updated PhonoNet for SRCLD and pubs

rpomper · rpomper · commit 23e9b7d5be71 · 2025-05-13T15:35:26.000-04:00
diff --git a/_bibliography/papers.bib b/_bibliography/papers.bib
@@ -4,6 +4,42 @@
 @string{aps = {American Physical Society,}}
 @string{apa = {American Psychological Association,}}
 
+@article{Infer,
+  abbr={JSLHR},
+  title={Inferring Word Class and Meaning From Spoken and Written Texts: A Comparison of Children With and Without Developmental Language Disorder},
+  author={McGregor, K. K. and Pomper , R. and Eden, N. and Appenzeller, M. and Arbisi-Kelm, T. and Polese, E. and Reed, D. K.},
+  abstract={Purpose: The aim of the study was to determine the ability of children with developmental language disorder (DLD) to infer word class and meaning from text and to document variations by word class (noun, verb, adjective) and modality (listening, reading). We also asked whether the children could integrate global cues across the entire passage as well as local cues from the immediate sentence frame to support inferences. Method: Fourth graders with DLD (n = 28) and typical language development (TLD; n = 41) read and listened to expository texts and guessed the noun, verb, and adjective removed from each. Adults (n = 20) completed the task to establish a baseline of correct responses. We used latent semantic analysis (LSA) to determine the semantic fit of the responses to the texts and to determine whether global cues were more difficult for children with DLD than local cues. Results: The DLD group was 24% less accurate than the TLD group. In both diagnostic groups, accuracy varied by word class (nouns > adjectives > verbs) but not modality (reading = listening). Word class errors were rare, and errors of semantic fit were frequent. LSA cosines were higher for correct responses relative to the passage as a whole than the immediate sentence frame, suggesting that both groups mined the more extensive information in the global cues to support inferences. Compared to the TLD group, the DLD group tended to make “worse” errors: repeating words from the sentence frame or coming up with no response at all. Accuracy in the DLD group, but not the TLD group, was related to vocabulary knowledge. When the two groups were collapsed, scores on verbal short-term/working memory and sustained attention also predicted performance, but weaknesses in these aspects of executive function on the part of individuals with DLD did not fully explain the difference between the performance of the DLD and TLD groups. Conclusions: Whether listening or reading, fourth graders with DLD are less able to infer word meaning from texts than their age-mates. The problem reflects, in part, deficits in executive function and lexical semantic knowledge.},
+  journal={Journal of Speech Language and Hearing Research,},
+  volume={67},
+  issue={12},
+  pages={4783-4798},
+  numpages={},
+  year={2024},
+  month={December},
+  publisher={American Speech-Language-Hearing Association},
+  html={https://pubs.asha.org/doi/10.1044/2024_JSLHR-23-00743},
+  doi={https://doi.org/10.1044/2024_JSLHR-23-00743},
+  pdf={McGregorEtAl_2024.pdf},
+  selected={false}
+}
+
+@article{PredictASD,
+  abbr={JADD},
+  title={Prediction by Young Autistic Children from Visual and Spoken Input},
+  author={Mathée-Scott, J. and Prescott, K. E. and Pomper , R. and Saffran, J. and Ellis Weismer, S.},
+  abstract={Recent theoretical accounts suggest that differences in the processing of probabilistic events underlie the core and associated traits of autism spectrum disorder (ASD). These theories hypothesize that autistic individuals are differentially impacted by disruptions in probabilistic input relative to neurotypical peers. According to this view, autistic individuals assign disproportionate weight to prediction errors such that novel input is overweighted relative to the aggregation of prior input; this is referred to as ‘hyperplasticity’ of learning. Prediction among autistic individuals has primarily been examined in nonverbal, visual contexts with older children and adults. The present study examined 32 autistic and 32 cognitively-matched neurotypical (NT) children’s ability to generate predictions and adjust to changes in predictive relationships in auditory stimuli using two eye gaze tasks. In both studies, children were trained and tested on an auditory-visual cue which predicted the location of a reward stimulus. In Experiment 1 the cue was non-linguistic (instrumental sound) whereas in Experiment 2 the cue was linguistically-relevant (speaker gender). In both experiments, the cue-reward contingency was switched after the first block of trials, and predictive behavior was evaluated across a second block of trials. Analyses of children’s looking behavior revealed similar performance in both groups on the non-linguistic task (Exp. 1). In the linguistically-relevant task (Exp. 2), predictive looking was less disrupted by the contingency switch for autistic children than NT children. Results suggest that autistic children may demonstrate hyperplastic learning in linguistically-relevant contexts, relative to NT peers.},
+  journal={Journal of Autism and Developmental Disorders,},
+  volume={},
+  issue={},
+  pages={1-13},
+  numpages={},
+  year={2024},
+  month={October},
+  publisher={Springer},
+  html={https://link.springer.com/article/10.1007/s10803-024-06568-z},
+  doi={https://doi.org/10.1007/s10803-024-06568-z},
+  selected={false}
+}
 
