Review Journal of Autism and Developmental Disorders
https://doi.org/10.1007/s40489-023-00399-x
REVIEW PAPER
A Systematic and Quality Review of Augmentative and Alternative
Communication Interventions that use Core Vocabulary
Amarie Carnett1,2
· Bailey Devine2 · Einar Ingvarsson3,4
· Barbara Esch5
Received: 6 December 2022 / Accepted: 27 July 2023
© The Author(s) 2023
Abstract
Core vocabulary is defined as “lexical items that are accepted as being central and indispensable to language use” (Bell,
2012, p. 1). Use of core vocabulary is common amongst professionals who teach augmentative and alternative communication (AAC) to individuals with disabilities. Although the use of AAC is often classified as an evidence-based practice
(EBP) (Steinbrenner et al., 2020; Wong et al., Journal of Autism and Developmental Disorders, 45(7), 1951–1966, 2015)
an analysis of the relevant intervention procedures as well as the vocabulary used is often missing from syntheses of the
literature. Therefore, a systematic review was conducted to determine the quality and strength of the evidence for AAC
interventions that use core vocabulary. A systematic database search and a subsequent screening process resulted in a total
of 10 peer-reviewed studies that involved an AAC intervention that used core vocabulary. Each study’s outcomes were then
categorized as positive, mixed, or negative and a quality review was performed using the Council for Exceptional Children’s
(CEC) standards for evidence-based practices (Cook et al., Teaching Exceptional Children, 46(6), 206-212, 2015a; Remedial
and Special Education, 36, 220-234, 2015b). Overall, the results suggest a lack of strong evidence in favor of AAC interventions that use core vocabulary. The results are discussed in the context of general suggestions for vocabulary selection and
teaching practices for AAC systems.
Keywords Augmentative and alternative communication · Autism spectrum disorder · Core vocabulary · Developmental
disabilities · Systematic review
Augmentative and alternative communication (AAC) systems are often used by individuals with developmental disabilities who have complex communication needs (CCN)
to support the development of communicative repertoires.
It is estimated that approximately 33% of individuals with
intellectual and developmental disabilities (Blackwell et al.,
1989; Ganz et al., 2017) and 30% of individuals with autism
spectrum disorder (ASD); Wodka et al. (2013) do not fully
* Amarie Carnett
amarie.carnett@vuw.ac.nz
1
School of Education, Educational Psychology, Victoria
University of Wellington, PO Box 600, Wellington 6140,
New Zealand
2
Behavior Experts of Texas, Hurst, TX, USA
3
Virginia Institute of Autism, Charlottesville, VA, USA
4
School of Education and Human Development, University
of Virginia, Charlottesville, VA, USA
5
Esch Behavioral Consultants, Kalamazoo, MI, USA
develop functional vocal speech. Thus, the use of AAC systems is often recommended to support the development of
their communication repertoires (Beukelman & Mirenda,
2005; Ganz et al., 2012).
AAC includes an array of options, ranging from unaided
AAC, such as manual sign or gestures; to aided AAC, such
as picture exchange and speech-generating devices (SGDs).
Both aided and unaided AAC systems have been effectively
used to establish basic communication skills (Ganz, 2015;
Gevarter et al., 2013; Schlosser & Koul, 2015). AAC is listed
as evidence-based practice (EBP) by the National Clearinghouse on Autism Evidence and Practice (Steinbrenner et al.,
2020) and considered an emerging practice by the National
Standards Project, Phase 2 (Wong et al., 2015).
In the last decade a substantial increase in the availability
of portable electronic aided AAC devices (speech-generating devices) such as tablets (e.g., iPad1) and portable touch
screen devices (e.g., iPod1) rather than non-electronic AAC
options (e.g., PECS, Lorah et al., 2022; Shane et al., 2012;
van der Meer & Rispoli, 2010) has occurred. These trends
13
Vol.:(0123456789)
Review Journal of Autism and Developmental Disorders
parallel changes in use of technology in society as a whole;
thus, it is not surprising to see increases in research utilizing
smart devices in communication-based interventions (Achmadi et al., 2012; Kagohara et al., 2012; van der Meer et al.,
2012, 2013).
To date, several researchers have conducted reviews of
the literature on AAC interventions (see Crowe et al., 2021;
Lorah et al., 2022; Morin et al., 2018; Schlosser & Koul,
2015) to evaluate the body of literature and quality of the
evidence. For example, Schlosser and Koul (2015) provided
a scoping review of AAC research to evaluate the effectiveness of interventions, identify gaps in the literature, and
provide suggestions for future research. Their primary findings indicated a robust body of high-quality studies aimed at
teaching requesting skills using speech output technologies.
Similarly, Morin et al. (2018) conducted a review of the
literature focused on appraising the quality of single-case
research on high-tech AAC interventions. Findings of this
review indicated implementation of high-tech AAC may be
considered an EBP for individuals with autism or intellectual
disabilities who have CCN.
In contrast, Crowe et al. (2021) conducted a mega-review
of literature reviews, systematic reviews, and meta-analyses, published from 2000 to 2020, that used AAC interventions with children with disabilities. The MeaSurement
Tool to Assess Systematic Reviews Revised (AMSTART
2, Shea et al., 2017) was used to assess rigor of the 84
reviews selected for inclusion. Overall, the authors noted
that although slight increases in methodological rigor have
occurred, several methodological weaknesses continue to
exist in the body of literature that purports to support AAC
interventions as evidence-based for individuals with developmental disabilities and CCN. However, these reviews were
each limited in their analysis of the intervention components
used to teach the use of AAC systems and analysis of the
system components (e.g., vocabulary used, display settings,
features).
More recently, Lorah et al. (2022) conducted a systematic
review of evidence-based teaching procedures for individuals with autism using mobile AAC systems. In this synthesis,
38 studies were reviewed, and findings indicated the most
used evidence-based teaching strategies used were prompting (N = 38), time delay (N = 32), reinforcement (N = 24),
and differential reinforcement (N = 14). However, similar to
the previously mentioned reviews, an analysis of the type
of vocabulary used within the interventions has not been
included.
To date, most of the research on procedures to teach the
use of AAC systems has evaluated learning to request (also
known as manding; Skinner, 1957) preferred items using
nouns (e.g., foods, object names, important people; Ganz,
2015; Mirenda, 2017; Schlosser & Koul, 2015). This
approach aligns with patterns observed in early development
13
of expressive communication, especially in the development
of English speakers (Bloom, 2000; Fenson et al., 2007).
Given the importance of establishing requesting skills for
a functional repertoire (Carnett et al., 2019; Sundberg &
Michael, 2001), this may simply be a result of the relevant
research considering the needs of the population with which
it has mostly been conducted; namely children with developmental disabilities.
More recently, research has extended to investigate the
type of vocabulary used within interventions for AAC. Specifically, studies have incorporated the use of core vocabulary based AAC systems for individuals with developmental disabilities (Laubscher & Light, 2020). Core vocabulary
is defined in the literature as the “lexical items which are
accepted as being central and indispensable to language use”
(Bell, 2012, p. 1). This vocabulary includes more general
words that can be used for multiple purposes and contexts
(e.g., A, GO, KNOW, WITH). Laubscher and Light (2020)
provided a narrative review of the literature to evaluate
core vocabulary lists for young children using AAC systems. Specifically, the authors evaluated five studies, only
one of which included participants who were classified as
having CCN. Their main findings suggested that many of
the categories of words that predominate early vocabulary
development were under-represented in the core vocabulary, and thus may not be an appropriate to guide to AAC
vocabulary selection for early learners of symbolic (picture/
icon-based) communication. Although these findings have
important implications for AAC users, a systematic review
of interventions that utilize core vocabulary in the context
of AAC systems for individuals with CCN has yet to be
conducted. Likewise, the quality and rigor of this body of
literature has yet to be evaluated. Thus, there are two aims of
the current review: (a) to synthesize and analyze the current
research, and (b) to evaluate the quality of research on this
topic to provide guidance on interventions that incorporate
core vocabulary withinAAC systems.
