Displaying results 1 - 7 of 7 (Go to Advanced Search)
Project
Description: The Western Reserve Reading and Math Project (WRRMP) is a NIH funded longitudinal study on child development. The project has collected data annually for 15 years, with data on approximately 450 twin pairs collected during this time. The project has had several focal points throughout its history.
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: Western Reserve Reading and Math Project
Description: This dataset contains all longitudinal data for the entirety of the WRRMP. This includes 10 waves worth of twin data, with extensive reading, math, behavioral, and environmental measures. Due to the twin nature of the data, data is presented as both long and wide, with each twin represented twice within the dataset.
Dataset
Part of Project: A Meta-Analysis of the Bilingual Advantage in Executive Function among Children
Description: This data set corresponds to 172 studies examining the bilingual advantage.
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.
