web viewthe word order errors observed were omissions, ... (pecs) to graphic symbol ... athis...

Error Patterns of Five-Year-Old Children Using AAC Within Simple Rule Based

Messages

Lee Buenviaje

30 July, 2013

ERROR PATTERNS OF FIVE-YEAR-OLD CHILDREN USING AAC

Purpose: The current study is a post-hoc analysis of four 5-year-old children with highly unintelligible speech who are using graphic symbols to communicate simple sentences. This analysis focused on the word order error and self-correction patterns of the participants.Method: The word order errors observed were omissions, substitutions, inversions, and additions. The self-correction analysis focused on the accuracy, mode and timing of each child’s responses.Results & Conclusion: The word order analysis revealed that the most common error for three out of four participants was the omission of a word. However, there were no consistencies throughout the data that revealed a linguistic pattern to the children’s errors. The results of the self-correction analysis revealed that, with auditory feedback from the voice output, the children corrected more often right after they made an error on the AAC device with their corrected response moving closer to the target.

INTRODUCTION

A motor speech disorder is a disruption in the fine motor acts required for an

individual to have intelligible speech. Motor speech disorders can be due to muscle

weakness (dysarthria) or a disruption in the motor planning stage of speaking (apraxia),

however these disorders are not limited to these etiologies (ASHA). Some individuals

with severe motor speech disorders have speech that is significantly unintelligible, such

that they cannot meet their communication needs by only relying on their speech. In such

cases, augmentative and alternative communication (AAC) may be used to help a person

meet his or her communication needs. For children and adults with motor-speech

disorders, AAC gives them a mode to communicate with others. There are various forms

of AAC from the popular Picture Exchange Communication System (PECS) to graphic

symbol communication, which consists of pictures with labels. Graphic symbols are

critical for preliterate children because while they may not be able to read, they can

recognize the symbols and use them to communicate with others. There are also many

high tech devices available that produce voice output. While the technology of AAC has

become increasingly popular, there are still many questions concerning the mode and the

2


populations that rely on it for everyday communication. For children communicating

using AAC, there are many challenges. Not only are they learning a different mode of

communication but they are also still in the process of acquiring and developing their

primary language (Poupart et al 2013). Children who communicate using AAC are in the

process of language learning.

Hypotheses. One current AAC issue is the fact that those who communicate with

AAC have grown up immersed in a native spoken language; however, transferring the

knowledge of this language onto an AAC device is not an intuitive process, and pre-

literate children face multiple challenges in learning how to express themselves

linguistically when using AAC. While these hypotheses are all presented individually, it

is important to note that they are not mutually exclusive. Current hypotheses explaining

the challenges of language learning via AAC include the following:

The linguistic deficit hypothesis explains that individuals who use AAC have a

language deficit that limits them in their expressive language, which includes

AAC communication (Smith & Grove 2003).

The communicative efficiency hypothesis suggests that individuals who use AAC

use structures different from spoken language in an attempt to speed up the

process of communicating with graphic symbols (Smith & Grove 2003; Sutton et

al 2002).

The modality asymmetry hypothesis suggests that the individuals who use AAC

have difficulties communicating with graphic symbols because they are receiving

a different input (i.e., speech) than they are expected to use as an output (e.g., a

voice output device). Another component of this hypothesis is that the

3


individuals receive spoken language input but do not have an intelligible spoken

output (Smith & Grove 1999; Sutton et al 2002; Smith & Grove 2003; Binger &

Light 2007; Sutton et al 2009).

The modality specific hypothesis suggests that graphic symbols are themselves

linguistic in nature and have their own rules that separate them from spoken

structure (Trudeau et al 2007). This hypothesis suggests that structures reflect the

limitations of graphic symbol communication as opposed to the true ability of the

communicators (Sutton et al 2002).

The translation hypothesis states that utterances must be transposed from

internalized spoken language to the graphic symbol modality (Sutton et al 2009).

Thus, there is nothing inherent to the graphic symbol modality that may cause the

people who use AAC to communicate in a different way than they would speak;

their task is to learn how to translate what is in their internalized language onto

their AAC devices.