Method
Search Procedures
Systematic searches were conducted using the following databases: Education Resources Information Center
(ERIC), PsycINFO, Linguistic and Language Behavior
Abstracts (LLBA), and ProQuest Dissertation. Database
searches were limited to English language peer reviewed
journals, except ProQuest Dissertation. The first author
searched each database using the combined search terms:
“core word*” or “core vocabulary” or “Makaton vocabulary” or “LAMP” and “auti*” or “ASD” or “cerebral palsy”
or “communication disorder” or “complex communication
Review Journal of Autism and Developmental Disorders
needs” or “deaf” or “developmental delay” or “developmental disability” or “disability” or “down syndrome” or
“minimally verbal” or “nonverbal” or “intellectual disability” or “speech disorder” and “treatment” or “teach*” or
“therapy” or “intervention”. The database yields were then
independently screened by the article abstracts to determine consideration for full screening. Duplicates, reviews,
and concept papers were removed; however, dissertations
were also included since intervention research on this topic
is relatively recent. In total, 94 articles were examined
to determine initial inclusion for full analysis. Reference
checks were conducted for each article that met the inclusion criteria to identify any additional relevant studies. A
total of 23 studies from the initial database searches and
eight studies from the hand searches were then identified
for further screening. Lastly, the first author conducted targeted searches from the last two years for relevant journals
to account for any additional relevant studies that did not
include the identified key terms (See Fig. 1).
Fig. 1 Search graphic
Screening and Inclusion Criteria
The first three authors then completed a second full screening process, in which the 31 studies were screened to determine if the study met the following inclusion criteria: (a)
included at least one participant with a diagnosis of a disability that warrants a communication intervention (e.g.,
ASD, developmental disability, communication disorder),
(b) included an intervention in which an independent variable and a dependent variable could be identified, and (c)
included the use of core vocabulary. Full article screening
involved checking each article for the inclusion components previously listed. For example, if the article described
the use of core vocabulary as a dependent variable, it was
included. Application of these inclusion criteria resulted
in 10 studies being included in this review (see Table 1).
Agreement for the application of the inclusion or exclusion
criteria was obtained for 29 out of the 31 studies (94%). For
articles in which there was disagreement, the third author
reviewed the study for consensus to be reached.
Articles retrieved from initial database
searches
n = 94
Duplicates removed
n = 29
Article screened title and abstract
n = 65
Articles excluded
n = 43
Articles screened by full text
n = 23
Articles excluded (n = 42)
Met Inclusion Criteria
n=8
Not English
Not Specific to Core Vocab.
Articles retrieved from hand searches
n=8
Articles excluded (n = 6)
Met Inclusion Criteria
n=2
Not English
Not Specific to Core Vocab.
Articles included in review
n = 10
13
13
Table 1 Summary of reviewed literature
Participant characteristics AAC system used
Bedwani et al. (2015)
N = 8 (7 male; 1 female)
Ages: 4 to 12
Diag: ASD
Dorney and Erickson
(2019)
N = 13 (9 male; 4 female) PE, PECS,
Aided Language Board
Ages: 3 to 6 (M = 4:5)
Diag: ASD
VantageLite
Dependent variable
Intervention components, Research design and
dosage, agent
rigor score
Comm target: functional
word use
(using AAC)
Pre/post-test of core
vocabulary and expressive vocabulary
Percentage of pre-intentional, intentional, and
symbolic communication spontaneous symbolic communication
Ongoing LAMP data log
filled out
Components: Child-led,
naturalistic opportunities, modeling,
prompting
Dosage: 5 weeks
Agent: SLP taught sessions, trained parents
and teachers to use
outside of session
Communication Matrix
Pre- and Post-Field
notes
20% randomized subset
coding of communicative intent (refuse,
obtain, engage social,
inform, and unclear)
Components: Professional Design: Mixed methods: quantitative and
development sessions
qualitative/
for staff on components
AAC and core vocabu- Rigor1: 58%
lary (e.g., integrating
vocabulary, attributing
meaning, modeling)
Dosage: 7 sessions
Agent: teachers, teaching
assistants, and speechlanguage pathologists
Design: Pre-post, AB
Rigor1: 41%
Outcomes
Results: Mixed; small to
moderate increases for
number of words from
baseline to intervention.
The percentage of children emitting pre-intentional, intentional, and
symbolic communication
increased slightly
Generalization and maintenance: Not measured
Social Validity: During
post-test; all parents were
more confident with
using the device, all but
one were more confident in teaching another
person, and all but two
were more confident that
the device would help
their child
Follow-up survey: Out
of seven responses,
five were still using the
device. Three reported
still working with a
LAMP trained SLP. All
seven reported some
technical difficulties
Results: Mixed; Some
gains were reported for
teacher use of instructional procedures (not
directly measured), and
student data indicated
some increases in pre/
post- measures (but this
was not statistically
significant)
Generalization, maintenance: not measured
Social validity: Not measured
Review Journal of Autism and Developmental Disorders
Study
Study
Participant characteristics AAC system used
Dependent variable
Intervention components, Research design and
dosage, agent
rigor score
*Hammond (2017)
N = 5 (3 male; 2 female)
Ages: 6 to 13
Diag: ASD
VantageLite
Design: Mixed methComponents: Teacher
Language acquisiods (quantitative and
training; discrete trial;
tion through motor
qualitative)
prompting and fading,
planning application
Rigor1: 82%
differential reinforcedata (targeted phrases
ment
containing core words
recorded by the device) Dosage: 1 to 18 sessions
per target
Discrete trial training
data (observational data Agent: Teacher aids, SLPs
collection)
Independent responses of
key sequence activation
*Karnes (2019)
N = 3 (3 males)
Ages: 2:11 to 5:1
Diag: ASD
iPad mini with Proloquo2Go
Components: EvaluatPercentage of accurate
ing preference of item,
and independent mandtime delay, variety of
ing via an SGD with
prompts, reinforcement
core vocabulary
Dosage: approx. 25 sessions
Agent: Researcher
Lal (2010)
N = 8 (gender not
reported)
Ages1: 9 to 12
Diag: ASD
Manual sign
Pre/post-test: Language
Assessment Test for
Children with Autism;
Social Behavior Rating
Scale
Components: Readiness
activity prior to target
instruction; modeling,
prompting, reinforcement
Dosage: 12 sessions
Agent: researcher
Design: Multiple
baseline across
participants/Rigor1:
96%
Design: Pre-post comparison (parametric
stats)
Rigor1: 50%
Outcomes
Results: Mixed; All participants showed increases in
use of targeted phrases.
