Effects of a Coaching Intervention on Paraeducator Use of Aided Language Modeling in Classroom Settings: A Pilot Investigation

Abstract

Paraeducators are the most frequent communication partners during the school day for students who use augmentative and alternative communication (AAC), yet they often lack training in AAC best practices. This intervention study examined the effect of an in-class coaching intervention on the aided language modeling (ALM) skills of paraeducators who work with students who use AAC. An intervention protocol using evidence-based coaching strategies was used to support paraeducator implementation of ALM in typical classroom activities. The multiple-baseline single-subject design measured the use of ALM by four paraeducators. Data were analyzed visually and by calculating Tau-U and gain scores. Results suggest a strong effect from the coaching intervention on ALM skills for each of the paraeducators. Challenges and benefits of paraeducator-focused interventions in classroom settings are presented.

Keywords

augmentative and alternative communication paraeducator training coaching aided language modeling

Effective use of augmentative and alternative communication (AAC) devices requires knowing how to access the necessary vocabulary/grammar on the device. Children who communicate via AAC devices can develop this skill by observing more fluent adult communication partners who use aided language modeling (ALM, O’Neill et al., 2018). ALM is an established best-practice strategy that improves children’s aided language production and refers to the demonstration of language use on AAC devices by competent communication partners. In ALM, the communication partner uses the AAC device to produce their own utterance and/or to model language for the child to use during the child’s communicative turn. Depending on the child, the partner may model only the key words of an utterance on the AAC device (O’Neill et al., 2018). ALM, similar to spoken language enrichment models, is commonly conducted in the context of naturalistic (i.e., “highly interactive, bi-directional, and multi-modal, [occurring] naturally in the context of the learner’s day” (Sennott et al., 2016, p. 103) interactions. ALM increases the numbers of communication turns taken by the child who uses AAC, as well as leads to increases in expressive vocabulary, number of communicative turns, and target morphology structures (O’Neill et al., 2018; Sennott et al., 2016).

When children who use AAC devices enter the school system, their most frequent communication partners are often the paraeducators who support their integration into classroom activities. The presence of paraeducators knowledgeable in AAC scaffolding is a key factor in the academic success of students who use AAC (e.g., Soto et al., 2001). However, high rates of paraeducator turnover (Ghere & York-Barr, 2007) and lack of formal AAC-related training for classroom staff frequently lead to a shortage of prepared paraeducators and to AAC device under-use in the classroom (Norburn et al., 2016). Given the importance of paraeducators to the successful communication of children who use AAC devices, building the skill sets of these communication partners has become a key goal of intervention in AAC. While traditional forms of professional development (e.g., workshops, trainings, and conferences) can increase paraeducator awareness of evidence-based intervention practices, these forms of professional development may be insufficient to support implementation of intervention practices in school settings. Coaching is a form of professional development that is considered essential for supporting implementation of evidence-based practices (Artman-Meeker et al., 2015; Brock & Carter, 2013). Coaching as a professional development strategy has been well supported by a body of literature, although mostly in early childhood settings. It is generally agreed upon that effective coaching interventions include the following essential components: (a) planning, (b) observation, (c) action (modeling, problem-solving, and assistance), (d) reflection, and (e) feedback (Snyder et al., 2018).

Several studies have explored ways to offer coaching to paraeducators to increase their knowledge and skills in supporting students who use AAC (Biggs et al., 2019; Douglas, 2012; Kent-Walsh et al., 2015; Shire & Jones, 2015). Key components of successful coaching interventions for communication partners have included description of the skill to be practiced, demonstration of the target skill by the coach to the partner, and the communication partner practicing with feedback from the coach (Binger et al., 2010; Kent-Walsh & McNaughton, 2005) as well as role-play, provision of printed materials, explanation of rationales for targeted skills, and individualized instructional plans for communication partners (Biggs et al., 2019).

Coaching interventions have been successful in increasing communication partner use of ALM and several other support strategies, such as expectant time delay (Biggs et al., 2019). The coaching has typically happened in structured activities and following structured protocols; a predetermined set of instructional strategies are taught to paraeducators in the context of specific and structured tasks (Biggs et al., 2019), often outside the context of naturally occurring activities. There is a need for support of communication partners directly within natural school activities (Biggs et al., 2019; Binger et al., 2010; Norburn et al., 2016) to better align with the typical service delivery models that speech–language pathologists in school follow, with predetermined amounts and frequency of services (e.g., twice a week for 30 minutes). It has been a challenge to situate paraeducator instruction within routine educational tasks. For coaching interventions to be sustainable in classroom settings, they must take into account logistical variables, such as paraeducator-to-student ratios, which can impact a paraeducator’s ability to implement supportive strategies in school environments. Evidence of successful coaching of paraeducators in a service delivery format common to school environments is necessary to bridge the research-to-practice gap in AAC intervention.

