Mistakes preschoolers make in multi-symbol utterances using AAC


Preschoolers learning to communicate via AAC systems typically start by using one symbol at a time. Many go on to construct 2–3 symbol utterances, but make mistakes along the way. In this study, the researchers looked back at data from a prior study to explore 10 three–four-year-olds’ errors when producing multi-symbol utterances. In total, they made errors on 45% of their utterances!

We’ll get to those errors, but first, some background. All the preschoolers had a speech sound disorder/delay diagnosis, although one child also had a secondary ASD diagnosis and another was diagnosed with cerebral palsy. During the intervention sessions, the kids used an AAC device (an iPad with Proloquo2Go) to describe videos, then the clinician briefly modeled the targets and facilitated play-based therapy for 20 minutes. Keep in mind that the preschoolers didn’t have access to the device outside of the study, and 8 of the 10 participants actually had no prior experience with AAC before the intervention.  

Because AAC literature has focused heavily on inversions (word order reversals), the researchers checked for other error patterns.

The Complexity Approach for Grammar_.png

The main takeaway? Inversions and omissions were more common than substitutions and additions overall, but there were differences across targets and—business as usual for AAC studies—there were differences across the children in the study.

So, what can we do with this information? For starters, when you collect data, think beyond the number of words in the utterance. Instead, try classifying the types of errors the students are making. Are they inversions, substitutions, omissions, or additions? We’d wager that you’d approach instruction just a little bit differently depending on the error type—and that type of modification to your instruction could make all the difference!

FYI: As we mentioned, data analyzed here was originally collected for a different study. Although the data set isn’t perfect, this is the first study we have that conceptualizes the errors these children might be making. Also, keep in mind these targets were chosen specifically for speakers of English, which has a Subject + Verb  + Object syntax structure.


Binger, C., Richter, K., Taylor, A., Williams, E. K., & Willman, A. (2019). Error patterns and revisions in the graphic symbol utterances of 3- and 4- year old children who need augmentative and alternative communication. Augmentative and Alternative Communication. doi:10.1080/07434618.2019.1576224

AAC carryover: Buy-in is only the beginning

One of the biggest frustrations for clinicians who support AAC are the devices that don’t get used. You know, the ones that sit in the cabinet unless you’re in the room, or the ones that parents ask you not to send home. There are a lot of factors that contribute to this kind of device abandonment (can’t you just picture a lonely device feeling sorry for itself?). We need to understand these factors, so we can focus our work on the key ingredients that will promote AAC device use and help students—and their support teams—be successful.  

You won’t be surprised by two of the most common caregiver-related barriers to device success: 

1)    The adults don’t know how to use the device (or, they lack operational competency).

This includes finding words, programming, troubleshooting, and navigating the device settings. Parents and teachers often report that they don’t get enough training in this stuff.

2)    The adults don’t have positive attitudes about the device (or, they lack buy-in).  

Specific aspects of buy-in can include considering the device the child’s voice and believing that it should be available at all times.

These two barriers are important, for sure, but how important? And what else are we missing? This study delved into this issue, focusing on the operational competency and buy-in of parents and teachers of school-aged (3–16 years) children with autism, and whether they related to how frequently the children’s AAC devices were used. The 33 children in the study all used a personally-owned PRC device or the related LAMP Words for Life app as their main method of communication at both home and school. To measure how much devices were used, the researchers analyzed data from PRC’s Realize Language feature across three school days and one weekend. Parent and teacher surveys were used to measure operational competency and buy-in.

The good news? Overall, buy-in and operational competency was high for everyone. The bad news? No one was using devices that much. In this group, teachers reported greater buy-in (or at least answered their surveys that way, but that’s a whole different topic...), but parents and teachers were equally comfortable operating the devices. The devices were used more frequently at school vs. home (over half of the kids didn’t use the devices at home at all). 


A big grain of salt here: the study looked at really a pretty small window in time (Is one weekend at your house representative of how your family works?), and only one device company—that uses a relatively complex language system—was in the mix. We also don’t know if looking at students with diagnoses other than autism would make a difference. Even so, it’s clear that something’s going on here. We can see that good intentions, valuing the device, and being trained in its use just isn’t enough. It looks like we need a broader conversation about barriers, including the practicalities of incorporating a device into daily activities and routines, especially at home. We definitely need to address operational competency and buy-in, but our families and other stakeholders are likely to need more support than that. The authors remind us to keep communication at the center of the conversation, rather than the technology. After all, the device is only the tool—communication is the point.


