National survey describing and quantifying students with communication needs

ABSTRACT

Purpose: Research literature has yet to quantify and describe how students with complex communication needs are supported in the classroom and how special educators are being prepared to offer support. This study sought out special educators to complete a survey about their students with complex communication needs. Method: Over 4,000 teachers representing 50 states reported on the communicative and behavioral characteristics of 15,643 students. Teachers described the training they have received and instructional approaches they used. Results: The majority of students were reported to use speech as their primary communication mode. Over half of students utilizing alternative and augmentative communication (AAC) were reported to have non-proficient communication. Teacher training varied across respondents as well as the supports they used to support these students in the classroom. Conclusion: The majority of students with disabilities using AAC when communicating across the nation are not proficiently communicating. Implications and recommendations will be discussed.

KEYWORDS:

• Augmentative and alternative communication
• complex communication needs
• special education teacher

Augmentative and alternative communication (AAC) has the potential to enhance communication, language, and literacy outcomes for children with complex communication needs.¹ AAC systems include a spectrum of communication modes and include unaided and aided varieties. Unaided AAC modes of communication include use of gestures, body language, and sign and aided modes require tools and or equipment beyond the person’s body ranging from a no technology pencil and paper system to a high technology speech generating device. Without AAC or other needed communication supports (e.g., speech-language pathologist, assistive technology), students with complex communication needs have limited access to their environment, limited interactions with communication partners, and limited opportunities for language and literacy development ² Often, without a functional way of communicating (e.g., AAC), students resort to using non-functional ways of communicating including challenging behaviors³, and although teachers can be effective change agents, researchers do not commonly employ classroom practitioners as the intervening agent.⁴

High levels of communication and academic engagement including speaking, listening, reading, and writing may be achieved when students have reliable access to effective communication supports.⁵ Despite the mitigating effects of AAC, students with communication support needs continue to experience challenges in education, employment, health care, family life, and community living and may exhibit challenging behaviors.⁶ In a survey of 275 American Speech-Language-Hearing Association (ASHA) Special Interest Division #12 members, participants reported that a limited usage of communication systems and abandonment of these systems are attributed to five factors: (a) not maintaining or adjusting the system by an expert, (b) attitude (i.e., motivation, history with the device, and social acceptability), (c) lack of training for those implementing the systems, (d) lack of support (i.e., from family, school team, and outside consultants), and (e) poor fit (i.e., difficult to use, mismatch, not used functionally).⁷ A comprehensive review of the literature found similar barriers related to AAC usage and abandonment including the ease and reliability of use, the need for technical support, the voice or language of the device, selection of an appropriate device, duration it takes to create a message, buy-in from the family, perceptions of others, lack of AAC services and training⁸.

One of the challenges in understanding the needs of students with communication needs is a lack of literature describing characteristics and services received by this population. Several researchers have observed these students in classroom settings to investigate the experience of students with communication needs. A study investigating 30 children using AAC in a preschool setting found that children initiated communication only 0.133 times per minute and primarily interacted with adults.⁹ These students increased their interactions when adults posed questions, but the frequency of questioning was lower than recommended interaction rates for children of this age. Chung, Carter, and Sisco¹⁰ reported similar findings regarding rates of peer interactions among 16 students using AAC in inclusive settings. Regardless of proximity to peers, students primarily interacted with adults and interactions did not use their aided AAC systems across the majority of communication. This study also reported that interaction among the target students was primarily to fulfill their wants and needs. Numerous other descriptive studies have found that students with disabilities are primarily interacting with adults.¹¹ Although descriptive studies are important in helping the education community understand what practitioners need to do to support students with communication needs, a larger-scale description of the population is necessary to understand the extent to which students are accessing the needed supports to effectively communicate a range of messages to multiple of partners, including novel partners.

