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Broadening the Scope of AAC Design: The Development of an AAC Reading System
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The Problem

How do we help students who require AAC to read aloud connected text in books?

This research was developed out of a desire to create an easier way for students who require AAC to learn to read aloud the connected text in mainstream books through AAC design. Research into developing literacy skills for students who require AAC is still a relatively new field. However, there is consensus that these students are at risk of not developing functional literacy and experiencing associated disadvantages:

Several factors may contribute to students being at risk of poor literacy outcomes including:

When students reach school age, speech pathologists and educators face a dilemma of how to teach literacy skills to students who require AAC:

Alternate methodologies for teaching students who require AAC have been developed for:

These skills are essential foundational literacy skills and are correlated with positive literacy outcomes for students, so it is unsurprising that these have been the initial focus of research.

Learning to read connected text in books is the important next step in instruction to support the transition from a cognitive focus on decoding text to reading with more automatic word recognition and a greater focus on reading comprehension. Supporting students to take this next step through reading aloud connected text in books is the focus of this research.

Although the ultimate goal for all students, including students who use AAC, is to read silently, reading aloud is an important instructional stage for students as they are developing reading proficiency because:

High tech AAC systems consisting of voice output combined with dynamically configured grids appear to be the most logical AAC choice for this task, however, existing vocabulary layouts in AAC systems are not optimised for reading aloud:

Developing an efficient vocabulary layout is critical to AAC design for reading. When reading, students who require AAC have the additional processing demands of translating text into meaning to select the correct symbol whilst their peers with natural speech can initially only focus on translating text to sound (Erickson et al., 2008). This means that students who require AAC must attend to both decoding and comprehending the word simultaneously even when they are just starting to learn to decode. Symbol navigation must therefore be designed to be as effortless as possible so that all the student’s cognitive resources can be applied to the complex task of reading the text. Positive early experiences of reading success are critical for motivating students to persevere with reading, particularly in the early stages when the process is effortful.

Of equal importance is the ease of vocabulary entry. Without a better method of entering vocabulary there is a danger that the task of entering book vocabulary will be abandoned and students will miss out on valuable opportunities to practise their reading skills using the connected text in books.

Stanovich (1986) describes the Matthew effect where students who enjoy reading read more and become more proficient whilst students who dislike reading read less and have a slower rate of improvement. This becomes a vicious cycle and the gap in abilities between the two types of students widens. Avoiding the negative path of the Matthew effect for students who require AAC, necessitates the development of AAC methodologies to effectively support reading aloud a variety of texts without burdening caregivers and educators with time-consuming vocabulary entry.

This research describes the development of a new AAC system specifically designed to meet the communication and vocabulary demands of reading aloud connected text in books.

Searching the Literature

A literature review was conducted to examine how AAC was being incorporated into literacy instruction, with a particular emphasis on examining how AAC systems with speech output technology were being utilised to inform future AAC design.

The following databases were searched:

The search terms were “augmentative and alternative communication” AND

The original search period was articles up to the year 2014. An additional hand search of the Augmentative and Alternative Communication (AAC) Journal from 1985 to 2014 was also completed. An ancestor search of all included articles was also conducted. For each dissertation a computer search was also conducted of the author’s name to determine whether there was a published journal article.

Inclusion criteria:

If a journal article and dissertation were located on the same topic by the same author, the dissertation was excluded as the journal article had been subjected to peer review.

The methodology for determining inclusion/exclusion was:

The search yielded 39 journal articles, of which 10 met the inclusion criteria:

The search yielded 355 dissertations , of which seven met the inclusion criteria:

Subsequently 4 were excluded because the content also appeared in a journal article:

Table 1: Summary of participant characteristics

There were 42 participants across the studies, 26 (62%) had speech output technology. The age range was 4-21 years. All participants were classified as having severe communication impairments (SCI).

Two studies made their participants’ speech output technology available for communication and responses during intervention:

One study explicitly incorporated their participant’s speech output technology into instruction:

Table 2: Summary of the intervention methods and materials used in instruction

Review of the included studies revealed three broad approaches to adapt literacy instruction:

Adapt input and output methods:

Nonverbal reading approach:

Integrate the participant’s speech output technologies into instruction:

Since completing this research in 2014, there have been additional papers published with a greater emphasis on using technology including AAC systems to support literacy skills (Ahlgrim-Delzell, Browder, & Wood, 2014), and incorporating iPad apps into literacy instruction (Ahlgrim-Delzell, Browder, & Wood, 2016). In addition, there have been papers specifically examining the redesign of AAC systems to support sight word acquisition (Caron Light, & McNaughton 2020; Caron, Light, & McNaughton, 2021). Mandak, Light and Boyle (2018) and Yorke, Gosnell Caron, Pukys, Sternad, Grecol, & Shermak (2020) also provide a summary of current literature on the efficacy of literacy intervention for students who require AAC in their recent systematic reviews. These reviews examined the efficacy of approaches to support single word reading (Mandak et al., 2018) and a broader review of early reading interventions (Yorke et al., 2020). Both these papers include a review of several articles published after this literature review was completed. Despite the increase in research, the focus is predominantly on supporting reading at a single word level or sentence level rather than investigating how the process of reading connected text in books can be facilitated.