DeCarlo, J., Bean, A., Lyle, S., & Cargill, L. P. M. (2019). The Relationship Between Operational Competency, Buy-In, and Augmentative and Alternative Communication Use in School-Age Children With Autism. American Journal of Speech-Language Pathology. doi:10.1044/2018_AJSLP-17-0175

And more...

  • Accardo and colleagues provide an overview of effective writing interventions for school-age children with ASD. Most interventions took place in the classroom and used mixed approaches, combining “ingredients” like graphic organizers, video modeling, and constant time delay—a prompting strategy borrowed from ABA. Within the review, Tables 1 and 2 give an idea of what each one looked like, so check that out.

  • Baker & Blacher assessed behavior and social skills in 187 13-year-olds with ASD, intellectual disabilities (ID), or both. They found that having ID along with ASD was not associated with more behavior problems or less developed social skills as compared with ASD only.

  • Cerdán et al. found that eighth graders who had poor comprehension skills correctly answered reading comprehension questions more often when the question was followed by a rephrased, simplified statement telling them exactly what they needed to do.

  • Curran et al. found that preschool-aged children who are DHH and receive remote microphones systems in their homes have significantly better discourse skills (but no better vocabulary or syntax skills) than otherwise-matched children who don’t get those systems.

  • Facon & Magis found that language development, particularly vocabulary and syntax comprehension, does not plateau prematurely in people with Down Syndrome relative to people with other forms of intellectual disability. Language skills continue to show growth in both populations into early adulthood. (We’ve previously reviewed specific interventions that have resulted in language gains among older children and teens with Down Syndrome. )

  • Hu et al. suggest that computer-assisted instruction (CAI) can improve matching skills in school-age children with autism and other developmental disabilities. Although techy and exciting, CAI on its own isn’t enough—evidence-based instructional strategies like prompting and reinforcement have to be programmed in, too. This CAI used discrete trial training, and was more efficient (fewer prompts and less therapy time were needed for mastery!) than a traditional, teacher-implemented approach with flashcards.

  • Lim et al. found that the literacy instruction program MULTILIT was effective with school-age children with Down syndrome. MULTILIT combines phonics and sight word recognition instruction, geared toward children with students who are “Making Up Lost Time in Literacy” (MULTILIT; get it?). The program was implemented 1:1 for 12 weeks, and the students made gains in phonological awareness, word reading and spelling. MULTILIT has been investigated by the developers, but this is the first time it’s been studied by other researchers—and with kids with Down syndrome in particular.  Note: This article wasn’t fully reviewed because the training (provided only in Australia) is not available to the majority of our readers.

  • Muncy et al. surveyed SLPs and school psychologists and found that, in general, these professionals are underprepared to assess and treat children with hearing loss and other, co-occurring disabilities, and that they lack confidence in this area. Participants reported many barriers to valuable collaboration with other professionals, like audiologists (hint: there aren’t enough of them!), and that they want more training in this area.

  • Schlosser et al. found that 3–7 year old children with ASD accurately identified more animated symbols than static symbols. The animated symbols represented verbs; for example, depicting a person turning around versus a still line drawing of “turn around.” It makes sense to see action verbs—well—in action; however, researchers acknowledge we can’t make grid displays full of animated symbols since that could be overstimulating. The next step is to test the effects of animation on symbol identification with other more well-known symbols sets like PCS.

  • Scott et al. used science books and a signed dialogic reading program with an 11-year-old Deaf student, and found increases in the student’s ability to answer comprehension questions.

  • St John et al. found that 92% of their sample of children and adolescents with Klinefelter syndrome also had a communication impairment. Pragmatic, language, and literacy impairments were common, and the researchers described some speech impairments as well. Establishing a comprehensive communication profile for this group is important because we’re still learning about Klinefelter syndrome, which is caused by one or more extra X chromosomes.

