Displaying results 1 - 8 of 8 (Go to Advanced Search)
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.
Project
Description: We sought to understand the speech and language skills of children with nonsyndromic cleft palate with or without cleft lip (NSCP/L) by meta-analyzing results of the literature.
Dataset
Part of Project: Improving the Academic Performance of First-Grade Students with Reading and Math Difficulty
Description: This data set includes teacher identification (nesting) variable, reading and math scores, cognitive scores, and demographics .
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: 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 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: Speech and language skills in children with nonsyndromic cleft palate with or without cleft lip
Description: These data are from our third meta-analysis project. The speech-vocabulary analysis represented eight samples and the speech-mlu analysis represented four samples. The ages ranged from 18-months to 39-months.
Document
Part of Project: Improving the Academic Performance of First-Grade Students with Reading and Math Difficulty
Description: This is the codebook accompanying the dataset Comorbid Word Reading and Math Computation Difficulty at Start of First Grade.
Document Type: Codebook