Since 2002, national survey efforts have been conducted to describe communication outcomes of students with disabilities on a larger scale. First, the Special Education Educational Longitudinal Study reported that of the 1 875 parents responding about their elementary-aged children with disabilities, 34.4% had a lot of trouble communicating or did not communicate at all and 34.2% reported having a little trouble communicating.¹² Similarly, in 2010, the National Longitudinal Transition Study-2 reported that 55% of individuals with intellectual disabilities, 61% of individuals with autism, and 72% of individuals with multiple disabilities communicated with difficulty.¹³ These surveys provided valuable information, but the description of difficulty communicating is not descriptive enough to allow for any additional analyses.

Several survey-based research studies have been conducted with the aim to provide more analysis about this population of students with communication needs.^14,15 The focus of these surveys has focused on a combination of specific geographic locations, communication modes, and/or ages. For example, Binger and Light¹⁶ surveyed 144 speech-language pathologists (SLP) providing services to preschoolers using AAC in Pennsylvania and found that 12.5% of students receiving special education services required AAC. Another survey captured responses from 54 special education directors in Connecticut indicating that only 3% of students across disability categories required AAC.¹⁷ The current survey extends these previous findings by seeking information about students across ages, disabilities, and communication modes (including students who use natural, vocal speech as their primary mode of communication). Researchers also extended previous survey studies by including information about challenging behaviors exhibited by students with communication needs.

The aim of this study was to update and extend the findings of previous descriptive research by describing aspects of special education teachers supporting students with complex communication needs (e.g., their demographics, preparation, classroom context), describing the supports these teachers are offering, and describing the students these teachers are serving (e.g., proficiency of AAC use, communication needs, challenging behavior). Specifically, researchers wanted to describe (a) the characteristics of students with communication needs as reported by special education teachers, (b) the reported level of proficiency of communication among these students, (c) the presence of challenging behavior among these students, (d) the type and amount of AAC training of the special education teachers supporting these students, and (e) the type and amount of AAC support strategies used by these special education teachers. Researchers surveyed special education teachers across 50 states to answer these questions.

Method

Survey development

A panel of five professionals in the field of special education developed the survey instrument used in this study. The panel consisted of one faculty member in special education, two doctoral students (both former special educators), and two practicing special education teachers with over 40 years of combined experience in the field of moderate to profound disabilities, communication needs, and AAC. The first author created an initial draft of the survey, and then, the panel members then revised the survey through an iterative process. After agreeing upon revisions, a pilot group of six former and current special education teachers filled out the draft survey to test its ease of use. With feedback from the testers, the panel again revised the draft into the final survey (the survey is available by request from the corresponding author).

Survey items

The survey began with questions on teacher-level information. This section included teachers’ demographics (i.e., years of experience, state, school district), type of classroom (i.e., inclusion, resource room, self-contained, other), type of AAC training completed (i.e., university coursework, professional development provided by the school, training provided through direct consultation with a school-based SLP, training provided directly by an AAC specialist, and training provided directly by parents), the number of hours spent engaging in each type of training (i.e., 1–3 hr, 4–10 hr, 10–15 hr, 16 hr or more), and AAC support strategies utilized in the classroom (i.e., collaboration with SLP or consultant, dedicated communication activities, embedded communication instruction, or other). “Other” responses were supports that could not fit into the prescribed categories such as the Earobics program or social skills class.

The second section of the survey asked respondents to provide information about individual students. This section contained a six-question loop for each eligible student and included questions about the student’s primary mode of communication (i.e., speech, gesture, pictures, or aided of a speech-generating device [SGD], and the number and content of communication-related Individualized Education Program (IEP) goals. Respondents were also asked if the student engaged in any of the following challenging behaviors: off-task behavior (e.g., work refusal, socializing), physical aggression, verbal aggression, self-injurious behavior (SIB), property destruction, and elopement.¹⁸ Each responder may have interpreted the previously mentioned survey items differently. For example, stating that one “plans activities dedicated to communication” could mean many different things. These broad categories were used in attempt to maintain an easy-to-use survey that was not excessively time-consuming. See the limitations section for suggestions for future researchers when developing categories.