Single symbol and multi-symbol utterances. Graphic symbol communicators

have a tendency to create single symbol utterances more than mutli-symbol utterances

(Smith & Grove 2003; Blockberger & Sutton 2003; Binger & Light 2008). Although the

early goal for first-time graphic symbol communicators is to start using single symbol

utterances, it is important to teach children to move beyond this initial stage and progress

into the creation of multi-symbol messages using semantic-syntactic categories (Nigam,

Scholsser, & Lloyd 2006), just as children who rely on speech move from single- to

multi-word utterances. However, once individuals who use AAC advance from single to

multi-symbol utterances, these utterances are still shorter than their spoken language

4


counterparts. It is important to note that individuals who use AAC are capable of

producing multi-symbol messages. For example, Binger & Light (2007) observed

children communicating with a higher frequency of multi-symbol messages after

providing more inputs (such as modeling) to the children using the AAC devices.

Morphology and syntax in graphic symbol communication. All languages and

modes of communication are governed by rules. Morphology and syntax are keys to

being able to produce complex messages via graphic symbols (Sutton et al 2002).

Individuals who use AAC tend to exhibit a high frequency of word order errors (Smith &

Grove 2003). This may speak to the above noted hypotheses in two ways. For the

modality specific hypothesis this would mean that graphic symbols have different

linguistic rules than spoken language. For the translation hypothesis this could mean that

the children have not been taught how to correctly map mentally represented messages

onto their AAC devices. For example, the children have acquired the skill of recognizing

that an English sentence is constructed of a subject followed by a verb, but they may not

know how to transfer their internalized language onto their AAC device. Binger & Light

(2007) speak to the translation hypothesis when they mention that incorrect word order

patterns were corrected during the intervention process of their study.

Studies involving semantic-syntactic relations with people communicating

with AAC. The field of AAC has had multiple studies thus far involving semantic-

syntactic relations with a wide range of participants. In a study that involved adults

without disabilities using AAC (Sutton et al 2000) the first time graphic symbol users

adjusted their utterances to not adhere to correct word order, in order to make their

messages less ambiguous. These messages appeared to be ambiguous to the typically-

5


developed adults because the communication boards that were being used had a limited

amount of morphological markers available, which speaks to the fact that those who use

AAC may be linguistically limited because of their devices (Binger & Light 2008;

Blockberger & Sutton 2003). In other studies that have been done with typically

developing children (Poupart et al 2013; Sutton et al 2009; Sutton & Morford 1998) the

researchers observed that these children used correct word order when they were

speaking, but failed to consistently follow word order when using graphic symbols to

communicate the same structures.

Graphic symbol communication word order errors. One of the most common

word order errors exhibited with graphic symbol communication is the reversal of words

in two-term utterances, however this can be corrected during intervention (Binger &

Light 2008). It is important to note that when word order is violated during graphic

symbol communication, the children’s utterances have all of the correct vocabulary, they

are just not strung together adhering to the rules of spoken word order (Smith 1996).

This suggests that they know what they want to say, but have a different strategy as to

how they want to communicate their messages.

The translation hypothesis in relation to word order. Based on the translation

hypothesis, we would assume that word order errors cannot solely be blamed on the

graphic symbol mode of communication. These errors could also be because the children

have not yet been taught how to use the device and given sufficient models (Binger &

Light 2007).

The modality specific hypothesis in relation to word order. In opposition to

the modality specific hypothesis, we should expect to observe word order errors that are

6


not all applicable to one certain rule. The fact that researchers use participants that are

first time AAC users, and they are not all consistent in the graphic symbol mode presents

an argument against the proposal of graphic symbols being governed by their own

specific rules.

Rationale for current study. Previous literature in the field of AAC has

primarily focused on both typically-developing populations and people who have been

using AAC as a primary mode of communication. Most of these studies focus on the

participants to produce multi-symbol messages or interpret messages from a graphic

symbol utterance. For example, when asking participants to produce multi-symbol

messages, the researchers would show the participants a picture portraying an action

(e.g., girl pushes boy) and then instruct them to use graphic symbols to communicate

what was happening in the picture (Sutton et al 2010). When asking the participants to

interpret messages using graphic symbol utterances the participants would be presented

with multiple pictures with an equal amount of utterances, they would then be instructed

to assign a picture to the utterance that describes it (Sutton et al 2010). However, only a

minute section of each analysis has focused on the errors within the multi-symbol

utterances that the participants constructed. Therefore, the current study focused on

analyzing the error patterns of children with motor-speech disorders when using graphic

symbols to communicate. Specifically, this study aimed to answer two questions: (1) Do

the children’s incorrect productions adhere to a consistent rule or pattern? And (2) for

messages that are self-corrected, at what point in the message construction does the child

make the corrections (i.e. during the construction of the message or after the message is

complete)?