Accepting that we had to create a completely new design

The current literature provides valuable insights into how to successfully adapt literacy tasks for students who use AAC, but little guidance on how to address vocabulary configuration for reading connected text in books. Our next task was to draw on this knowledge base of existing literacy intervention and AAC design and then figure out how to adapt it to meet the communication and instructional demands of reading aloud connected text.

Based on our research we knew we needed a system where:

The Solution

When considering how to speed up vocabulary access and vocabulary entry, it occurred to us that we have one distinct advantage over AAC systems used for spoken conversation – we always know what word will be spoken next because all the words are presented in order in the book text.

The key to the AAC system design was to develop a method of parsing the text in the books so that that the AAC system always knows the current word, and the meaning of the word in the context of the current sentence of the text.

Parsing the text of the book provides several advantages:

Once we had successfully developed a methodology to parse the text in books, the next challenge was how to optimise the symbol layout for the text. The goal was to always display the base symbol for the word on the grid.

Drawing on our knowledge of existing grid layouts in AAC systems, our initial attempt involved:

Although this methodology initially looked promising when using books with a limited amount of text, the methodology failed when applied to texts with larger passages of text:

At this point we had to suspend our preconceptions of vocabulary layout which were constrained by existing AAC technologies, primarily designed for effective communication in conversation.

For reading, a completely new way of displaying vocabulary was required.

Through prototyping and repeated testing with book data we determined that the sheet layer model was the best method of storing and displaying vocabulary for reading:

The cell position assigned to a word is determined by three factors:

In the AAC Reading System the Fitzgerald classification of words is represented by a series of layers which includes a verb layer, noun layer, adjective and adverb layer, pronouns and people layer and a miscellaneous layer for all other words that do not fit within the other layers.

The following process is used to assign words to cells:

For example, the words “use”, “user” and “useful” are all semantically related words but have different word classes so the words appear on different layers but occupy the same cell position. The sheets and layers displayed dynamically change on a word-by-word basis as the student reads the text of the book.

Grouping related words in the same cell position and in their grammatically correct layers reduces learning load by ensuring similar words appear in a single predictable location. The sheet and layer data structure and the predictable nature of the text enables the Reading System to present every word in the English language (and most other languages) in a way that is accessible in one or two button presses, with most words accessible with one button press. Combined with the consistency of location for each word this substantially improves reading fluency.

This system also makes it possible to display a symbol that is semantically congruent with the meaning of the word in the context of the sentence, for example the different meanings of words in different word classes such as the noun ‘spy’ (the person) and the verb ‘spy’ (the act of watching another person’s actions).

Provision of semantically congruent symbols enhances reading fluency by providing symbols that make sense in the context of the sentence which reduces the symbol search time. It also supports reading comprehension and vocabulary expansion by providing an accurate depiction of the meaning of the word in the specific context of the current sentence.

We are currently working on programming the system to have an overlay layer displaying symbols adjacent to the target symbol, that contain similar graphemes to the target word. So for example, next to cat you might also have cot, bat and cab. This will reduce the temptation to only decode the first grapheme in a word and then guess. It will also provide information about error patterns for the student which may guide further instruction.

Summary

Many factors contribute to students who require AAC being at risk of literacy difficulties. Difficulty participating in instruction is a factor that can be addressed through both instructional design and design of AAC systems. This research sought to extend the existing literature to examine how AAC systems could be redesigned to support reading aloud the connected text in books. Through redesign it was possible to develop a system that will enable students to read aloud whilst minimising the cognitive load associated with symbol navigation.

There is still considerable research needed to examine the efficacy of this approach for students, however we hope that this presentation will stimulate research and discussion on how AAC design may be adapted to ensure that we maximise the ability of students who require AAC to participate in instruction.

References

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Watch a short (3 minute) video showing Aacapella Read in action.

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Conference Declaration

On completion of the research and development phase, this research will become a commercial product.

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— Acknowledgements —

We would like to acknowledge and thank Pearson in the UK and Australia for their interest, support and co-operation and for allowing us to use their Bug Club readers throughout the development of
read by aacapella

We would also like to thank the following businesses for their support:
Symbols Worldwide Limited, UK, for the use of their Widgit symbol set
Acapela Group S.A., Belgium, for the use of their synthesised voices