For each student’s primary communication mode, respondents were given different choices to evaluate the level of proficiency depending on the mode identified. For example, a teacher that chose SGD as a student’s primary mode would be asked about the number of messages the student independently produced. Responses to the question about level of proficiency were recoded into a dichotomous variable. Responses were recorded as proficient level of communication if the student was reported to (a) use verbal speech mostly understood by unfamiliar listeners, (b) use sign language mostly understood by fluently sign language users, (c) independently identify or exchange 30 or more pictures or combinations or pictures, or (d) independently activate or spell out using a SGD to communicate 30 or more words or phrases. All other responses were coded as non-proficient level of communication. This included students using vocal speech and gestural modes as mostly being understood by familiar listeners, students using pictures to independently exchange 10 or fewer icons, and students using SGDs activate a one-touch tech device when provided with two to five options.

Survey distribution

After receiving the approval of a university IRB, the first author began recruiting participants in the United States via email. Twenty-four states publically available lists of the email addresses for each building principal (i.e., head administrator) working in traditional K-12 public school buildings (i.e., these lists excluded administrators at private or public charter schools). In these states, emails were sent directly to school principals with a request to forward a recruitment email to the special education teachers working in that building. We included a question asking respondents to identify their role in order to further ensure that we could parse out special education teachers (i.e., out intended respondents) from accidental respondents (e.g., others working with students with communication impairments such as speech and language pathologists). The email contained a link to the survey hosted on the online platform, Qualtrics¹⁹. For the remaining 26 states, the first author obtained building principles’ or superintendents’ emails through email request to the state board of education or by searching school district websites one-by-one. The survey distribution excluded school districts that required additional district IRB approval. In total, researchers sent out 101,537 recruitment emails to building principals, superintendents with requests to forward. Response rates could not be calculated given that the survey link was not sent directly to the target population. The email had to be forwarded, and without information about what percentage of principals did forward to teachers (and to how many teachers), researchers cannot determine how many teachers were provided access to the link and then how many did or did not respond. Responses were recorded for 15 weeks (January through May). If participants had questions regarding the survey, the first author’s email was available to them. The only questions asked surrounded if certain students teachers supported would qualify for the survey (e.g., if their student used a communication system). To incentivize participation, researchers offered a chance to be randomly selected to receive one of five (US) $100 gift cards for special educators who returned the survey and provided their email address in a separate, confidential capture.

Data analysis

Data were analyzed using Statistical Package for the Social Science (SPSS) 22.0²⁰. Researchers calculated descriptive statistics for the responses to each survey item. Additionally, researchers calculated descriptive statistics of proficient and non-proficient communication by disability category and communication mode. Researchers also reported statistics of each type of challenging behavior by communication mode.

Results

Respondents

A total of 9,577 individuals from 50 states responded to the survey. On average, each state contributed 1.9% of responses (range: 0.4–7.7%) To be included for analysis in this study, each respondent had to meet the following inclusion criteria: (a) consent to participate and allow their answers to be reported anonymously, (b) identify his or her role as a special education teacher (as opposed to a speech-language pathologist or other), and (c) complete the survey for a minimum of one student who needed support when communicating.

Of the 9,577 original respondents, 4 031 special education teachers met the inclusion criteria. Together, these teachers reported information for 15 643 students, with an average of 3.8 students with communication needs per teacher. Teachers reported primarily (39.3%) supporting elementary school students (Grades K–5), 20.8% serving students high school students (Grades 9–12), 14.7% serving middle school students (Grades 6–8), 13.5% serving adult students (ages 19–22), 5.9% serving an age span covering two or more categories, and 5.5% preschool students. Teachers reported primarily (38.4%) in self-contained classrooms, 33.5% worked primarily in resource rooms, 15% working primarily in inclusion (i.e., general education) classroom settings, 11.8% reported that they worked in a variety of settings equally, and 0.4% reported their setting as other. Concerning experience, 27.2% of teachers reported teaching 16 years or more, 22.1% taught between 4 and 9 years, 17.7 taught between 10 and 15 years, 16.9% did not indicate their years of experience, and 16.2% teaching between 0 and 3 years.