7


METHOD

General Procedures

This study was a post hoc analysis of a portion of the data from a larger study

conducted in the augmentative and alternative communication (AAC) laboratory at the

University of New Mexico (UNM). The larger study was a three-year investigation

designed to evaluate the effects of an AAC intervention on the graphic symbol

productions of preschoolers with severe speech disorders.

Participants

The current study included the first four children enrolled in the larger study.

These children were aged 5;0 to 5;11 and met the following entrance criteria: receptive

language within normal limits, as defined by scores < 1.5 SD below the mean on the Test

of Auditory Comprehension of Language-3(TACL-3; Carrow-Woolfolk, 1999), and

presence of severe motor-speech impairments as defined by less than 50% intelligible

speech in the “no context” condition of the Index of Augmented Speech

Comprehensibility in Children (IASCC; Dowden, 1997). In addition, participants were

required to have an expressive vocabulary of at least 25 words/symbols on the

Communicative Development Inventories (CDI; Fenson et al., 1993) via any

communication mode (speech, sign, AAC). See Table 1 for a list of participant

characteristics.

Table 1

Participant Characteristics Including Chronological Age, Sex, Disability, and Prior AAC Experience

Amy Benjamin Carmen Darryl

8


Chronological age (mo.) 5;10 4;11 5;1 5;9

Gender Female Male Female Male

Disability

Suspected ataxia

Severe speech disorder

Suspected CP


History of TBI;

Microdeletion of 7q11.22a



CDI (expressive vocabulary) 657 115 514 --

I-ASCC (no context/ context) 13%/52% 0%/3% 16%/55% 35%/68%

Note. TBI = Traumatic Brain Injury.aThis deletion has been associated with autism, but data are incomplete in the research literature at this time. Benjamin does not demonstrate symptoms of autism.

In addition to meeting criteria for speech and language abilities, the participants

were: (a) monolingual English speakers; (b) demonstrated comprehension of target

semantic-syntactic relations with at least 80% accuracy, based on Miller and Paul’s

[1995] guidelines); (c) received no prior intervention targeting semantic-syntactic

relations; (d) had vision and hearing functional for viewing graphic symbols and

participating in study activities; (e) had no diagnosis of autism spectrum disorder; (f) had

motor skills adequate to direct select with at least one finger on an SGD. Additional

measures collected purely for descriptive purposes included: (1)Mullen Scales of Early

Learning (Mullen, 1995), a test measuring various developmental domains including:

visual reception, fine motor skills, gross motor skills, receptive language and expressive

language; (2) Peabody Picture Vocabulary Test 4th Ed. (Dunn & Dunn, 2006), a test of

receptive vocabulary; (3) Leiter-R (Roid & Miller, 1996), a test of nonverbal intelligence;

(4) Vineland Adaptive Behavior Scales (Sparrow, Cicchetti & Balla, 2005), a parent

interview which measured functional adaptive behaviors across various domains. Of the 4

9


participants included in the proposed study, only Amy and Benjamin had prior AAC

experience. For the larger study, Dynamic Assessment was conducted purely for

descriptive purposes and did not affect inclusion/exclusion in the study.

Setting and Experimenter

Three different clinicians conducted augmented output (AO) sessions with the

participants. One was the principal investigator (PI) of the larger study, who has had

over 20 years of experience working with children who use AAC, and the other two were

speech-language pathology graduate research assistants who were supervised by the PI.

During the AO portion of the larger study, the experimenters administered the sessions

individually with each child in a quiet room at the UNM Speech and Hearing Clinic.