Only 2 participants completed all training targets
(19 total)
Generalization: Negative;
no clear evidence of
substantial generalization
was observed
Maintenance: Mixed
Social validity: Not measured
Results: Positive; each
child showed increases in
independent mands
Generalization, maintenance: not measured
Social validity: pre/post
indirect assessment indicated acceptance of the
intervention procedures
and mix results on the
use of core vocabulary
Results: Positive; each
child showed increases in
their Language Assessment Test for Children
with Autism and Social
Behavior Rating Scale
scores from pre to posttest
Generalization, maintenance: not measured
Social validity: Not measured
Review Journal of Autism and Developmental Disorders
Table 1 (continued)
13
13
Table 1 (continued)
Study
Participant characteristics AAC system used
*Mason (2016)
N = 5 (3 males, 2 female)
Ages: 9 to 14
Diag: Apert syndrome,
cerebral palsy, Rubinstein- Taybi syndrome,
or spastic quadriplegia
Intervention components, Research design and
dosage, agent
rigor score
Design: Mixed methComponents: Teacher
Accent 1400 with NuEye Language acquisition
ods; quantitative and
training on LAMP
through motor plantracking system
qualitative/Rigor1:
system; naturalistic,
ning application data
Accent 800, Accent
modeling, prompting
(utterances, vocabulary
1200, Vantage Lite
50%
Dosage: 6 intervention
selection) prompting
sessions
level
Pre/post-test: Functional Agent: Teacher or teacher
assistant
communication profile
revised
Interviews with staff
using open ended questions
Core board
Pre/post-test of core
vocabulary and expressive vocabulary
Components: Core
vocabulary taught
during speech therapy
session, naturalistic
Dosage: 12 weeks
(30 min. per week)
Agent: Speech-language
pathologist
Design: Quantitative
quasi-experimental/
Rigor1:
83%
Outcomes
Results: Mixed; some
increases in frequency,
utterances, and of use
were noted, but not
statistically significantly
compared to baseline.
Most participants
required prompting during the sessions
Generalization: Negative;
no clear evidence of
substantial generalization
was observed
Maintenance: Not measured
Social validity: indicated
acceptance of the intervention procedures and
increases in communication use
Results: Positive; the
treatment had a statically
significant effect on core
vocabulary and expressive vocabulary
Generalization, maintenance: not measured
Social validity: Not measured
Review Journal of Autism and Developmental Disorders
*Riccelli-Sherman (2017) N = 30 (gender not
reported)
Ages: 5 to 6
Diag: Treatment Group
(N = 15): ASD,
Apraxia, Articulation Delay, Developmental Delay, Down
Syndrome, Jacobsen
Syndrome, Language
Delay, or Spina Bifida
Control Group: (N = 15)
Not reported
language delay, or spina
bifida
Dependent variable
Study
Participant characteristics AAC system used
Dependent variable
Intervention components, Research design and
dosage, agent
rigor score
Snodgrass, et al. (2013)
N = 1 (male)
Ages: 9
Diag: Down syndrome,
orthopedic impairment, deaf-blindness,
and severe intellectual
disability
Tactile symbols
Reaching for the symbol
(MORE, DONE, NEW)
Components: Modified PECS instruction
(graduated guidance
with forward chaining),
reinforcement
Dosage: 0 to 17 trials
across the school day
Agent: Six adults on the
education team
Tan et al. (2014)
N = 3 (males)
Ages: 3–4
Diag: ASD
Manual sign
Use of core sign and
fringe sign, gestures
and spoken words
Design: Single case
– multiple baseline
design across stimuli
Rigor1: 96%
Outcomes
Results: Positive; the
participant acquired each
target request
Generalization: Mixed;
direct training was
needed for some stimuli
Maintenance: Data were
stable for each target for
the last 17 days of the
study
Social validity: Not measured
Design: Single case –
Components: Key word
Results: Mixed; 1 parmultiple baseline across ticipant had increases in
sign (KWS) procedures
toy sets
across three phases;
core signs and two of the
Rigor1: 91%
naturalistic, vocal
six participants showed
and model prompts,
increases (N = 4; N = 34)
responding to the
in both categories of both
child’s communicative
core and fringe signs.
behaviors
Intervention effect size
Dosage: 13 intervention
were modest and not
sessions (10 min each)
statistically significant
plus two follow up sesGeneralization: Mixed;
sions (15 min each)
2 participants were
Agent: Speech pathologist
reported to engage in
core signs across toy sets
Maintenance: Mixed;
2 participants had
decreases compared
to rates of responding
during intervention; 1
participant maintained
rates similar to the intervention phase
Social validity: Not measured
Review Journal of Autism and Developmental Disorders
Table 1 (continued)
13
Results: Mixed; four
children showed minor
increases in scores from
pre to post-test
Generalization, maintenance: not measured
Social validity: Not measured
Data Extraction
13
*
Denotes doctorate dissertation; 1Based on criteria from Council for Exceptional Children, 2014
Design: Pre-post comparison/
Rigor1: 42%
Pre/post-test using the
Components: Modeling
Communication Matrix
the construction of
the relevant core word
and the exchange of
the sentence strip to
another staff
Dosage: 8wks
Agent: Teacher
PE
N = 6 (males)
Ages: 3–4
Diag: ASD
*Willis (2020)
Study
Table 1 (continued)
Participant characteristics AAC system used
Dependent variable
Intervention components, Research design and
dosage, agent
rigor score
Outcomes
Review Journal of Autism and Developmental Disorders
Data were extracted for the 10 included studies and summarized in terms of the following variables: (a) participant
characteristics, (b) dependent variables, (c) intervention
components, (e) research design, (f) rigor, and (g) study
outcomes. Data were extracted to a summary table by the
first author and checked for accuracy by the second and third
authors.
Similar to other published systematic reviews, each study
was evaluated for overall effects (certainty of evidence) and
classified as positive, mixed, or negative based on visual
analysis of graphed results for single case studies (Gast &
Ledford, 2009), and for group designs (Davis et al., 2013;
Lang et al., 2012). Studies were coded as yielding positive
results if all participants showed increases (above baseline
levels) on all dependent variables or if statistically significant increases were shown for all dependent variables in
a group design. Studies were coded as mixed if some participants showed increases and others did not or if increases
were found in some dependent variables, but not all. For
group design coding, mixed results were identified if some
increases in some of the dependent variables were statistically significant, but others failed to reach statistical significance. Studies were coded as yielding negative results if
participants did not show increases on any of the dependent
variables or if a group design failed to yield statistically
significant improvement in any of the dependent variables.
Additionally, a quality review of each study was completed using the criteria defined by the Council for Exceptional Children (CEC) Evidence-Based Practices (EBP)
workgroup (Cook et al., 2015a, b). Specifically, there are
eight dimensions included for a study to be identified as
high-quality (i.e., context and setting, participants, intervention agents, description of practice, implementation fidelity,
internal validity, measurement, and data analysis). The CEC
quality standards were selected given the population of focus
for this review and because most of the studies took place
within school settings.
Results
Table 1 provides a summary of each study.
Participants and Settings
A total of 67 participants with a variety of diagnoses (e.g.,
ASD, developmental disability, intellectual disability) were
included; the most reported was ASD (63%). Of the studies
in which gender was reported (8 studies), 80% (N = 35) of
participants were male and 20% (N = 9) were female; however, it should be noted that gender was not reported for 23
Review Journal of Autism and Developmental Disorders
(33%) of the participants (i.e., Lal, 2010; Riccelli-Sherman,
2017). Participant age ranged from 3 to 12 years; however, a
mean age could not be determined given the lack of specific
participant demographic data. Some information on communication abilities were provided, but most studies relied
on anecdotal information or Individual Education Program
(IEP) information. Two studies provided assessment (e.g.,
Mullens Scales of Early Learning, Verbal Behavior Milestone Assessment and Placement Program, Vineland Adaptive Behavior Scales) information related to communication
abilities (e.g., Karnes, 2019; Tan et al., 2014), and three
studies used established pre and post assessments (e.g.,
Communication Matrix, Language Assessment Test for
Children with Autism).