Student characteristics

Table 1 presents the overall characteristics of 15 643 students with communication needs. Data included all disability categories recognized by the Individuals with Disabilities Education Act²¹. Special education teachers reported autism (23.2%), multiple disabilities (20.2%), and intellectual disability (18.9%) as the three largest disability categories of their students with communication needs. An additional 3.8% of students were reported to have both intellectual disability and autism. In total, the majority (66.1%) of the students reported by the respondent had a disability label of autism, intellectual disability, or multiple disabilities. Of those remaining, the largest groups were learning disability (11.8%), developmental delay (6.7%) and speech and language impairment (6.5%). The majority of students (71.9%) were reported to have between one to three communication-related IEP goals. Only 4.3% of students had five or more goals.

Table 1. Characteristics of students with communication needs.

Characteristics	n	%
Disability category
Autism	3,628	23.2
Multiple disabilities	3,167	20.2
Intellectual disability	2,952	18.9
Developmental delay	1,053	6.7
Speech and language impairment	1,022	6.5
Other health impairment	719	4.6
Intellectual disability and autism	596	3.8
Hearing impairment	235	1.5
Emotional disturbance	220	1.4
Orthopedic impairment	65	0.4
Traumatic brain injury	70	0.4
Visual impairment	32	0.2
Deaf blindness	23	0.1
Number of communication oriented IEP goals
1	1,040	6.6
2	5,836	37.3
3	4,376	28
4	2,009	12.8
5 or more	684	4.3
Communication mode
Vocal speech	12,768	81.7
Non-proficient	5,675	44.4
Proficient	7,093	55.1
Gestural	1,081	6.9
Non-proficient	942	87.1
Proficient	139	12.9
Pictorial	1,018	6.5
Non-proficient	833	81.8
Proficient	185	18.2
SGD	753	4.8
Non-proficient	469	62.3
Proficient	284	37.7

Note. Percentages do not reflect missing data and therefore may not total 100%. IEP = Individualized Education Program, SGD = speech generating device.

Communication mode and level of proficiency

Descriptive statistics for communication mode and proficiency of the whole sample are provided in Table 1. Tables 2 and 3 provide a breakdown of communication mode and proficiency by disability category. Special educators reported that the vast majority of their students with communication needs (81.7%) primarily used vocal speech with slightly over half of those students using the mode proficiently (56%). Breaking down this mode by disability status provides a wide range between categories. In the most proficient group of vocal speech users, 74.1% of students with emotional disturbance displayed proficient communication skills. In the least proficient group of those using vocal speech, only 32.7% of students with a dual diagnosis of intellectual disability and autism displayed proficient communication skills. Students using gestural, pictorial, and SGD modes accounted for smaller percentages of total participants (6.9%, 6.5%, and 4.8%, respectively). For each of these groups, students with non-proficient communication skills outweighed those with proficient communication skills. The imbalance of proficiency was present in most of the disability subgroups with a few exceptions where some students had more proficient skills than did not. In the gestural mode, only hearing impairments or deaf-blindness disability groups had more students with proficient communication skills than not. In the pictorial mode, only deaf-blindness disability group had more students with proficient communication skills than not. In the SGD mode, students with autism (not those dually diagnosed with an intellectual disability and autism) were the only group with more proficient communicators.

Table 2. Proficiency of students’ communication skills by mode and disability category.