Materials and Targets

During the AO sessions, the clinicians and children sat either at a table or on the

floor with two Apple iPads™. Displayed on one iPad was the ProLoQuo2Go™ app

which contained the communication boards that the children used and the other iPad

contained videos depicting the targeted semantic-syntactic structures that the child

completed for that session. The communication boards (see Appendix A for example)

contained 39 graphic symbols that portrayed all of the vocabulary needed to complete the

task. Of the 39 graphic symbols, represented were 5 characters, 12 verbs (6 transitive and

6 intransitive), 10 adjectives, 10 objects and the pronouns “my” and “your”. The

backgrounds of the icons were color coded according to their categories (subjects-yellow,

verbs-green, adjectives-red, objects-blue). The icons used for the communication boards

were preinstalled on the ProLoQuo2Go™ app with the exception of the word “fall”

which was found on a Google image search. The top portion of the app included both a

10


message bar and delete button. The purpose of the message bar was for the children to be

able to construct an utterance and see the symbols that they had already chosen for their

message. The message bar in combination with the delete button gave the children the

option to edit their utterances both during and after they were complete. After the child

completed their message, they were then taught to push the message bar and have the

voice generating device play back their message.

Each of the videos was filmed on the iPad and then organized in the Photo

Manager Pro app. The videos were filmed in front of white photo paper with only the

characters and/or possessions being controlled by one of the experimenter’s hands. The

videos also included sound effects related to the actions in order to entice the children

and make the probes more enjoyable to watch. For example, the “Minnie falls” video

depicts Minnie wavering on a set of ropes saying “whoa” repeatedly until she falls off the

ropes and lets out an excruciating “ouch!” as she hits the floor.

For each target (agent-action, possessor-entity, attribute-entity, attribute-agent-

action, and agent-action-object) 10 randomized probe lists were created from the videos

that were filmed. For the target of action-object only 5 randomized probe lists were

created. Only transitive verbs were used for this target, which limited the available

combinations of vocabulary. Each randomized probe list contained 10 videos depicting

the target. For example, for the agent-action target, a probe set might contain videos of

Mickey crying, Minnie falling, etc. Additionally, 2 foils were included in each set to

ensure the children were not merely adhering to certain patterns on the communication

board (e.g., first hit a blue button, then hit an orange button). Foils consisted of videos

11


containing two characters, one character moved closer to the camera. The children were

then asked to identify the character being highlighted in the video.

Procedures during Probe Session

Probe sessions were conducted to track the child’s ability to produce the targeted

semantic-syntactic structures. Prior to each session, the clinician(s) set up the iPads as

well as a camera with a tripod to video record the session. Each session lasted

approximately 60 minutes, and each child completed multiple probe lists during each

session. Once the child was ready, the clinician selected the probe list assigned for that

session and played the videos. After each video the clinician provided a brief prompt.

For the agent-action, action-object, agent-action-object, and attribute-agent-action targets,

the experimenter played a given video and then asked, “What’s happening?” For the

remaining two targets – attribute-entity and attribute-agent-action, the experimenters used

the cloze sentence “This is ____.” If the children did not react to the prompts, the

clinicians would gesture towards the communication board as needed also adding “Tell

me here.” The experimenters recorded each child’s productions on a data collection sheet

during the session.

Interrater Reliability for Coding

20% of the data that was recorded during the sessions were re-analyzed by a blind

coder for reliability and the calculated Cohen’s kappa for all children (Amy, Benjamin,

Carmen and Darryl) was 1, .97, .97, and 1 respectively. The first author collected her

own set of data by watching the video recorded sessions and then compared her data with

the same 20% of data that was taken during the sessions.

12


The self-correction data was recorded by the first author and 20% of the sessions

were also recorded by a blind coder to ensure reliability.

Procedures for Self-correction Analysis

To collect the self-correction data the first author watched the video recordings of

all of the sessions for each of the four children and recorded the data on data collection

sheets. The experimenter coded the following for each production: mode of correction

(speech vs. iPad), time (was the correction made during the construction of the message

or after the child completed the message and heard the final utterance), and type of

correction (did the correction move closer towards the target or further away). The

examiner recorded all symbols the child selected during any given production, including

both deleted symbols as well as symbols included in the child’s final production.