The purpose of this pilot study was to extend existing research on paraeducator training by embedding a paraeducator-focused coaching intervention within regular classroom activities and adding in the evidence-based practices of situated coaching, reflection, and problem-solving as established professional development strategies that address the needs of the adult learner (the paraeducator). Therefore, the study addressed the following research question: Can a paraeducator coaching program integrated into existing classroom activities increase the frequency of ALM by paraeducators within these activities?

Method

Participants

Participants were recruited by contacting special education classrooms in local school districts. Six paraeducators within self-contained special education classrooms in different schools were selected to participate in the study. The paraeducator had to be interested and available for coaching at least twice a week for 20 minutes, in the context of a regular classroom activity. To provide a contextualized learning opportunity for the paraeducator to practice ALM, there had to be at least one student in the classroom whose individual education program (IEP) included the use of aided AAC, with the AAC system available regularly in the classroom. Students were considered appropriate practice partners for the paraeducators if they had an aided AAC system that they were expected to use for communication and at least one-word productions, spoken, signed, or aided. Students also had to be able to point and follow concrete one-step and two-step instructions. These criteria fit the primary purpose of the study (training paraeducators) and session length closely matched special education classroom realities. Six paraeducator–student dyads that met these criteria began the study. Two of the six dyads did not complete the study as planned, as external confounding variables (a move to a new, more sophisticated AAC system for one dyad and a change in paraeducator employment status for another dyad) impacted their participation in the intervention, resulting in two cohorts of two dyads each.

Information on prior experience relevant to AAC was collected from participating paraeducators via survey. Paraeducator demographic information, as well as student information that impacted paraeducator goals, is available in Table 1. All paraeducator and student participants are referred to by pseudonyms.

Table 1.

Paraeducator and Student Participant Descriptions.

Dyad (paraeducator/student)	Paraeducator							Student
Dyad (paraeducator/student)	Sex	Racial/ethnic background	Years as para.	Years working with AAC	AAC Workshops	Students with AAC	Paraeducator or target skill	Classroom	Sex	Racial/ethnic background	MLAU	Type of AAC System
Kisha/Ben	F	South Asian	4–9	<1	0	2	1, 2, and 3 word ALM	Public elementary SDC	M	South Asian	1.6	Proloquo2Go (77-icon interface)
Eva/Khalil	F	African America	10+	1–3	>2	1	2 word ALM	Public high school SDC	M	African American	2	Touch Chat, WordPower 42-basic (42-icon interface)
Opal/Sergio	F	Caucasian	1–3	1–3	>2	5	1, 2, and 3 word ALM	Nonpublic elementary SDC	M	Hispanic	1.6	Touch Chat, WordPower 25-basic (25-icon interface)
Nalini/Tara	F	African American	1–3	1–3	0	4	2 and 3 word ALM	Public preschool SDC	F	Hispanic	1.1	Proloquo2Go (77-icon interface)

Note. AAC = augmentative and alternative communication; MLAU = mean length of aided utterance, defined as the number of total aided words or single-symbol phrases (O’Neill et al., 2018) produced by the child over all baseline sessions, divided by number of total utterances; ALM = aided language modeling; SDC = special day class.

(Additional information on paraeducators’ self-reported experience for three out of four paraeducators is available in Table 3.) All paraeducators had previously worked with children with varied needs, including autism, cerebral palsy, and intellectual disabilities. Paraeducators in the study had a large range of experience and self-perceived knowledge with ALM and with supporting children with AAC needs in classroom settings. Nalini and Opal indicated that they had worked with four and five AAC users prior to participating in this project, while Kisha had worked with 2 AAC users and Eva had worked with 1 AAC user. Opal also reported the highest levels of knowledge of AAC support strategies. Kisha and Nalini reported similar levels of confidence in being able to clarify and extend their students’ aided utterances and varied self-reported confidence levels in their ability to wait and familiarity with fluent-aided communicators (see Table 3).

