Displaying results 1 - 20 of 27 (Go to Advanced Search)
Project
Description: The goal of this project is to stimulate language and comprehension skills in Grade 1 children at risk for reading comprehension difficulties by testing the efficacy of a modified, small-group, version of the Let’s Know! intervention.
Project
Description: Science of reading experts have called for increased attention on oral academic language. Specifically, interventions need to integrate multiple dimensions of academic language—word-, sentence-, and discourse-level patterns—to impact listening comprehension.
Project
Description: Early language skills are critical to students’ later reading comprehension and writing. As they progress through school, the complexity of language they need to understand and use increases, suggesting that young children can leverage oral language resources to acquire literacy and knowledge.
Project
Description: Some children with autism may require additional supports to meet academic expectations for comprehension. Oral narration, which is linked to listening and reading com-prehension, may be a viable approach.
Project
Description: In research, augmentative and alternative communication (AAC) interventions have primarily focused on teaching children to make requests (Logan et al., 2017); however, AAC intervention should not stop there.
Project
Description: This LDbase project page containes the open science materials for our meta-analysis on the reading anxiety and reading achievement.
Project
Description: Language sampling is a critical component of language assessments. However, there are many ways to elicit language samples that likely impact the results. The purpose of this study was to examine how different discourse types and elicitation tasks affect various language sampling outcomes.
Project
Description: The aim of this research is to create developmentally appropriate, play-based storytelling elicitation procedures to collect language samples of young children aged 18-48 months, tools for evaluating the magnitude and quality of narrative language produced in play-based storytelling sessions, and examine the psychometric properties of these new
Project
Description: The analysis of narratives often accompanies comprehensive language assessments of students. While analyzing narratives can be time-consuming and labor-intensive, recent advances in large language models (LLMs) indicate that it may be possible to automate this process.
Dataset
Part of Project: Impact of Discourse Type and Elicitation Task on Language Sampling Outcomes
Description: These are the data for 1037 K-3 students who contributed oral academic language samples. https://doi.org/10.1044/2023_AJSLP-22-00365
Dataset
Part of Project: Oral Academic Narrative Language Intervention
Description: This file contains data according to two research designs: small scale RCT and a Repeated Acquisition Design (single case research). The vocabulary at the pre- and post- collections were untaught words whereas the weekly probes for the RAD were the taught words of that week.
Dataset
Part of Project: Effect of Narrative Intervention with Strategy Instruction on the Listening and Reading Comprehension of Children with Autism
Description: These are the total scores for each of the participants' listening and reading retells across baseline, intervention, and post-intervention conditions.
Dataset
Part of Project: AAC Narrative Intervention for Children with Autism
Description: These are the data for story grammar scores and number of different symbols used that resulted from the AAC narrative intervention. They are organized according to multiple baseline across participants design and pseudonyms are used instead of children's names.
Dataset
Part of Project: Automated Narrative Scoring Using Large Language Models
Description: Narrative language samples elicited using the ALPS Oral Narrative Retell and Oral Narrative Generation tasks from diverse K-3 students. The tworaters data set was drawn randomly from the larger corpus of narrative language samples. These samples were scored by two raters for reliability purposes.
Dataset
Part of Project: Automated Narrative Scoring Using Large Language Models
Description: Narrative language samples elicited using the ALPS Oral Narrative Retell and Oral Narrative Generation tasks from diverse K-3 students. The training data set was drawn randomly from the larger corpus of narrative language samples.
Dataset
Part of Project: Automated Narrative Scoring Using Large Language Models
Description: Narrative language samples elicited using the ALPS Oral Narrative Retell and Oral Narrative Generation tasks from diverse K-3 students. The test data set was drawn randomly from the larger corpus of narrative language samples.
Dataset
Part of Project: Reading Anxiety and Reading Achievement: A Meta-Analysis
Description: This is the data that was extracted from existing studies for use in this meta-analysis on reading anxiety and reading achievement. This includes 44 studies. Many of the studies had multiple effect sizes. Each row of data represents a effect size (long format).
Dataset
Part of Project: National Project on Achievement in Twins
Description: Demographic variables like race, ethnicity, and disability can be particularly problematic for data reidentification and data misuse in publicly available dataset. Therefore, these were removed from the original dataset. This dataset includes race, ethnicity, and disability information for participants in the COVID 2023 survey.
Dataset
Part of Project: National Project on Achievement in Twins
Description: This is the survey that was sent to NatPAT caregivers and twins in fall 2023, focused on COVID-19 pandemic impacts on caregivers' and twin's lives.
Dataset
Part of Project: Reading Anxiety and Reading Achievement: A Meta-Analysis
Description: This is a spreadsheet format of table 4 that is included in the manuscript. Table 4 reports the reading anxiety measure used in each of 44 studies included in the reading anxiety meta-analysis.