Mode of correction. When examining the mode of correction the experimenter

analyzed the graphic symbols that were deleted both during and after utterance

construction. A spoken correction (S) was only recorded when the child used speech to

indicate verbally that a specific symbol was selected accidentally (e.g., “Mickey was a

mistake”). If the child selected an incorrect button, but said “no”, this was not counted as

a spoken correction, because there was no direct connection to what the child may be

saying “no,” to. For example, they may be saying it because they don’t like the character

or the action that is being portrayed. An AAC correction (A) was coded when the child

deleted any graphic symbol that was in the message bar, regardless of the length of the

message that was deleted (e.g. MINNIE RED HITS CHASES). A spoken and AAC

correction (B) was coded when the child made both a spoken and an AAC correction.

13

Elijia Buenviaje, 07/17/13,

We are in the process of doing this, is there anything else you think I should add right here?


Timing of correction. Examining for time of correction was determined based

on the timing of a graphic symbol change. A message was coded as “before the message

bar” when the child corrected his/her utterance prior to pressing the message bar to

indicate his/her final message (e.g., MINNIE HITS THROWS). A message that is self-

corrected “after the message bar” is when the child pressed the message bar to indicate

that he/she was finished with the message, and then he/she edited the final message after

hearing the voice output from the device.

Accuracy of correction. A correct self-correction was when the child’s final

utterance resulted in the correct target (e.g., for the target “Minnie throws”, MICKEY

MINNIE THROWS). A correction was coded as positive but incorrect (+) when the

corrected symbol(s) were closer to the target (e.g., “Minnie throws”, MICKEY MINNIE

HITS). A non-positive (-) self-correction resulted when the production moved further

from the target (e.g., for “Minnie throws”, MINNIE MICKEY HITS) or the new symbol

was the same as the previously deleted symbol (e.g., for “Minnie throws”, MINNIE HITS

HITS).

Procedures for Word Order Analysis

Using the data recorded from the self-correction analysis, the experimenter

analyzed all data marked as incorrect (child did not produce the target structure). Each

error was analyzed individually as opposed to being analyzed per target. If there were

two errors for one target, each would be counted individually instead of counting the

whole target as one error. Each error was categorized as one of the following: omission,

substitution, addition, or inversion. An omission was recorded when the child failed to

mention a symbol that was part of the target (e.g., MINNIE instead of MINNIE FALLS).

14


A substitution was recorded when the child’s message contained the correct number of

symbols, but they were not the correct target (e.g., MINNIE HITS instead of MINNIE

FALLS). An addition was recorded when the child’s message contained more symbols

than the number of symbols that were in the correct target (e.g., MINNIE FALLS

CHASES instead of MINNIE FALLS). An inversion was recorded when the child’s

message contained the correct number of symbols but in the wrong order (e.g., FALLS

MINNIE instead of MINNIE FALLS).

RESULTS

Word Order Analysis

The word order analysis revealed that three out of the four participants (Amy,

Benjamin, and Darryl) had omissions (71%, 58%, and 51% respectively) as their primary

error followed by substitutions (19%, 33%, and 21%) as their second most common error.

However, one participant did not follow this pattern. Carmen deviated from the other

three children in the fact that he/she did not have omissions as the primary error.

Carmen’s error pattern, from least to greatest was inversions (40%), omissions (33%),

substitutions (16%) and additions (11%). A further look into the omission data reveals

that there is not a common part of speech that is omitted most often across all

participants. See APPENDIX B for graphs pertaining to each individual.

15


Inversions26%

Substitutuions19%

Additions9%

Verbs19%

Adjectives55%

Nouns26%

Distribution of Errors for all Partic-ipants

Self-Correction Analysis

The results of the self-correction analysis revealed consistent patterns across all

participants for both mode and time of correction. While the numbers for accuracy of

correction are not as robust, they show a pattern of all of the children’s corrections

moving toward the correct answer, or being corrected to the exact correct answer. The

results for mode of correction show that all of the children stayed within of the mode of

AAC while making their corrections. However, Amy did make a significant amount of

corrections with her spoken language as well. Graphs depicting this data are shown

below. The children also had higher numbers for correcting their utterances right after

they made a mistake as opposed to waiting to hear the utterance as a whole to wait and

correct themselves.