All students in the dyads had diagnoses of intellectual disabilities and one student had an additional diagnosis of autism. The developmental levels of the students were not assessed beyond initial study acceptance criteria; mean length of independently produced aided utterance (MLAU, see Table 1) was collected and used as a basis for the collaborative paraeducator goal-setting interview. All students had access to their own personal AAC device in school; no information was gathered on expectations for use of device outside of school settings. Paraeducators and parents of target students provided informed consent. For the dyad Eva-Khalil, Khalil additionally provided informed assent.

Research Design

A single-subject, multiple-probe design replicated across two cohorts each was used to evaluate the effectiveness of this coaching protocol. Dyads were separated into two cohorts to complete baseline observations in a time-efficient manner. Single-subject designs are commonly used in intervention research with low-incidence/heterogeneous populations (Byiers et al., 2012). The study was approved by the Institutional Review Board at the university with which the authors are affiliated.

Measures

Dependent measures

In this study, the dependent measure for each paraeducator was the number of instances of ALM within an activity. The type of ALM was individualized based on the paired student’s communication goals (see Table 1 for each dyad’s identified target levels/goals). For example, Eva (paraeducator) practiced using two-word ALM with Khalil (student), whereas Kisha was encouraged to increase the frequency of use of all ALM based on Ben’s target skills.

Intervention fidelity

All coaches used a jointly developed checklist to ensure consistency in implementation of the coaching intervention (see Figure 1). In addition, all coaching interactions were coded for implementation fidelity by a trained research assistant who reviewed videotaped intervention sessions and coded for the presence or absence of coaching behaviors as outlined on the checklist. Intervention fidelity for each dyad was calculated as the number of coaching steps implemented divided by six (the total number of steps excluding the first and last step). Across 33% of sessions, fidelity of implementation ranged between 80% and 100% with an average of 93%.

Figure 1.

Paraeducator coaching protocol.

Materials

Sessions were recorded by digital video camera. Video files were transferred to two separate hard drives that were kept offline in locked cabinets. Existing classroom materials were used in all sessions. No new device pages or boards were created specifically for this study and dyads were expected to produce aided language on the students’ (or similar) device layouts.

Procedure

Environment

Classrooms

The selected special education classrooms were part of four public and nonpublic schools across a large urban area in the western United States. Classrooms had six to eight students and three to five staff. Coaching was conducted in classrooms during typical class activities chosen in consultation with the teacher and paraeducator according to the following criteria: the paraeducator had to be available to work individually with the coach and target student for 20 to 30 consecutive minutes, the activity typically involved opportunities for communication and occurred at a consistent time during the school day. As the intervention was intended to fit within the existing structure of each classroom, the teacher and paraeducator led the decision-making in choosing the target activity for the project, taking into account the study criteria, classroom logistics, and student motivation.

Activities

The chosen activities were small group play (Nalini/Tara), morning circle (Kisha/Ben), individual table-top art and literacy activities (Opal/Sergio), and language arts (Eva/Khalil). Classroom visits occurred twice a week. Each visit lasted between 20 and 30 minutes, with data reflecting paraeducator use of aided modeling in a 15-minute segment of the session.

Intervention coaches

Two of the authors served as intervention coaches along with a second-year graduate student in speech–language pathology. The authors are licensed speech-language pathologists (SLPs) with over 18 years of clinical experience each in serving children with disabilities and their families. The graduate student was in her last semester of graduate study and had 2 years of prior experience working in AAC classrooms as a paraeducator and SLP-A. The coaches met several times prior to and during the intervention to review the intervention protocol, role-play, and brainstorm strategies to ensure consistency in approach across coaches.

Baseline

Research assistants videotaped the target paraeducators interacting with the target students prior to intervention during a consistent jointly chosen activity, as described above. Paraeducators were instructed to go about their usual activities. Although an effort was made to keep the activity as stable as possible, activities varied somewhat across sessions due to classroom schedule adaptations on any particular day. Each session was 15 minutes long, and the number of baseline sessions per dyad was determined by the staggered baseline design, between three and six sessions long. Baseline and intervention sessions were scheduled to occur twice a week, with single sessions some weeks due to paraeducator or student absences.