  • Updates on PEERS, a structured social skills program for adolescents and young adults we’ve discussed before! Wyman & Claro used the school-based version of PEERS both with adolescents with ASD (the target audience) and those with intellectual disabilities (ID; an overlooked group in social skills research who may benefit nonetheless). Both groups of students improved their social knowledge, and the ID group (but not the ASD group) increased social interactions with friends outside of school. Meanwhile, Matthews et al. found that speeding up the traditional, clinic-based PEERS program, by offering it in 7 weeks (twice weekly sessions) instead of 14, didn’t reduce its effectiveness.

Accardo, A. L., Finnegan, E. G., Kuder, S. J., & Bomgardner, E. M. (2019). Writing Interventions for Individuals with Autism Spectrum Disorder: A Research Synthesis. Journal of autism and developmental disorders, 1-19. doi:10.1007/s10803-019-03955-9

Baker, B. L., & Blacher, J. (2019). Brief Report: Behavior Disorders and Social Skills in Adolescents with Autism Spectrum Disorder: Does IQ Matter? Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-03954-w

Cerdán, R., Pérez, A., Vidal-Abarca, E., & Rouet, J. F. (2019). To answer questions from text, one has to understand what the question is asking: Differential effects of question aids as a function of comprehension skill. Reading and Writing. doi:10.1007/s11145-019-09943-w

Curran, M., Walker, E. A., Roush, P., & Spratford, M. (2019). Using Propensity Score Matching to Address Clinical Questions: The Impact of Remote Microphone Systems on Language Outcomes in Children Who Are Hard of Hearing. Journal of Speech, Language, and Hearing Research. doi:10.1044/2018_JSLHR-L-ASTM-18-0238

Facon, B., & Magis, D. (2019). Does the development of syntax comprehension show a premature asymptote among persons with Down Syndrome? A cross-sectional analysis. American Journal on Intellectual and Developmental Disabilities. doi: 10.1352/1944-7558-124.2.131

Hu, X., Lee, G. T., Tsai, Y, Yang, Y., & Cai, S. (2019). Comparing computer-assisted and teacher-implemented visual matching instruction for children with ASD and/or other DD. Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-03978-2

Lim, L., Arciuli, J., Munro, N., & Cupples, L. (2019). Using the MULTILIT literacy instruction program with children who have Down syndrome. Reading and Writing. doi:10.1007/s11145-019-09945-8

Matthews, N. L., Laflin, J., Orr, B. C., Warriner, K., DeCarlo, M., & Smith, C. J. (2019). Brief Report: Effectiveness of an Accelerated Version of the PEERS® Social Skills Intervention for Adolescents. Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-03939-9

Muncy, M. P., Yoho, S. E., & McClain, M. B. (2019). Confidence of School-Based Speech-Language Pathologists and School Psychologists in Assessing Students With Hearing Loss and Other Co-Occurring Disabilities. Language, Speech, and Hearing Services in Schools. doi:10.1044/2018_LSHSS-18-0091

Schlosser, R. W., Brock, K. L., Koul, R., Shane, H., & Flynn, S. (2019). Does animation facilitate understanding of graphic symbols representing verbs in children with autism spectrum disorder? Journal of Speech, Language, and Hearing Research. doi:10.1044/2018_JSLHR-L-18-0243

Scott, J. A., & Hansen, S. G. (2019). Comprehending science writing: The promise of dialogic reading for supporting upper elementary deaf students. Communication Disorders Quarterly. doi:10.1177/1525740119838253

St John, M., Ponchard, C., van Reyk, O., Mei, C., Pigdon, L., Amor, D. J., & Morgan, A. T. (2019). Speech and language in children with Klinefelter syndrome. Journal of Communication Disorders. doi:10.1016/j.jcomdis.2019.02.003 

Wyman, J., & Claro, A. (2019). The UCLA PEERS School-Based Program: Treatment Outcomes for Improving Social Functioning in Adolescents and Young Adults with Autism Spectrum Disorder and Those with Cognitive Deficits. Journal of Autism and Developmental Disorders. doi:10.1007/s10803-019-03943-z

Diagnosing DLD when you don’t speak a child’s first language


We know that it’s best to assess children in their first languages. But, we simply don’t have access to measures or interpreters for all of the world’s languages. What’s a monolingual SLP to do?