16


Amy Benjamin Carmen Darryl0

20

40

60

80

100

Corrections in Relation to the Target

% not positive% positive% correct


102030405060708090

100

Mode of Correction

% Both% AAC% Spoken

17



102030405060708090

100

Time of Correction

% after final message% right after

DISCUSSION

Based on the word order data it can be determined that no overarching rule

governed the errors that the children are making. This could possibly work against the

modality specific hypothesis in the fact that if graphic symbols were linguistic nature,

then each child’s errors would follow the same rule, which was not the case based on the

different errors that each child made. While the fact that three of the four children did

have the same most common and second most common error, it is important to note that

the omissions of these three children did not have the same profiles. For example, while

Amy had a close to even distribution of omissions between verbs (23%), adjectives

(39%), and nouns (38%), the other two children did not exhibit the same distribution.

Benjamin had a distribution of omissions between verbs (7%), adjectives (15.5%), and

nouns (77.5%), and Darryl’s distribution was verbs (15.5%), adjectives (69%), and nouns

(15.5%). These errors are not unified at all, and thus display that the errors are not being

represented through a pattern.

18


Do these numbers belong more in the results or discussion section?


Trudeau et al 2007 states that “The modality-specific hypothesis suggests that biases specific o the visual-graphic modality influence the construction of graphic symbol utterances.” This just mentions the modality, not whether its specific to each individual or rather an overarching rule.


The self-correction analysis revealed that the majority of the children remained in

the same mode throughout the whole task. That is, they made their corrections via AAC

far more often than through spoken language. The timing of their corrections revealed

that the voice output may have helped them realize that they selected the wrong symbol.

For example, if the children were mapping their internalized language onto the device,

they may select the wrong button and then after hearing the voice output, the auditory

feedback may have cued them that they did not choose the word that they wanted. The

accuracy of corrections revealed that these children were making beneficial corrections.

Limitations and Future Directions

The largest limitation of the current study was the small number of participants.

More participants need to be studied in order to make more valid conclusions from a

larger pool of children. In the future we will also be examining the patterns of children

younger than age five under the exact same criteria. Analysis of younger children may

help develop a better understanding of if there is a timeline or specific age in which

children’s graphic symbol communication skills develop.

Another limitation to the current study would be the difference in cognitive load

for the children across all of the categories and, furthermore, across all of the sessions.

Cognitive load refers to the amount of work that has to be done within an individual’s

working memory during a given task. Cognitive load for a new activity is high because

the individual is constantly focusing on all of the details pertaining to the new activity.

However, when an individual is doing an everyday activity, that individual’s cognitive

load is low because they don’t have to completely focus on doing that activity because

they are used to doing it. An example for a high cognitive load would be going to your

19


first day at a new school. When you arrive you are only focusing on getting to your first

class, as opposed to thinking about your whole day. However, this once high cognitive

load activity gets easier because by going to school on a day by day basis you know

exactly where all of your classes are and can focus on more than where you need to go.

More examples of high to load cognitive load tasks are typing and driving, they are hard

at first but after thorough practice they become second nature.

Cognitive load is a limitation to this study because all of these children are using

an AAC system that they have had no prior experience with. Furthermore, two of the

participants have had previous experience with AAC while the other two participants

were using AAC for the first time. This also affects the children’s data because as they

go on throughout the sessions and targets their cognitive load may be decreasing due to

exposure to the task. Therefore, a further examination of the children’s chronological

results needs to be done in order to determine if exposure to the task decreases the

cognitive load and therefore helps the child communicate the target with more accuracy

or less self-correction.

20


APPENDIX ACommunication Board

21


APPENDIX BWord Order Errors for each Participant

Inversions6%

Substitutuions19%

Additions4%Verbs

23%Adjectives

39%

Nouns38%

Distribution of Errors for Amy

Inversions7%

Substitutuions33%

Additions2%

Verbs7%Adjectives

15.5%

Nouns77.5%

Distribution of Errors for Ben-jamin

22


Inversions40%

Substitutuions16%

Additions11%

Verbs 21%

Adjectives76%

Nouns3%

Distribution of Errors for Carmen

Inversions8%

Substitutuions22%

Additions20%

Verbs15.5%

Adjectives69%

Nouns15.5%

Distribution of Errors for Darryl

23


References

Binger, C. & Light, J. (2007). The effect of aided AAC modeling on the expression of

multi-symbol messages by preschoolers who use AAC. Augmentative and

Alternative Communication, 23(1), 30-43.