	Vocal speech		Gestural
	Non-proficient	Proficient	Non-proficient	Proficient
	n	n	n	n
Autism	1,247(44.4)	1,560(55.6)	208(95.9)	9(4.1)
Deaf blindness	5(50)	5(50)	3(30)	7(70)
Developmental delay	5,14(57.2)	384(42.8)	7,297.3)	2(2.7)
Emotional disturbance	52(25.4)	153(74.6)	10(76.9)	3(23.1)
Hearing impairment	69(47.6)	76(52.4)	26(30.2)	60(69.8)
Intellectual disability	1,231(61.7)	765(38.3)	345(96.9)	11(3.1)
Intellectual disability and autism	214(67.3)	104(32.7)	79(97.5)	2(2.5)
Learning disability	469(25.9)	1,341(74.1)	8(66.7)	4(33.3)
Multiple disabilities	1,181(41.2)	1,684(58.8)	114(74.5)	39(25.5)
Other health impairment	213(35.1)	393(64.9)	42(100)	0(0)
Orthopedic impairment	19(47.5)	21(52.5)	7(100)	0(0)
Speech and language impairment	429(43.5)	557(56.5)	22(95.7)	1(4.3)
Traumatic brain injury	24(43.6)	31(56.4)	2(66.7)	1(33.3)
Visual impairment	8(29.6)	19(70.4)	4(100)	0(0)
Total/% of group	5,675(44)	7,093(56)	942(87)	139(13)

Note. Percentages represent percent of students within the given disability category and mode rather than the total sample.

Table 3. Proficiency of students’ communication skills by mode and disability category.

	Pictorial		SGD
	Non-proficient	Proficient	Non-proficient	Proficient
	n	n	n	n
Autism	333(75.5)	108(24.5)	60(36.8)	103(63.2)
Deaf blindness	0(0)	1(100)	2(100)	0(0)
Developmental delay	40(80)	10(20)	22(71)	9(29)
Emotional disturbance	2(100)	0(0)	0(0)	0(0)
Hearing impairment	1(33.3)	2(66.7)	1(100)	0(0)
Intellectual disability	243(90.3)	26(9.7)	238(71.9)	93(28.1)
Intellectual disability and autism	115(87.1)	17(12.9)	40(61.5)	25(38.5)
Learning disability	9(90)	1(10)	4(66.7)	2(33.3)
Multiple disabilities	49(75.4)	16(24.6)	57(67.9)	27(32.1)
Other health impairment	24(88.9)	3(11.1)	28(63.6)	16(36.4)
Orthopedic impairment	6(100)	0(0)	6(50)	6(50)
Speech and language impairment	7(87.5)	1(12.5)	5(100)	0(0)
Traumatic brain injury	3(100)	0(0)	6(66.7)	3(33.3)
Visual impairment	1(100)	0(0)	0(0)	0(0)
Total/% of group	833(82)	185(18)	469(62)	284(38)

Note. Data displayed the number and percentage. Percentages represent percent of students within the given disability category and mode rather than the total sample. SGD = Speech Generating Device.

Challenging behavior

Table 4 provides a summary of students engaging in challenging behavior by primary communication modes. Special education teachers reported that almost one-third (30.1%) of their students with communication needs did not engage in any challenging behavior. Off-task behavior was the most commonly reported (57.5%) behavior exhibited by students with communication needs across modes, followed by verbal aggression (22.7%) and physical aggression (15.4%).

Table 4. Reports of students with communication needs engaging in challenging behavior by mode.

	Vocal speech	Gestural	Pictorial	SGD
	n	n	n	n
Off-task	7,375(59.3)	559(54.6)	704(70.8)	354(48.8)
Verbal aggression	2,721(21.9)	270(26.4)	419(42.1)	151(20.8)
Physical aggression	1,657(13.3)	244(23.8)	356(35.8)	152(20.9)
SIB	647(5.2)	156(15.2)	240(24.1)	102(14.0)
Property destruction	1,052(8.5)	147(14.4)	192(19.3)	97(13.4)
Elopement	1,545(12.4)	247(24.1)	327(32.9)	131(18.0)
None	3,948(31.7)	288(28.1)	150(15.1)	248(34.2)

Note. Data displayed the number and percentage. Percentages represent percent of students within the mode rather than the total sample. SIB = self-injurious behavior; SGD = speech-generating device.