New research supports what we’ve discussed previously: that by using parent questionnaires and measures of language processing, we can accurately diagnose language disorders in English language learners using only English measures. Li’el et al. recruited a sample of bilingual and monolingual Australian English-speaking 5- to 6-year-old children with and without developmental language disorder (DLD). “Bilingual” was defined as hearing English less than half the time at home. Parents completed a questionnaire and children completed the CTOPP nonword repetition and CELF-P2 recalling sentences subtests.

The researchers found that the parent questionnaire alone had the highest sensitivity and specificity (accuracy at ruling in and ruling out DLD). However, all of the assessments in combination still had good diagnostic accuracy, and it’s not a good idea to diagnose a child with only one test, so the authors recommend using more than one measure.

Overall, this study adds to evidence that by interviewing parents and using language processing tasks, we can do a pretty good job teasing apart a lack of English exposure from an underlying language disorder even if we can’t assess in a child’s first language.


Li’el, N., Williams, C. & Kane, R. (2018). Identifying developmental language disorder in bilingual children from diverse linguistic backgrounds. International Journal of Speech-Language Pathology. Advance online publication. doi: 10.1080/17549507.2018.1513073

And more...

Chester et al. enrolled school-aged children with ASD in group social skills training that included play (unstructured or semi-structured) for 8 weeks. They found that participants gained social skills (as rated by parents, teachers, and the children themselves) compared to waiting controls.  

Conlon et al. looked at narratives (via the ERNNI) produced by 8-year-old boys and girls with ASD and average nonverbal intelligence. While we know that children with ASD often struggle with narratives in general, there may be important gender-related differences. This study found that girls’ stories were more complete, included more information about characters’ intentions, and were easier to follow (i.e. they had better referencing).

Joseph used word boxes (a low-tech method using drawn rectangles and letter tiles) to teach sound segmentation, word identification, and spelling skills to three third graders with autism, and found that all children improved on sound segmentation and word ID and two children improved on spelling. 

Montallana et al. studied inter-rater reliability of the VB-MAPP Milestones and Barriers assessments. The VB-MAPP is commonly used to assess and plan intervention for children with ASD, but we haven’t known much about its psychometrics. While the milestones section had largely moderate to good reliability, agreement between raters on barriers was poor to moderate.  

Thirumanickam et al. found that a video-based modeling intervention was effective in increasing conversational turn-taking in a small number of adolescents with ASD who used AAC—BUT, only when provided with additional instruction (least-to-most prompting). They stated that for students with ASD, some level of prompting is likely required to engage in video-based interventions.


Chester, M., Richdale, A. L., & McGillivray, J. (2019). Group-Based Social Skills Training with Play for Children on the Autism Spectrum. Journal of Autism and Developmental Disorders. Advance online publication. doi:10.1007/s10803-019-03892-7

Conlon, O., Volden, J., Smith, I. M., Duku, E., Zwaigenbaum, L., Waddell, C., … Pathways in ASD Study Team. (2019). Gender Differences in Pragmatic Communication in School-Aged Children with Autism Spectrum Disorder (ASD). Journal of Autism and Developmental Disorders. Advance online publication. doi:10.1007/s10803-018-03873-2

Joseph, L. M. (2018). Effects of word boxes on phoneme segmentation, word identification, and spelling for a sample of children with autism. Child Language Teaching and Therapy34(3), 303–317.

Montallana, K. L., Gard, B. M., Lotfizadeh, A. D., & Poling, A. (2019). Inter-Rater Agreement for the Milestones and Barriers Assessments of the Verbal Behavior Milestones Assessment and Placement Program (VB-MAPP). Journal of Autism and Developmental Disorders. Advance online publication. doi:10.1007/s10803-019-03879-4

Thirumanickam, A., Raghavendra, P., McMillan, J. M., & van Steenbrugge, W. (2018). Effectiveness of video-based modelling to facilitate conversational turn taking of adolescents with autism spectrum disorder who use AAC. Augmentative and Alternative Communication, 34(4), 311–322.

Parent-reported outcome measure: Measuring what counts in AAC therapy

What outcomes are you measuring in your AAC therapy? Frequency of initiation, purposes of communication, number of symbols mastered? All important, but are we forgetting something here?