Binger, C. & Light, J. (2008). The Morphology and Syntax of Individuals who use

AAC: Research Review and Implications for Effective Practice. Augmentative

and Alternative Communication, 24 (2), 123-138.

Blockberger, S. & Sutton, A. (2003). Towards linguistic competence: The language

experiences and knowledge of children with extremely limited speech. In J.

Light, D. Beukelman, & J. Reichele (Eds), Communicative competence for

individuals who use augmentative and alternative communication. Baltimore,

MD: Paul H. Brookes.

Nigam, R., Schlosser, R., & Lloyd, L. (2006). Concomitant use of the matrix strategy

and the mand-model procedure in teaching graphic symbol combinations.

Augmentative and Alternative Communication, 22 (3), 160-177.

Poupart, A., Trudeau, N., & Sutton, A. (2013). Construction of graphic symbol

sequences by preschool-aged children: Learning, training, and maintenance.

Applied Psycholinguistics, 34 (1), 91-109.

Romski, M., Sevcik, R., Adamson, L., Cheslock, M., Smith, A., Barker, R., Bakeman, R.

(2010). Randomized comparison of augmented and nonaugmented language

interventions for toddlers with developmental delays and their parents.

Journal of Speech, Language, and Hearing Research, 53 (1), 350-364.

Smith, M. (1996). The medium or the message: A study of speaking children using

24


communication boards. In s. von Tetzchner & M.H. Jensen (Eds), Augmentative

and alternative communication: European perspectives (pp. 119-136). San

Diego, CA: Singular Publishing Group.

Smith, M. & Grove, N. (1999). The bimodal situation of children learning language

using manual and graphic signs. In F.T. Loncke, J. Clibbens, H. H. Arvidson, 7

L. L. Lloyd (Eds), Augmentative and alternative communication: New

directions in research and practice (pp. 8-30). London: Whurr Publishers.

Smith, M. & Grove, N. (2003). Asymmetry in input and output for individuals who

use augmentative and alternative communication. In J. Light, D. Beukelman,

& J. Reichle (Eds), Communicative competence of individuals who use

augmentative and alternative communication. Baltimore, MD: Paul H.

Brookes.

Soto, G. (1999). Understanding the impact of graphic sign use on the message

structure. In F.T. Loncke, J. Clibbens, H.H. Arvidson, & L.L. Lloyd (Eds),

Augmentative and alternative communication: New directions in research and

practice (pp. 40-48). London: Whurr Publishers.

Sutton, A., Gallagher, T., Morford, J., Shahnaz, N. (2000). Relative clause sentence

production using augmentative and alternative communication systems.

Applied Psycholinguistics, 21 (4), 473-486.

Sutton, A., & Morford, J. (1998). Constituent order in picture pointing sequences

produced by speaking children using AAC. Applied Psycholinguistics, 19 (4),

525-536.

25


Sutton, A., Morford, J., & Gallagher T. (2004). Production and comprehension of

graphic symbol utterances expressing complex propositions by adults who

use augmentative and alternative communication systems. Applied

Psycholinguistics, 25 (3), 349-371.

Sutton, A., Soto, G., & Blockberger, S. (2002). Grammatical issues in graphic symbol

communication. Augmentative and Alternative Communication 18(1), 192-

204.

Sutton, A., Trudeau, N., Morford. J., Rios, M., & Poirier, M. (2010). Preschool-aged

children have difficulty constructing and interpreting simple utterances

composed of graphic symbols. Child Language, 37, 1-26.

Trudeau, N., Sutton, A., Dagenais, E., Broeck, S., & Morford, J. (2007). Construction of

graphic symbol utterances by children, teenagers, and adults: The effect of

structure and task demands. Journal of Speech, Language, and Hearing

Research, 50, 1314-1329.

Trudeau, N., Sutton, A., Morford, J., Cote-Giroux, P., Pauze, A., & Vallee, V. (2010).

Strategies in construction and interpretation of graphic-symbol sequences by

individuals who use AAC systems. Augmentative and Alternative

Communication, 26 (4). 299-312.

26

web viewthe word order errors observed were omissions, ... (pecs) to graphic symbol ... athis...

Documents