Intervention

Workshop

After baseline observations were completed, paraeducators participated in a standard 75- to 90-minute introductory workshop on AAC. The purpose of the workshop was to introduce participants to concepts in AAC maintenance and scaffolding in preparation for hands on practice. The workshop was developed jointly by the three coaches and administered to all paraeducators by the second author. It included five interactive modules: (a) device management, (b) recognizing multimodal communication attempts, (c) recognizing authentic communication opportunities, (d) ALM, and (e) responding to and reinforcing communication. Modules reflected skills expected of educational/vocational personnel who work with students who use AAC (Beukelman & Light, 2020, p. 128). Nalini and Kisha received individual workshop instruction, while Opal and Eva each participated with an additional paraeducator from their classroom who had also expressed interest. Workshops happened about 3 to 4 school weeks after end of baseline, and planning sessions (see next section) about 2 to 3 weeks after workshops.

Planning session

Following the baseline measures and workshop, the paraeducator and classroom teacher participated in a 20-minute joint planning session without the student present. Here, the coach presented information gleaned about paraeducator performance during baseline, including skills demonstrated frequently and less frequently by the paraeducator. Skills included ALM and others not described in this article (expectant waiting and verbal and gestural cueing, not selected by paraeducators as target skills). The following questions guided the planning session: Which scaffolding skill(s) would the para like to develop? What are the target student’s IEP goals? How will these para skills support the target student’s goals? What opportunities are available during scheduled meeting times to develop these scaffolding skills? These guiding questions align with best-practices in adult coaching described in Dunst (2015) and Biggs et al. (2019). The paraeducator chose which skills to target, with input from the teacher. All four paraeducators chose a primary focus on ALM, but at different target levels (see Table 1).

Coaching

Coaching sessions were conducted during the same scheduled time slot as baseline sessions. Each coaching session followed the same structure, guided by a written protocol that was shared with the paraeducator during the session (see Figure 1). Each session began with a skills reminder and initial observation by the coach, followed by specific positive and instructive feedback on paraeducator use of target strategy, including modeling by the coach if the paraeducator did not demonstrate adequate strategy use after feedback (Kent-Walsh & McNaughton, 2005). Then, the coach used guiding problem-solving questions to support the paraeducator’s independence (e.g., “What do you think your student may want to say right now?”) and skill generalization (“Where else could you use these words?”). Paraeducators received between five and eight 15- to 20-minute coaching sessions, for a total time commitment of between 75 minutes to 2 hours of within-activity coaching over the course of 4 to 8 weeks.

Data Coding

A 15-minute video segment of each session when the paraeducator and student were interacting in the preferred routine was coded for ALM instances by the paraeducator. The coach was present during these segments, and the nature of the intervention meant that coach-paraeducator problem-solving conversations sometimes happened during these 15 minutes. However, only independent instances of ALM by paraeducator were coded, with “independent” defined as no part of the ALM having been demonstrated or suggested by the coach. Segments of 30 seconds or longer that involved coach/paraeducator conversation with no child participation were excluded. Research assistants trained to follow a transcription/coding manual (graduate and undergraduate students in speech–language pathology) coded all paraeducator behaviors during each session. All instances of aided language produced by each paraeducator were coded as one-word, two-word, or three-plus-word utterances.

AAC devices sometimes have multiword phrases programmed into a single symbol or symbol-sequence (O’Neill et al., 2018). To not over-inflate the true aided utterance length of participants, a phrase produced via a single symbol sequence (e.g., “the-weather-today-is” produced with one, two-step, symbol sequence) was considered a single aided word, so that the utterance “the-weather-today-is cloudy” was coded as a two-word utterance. Paraeducator models and student language were coded within the same 15-minute segment.

Data Analysis

Participant data were graphed and analyzed using protocols for visual analysis (Ledford & Gast, 2018; Vannest & Ninci, 2015). In addition, Tau-U and gain scores were calculated to evaluate the size and significance of observed effects.

Reliability

Thirty-three percent of all sessions were coded independently by two research assistants to calculate reliability of measurement. When disagreements occurred, both coders reviewed and discussed the disagreements and independently coded the session a second time. Any remaining differences were resolved with consensus coding. Less than 10% of reliability sessions required consensus coding to resolve coding differences. Coding reliability for paraeducator data was 100% for Kisha, 99.3% for Eva, and 98.8% for Opal and for Nalini, with an average of 99.2% across paraeducators.

