relationship is in line with earlier research on student manual sign use and is one of the purposes of using augmented input. This study illustrates that staff can incorporate augmented input within naturalistic multi-participant interactions in school. However, the use of augmented input differed significantly across activities in both students and staff and was less used during the unstructured activity. Aided augmented input was overall used to a limited degree, especially speech-output technologies. Students with restricted abilities to use and comprehend unaided modes, for example, speech and manual signs, are thus likely to be most communicatively vulnerable in this context. The struggle to incorporate communication aids in less structured activities with high spontaneity has also been acknowledged in other studies. The focus of everyday practice in the classroom should thus be put on providing AAC access across activities and efficiently incorporating augmented input, particularly aided augmented input, in unstructured and more spontaneous group activities.

Limitations and future directions

Exploring the real-world settings of interactions in group activities in non-inclusive schools is challenging. Not only because of the multiple actors and co-occurring interactions but also because personal relationships, fluctuating mood, and motivation can influence the participants’ behavior and is difficult to quantify and take into account. As communication is a complex behavior, there might be important aspects of interaction not represented in this study’s findings due to the choice to focus on coding turn-taking and communication modes. Other aspects of communication explored in previous studies are, for example, communicative function (as socialization, offers/providing information, requests, confirmation/denial) (Bunning et al., 2013; Pennington et al., 2009; Romski et al., 1989); type, number, and length of topic segments (Thunberg et al., 2011); communication opportunities (Andzik et al., 2016; Wilder, 2008); peer interactions (Chung et al., 2012; Nijs et al., 2016); and degree of engagement (Romski et al., 2005; Thunberg et al., 2011). Future research could study these aspects of interaction in group settings involving multiple students with intellectual disability and their school staff.

Although the group sample explored in this study does not permit generalization to the broader population of students and staff in CSSID schools, it did include more participants than most observational studies within the field of AAC in school settings. As the findings build upon cross-sectional data and the students’ fluctuating daily functioning is not considered, future studies may incorporate multiple observations throughout the day or across multiple days.

Future studies could also aim to develop and evaluate AAC interventions designed to be carried out in non-inclusive school settings for students with intellectual and communicative disability. Such interventions would benefit from an implementation science view, meaning that the intervention would be designed to fit the reality and contextual constraints of the school context. Such a stance would intend to narrow the research-to-practice gap acknowledged in both special education and speech-language pathology research fields (Cook & Odom, 2013; Douglas & Burshnic, 2019). Based on the findings in the present study, a communication intervention would, for example, take into account the reality of multiple-participant interactions that include students with high variability in communication needs and staff members with various roles and backgrounds. In addition, concerns would be put on incorporating augmented communication modes in everyday school activities that are unstructured and not pre-planned, especially those activities that tend to occupy hands and have no fixed classroom location.

Conclusion

This cross-sectional study explored turn-taking contributions and communication modes of students and staff in everyday group activities involving students with intellectual disability. The findings expand on earlier findings of interaction and AAC use that have studied a single or a few participants in the classroom in various school settings for students with intellectual disability by exploring multi-participant interactions in non-inclusive settings. This study adds that also in groups of students and staff, students with intellectual and communicative disability mainly act as recipients in interaction, even more so during structured and pre-planned activities. Students and staff were also found to struggle to use augmented communication modes during unstructured group activities, particularly aided communication modes, in line with research on a single or a few participants in the classroom. The study’s findings collectively highlight the importance of supporting staff members in applying partner strategies consistently and providing AAC access across various activities at school. Special considerations should be taken into incorporating such strategies in group contexts.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study received funding as part of the Research School in Special Education directed toward Early Interventions in Early Childhood Education (Swedish Research Council 2017-03683). We have no conflicts of interest to disclose.

Notes

1 iPad is a product of Apple Computers Inc., Cupertino, CA, www.apple.com

2 Reflector is a product of Squirrels, LLC, www.airsquirrels.com

3 Camtasia is a product of TechSmith Corporation, www.techsmith.com

4 The Observer XT is a product of Noldus Information Technology, www.noldus.com