In order for AAC to be successful, it has to be valued by the family and be seen as improving the child’s participation in the family’s everyday life. Okay—so we all know this, but how do we actually measure and track these parent perceptions? Luckily, there is a (free!) parent-report outcome measure that can help. The Family Impact of Assistive Technology Scale for AAC (FIATS-AAC) is a relatively new tool that was developed to measure the impact of AAC on the lives of children and families.

This study found that the FIATS-AAC could capture improvements in children’s (3–17 years old) functioning—as rated by parents—in the first 6 and 12 weeks of therapy with a new device, with more change reflected in cases where the clinicians also noted progress. When change was expected to occur (as therapy progressed), the questionnaire was sensitive enough to show that change. Great data for your first periodic review? Parents and therapists on the same page? This is what we all want!

This tool is fairly new, but it can definitely be useful to SLPs looking for ways to involve families, identify important therapy outcomes, and measure short-term, meaningful change during AAC intervention.

Ready to take a closer look? You can access the questionnaire here for free!


Ryan, S. E., Shepherd, T. A., Renzoni, A. M., Servais, M., Kingsnorth, S., Laskey, C., ... & Bradley, K. (2018). Responsiveness of a parent-reported outcome measure to evaluate AAC interventions for children and youth with complex communication needs. Augmentative and Alternative Communication. Advance online publication. doi: 10.1080/07434618.2018.1520296

Throwback (2015): AAC and verbal speech–language therapy: a perfect multimodal pairing?

We all know that teaching minimally verbal children with ASD to use AAC doesn’t equate to giving up on spoken communication, but sometimes it feels that way. And to many parents, shifting all of our efforts to teaching a new mode of communication looks like we are waving a white flag. But what if, rather than choosing only one modality to focus on, there was a way to integrate spoken language and AAC instruction into one multimodal intervention to improve speech and language outcomes? And what if we had clear indicators of which children would respond well to this? That’s what these researchers aimed to explore. 

In this pilot study, the researchers targeted both high-tech AAC use and spoken language for 10 children with ASD ages 6­–11 who used fewer than 20 spoken words spontaneously. The intervention consisted of choosing 30 target words and practicing them in the following ways:

  • massed trial speech sound practice,

    i.e. providing models, physical prompts, and corrective feedback for specific speech sounds within the target words

  • joint book reading,

    i.e. reading books that included the target words and using cloze prompts to elicit productions

  • interactive routines with embedded AAC,

    i.e. modeling and encouraging production of target words on the child’s AAC device within a fun activity

  • and receptive matching trials

    i.e. completing multiple choice target word comprehension questions on a computer


And exciting news–the researchers found strong results! These minimally verbal school-age children with ASD learned to say new words over the course of the intervention. The children who responded best to the intervention were (no surprises here) those who at baseline communicated intentionally and frequently, had larger consonant inventories, and had higher verbal and oral imitation abilities. Rather than needing to choose either spoken or AAC, these researchers are finding promising results that incorporating both spoken and AAC modalities into intervention may lead to the best speech and communication outcomes for our students.

For further descriptions of intervention activities and their process for choosing target words, check out the full article!

Brady, N. C., Storkel, H. L., Bushnell, P., Barker, R. M., Saunders, K., Daniels, D., & Fleming, K. (2015). Investigating a multimodal intervention for children with limited expressive vocabularies associated with autism. American Journal of Speech-Language Pathology, 24(3), 438–459.

Building receptive vocabulary in complex communicators

It’s one of those “the rich get richer and the poor get poorer” situations: children with complex communication needs tend to miss out on opportunities to increase their vocabularies compared to typical peers. Then, as we know, that disadvantage can snowball over time, contributing to reduced comprehension and literacy skills, which limits vocabulary growth even more. A vicious cycle for sure. So what can we do to support our young complex communicators in learning new words, especially academic vocabulary?


In this new study, Yorke and colleagues found that direct instruction during shared book reading was a potentially* effective way to teach academic vocabulary to a trio of preschool-aged boys with various disabilities who used forms of AAC to communicate. If you’re wondering what counts as academic vocabulary for the preschool crowd, the experimenters focused on animal names, but note that the same intervention approach could potentially be used to teach all kinds of concepts.