Teacher-level data

Training received

Table 5 presents the type and amount of AAC training provided to these special education teachers. Of those that reported their training related to supporting student communication needs, the type varied considerably. Training provided directly by an SLP, university course work, and professional development provided by schools were the most common types of communication-related training special education teacher reported receiving (68.5%, 67.5%, and 61%, respectively). Within each type the amount of hours spent receiving training varied, the majority of teachers reported that they had either received 0–3 hr (range: 16.2–25.7%) or 15 or more hours (range: 1.2–28.6%) of training.

Table 5. Type and total amount of communication-related training reported by special education teachers.

	University course	Professional development	Trained by SLP	Trained by AAC specialist	Trained by parent
	n	n	n	n	n
1–3 hr	654(16.2)	847(21)	1,034(25.7)	732(18.2)	533(13.2)
4–10 hr	601(14.9)	518(12.9)	531(13.2)	319(7.9)	117(2.9)
10–15 hr	314(7.8)	309(7.7)	282(7)	111(2.8)	19(0.5)
15+ hr	1,151(28.6)	780(19.4)	910(22.6)	172(4.3)	47(1.2)
None	494(12.3)	770(19.1)	473(11.7)	1,782(44.2)	2,351(58.3)
No response	817(20.3)	807(20)	801(19.9)	915(22.7)	964(23.9)
Total with any training	2,720(67.5)	2,454(61)	2,757(68.5)	1,334(33.2)	716(17.8)

Instruction approach

Table 6 displays descriptive statistics for the type AAC support strategies used by these special education teachers in the classroom. Collaborating with a SLP, embedding communication training, and planning dedicated communication skills, activities were the three types of supports respondents reported utilizing (50.8%, 45%, and 32.8%, respectively). When provided with an option to expand on additional strategies used, some special education teachers described using technology (e.g., Earobics program, social skills class), utilizing visual schedules and other visual to supplement their communication, and collaborating with parents to extend communication training at home.

Table 6. The type of supports utilized by special educators to support students’ communication.

Collaborated with SLP to provide instruction in the classroom	2,050(50.8)
Planned dedicated communication skills activities in the classroom	1,325(32.8)
Embedded communication training throughout the day	1,816(45.0)
Collaborated with a consultant to provide instruction in the classroom	13(0.3)
Other	69(1.7)
No response	662(16.4)

Note. SLP = speech-language pathologist.

Discussion

Special education teachers from across the United States completed an online survey describing their students with communication needs. In this analysis, researchers included responses from a sample of 4 031 teachers reporting on a total of 15 643 students. The survey revealed a diverse picture of both teachers and students working on building communication skills. Teachers reported working in several different settings with students with a range of primary disabilities, while teachers also described receiving a varied amount of training to support their students’ communication needs. Overall, this survey extends the literature in several key ways.

First, results indicated that this sample of special education teachers works with multiple students ranging in communicative proficiency and disability label. About 40% of teachers reported working with elementary school students with communication needs. Across school levels, teachers reported supporting on average 3.8 students with communication needs. Consistent with previous studies reporting on this population of students, two thirds of the sample were comprised of students with autism spectrum disorder, multiple disabilities, and an intellectual disability. Teachers also reported serving a lot of students with mild disabilities (i.e., learning disability, emotional disturbance). Communication needs are not exclusively related to students with severe disabilities and teachers may have different perceptions/definitions of communication impairment, given the absence of an IDEA category for this need. These findings should encourage researchers to consider including all disability labels when conducting research with students who require support when communicating.