Results

The purpose of this study was to examine the effects of an in-class coaching intervention on paraeducators’ use of aided modeling with a student using an AAC device. Results for paraeducator outcomes are presented in Figure 2. Each paraeducator was taught to provide aided language models at target levels that matched the child’s communication goal (see Table 1, Figure 2). Paraeducator data are presented in two cohorts of two paraeducator–student dyads.

Figure 2.

Paraeducator aided language modeling (ALM).

Single-case data were analyzed using the guidelines for visual analysis described by Ledford and Gast (2018) and Barton et al. (2018) and were assessed for changes in level, trend, overlap, and variability within and between participants. Overall visual analysis indicates a positive relationship between the pilot coaching intervention and paraeducator use of ALM across all four dyads.

Paraeducator Use of ALM

Baseline

Visual analysis indicated that baseline frequency of aided language models for all paraeducators was low (average: 0.8; range: 0–5). For Cohort 1, Kisha’s baseline was low and stable with a descending trend. Opal’s baseline data exhibited more variability with one session of increased use of ALM; however, the overall trend line appeared to be flat. In Cohort 2, Eva had a low and flat baseline, whereas Nalini’s baseline data indicated variability in use of ALM across sessions. While the last baseline data point for Nalini indicated a slight increase in use of ALM, it was still lower than the highest baseline data point and did not appear to change the overall trend of baseline data significantly. Nalini’s baseline demonstrated a slight positive trend (Tau-U 0.27, with Tau-U > 0.2 considered needing correction; Vannest et al., 2016), so the reported Tau-U score for Nalini was calculated with corrected baseline value.

Intervention

As seen in Figure 2, all paraeducators showed a clear increase in frequency of aided modeling strategies in response to the coaching intervention (average: 6.6; range: 0–19). A dramatic ascending trend was observed in Opal’s use of ALM while Nalini’s data indicated a stable increase in use of ALM. Eva demonstrated a modest level of increased use of ALM with the least compelling overall positive trend. Kisha demonstrated an initial strong ascending trend followed by a decrease in ALM use after the first three sessions; however, overall ALM use remained above baseline levels. Overall magnitude of change in intervention was most compelling for Opal, followed by Nalini, as both Opal and Nalini’s data displayed clear and stable ascending trends, as described by Ledford and Gast (2018). Kisha and Eva demonstrated modest increases in the use of ALM compared to baseline levels, their strategy use was variable, and did not follow a clear ascending trend.

The research project was intended to be flexible in its approach. Intervention for all dyads was continued as long as it suited the needs of the paraeducator and classroom and fit the calendar of the classroom. As a result, the number of intervention sessions varied for each dyad from 5 to 8 sessions. From baseline to end of intervention, including school vacation weeks, the study lasted 26 weeks for Nalini/Tara, 24 weeks for Opal/Sergio, 20 weeks for Eva/Khalil, and 20 weeks for Kisha/Ben. For two of the dyads (Kisha/Ben and Nalini/Tara), events outside of the classroom delayed intervention by about 3 weeks. From visual inspection of the data (see Figure 2), it does not appear that the varying duration of intervention had a significant impact on the immediacy of intervention effects. It is possible that it may impact maintenance or generalization of intervention effects—neither of which were assessed in the current investigation.

The effects of the intervention were assessed via the Tau-U measure (Vannest & Ninci, 2015) and by calculating gain scores. Tau-U has been applied consistently as a supplement to visual analysis in single-subject research (O’Neill et al., 2018). Tau-U is a more precise measure of improvement than percentage of nonoverlapping data (PND) because it generates an effect size by comparing all intervention points with all baseline points and allows for control of positive baseline trends. Tau-U scores, gain scores, and variability analyses offer complementary information on outcomes. Effect sizes were very large for all four paraeducators, with Opal and Nalini achieving larger overall gain scores than Kisha and Eva (see Table 2). The Tau-U measure alone does not describe variability of performance in the intervention phase and does not demonstrate the magnitude of improvement between baseline and intervention scores. Therefore, variability was additionally assessed via visual analysis (described above), and gain scores (calculated as difference between the average of all baseline points and the average of the last three intervention points, O’Neill et al., 2018) were used as an additional measure of effect magnitude.

Table 2.

Effects of Coaching on Paraeducator Aided Language Modeling.