For settings, 80% (N = 8) of the included studies conducted sessions within school settings, and two studies (i.e.,
Karnes, 2019; Tan et al., 2014) conducted sessions in a clinical setting.
Communication Systems
Table 2 provides a summary of AAC systems used and
related information. For each of the included studies, the
dependent variable involved an AAC system, such as picture exchange (PE), manual sign, aided language board,
or a speech-generating device (SGD). For all studies, participants’ target behavior included the use of an AAC in
conjunction with core vocabulary communication targets.
Within the reviewed studies, the most common modality
was SGD-based systems (e.g., Accent, VantageLite, Proloquo2Go), which were used in four (40%) of the studies
as the specific communication device (i.e., Bedwani et al.,
2015; Hammond, 2017; Karnes, 2019; Mason, 2016). The
second most common modality was an exchanged-based
system (e.g., picture/symbol exchange, picture exchange
communication system; [PECS] (Bondy & Frost, 1994), or
tactile symbol exchange), which were used in three (30%) of
the studies (i.e., Dorney & Erickson, 2019; Snodgrass et al.,
2013; Willis, 2020). The remaining studies used manual sign
(i.e., Lal, 2010; Tan et al., 2014), and communication boards
(i.e., Dorney & Erickson, 2019; Riccelli-Sherman, 2017).
Of note, Dorney and Erickson (2019) reported a variety of
AAC systems.
For studies in which SGDs, communication boards,
and PECS systems were used, most studies provided little
to no information on the grid organization and number of
symbols on the grid. Of the two studies who provided grid
display information, Dorney and Erickson (2019) specified that a total of 65 symbols (54 core vocabulary symbols
and 5 color symbols) were used. Karnes (2019) specified
that 60 symbols were presented in the grid display, but the
study included three phases of stimulus fading (i.e., Phase
1 included 1 symbol; Phase 2 included 1 symbol with 59
dimmed symbols; Phase 3 included 60 symbols).
Dependent Variables
All the studies included in this review used core vocabulary
communication targets as part of the dependent variables
(DV). Half of the studies included teaching only core vocabulary words; however, only 60% of the studies reported the
specific words targeted during intervention sessions. Of the
studies that used both core and fringe vocabulary (N = 5),
only two provided information on the actual vocabulary
words (e.g., Hammond, 2017; Lal, 2010) Of the studies that
included only core vocabulary (N = 5), four provided information on the specific words targeted.
The most commonly reported DV was pre/post measures of communication (i.e., vocabulary use or formal
assessment), seen in 60% of the studies. The second most
common DV reported was direct measurement of communication (e.g., frequency, rate, percentage of independent
responses), seen in 50% of the studies. Of note, 30% of the
studies included frequency logs of word use (i.e., Bedwani
et al., 2015; Hammond, 2017; Mason, 2016).
Independent Variables
Table 3 provides a breakdown of intervention components
for the studies. A variety of evidence-based teaching procedures (Steinbrenner et al., 2020) were reported across the
included studies. Most (90%) of the studies involved used a
combination of intervention procedures. The most frequently
reported component included prompting, used in seven studies (70%), modeling, used in five studies (50%), naturalistic
instruction, used in five studies (50%), and reinforcement,
used in five studies (50%). The least often used component
was time delay procedures and differential reinforcement,
used in one study (10%).
Research Designs
Of the 10 included studies, six (60%) employed single case
research design (e.g., multiple baseline design Bedwani
et al., 2015; Hammond, 2017; Karnes, 2019; Mason, 2016;
Tan et al., 2014), and four (40%) utilized group designs (e.g.,
quasi-experimental, convergent mixed-method design (i.e.,
Dorney & Erickson, 2019; Lal, 2010; Riccelli-Sherman,
2017).
Interobserver Agreement and Procedural Integrity
Four studies (40%) (i.e., Dorney & Erickson, 2019; Hammond, 2017; Snodgrass et al., 2013; Tan et al., 2014)
reported interobserver agreement (IOA). For each of these
13
13
Table 2 Summary of AAC systems and communication targets
Study
AAC system used
Bedwani et al. (2015)
VantageLite
Dorney and Erickson (2019) PE, PECS,
Aided Language Board
*Hammond (2017)
VantageLite
Grid display
Type of vocabulary Vocabulary taught/Targeted
48, 60 and 84 symbols
Core and fringe
65 symbols including 54 core vocabulary and Core
symbols representing colors
Information not provided
Core and fringe
Core
iPad mini with Proloquo2Go Phase 1—1 symbol
Phase 2—1 symbol with 59 dimmed symbols
Phase 3—60 visible symbols
Lal (2010)
Manual sign
n/a
Core and fringe
*Mason (2016)
Accent 1400 with NuEye
tracking system
Accent 800, Accent 1200,
Vantage Lite
Information not provided
Core and fringe
*Riccelli-Sherman (2017)
Core board
Information not provided
Core
Snodgrass, et al. (2013)
Tan et al. (2014)
*Willis (2020)
Tactile symbols
Manual sign
PE
n/a
n/a
Information not provided
Core
Core and fringe
Core
*
Denotes doctorate dissertation; 1Based on criteria from Council for Exceptional Children, 2014
YES, NO, I WANT THAT, WHAT IS IT, I WANT YOU TO
___, I WANT A ____, I WANT THE ____, I WANT SOME,
I WANT IT OUT, I WANT ON, I WANT ___ OFF, I WANT
MINE, I WANT MY ___, I WANT MORE, IN THE ___, I
WANT IT HERE, I WANT HELP, I WANT TO GO, ALL
DONE
Participant 1: PLAY, GET, ALL DONE, DRINK, EAT,
WANT, SPIN, PUT;
Participant 2: PLAY, WANT, GET EAT, DRINK, OUT,
MORE, READ, ALL DONE, STOP, GO, THIS, LIKE;
Participant 3: PLAY, ALL DONE, GET, WANT, EAT, READ,
HELP, GO, PUT, WANT WHO, WANT THIS, WANT GO,
GLUE STICK, GLUE
Stage 1: Food, Biscuit, Cup, Toilet, House, Table, Bed, To
sleep, To drink, To eat, To wash
Stage 2: Water, Milk, TV, Telephone, Fan, Ball, Bat, Cat, Dog,
Clean, Dirty
Stage 3: Apple, Mango, Banana, Boat, To walk To run, Big,
Small
Participant 1: LITTLE CRITTER DOLL, YES, OPEN,
BOOK, RED, COOKIE, FOOD
Participant 2: NO, HE, I, THEY, WANT, HELP, LIKE, HIGH,
THEY’RE, LOVE, BAD, WEATHER
Participant 3: NO, I, ME, IT, RED, SHOE, CAT, BLUE, YES,
GLASSES, HE, BUTTON
Participant 4: THE, GOAT, HUNGRY, EAT, YES, NO,
BOOK, ALL DONE, HUNGRIER, PLEASE, PUPPY, DOG,
PLAY, FROG, SANDWICH, OF, I
Participant 5: I, WANT, GOLDFISH, NOT FUNNY, TIRED,
AND, PLAY, FEEL, HAPPY, MONKEY, ON, TOY, WALK,
A, HUNGRY, DOG, SHE, HARD, WORK, CAT, WENT,
SEE, ATE
I, NO, YES, THE, WANT, IS, IT, THAT, A, GO, MY, MINE,
YOU, WHAT, ON, IN, HERE, MORE, OUT, OFF, SOME,
HELP, FINISHED, ALL DONE, YEAH, ALL
MORE, DONE, NEW
Not specified
LIKE, WANT, GET, GO, MORE, IT, IS, NOT, SEE
Review Journal of Autism and Developmental Disorders
*Karnes (2019)
Not specified
Most frequently modeled: WANT, ON, FINISHED, LIKE
Review Journal of Autism and Developmental Disorders
Table 3 Summary of intervention components
Discrete trial Differential
reinforcement
Bedwani et al. (2015)
Dorney and Erickson
(2019)
*Hammond, (2017)
*Karnes, (2019)
Lal, (2010)
*Mason, (2016)
*Riccelli-Sherman,
(2017)
Snodgrass and et al.,
(2013)
Tan et al. (2014)
*Willis (2020)
*
Error
correction
Modeling Naturalistic Prompting Reinforcement Task analysis Time delay
Intervention
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Denotes doctorate dissertation
studies, IOA was calculated for at least 20% of the sessions
(range: 20% to 37%) with mean agreement at or above 87%
(range: 87% to 100%). Four of the studies (i.e., Hammond,
2017; Karnes, 2019; Snodgrass et al., 2013; Tan et al.,
2014) reported treatment fidelity data. For Tan et al. treatment fidelity data were collected for 20% of the sessions. In
Snodgrass et al. fidelity was collected for 30% of sessions.