 @article{SSDCase,
   abbr={AJSLP},
@@ -20,7 +56,6 @@ @article{SSDCase
   publisher={American Speech-Language-Hearing Association},
   html={https://pubs.asha.org/doi/full/10.1044/2024_AJSLP-23-00370},
   doi={https://doi.org/10.1044/2024_AJSLP-23-00370},
-  pdf={},
   selected={false}
 }
 
diff --git a/_pages/about.md b/_pages/about.md
@@ -22,7 +22,7 @@ I study how children learn language, including children with typical language de
 
 I completed my postdoctoral fellowship with Karla McGregor in the <a href="https://www.boystownhospital.org/research/speech-language/word-learning">Word Learning Lab</a> at Boys Town National Research Hospital and my PhD with Jenny Saffran in the <a href="https://infantlearning.waisman.wisc.edu/" target="\_blank">Infant Learning Lab</a> at the University of Wisconsin-Madison.
 
-I created a Shiny application to look up phonological information (frequency, age of acquisition, neighbors, clustering coefficient) for real words and made-up words. You can access it <a href="https://rpomper.github.io/phono/">here</a>. Note: it will take 1 to 2 minutes for the website to load, because it uses <a href="https://posit-dev.github.io/r-shinylive/">shinylive</a> to run the Shiny application locally rather than hosting it on an external server. I am in the process of writing up a manuscript describing the Shiny application and how to use it. Please let me know if you are using it, especially if you yave any feedback!
+I created a Shiny application to look up phonological information (frequency, age of acquisition, neighbors, clustering coefficient) for real words and made-up words. You can access it <a href="https://rpomper.github.io/phono/">here</a>. Note: it will take 1 to 2 minutes for the website to load, because it uses <a href="https://posit-dev.github.io/r-shinylive/">shinylive</a> to run the Shiny application locally rather than hosting it on an external server. I am in the process of writing up a manuscript describing the Shiny application and how to use it. Please let me know if you are using it, especially if you have any feedback!
 
 If you are interested in learning more about Developmental Language Disorder (DLD), check out this free <a href="https://bcpractice.com/developmental-language-disorder-guide-for-parents-and-families/">eBook</a> by Dr. Jeanne Tighe and the organizations <a href="https://radld.org">Raising Awareness of Developmental Language Disorder (RADLD)</a> and <a href="https://dldandme.org">DLD and Me</a>.
 
diff --git a/_projects/PhonoNet.md b/_projects/PhonoNet.md
@@ -14,11 +14,32 @@ This project is funded by the <a href="https://reporter.nih.gov/project-details/
 
 We are developing a website to calculate and plot different values for the phonological structure of words (both real and novel).
 
-The beta version of this website is available here: <a href="https://rpomper.shinyapps.io/phono/">https://rpomper.shinyapps.io/phono/</a>
+The beta version of this website is available here: <a href="https://rpomper.github.io/phono/">https://rpomper.github.io/phono/</a>
 
 Note: this website is coded using Shiny and is being hosted for free via shinnyapps.io. If it fails to load, we may have exceeded our active usage quota for the month :(
 
-<h2> SRCLD </h2>
+<h2> SRCLD 2025 </h2>
+
+We presented this research at the 2025 <a href="https://srcld.wisc.edu">Symposium on Research in Child Language Disorders</a>:
+
+<div class="row">
+    <div class="col-la mt-3 mt-md-0">
+        <img class="img-fluid rounded z-depth-1" src="{{ '/assets/img/PhonoNet-SRCLD-2025.png' | relative_url }}" alt="" title="example paragraph"/>
+    </div>
+</div>
+<div class="caption">
+    <a href="https://rpomper.github.io/assets/img/PhonoNet-SRCLD-2025.png">Click here</a> to download our 2025 SRCLD poster. <br>
+</div>
+
+
+Citation:
+<!-- <blockquote font-size=12px > -->
+Pomper, R., McGregor, K. K., & Vitevitch, M. S. (2025, May).
+Age-related changes in the effect of vocabulary structure on children's word learning.
+Poster presented at the Symposium for Research on Child Language Disorders, Madison, WI.
+<!-- </blockquote> -->
+
+<h2> SRCLD 2024 </h2>
 
 We presented this research at the 2024 <a href="https://srcld.wisc.edu">Symposium on Research in Child Language Disorders</a>:
 
@@ -28,7 +49,7 @@ We presented this research at the 2024 <a href="https://srcld.wisc.edu">Symposiu
     </div>
 </div>
 <div class="caption">
-    <a href="https://rpomper.github.io/assets/img/PhonoNet-SRCLD-2024.png">Click here</a> to download our 2023 SRCLD poster. <br>
+    <a href="https://rpomper.github.io/assets/img/PhonoNet-SRCLD-2024.png">Click here</a> to download our 2024 SRCLD poster. <br>
 </div>
 
 