Paraeducator	Tau-U	p	Effect size^a	Gain score^b
Kisha	1	.014	very large	3
Eva	0.86	.023	very large	5
Opal	0.92	.016	very large	11.3
Nalini	0.90	.006	very large	9.2

Tau-U < 0.20—small change, 0.20 to 0.60—moderate change, 0.60 to 0.80—large change, >0.8—very large change (Vannest & Ninci, 2015). ^bGain scores were calculated as the difference between average performance during the final three intervention sessions and average performance during baseline.

Discussion

The purpose of this study was to evaluate the effects of a coaching intervention, embedded within naturally occurring classroom activities, on paraeducator implementation of ALM. The authors used a multiple-baseline design across two cohorts to evaluate the effects of intervention. Analysis of data was conducted visually and using statistical estimates of intervention effectiveness (Tau-U) and gain scores. Participants were grouped in two cohorts of two paraeducators each. Baseline was staggered between participants with a difference of two sessions across each pair. While this research design is not in complete alignment with the What Works Clearinghouse Design Standards for multiple-baseline single-case designs (Kratochwill & Levin, 2010) for a minimum of five baseline sessions prior to initiating intervention and a staggering of a minimum of three sessions across participants, the clear intervention effects replicated across participants support the overall effectiveness of the intervention.

This study adds to previous research on coaching paraeducators on ALM that was conducted under more controlled conditions. Despite the inclusive participant selection criteria and flexible design considerations, all four paraeducators in this study demonstrated increases in the use of ALM with target students subsequent to intervention. The coaching approach incorporated best practices from established partner focused AAC models and coaching interventions in early childhood education literature (Romano & Woods, 2018; Snyder et al., 2015), as well as evidence-based strategies that support adult learners, such as collaborative planning, coaching, and joint problem solving (Knowles et al., 2005) and factors known to facilitate implementation of interventions in naturalistic settings, such as repeated opportunities for practice in embedded contexts and opportunities for explicit feedback and reflection (Artman-Meeker et al., 2015). The teacher and paraeducator led the decision-making on what routines and strategies to address, likely leading to participants’ buy-in and ownership of the intervention. As a result, paraeducators with different levels of experience with AAC, in classrooms spanning from pre-K to high school, all developed ALM skills, although paraeducators varied in their overall intervention implementation. The variability of intervention effects can be better understood by a careful analysis of contextual variables that impact naturalistic interventions.

First, participant criteria in this study were designed to be inclusive. As described in Table 3, Nalini and Opal had had more students who used AAC and reported higher levels of confidence with AAC preintervention. Nalini and Opal had the strongest responses to intervention both in terms of immediacy of effects, overall ascending trend in intervention and number of overlapping data points compared to baseline. It is possible that prior knowledge and experience provided a scaffold for these paraeducators to grasp and implement ALM quicker as compared to Kisha and Eva, who demonstrated slower and more variable growth in their use of ALM. In addition, the child’s level of participation and competence using their AAC device impacts the need for paraeducator use of ALM. While child communication outcomes are not included in the current analysis, the apparent decline in ALM by Kisha, rather than suggesting that coaching was not working, may have been a natural response to this particular child’s increasing independence in communicating with his AAC device. Effective interventions that are embedded in naturalistic interaction must strike a balance between modeling and allowing the student to guide the flow of conversation.

Table 3.

Paraeducator Self-Perceived Confidence With AAC Prior to Coaching.

Paraeducator	Familiarity^a	Clarification	Length	Waiting	Competence	Training	Experience with AAC tools
Kisha	3	4	5	4	1	1	Touch-screen apps
Opal	4	5	4	4	5	4	PECS, printed boards, touch-screen apps
Nalini	1	3	5	1	5	4	Single message buttons, printed boards, touch-screen apps
Eva	n/a	n/a	n/a	n/a	n/a	n/a	Touch-screen apps

Note. 1—Strongly disagree, 2—Somewhat disagree, 3—Neither agree nor disagree, 4—Somewhat agree, 5—Strongly agree. AAC = augmentative and alternative communication;

PECS = Picture Exchange Communication System.

Questions: Familiarity—“I am familiar with the term ALM,” Clarification—“I know how to help an AAC user clarify their statements using their AAC system,” Length—“I know how to help an AAC user make their sentences longer using their AAC system,” Waiting—“I know how long I should wait for an AAC user to communicate,” Competence—“I have seen people use AAC systems effectively to communicate,” Training—“I have received enough training to help this student use their system successfully.”