Second, the teachers reported that the majority of their students using AAC were not communicating proficiently. Students described as using natural vocal speech as their primary mode of communication were overall more proficient than those using AAC but a staggering 42% of these students were non-proficient communicators. This might indicate an under-use of AAC for students who have minimal vocal speech and may suggest the need for training teachers in the use of multimodal interventions. Without tools to support their communication (e.g., AAC), these primarily verbal students are left without any means to communicate. These findings are not novel given that students with significant disabilities have been documented as having difficulty communicating.¹³ These outcomes, however, surprising and discouraging given the recommendation set out by the Federal government for schools to ensure every child have the ability to communicate with others.²² Without proficient means of communicating with others, students’ ability to communicate with peers, transition to adulthood, and seek independence is negatively impacted. The findings from this survey highlight the continuing need for intervention for these students and should encourage educational teams to make a more deliberate effort to address the communication needs of their students.

Third, across all modes, students displayed a wide range of challenging behaviors ranging in severity. Over half of all students represented across modes engaged in off-task behavior but a more alarming finding was the presence of challenging behaviors. Students, who are not able to communicate proficiently, will often resort to using challenging behavior as a way of communicating their wants and needs.²³ These behaviors often limit students’ access to less restrictive educational placements (e.g., general education classrooms).²⁴ Functional communication training has been widely accepted as an evidence-based solution to these behavior issues by providing students with a communicative alternative to challenging behavior.² Although validated by over 40 years of research, special educators reporting high rates of challenging behaviors among their students can be an indicator of the presence of a research-to-practice gap.

Fourth, 68% of teachers reported being trained by the SLP but only 50% of them reported collaborating with the SLP to provide supports for students in the classroom. In addition, a portion of the teachers (11.7%) responding reported receiving no training from the SLP and no training from the AAC specialist (44.2%) to help them support the students with communication needs in the classroom. This statistic is alarming given the ever changing and evolving technology used to support students with communication needs. Without ongoing and regular training, these teachers may find themselves incapable of providing effective supports to their students. This might be a reality for some educators given the perhaps limited access to SLPs due to lack of resources (e.g., rural areas) or extraneous variables (e.g., medical leave), or perhaps SLPs not having content knowledge on AAC systems.

Implications for practice

The results of this study indicate that rates of proficiency vary across disability categories and modes. For example, the findings from this study imply that students with autism were more proficient with alternative modes of communication than students with other disabilities. Given this variability, teachers should consider the individual student when considering AAC options. Beukelman and Mirenda’s²⁵ Participation Model provides a framework to guide the ongoing and multi-level process of identifying the most appropriate AAC system to support a child’s participation across contexts and communication partners. This framework initiates AAC consideration through, (a) the identification of a child’s participation patterns and communication needs across environments and (b) providing detailed consideration of both opportunity and access barriers. Opportunity barriers include factors such as policy, practice, attitude, knowledge, and skill that may impede successful acquisition and use of AAC systems. Access barriers assess the child’s current communication and individual variables (e.g., motor, cognitive/linguistic, and literacy skills) that guide AAC system decision-making.

Feature-based matching assessment is a process used to make decisions on the most appropriate AAC system for a child. For example, a student with a physical impairment may need to be matched with a system that allows for alternative access (e.g., eye tracking, switch and scanning software). Through assessment, observation, and AAC system trials, with embedded data collection, this process matches the specific needs of the child, which can be well described using the Participation Model, to the individual features of AAC systems.²⁶ This assessment process identifies features of AAC systems that support the child. Physical access to AAC systems as well as cognitive, language, literacy, and sensory (vision and hearing) needs of a child can be carefully matched to the most appropriate AAC system.²⁶

Which AAC technique is ‘best’ for a given individual depends on: the learning/developmental priorities for the person; the person’s existing skills and abilities; the person’s and family’s preferences; the person’s current and future communication needs; and the environments in which and the people with whom the person is likely to interact.²⁷, p. 52)