In the Hammond study, treatment fidelity data were only collected for an average of 12 trials for each participant (out of
an average of 680 trials per participant), which is generally
considered insufficient. Fidelity was reported at or above
95% for Hammond and Snodgrass et al.; however, in Tan
et al. fidelity was collected using a 5-point Likert scale (e.g.,
1 = strongly disagree, 5 = strongly agreed), which averaged
3.7 (74%). One study reported a variation of standard treatment fidelity method in that a self-assessment score was
reported (i.e., Karnes, 2019). Lastly, Mason reported that
fidelity data were coded from four video recorded sessions
for each participant (out of an average of 53 sessions); however, the author reported only anecdotal results.
Results
The majority of the reviewed studies (60%) were coded as
showing mixed results (i.e., Bedwani et al., 2015; Dorney
& Erickson, 2019; Hammond, 2017; Mason, 2016; Tan
et al., 2014; Willis, 2020) when applying the certainty of
evidence standards (Davis et al., 2013; Lang et al., 2012).
The remaining four studies were each coded as showing
positive results (i.e., Karnes, 2019; Lal, 2010; RiccelliSherman, 2017; Snodgrass, et al., 2013). Additionally,
the majority of the studies (70%) did not collect generalization or maintenance data. Hammond reported both
generalization and maintenance results; however, there
was no clear evidence of substantial generalization, and
maintenance effects were mixed. Mason reported generalization; however, there was no clear evidence of substantial generalization. Snodgrass et al. also reported data for
both generalization and maintenance, which were coded as
mixed results because direct training was needed for some
of the targets and stability was not observed until the end
of the study. Additionally, Tan et al. reported both maintenance and generalization, each of which were scored as
mixed. For generalization, only two out of three participants continued to engage in core signs across toy sets,
and for maintenance, two participants showed decreases
in their rates of responding.
Quality Indicators
Each article was also evaluated for quality using the CEC
quality standards across the eight dimensions specified
for high-quality studies (see Figs. 2 and 3 for percentage scores). Coding definitions were derived from the
descriptions provided by Cook et al. (2015a, b) for both
single case and group designs. Of the reviewed studies,
three (i.e., Karnes, 2019; Snodgrass et al., 2013; Tan et al.,
2014) scored 90% or better within the eight dimensions
of quality indicators, two studies (i.e., Hammond, 2017;
Riccelli-Sherman, 2017) scored 80% or better, and the five
remaining studies (i.e.,Bedwani et al., 2015; Dorney &
Erickson, 2019; Lal, 2010; Mason, 2016; Willis, 2020)
scored 60% or less, (range: 58% to 41%). For a specific
breakdown of the scores see Tables 4 and 5.
13
Review Journal of Autism and Developmental Disorders
Fig. 2 Percentage of CEC quality standards included for single
case studies. Note. *Denotes
doctorate dissertation
Fig. 3 Percentage of CEC quality standards included for group
studies. Note. *Denotes doctorate dissertation
Discussion
This systematic review identified and summarized 10 studies that taught the use of core vocabulary within an AAC
intervention to individuals with developmental disabilities.
Although various systems (i.e., manual sign, PE, SGDs)
were used in the reviewed studies, each included the use
of core vocabulary as a dependent variable.
The first aim of the current review was to synthesize the
literature to evaluate the evidence base for interventions to
teach core vocabulary to individuals with language delays
and developmental disabilities. The current findings indicate a very limited research base for AAC interventions
aimed at teaching core vocabulary. Specifically, out of the
13
10 reviewed studies, only five were peer reviewed journal
articles, which highlights the need for further research,
given the popularity of core vocabulary based AAC systems in practice (AssistiveWare, 2023; Brydon & Pretorius, 2021; Thistle & Wilkinson, 2015; Tobii Dynavox
Global, 2023).
The second aim of this systematic review was to evaluate the quality of the literature. For the 10 studies that met
the inclusion criteria, only five studies met 80% or more of
the CEC quality standards. The CEC workgroup specified
that 100% of the criteria should be met to achieve acceptable quality standards for research supporting evidencebased practices (Cook et al., 2015a, b). Thus, these findings
indicate an unacceptable level of rigor and methodological quality based on current quality standards in the field
Review Journal of Autism and Developmental Disorders
Table 4 Item analysis of
CEC quality standards and
percentage included for singlecase studies
Citation
1
2
3
4
5
6
7
8 Total %
Bedwani et al. (2015)
41
*Hammond (2017)
82
*Karnes (2019)
96
Lal (2010)
50
*Mason (2016)
Snodgrass, et al. (2013)
50
96
Tan et al. (2014)
91
This table displays the number of each quality indicator item for the CEC Quality Standards (see Cook
et al., 2015a, b for the description of each numbered item) and the total percentage of indicators met by
each study. Shaded rectangles represent each sub item included (e.g., item 2.1, 2.2)
*
Denotes doctoral dissertation
Table 5 Item analysis of CEC quality standards and percentage included for group studies
Citation
1
2
3
4
5
6
7
8
Total %
Dorney & Erickson (2019)
58
*Riccelli-Sherman (2017)
83
*Willis (2020)
42
This table displays the number of each quality indicator item for the CEC Quality Standards (see Cook et al., 2015a, b for the description of each
numbered item) and the total percentage of indicators met by each study. Shaded rectangles represent each sub item included (e.g., item 2.1, 2.2)
*
Denotes doctoral dissertation
(Reichow et al., 2008; What Works Clearinghouse, 2017).
Moreover, these results indicate limits of the generality and
utility of interventions that aim to teach core vocabulary to
AAC users.
Further, articles that had higher quality indicator scores
(i.e., Karnes, 2019; Snodgrass et al., 2013; Tan et al., 2014)
employed three or more evidence-based intervention components (e.g., stimulus fading, systematic prompting, task
analysis, reinforcement). In contrast, studies with the lowest
quality indicators (Bedwani et al., 2015; Lal, 2010; Mason,
2016; Willis, 2020) each had issues with implementation
fidelity, internal validity, measurement, and data analysis,
which likely account for the mixed results reported. Overall, given the lack of clarity of effect, future high-quality
research is needed to help establish best practice standards
for the procedures selected to teach individuals to use AAC
systems. Doing so would help practitioners and teachers
more effectively support individuals learning to use AAC
systems.