While all attempts were made to provide intervention in the same/similar activities, there were some naturally occurring exceptions. Naturalistic interventions are impacted by the number of opportunities for practice within the identified intervention contexts. Variability in routines and activities impacts the number of opportunities for engagement by the paraeducator and the child. For example, a circle time activity that focuses on conversation about daily events, weather, and classroom roles may offer different opportunities for interaction as compared to circle time where the conversation is focused on a book that the class is reading. Additional variables that impact intervention include the motivation and interest of the child in the activity, which can lead to fewer communication initiations and thereby impact the number of Aided Language Models used by the paraeducator.

For a school-based intervention to be sustainable, its dosage must align with classroom logistics and instructional time mandates for paraeducator to student ratios. This intervention included baseline assessment, workshop, collaborative planning, and coaching. In a classroom setting, the time required to implement this intervention would include about 1 hour of precoaching observation by the coach (across at least three natural opportunities), about one to one-and-a-half hours of initial workshop training (possibly conducted with other classroom staff), one half-hour of planning, and about 2 hours of coaching (across four to six sessions), for a total of about 5 hours across several weeks. A recent review of coaching interventions focused on communication partners of AAC users (Biggs et al., 2019) reported that while most interventions (82%) took place in school settings, fewer than half of these were implemented in natural settings and activities. In a review of ALM by communication partners (O’Neill et al., 2018), only four listed studies targeted paraeducators (Binger et al., 2010; Kent-Walsh, 2003; Pitman, 2015; Sennott, 2013). In these studies, students were assessed within structured shared book-reading activities, sometimes with displays that were set up specifically for study purposes. In this study, activities were embedded to fit completely within the paraeducators’ and student’s classroom routine. This approach was aligned with common SLP service delivery models that emphasize in-class services conducted “in short, intense bursts,” as well as consultative services provided by the SLP to classroom staff (Rudebusch & Wiechmann, 2013).

Limitations/Future Directions

This study has several limitations that must be acknowledged. First, longer and/or more stable baselines would have provided stronger experimental validation of the intervention.

Because the school year ended, maintenance data are not available. The fully embedded structure of this study means that, while it is easily applicable to the logistics of any classroom setting, there is a lot of variability, including differences in paraeducator familiarity with ALM, nature of activities within which intervention was embedded, impact of these activities on the paraeducator’s ability to embed intervention, and child variables such as motivation and engagement. More data on child communication outcomes is needed to demonstrate effects of this coaching protocol on children’s aided language use. Future research should investigate the effects of the intervention on frequency of aided language productions of the student, as well as qualitative measures of child communication.

Another important consideration in coaching studies is the professional qualification of the coach. Coaching within naturalistic activities requires significant flexibility on the part of the coach that cannot be precisely written into any protocol. This approach is likely to be most successful for coaches who have expertise in both AAC and consultative approaches to intervention.

Conclusion

Paraeducators play a critical role as primary communication partners for students who use AAC devices (Douglas, 2012). However, many paraeducators have limited training in facilitating student use of AAC devices, leading to AAC device underuse and abandonment (Norburn et al., 2016). Broad characteristics of successful paraeducator training models have been identified (Biggs et al., 2019; Douglas, 2012; Kent-Walsh & McNaughton, 2005) and typically involve coaching strategies such as skill explanation and modeling by an expert and practice by the trainee with ongoing expert feedback. The disconnect between research focused on increasing AAC scaffolding by paraeducators and the real-world circumstances in which they must use these strategies begs the question of how this research to practice gap can be closed. It is the responsibility of researchers to design and test coaching approaches in real-world settings to facilitate educators’ implementation of these evidence-based approaches in their classrooms. This study represented a first step toward bridging this gap. Continued investigations such as this one that examine variables that impact implementation of evidence-based practices may ultimately provide professionals and educators with the tools they need to improve outcomes for AAC users in school and community settings.

Footnotes

Acknowledgements

The authors would like to thank student research assistants My’Unique Anderson, Shannon Bruce, Emma Davis, Sierra Fields, Caroline McNeill, Daisy Medrano, Porscha Moua, Deepajayan Nair, Candice Nosworthy, Meghan Richards, and Emily Van Loo, as well as the students, paraeducators, and teachers who participated in the study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

This research was completed with funding from the Ability Central Foundation as well as internal student fellowships from the Center for Student Research at Cal State East Bay.

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