Shared book reading is a great context for teaching words, for a lot of reasons. You’re sitting still (ish? Depends on the kid!), may have long periods of joint attention, and can focus on communication without lots of extra materials in the way. Plus, you, as the instructor, know what vocabulary you’re going to encounter, so you have a chance to find or pre-program the words in the child’s AAC system, if needed. But reading alone isn’t enough: we know that kids learn best when direct teaching elements (i.e., introducing the task, providing modeling, supported practice, and independent practice) are part of the process.

The authors targeted five words (animal names, previously unknown to the kids) in each of two nonfiction books. (Pro tip: they found earlier that teaching 10 items at a time was too many.) They used a scripted intervention plan, with all those excellent direct teaching pieces mentioned above. The paper’s Appendix walks you through all the steps of the intervention, complete with sample scripts for what to say, and explicitly describes the steps to decrease scaffolding during practice. They probed for understanding of the words using pictures from the book on a 2 x 2 grid (think of the PPVT—one target answer and three foils).

Basically, they did some really solid vocab instruction, and paired it with testing methods that don’t require a verbal response. The children in the study were all able to point to pictures, but a logical extension would be using an eye-gaze frame for kids who are limited in their motor abilities.

The children in the study learned the first set of words in 10–12 sessions (15 to 20 minutes each, done about three times per week), but that time was cut in half for the second set of words, showing that kids may learn how to learn words this way more effectively over time. They maintained their knowledge well over 4–6 weeks, and were able to generalize to new pictures of the same animals.

Need a bonus? During shared reading, kids are getting exposure to lots of language and early literacy concepts, in addition to the words you’re explicitly targeting. Efficient use of your all-too-brief intervention time! And although this study was done one-on-one, the authors note that you could try the same approach in a group setting, with the help of classroom staff if needed.


*The quality of the experimental design was compromised when the authors had to eliminate a planned third book/set of words from the study. Ideally, we want to see a treatment effect three times (so here, with three sets of vocabulary) to feel confident that it was effective; in this case, we only could see it two times.

Yorke, A. M., Light, J. C., Gosnell Caron, J., McNaughton, D. B., & Drager, K. D. R. (2018). The effects of explicit instruction in academic vocabulary during shared book reading on the receptive vocabulary of children with complex communication needs. Augmentative and Alternative Communication. Advance online publication. doi: 10.1080/07434618.2018.1506823.

Early verbs and inflections in children who use AAC

When developing therapy plans for kids who use AAC, it’s common to look at kids with typically developing language to decide what to work on next. But should we? Do kids who use SGDs to communicate develop early verbs and inflectional morphemes similarly to typically-developing children?

In this study, conversations between four 8–9-year-old children who used AAC and an adult were analyzed across a 10-month period. The conversations with adults were examined to see which verbs the kids used (ACTION verbs—John is playing versus STATE verbs—John is being silly), in which order, and whether they added inflection. Since the participants were just first learning to use verbs, their patterns were compared to children in a similar developmental period (1;6-3;0).

Compared to kids without disabilities, the participants:

  • used more action verbs than state verbs

  • used go, want, and like frequently

  • produced third-person singular -s less often and later than -ing and -ed

While the participants seemed to mirror typical kids, they did differ in one way—by NOT producing action verbs before state verbs, but rather producing both at the same time.

How does this help us? It gives us some idea of which verbs to target and in what order. For school-age kids with no cognitive impairment, we should target both action verbs and state verbs. As the authors point out, these kids are likely to already have the mental representations of these categories. So why aren’t they producing them?  That likely falls on us (verbs aren’t on their systems, low expectations, lack of appropriate instructions, etc.). For young kids, we should follow typical development and focus on action verbs before state verbs. With action verbs, we can then follow typical verbal inflection development by targeting -ing (swimming) and -ed (opened), followed by state verbs and third person singular -s (knows).

Although this study only included four participants, it can boost our confidence in following typical language patterns for children who use AAC, and it offers some guidance in an area that many SLPs find challenging—making the jump to verb usage and morphology.


Savaldi-Harussi, G., & Soto, G. (2018). Early verbal categories and inflections in children who use speech-generating devices. Augmentative and Alternative Communication, 34(3), 194–205.