Additionally, although all the articles included in this
review used at least one evidence-based teaching component, it should also be noted that some studies included nonevidence-based practices, such as motor planning (e.g., Bedwani et al., 2015; Karnes 2019; Mason, 2016). It is unclear
what the impact these procedures have on the acquisition
of core vocabulary use since these studies did not include a
specific dependent variable that measured motor behavior
related to AAC use (e.g., activation precision, activation
13
Review Journal of Autism and Developmental Disorders
error analysis). These findings are consistent with previous
research, since to date, there is a lack of evidence specific to
motor learning in research on AAC (Thistle & Wilkinson,
2015). Although AAC is classified as an evidence-based
practice (Steinbrenner et al., 2020; Wong et al., 2015), it
should also be emphasized that AAC is a set of tools that
requires the use of evidence-based teaching procedures to
achieve their purpose. Simply providing access to an AAC
system may not rise to the level of evidence-based practice if the intervention procedures for teaching the use of
the system do not have sufficient research showing their
effectiveness (Ledford et al., 2021). Thus, these findings
also highlight the importance of selecting evidence-based
teaching procedures (e.g., systematic prompting, time delay,
reinforcement) based on individual needs.
Lastly, these findings also indicate that caution should
be used until scientifically sound demonstrations of effectiveness have been published and replicated sufficiently to
meet the requirements specified in evidence-based practice
standards (Horner et al., 2005). When coupled with the
mixed findings from the analysis of certainty of evidence,
the outcome of the current review indicates lack of evidence.
Implications
In light of the current findings, discussion of the implications for future research and practice is warranted. First,
more research is needed to evaluate the outcomes of core
vocabulary targets within AAC interventions. The limited
current body of literature for AAC interventions that incorporate core vocabulary targets do not allow for firm conclusions to be made related to the characteristics of learners
who might benefit from these types of interventions. This
is also confounded by the lack of rigor seen in the reviewed
studies. Thus, more research is needed, and studies should
focus on the inclusion of quality standards for designing and
conducting research (Cook et al., 2015a, b; Ganz et al., 2023;
Reichow et al., 2008; What Works Clearinghouse, 2017).
Further, although half of the studies included in this
review incorporated only core vocabulary targets, research
indicates the need to include both core and fringe vocabulary
based on the individualized needs of the learner (Laubscher
& Light, 2020). Thus, practitioners should consider current
recommendations, such as selecting individualized communication targets and teaching a variety of vocabulary types,
until research provides further clarity on selecting vocabulary targets. Utilizing a standard set of core vocabulary may
not account for prerequisite skills, individual preferences,
or current communication needs (Laubscher & Light, 2020;
Thistle & Wilkinson, 2015). Additionally, only half of the
studies in this review included the use of a formal communication assessment to identify the participants’ current abilities and needs, however, a specific rationale for
13
the vocabulary selection was not provided for any of the
reviewed studies. In future research, it will be important to
conduct a thorough communication assessment that evaluates current functioning levels, abilities, and preferences
prior to selecting communication targets.
Lastly, a variety of evidence-based teaching components
were used across the included studies; however, the rationale
for selecting each component was unclear, which may be
important when considering the types of prompts selected
for an intervention (e.g., model, hand over hand, stimulus
prompting). For example, some of the studies included in
this review provided access to a variety of core words at the
start of the intervention whereas studies that used a more
systematic approach that involved teaching one core word
at a time, before introducing new targets. And further, one
studies (Karnes, 2019) included in this review used a systematic teaching approach that not only taught one core word
at a time, but also involved three phases of stimulus fading
(e.g., hiding the other vocabulary and slowly making them
visible) which might have impacted the levels of vocabulary acquisition achieved. For current practice, this review is
consistent with previous research, which highlights the need
to include effective evidence-based teaching strategies and
consideration for individual learner profiles when selecting
components for teaching (Ganz, 2015; McNaughton et al.,
2019; Light et al., 2019; Lorah et al., 2022).
Taken as a whole, these findings highlight the need for
consideration on how best to individualize interventions for
AAC systems, including consideration for the vocabulary
taught, and teaching components used, to ensure AAC interventions meet the needs of each individual and their unique
needs.
Limitations and Future Directions
Currently, it is unclear what learner prerequisite skills are
needed and what considerations should be made when
selecting core vocabulary words for AAC users. Previous
research has indicated a just-in-time approach may be useful
for vocabulary expansion (Laubscher & Light, 2020; Light
& McNaughton, 2012; Schlosser et al., 2016). Thus, future
research should evaluate this approach for targeting core
vocabulary.
Additionally, this review is limited by the lack of participant information provided and vocabulary selection,
which prevented in depth analysis of these specific variables.
Further, since most of the studies had mixed findings, it is
unclear what intervention components accounted for gains in
learner acquisition. Rigorous future research is needed that
provides more in-depth and assessment-based participant
information to help understand what intervention components best compliment learner characteristics and communication needs.
Review Journal of Autism and Developmental Disorders
Although some of the studies included in this review
reported gains in the use of core vocabulary, it is unclear
how these gains might compare to individualized vocabulary targets. Thus, future research is needed to help evaluate
acquisition, frequency of use, and maintenance of communication skills learned through AAC interventions that target
core vocabulary.
Lastly, our analysis is limited in that the current version of
the CEC quality standards only allows for analysis in terms
of the presence or absence of individual study qualities, and
do not specify the relative importance of individual items
for determining study rigor. For example, items such as
design and within-study variability may be more important
indicators for establishing strong evidence for experimental
control and the establishment of functional relations relative
to some other items. (Zimmerman et al., 2018). However,
establishing the importance of the individual quality indicators is outside the scope of this review, and future research is
needed to analyze the relative importance of study features
in determining overall quality of research studies. Because
the current review included a very small number of studies
with high quality standards, this kind of analysis would be
inconclusive. Additional research with a larger set of published studies is needed to provide guidance on predictive
study features.
Conclusion
In sum, this review summarizes the current research on the
teaching core vocabulary within AAC interventions and
highlights the needs for more rigorous research that aligns
with relevant quality standards. As research continues to
progress, these areas of concern should be prioritized to
ensure that services aimed at teaching the use of AAC systems are grounded in evidence-based practices and tailored
to the specific needs of the learner.
Funding Open Access funding enabled and organized by CAUL and
its Member Institutions
Declarations
Conflict of Interest The authors declare no competing interests.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article's Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
References
Achmadi, D., Kagohara, D. M., van der Meer, L., O’Reilly, M. F.,
Lancioni, G. E., Sutherland, D., & Sigafoos, J. (2012). Teaching
advanced operation of an iPod-based speech-generating device to
two students with autism spectrum disorders. Research in Autism
Spectrum Disorders, 6(4), 1258–1264. https://doi.org/10.1016/j.
rasd.2012.05.005
AssistiveWare. (2023). AssistiveWare’s core word boards. Retrieved
July 17, 2022, from https:// www. assistiveware. com/ learn- aac/
quick-communication-boards
Bell, H. (2012). Core vocabulary. The Encyclopedia of Applied Linguistics. https://doi.org/10.1002/9781405198431.wbeal0223
Bedwani, M. A. N., Bruck, S., & Costley, D. (2015). Augmentative
and alternative communication for children with autism spectrum disorder: An evidence-based evaluation of the Language
Acquisition through Motor Planning (LAMP) programme.
Cogent Education, 2(1), 1045807. https:// doi. org/ 10. 1080/
2331186x.2015.1045807
Beukelman, D. R., & Mirenda, P. (2005). Augmentative and alternative communication: Supporting children and adults with complex communication needs (3rd ed.). Paul H. Brooks Publishing.