Given that the lack of ongoing training teachers is often exposed to post-gradation surrounding AAC supports and communication systems, teachers may benefit from the use of a number of assistive technology planning tools to successfully implement AAC systems. The Quality Indicators of Assistive Technology (http://qiat.org/index.html) is a useful tool in evaluating school systems assistive technology practices and should be followed by developing quality services and delivering these services to students. The Student Environment, Tasks, and Tools (SETT) Framework (http://www.joyzabala.com/) promotes collaborative team-based AT service delivery through consideration, implementation, and ongoing evaluation of effectiveness. The Wisconsin Assistive Technology Initiative (WATI) resources (http://wati.org/) also provide comprehensive tools for the consideration and implementation of assistive technology through the Assessing Students’ Needs for Assistive Technology (ASNAT) 5th Edition. The WATI AT Checklist is also valuable when a team is considering the assistive technology tools a child may need. Each of these tools is readily available online.

Teachers should consider seeking multiple avenues of training regarding AAC and communication needs. Although not a traditional means of gaining professional development, training provided by parents should not be discounted. The partnership that comes from collaborating with parents can be powerful and beneficial to the students. Collaborative teaming²⁸ and communication partner training²⁹ are two evidence-based methods to enhance the communication outcomes of students with complex communication needs. When collaborative teams provide supportive communication opportunities for students, it is possible to consider that “The ultimate measure of the success of AAC intervention is the degree to which it improves access and participation in valued activities and experiences of everyday life” (p. 204).¹

Limitations and future research

Limitations to the survey instrument and descriptions derived from the data exist and should be taken into consideration. Although over 4,000 teachers met the criteria for inclusion and reported for nearly 16,000 students across all 50 states, these respondents were included, as part of a convenience sample, and therefore, the generalization of these findings across a wider population should be made with caution. The data gathered were obtained through anonymous teacher reports, and this measure of student information could not be verified. Future descriptive studies should consider seeking more specific demographic data of the respondents and use random sampling measures to allow for a response rate calculation and to ensure that more generalizable findings are obtained.

This study did not take into consideration students’ use of multiple modes of communication when creating a dichotomous variable of proficient and non-proficient communication performance. The authors recognize that some students using alternate ways of communicating do so across modes. Additionally, educational teams evaluating the proficiency of an individual student’s communication may take many other factors into consideration (e.g., age, maturity, disability, years of intervention, the communication demands of the individual’s environment); however, given the scope of the survey, we chose this delineation in order to examine this variable broadly. Future researchers who are interested in investigating the effects of mode on communicative competence across multiple modes should inquire further about student ability level and communication use (e.g., functioning level, standardized assessment information, etc.).

To better understand how teachers support the communication use of students in their classroom, more specific questions, explicit category definitions (e.g., “communication supports”), and survey choices for some questions may be warranted. Possible questions may include to what extent are these students included with the general population of students and what setting are the communication supports and instruction being conducted. Possible future directions could include inquiring about what specific AAC training teachers have received and the fidelity by which they implemented AAC in their classrooms and future research could examine specific instructional strategies used. Also, inquiry into the specific communication-related evidence-based practices they use (e.g., partner assisted modeling, naturalistic intervention) would be helpful when identifying specific research-to-practice gaps within the communication domain. Survey length can be a factor as 20% of questions related to training were not answered impeding completion by respondents, and future researchers should take this into consideration and possibly seek information about communication supports separately or as a follow-up survey to encourage completion.

Conclusion

In summary, communicative proficiency among students with disabilities has been documented by past survey and descriptive studies for decades, and there has been a push from the federal government to reverse these outcomes. Yet still, the majority of students with disabilities using AAC when communicating across the nation are not proficiently communicating. AAC intervention has been proven over the past thirty years to be an effective tool when supporting the communication among students with disabilities.³⁰ Special education teachers need to seek training related to supporting this population with the communication supports necessary to ensure that the students can become proficient communicators. By ensuring that every student has an effective way of communicating with others through providing supports, obtaining training, and engaging in collaboration with the SLP, students will be more successful making relationships with others, becoming independent, and having a better quality of life.

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.