Blackwell, C. L., Hulbert, C. M., Bell, J., Elston, L., Morgan, W., Robertshaw, B. A., & Thomas, C. (1989). A survey of the communication abilities of people with a mental handicap. The British
Journal of Mental Subnormality, 35(68), 63–71. https://doi.org/
10.1080/2331186x.2015.1045807
Bloom, P. (2000). How children learn the meanings of words. MIT
Press.
Bondy, A. S., & Frost, L. A. (1994). The picture exchange communication system. Focus on Autistic Behavior, 9, 1–19. https://doi.org/
10.1177/108835769400900301
Brydon, S., & Pretorius, E. (2021). Spotlight on core boards. All
Together Autism. Retrieved July 17, 2022, from https:// www.
altogetherautism.org.nz/spotlight-on-core-boards/
Carnett, A., Raulston, T. J., & Charpentier, J. (2019). The application
of Skinner’s analysis of verbal behavior for teaching communication skills to persons with developmental disabilities. Current
Developmental Disorders Reports, 6(3), 131–137. https://doi.org/
10.1007/s40474-019-00170-0
Cook, B., Buysse, V., Klingner, J., Landrum, T., McWilliam, R., Tankersley, M., & Test, D. (2015a). Council for exceptional children:
Standards for evidence-based practices in special education.
Teaching Exceptional Children, 46(6), 206–212. https://doi.org/
10.1177/0040059914531389
Cook, B. G., Buysse, V., Klingner, J., Landrum, T. J., McWilliam, R.
A., Tankersley, M., & Test, D. W. (2015b). CEC’s standards for
classifying the evidence base of practices in special education.
Remedial and Special Education, 36, 220–234. https://doi.org/
10.1177/0741932514557271
Crowe, B., Machalicek, W., Wei, Q., Drew, C., & Ganz, J. (2021).
Augmentative and alternative communication for children with
intellectual and developmental disability: A mega-review of the
literature. Journal of Developmental and Physical Disabilities,
1–42. https://doi.org/10.1007/s10882-021-09790-0
Davis, T. N., O’Reilly, M., Kang, S., Lang, R., Rispoli, M., Sigafoos,
J., ..., & Mulloy, A. (2013). Chelation treatment for autism spectrum disorders: A systematic review. Research in Autism Spectrum
Disorders, 7(1), 49–55. https://doi.org/10.1016/j.rasd.2012.06.005
13
Review Journal of Autism and Developmental Disorders
Dorney, K. E., & Erickson, K. (2019). Transactions within a classroombased AAC intervention with preschool students with autism spectrum disorders: A mixed-methods investigation. Exceptionality
Education International, 29(2), 42–58. https://doi.org/10.5206/
eei.v29i2.9401
Fenson, L., Marchman, V., Thal, D., Reznick, S., & Bates, E. (2007).
MacArthur-Bates Communicative Development Inventories:
User’s guide and technical manual (2nd ed.). Paul H. Brookes
Publishing.
Ganz, J. B. (2015). AAC interventions for individuals with autism spectrum disorders: State of the science and future research directions.
Augmentative and Alternative Communication, 31(3), 203–214.
https://doi.org/10.3109/07434618.2015.1047532
Ganz, J. B., Earles-Vollrath, T. L., Heath, A. K., Parker, R. I., Rispoli,
M. J., & Duran, J. B. (2012). A meta-analysis of single case
research studies on aided augmentative and alternative communication systems with individuals with autism spectrum disorders.
Journal of Autism and Developmental Disorders, 42(1), 60–74.
https://doi.org/10.1007/s10803-011-1212-2
Ganz, J. B., Morin, K. L., Foster, M. J., Vannest, K. J., Genç Tosun,
D., Gregori, E. V., & Gerow, S. L. (2017). High-technology augmentative and alternative communication for individuals with
intellectual and developmental disabilities and complex communication needs: A meta-analysis. Augmentative and Alternative
Communication, 33(4), 224–238. https://doi.org/10.1080/07434
618.2017.1373855
Ganz, J. B., Pustejovsky, J. E., Reichle, J., Vannest, K. J., Foster, M.,
Pierson, L. M., ..., & Yllades, V. (2023). A case for increased rigor
in AAC research: A methodological quality review. Education and
Training in Autism and Developmental Disabilities, 58(1), 3–21.
Gast, D. L., & Ledford, J. R. (2009). Single subject research methodology in behavioral sciences. Routledge.
Gevarter, C., O’Reilly, M. F., Rojeski, L., Sammarco, N., Lang, R.,
Lancioni, G. E., & Sigafoos, J. (2013). Comparing communication
systems for individuals with developmental disabilities: A review
of single-case research studies. Research in Developmental Disabilities, 34(12), 4415–4432. https://doi.org/10.1016/j.ridd.2013.
09.017
Hammond, N. (2017). Generalization of core vocabulary taught to children diagnosed with autism spectrum disorder using an augmentative communication device. [Doctoral dissertation, The Chicago
School of Professional Psychology].
Horner, R. H., Carr, E. G., Halle, J., McGee, G., Odom, S., & Wolery,
M. (2005). The use of single-subject research to identify evidencebased practice in special education. Exceptional Children, 71,
165–179. https://doi.org/10.1177/001440290507100203
Kagohara, D. M., van Der Meer, L., Achmadi, D., Green, V. A.,
O’Reilly, M. F., Lancioni, G. E., ..., & Sigafoos, J. (2012). Teaching picture naming to two adolescents with autism spectrum disorders using systematic instruction and speech-generating devices.
Research in Autism Spectrum Disorders, 6(3), 1224–1233. https://
doi.org/10.1016/j.rasd.2012.04.001
Karnes, A. J. (2019). Evaluating the effectiveness of motor planning
with core vocabulary: A behavior analytic account. [Doctorial
dissertation, University of Arkansas].
Lal, R. (2010). Effect of alternative and augmentative communication
on language and social behavior of children with autism. Educational Research and Reviews, 5(3), 119–125.
Lang, R., O’Reilly, M., Healy, O., Rispoli, M., Lydon, H., Streusand,
W., ..., & Giesbers, S. (2012). Sensory integration therapy for
autism spectrum disorders: A systematic review. Research in
Autism Spectrum Disorders, 6(3), 1004–1018. https://doi.org/10.
1016/j.rasd.2012.01.006
Laubscher, E., & Light, J. (2020). Core vocabulary lists for young
children and considerations for early language development: A
13
narrative review. Augmentative and Alternative Communication,
36(1), 43–53. https://doi.org/10.1080/07434618.2020.1737964
Ledford, J. R., Lambert, J. M., Barton, E. E., & Ayres, K. M. (2021).
The evidence base for interventions for individuals with ASD: A
call to improve practice conceptualization and synthesis. Focus
on Autism and Other Developmental Disabilities, 36(3), 135–147.
https://doi.org/10.1177/108835762110233
Light, J., & McNaughton, D. (2012). The changing face of augmentative and alternative communication: Past, present, and future
challenges. Augmentative and Alternative Communication, 28(4),
197–204. https://doi.org/10.3109/07434618.2012.737024
Light, J., McNaughton, D., Beukelman, D., Fager, S. K., Fried-Oken,
M., Jakobs, T., & Jakobs, E. (2019). Challenges and opportunities
in augmentative and alternative communication: Research and
technology development to enhance communication and participation for individuals with complex communication needs. Augmentative and Alternative Communication, 35(1), 1–12. https://
doi.org/10.1080/07434618.2018.1556732
Lorah, E. R., Holyfield, C., Griffen, B., & Caldwell, N. (2022). A systematic review of evidence-based instruction for individuals with
autism using mobile augmentative and alternative communication
technology. Review Journal of Autism and Developmental Disorders, 1–15. https://doi.org/10.1007/s40489-022-00334-6
Mason, P. H. (2016). Language acquisition through motor planning
(LAMP): Impact on language and communication development
for students with complex disabilities. [Doctoral dissertation, Boston College].
McNaughton, D., Light, J., Beukelman, D. R., Klein, C., Nieder, D., &
Nazareth, G. (2019). Building capacity in AAC: A person-centred
approach to supporting participation by people with complex communication needs. Augmentative and Alternative Communication,
35(1), 56–68. https://doi.org/10.1080/07434618.2018.1556731
Mirenda, P. (2017). Values, practice, science, and AAC. Research
and Practice for Persons with Severe Disabilities, 42(1), 33–41.
https://doi.org/10.1177/1540796916661163
Morin, K. L., Ganz, J. B., Gregori, E. V., Foster, M. J., Gerow, S.
L., Genç-Tosun, D., & Hong, E. R. (2018). A systematic quality review of high-tech AAC interventions as an evidence-based
practice. Augmentative and Alternative Communication, 34(2),
104–117. https://doi.org/10.1080/07434618.2018.1458900
Reichow, B., Volkmar, F. R., & Cicchetti, D. V. (2008). Development of the evaluative method for evaluating and determining
evidence-based practices in autism. Journal of Autism and Developmental Disorders, 38(7), 1311–1319. https://doi.org/10.1007/
s10803-007-0517-7
Riccelli-Sherman, A. (2017). Using a Core Vocabulary Intervention
to Improve Communication of Students Who Use Augmentative
and Alternative Communication (AAC) (Doctoral dissertation,
University of St. Francis).
Schlosser, R. W., & Koul, R. K. (2015). Speech output technologies in
interventions for individuals with autism spectrum disorders: A
scoping review. Augmentative and Alternative Communication,
31(4), 285–309. https://doi.org/10.3109/07434618.2015.1063689
Schlosser, R. W., Shane, H. C., Allen, A. A., Abramson, J., Laubscher,
E., & Dimery, K. (2016). Just-in-time supports in augmentative and alternative communication. Journal of Developmental
and Physical Disabilities, 28, 177–193. https://doi.org/10.1007/
s10882-015-9452-2
Shane, H. C., Laubscher, E. H., Schlosser, R. W., Flynn, S., Sorce, J. F.,
& Abramson, J. (2012). Applying technology to visually support
language and communication in individuals with autism spectrum
disorders. Journal of Autism and Developmental Disorders, 42(6),
1228–1235. https://doi.org/10.1007/s10803-011-1304-z
Shea, B. J., Reeves, B. C., Wells, G., Thuku, M., Hamel, C., Moran,
J., Moher, D., Tugwell, P., Welch, V., Kristjansson, E., & Henry,
Review Journal of Autism and Developmental Disorders
D. A. (2017). AMSTAR 2: A critical appraisal tool for systematic
reviews that include randomised or non-randomised studies of
healthcare interventions, or both. BMJ, 358, j4008. https://doi.
org/10.1136/bmj.j4008
Snodgrass, M. R., Stoner, J. B., & Angell, M. E. (2013). Teaching
conceptually referenced core vocabulary for initial augmentative
and alternative communication. Augmentative and Alternative
Communication, 29(4), 322–333. https://doi.org/10.3109/07434
618.2013.848932
Steinbrenner, J. R., Hume, K., Odom, S. L., Morin, K. L., Nowell, S.
W., Tomaszewski, B., Szendrey, S., McIntyre, N. S., YücesoyÖzkan, S., & Savage, M. N. (2020). Evidence-based practices for
children, youth, and young adults with Autism. The University of
North Carolina at Chapel Hill, Frank Porter Graham Child Development Institute, National Clearinghouse on Autism Evidence and
Practice Review Team.
Skinner, B. F. (1957). Verbal behavior. Prentice-Hall.
Sundberg, M. L., & Michael, J. (2001). The benefits of Skinner’s
analysis of verbal behavior for children with autism. Behavior
Modification, 25(5), 698–724. https:// doi. org/ 10. 1177/ 01454
45501255003
Tan, X. Y., Trembath, D., Bloomberg, K., Iacono, T., & Caithness, T.
(2014). Acquisition and generalization of key word signing by
three children with autism. Developmental Neurorehabilitation,
17(2), 125–136. https://doi.org/10.3109/17518423.2013.863236
Thistle, J. J., & Wilkinson, K. M. (2015). Building evidence-based
practice in AAC display design for young children: Current practices and future directions. Augmentative and Alternative Communication, 31(2), 124–136. https://doi.org/10.3109/07434618.
2015.1035798
Tobii Dynavox Global. (2023). Core First Communication Books.
Retrieved July 17, 2022, from https://www.tobiidynavox.com/
products/core-first-communication-boards
What Works Clearinghouse. (2017). Procedures and standards handbook (Version 4.0). Retrieved July 17, 2022, from https://ies.ed.
gov/ncee/wwc/
Willis, J. (2020). Improvement of the communication skills of students
with autism spectrum disorder and moderate to severe disabilities
receiving education in a self-contained setting. [Doctoral dissertation, Wilmington University].
Wodka, E. L., Mathy, P., & Kalb, L. (2013). Predictors of phrase and
fluent speech in children with autism and severe language delay.
Pediatrics, 131(4), e1128–e1134. https://doi.org/10.1542/peds.
2012-2221
Wong, C., Odom, S. L., Hume, K. A., Cox, A. W., Fettig, A., Kucharczyk, S., ..., & Schultz, T. R. (2015). Evidence-based practices
for children, youth, and young adults with autism spectrum disorder: A comprehensive review. Journal of Autism and Developmental Disorders, 45(7), 1951–1966. https://doi.org/10.1007/
s10803-014-2351-z
van der Meer, L., & Rispoli, M. (2010). Communication interventions
involving speech-generating devices for children with autism: A
review of the literature. Developmental Neurorehabilitation, 13,
294–306. https://doi.org/10.3109/17518421003671494
van der Meer, L., Didden, R., Sutherland, D., O’Reilly, M. F., Lancioni,
G. E., & Sigafoos, J. (2012). Comparing three augmentative and
alternative communication modes for children with developmental
disabilities. Journal of Developmental and Physical Disabilities,
24(5), 451–468. https://doi.org/10.1007/s10882-012-9283-3
van der Meer, L., Kagohara, D., Roche, L., Sutherland, D., Balandin,
S., Green, V. A., ..., & Sigafoos, J. (2013). Teaching multi-step
requesting and social communication to two children with autism
spectrum disorders with three AAC options. Augmentative and
Alternative Communication, 29(3), 222–234. https://doi.org/10.
3109/07434618.2013.815801
Zimmerman, K. N., Ledford, J. R., Severini, K. E., Pustejovsky, J. E.,
Barton, E. E., & Lloyd, B. P. (2018). Single-case synthesis tools
I: Comparing tools to evaluate SCD quality and rigor. Research in
Developmental Disabilities, 79, 19–32. https://doi.org/10.1016/j.
ridd.2018.02.003
Publisher's Note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
Apple iPad and iPod are touchscreen devices that can be installed with
speech-generating apps. They are products of Apple computer Inc.,
Cupertino, CA, www.apple.com.
13