Displaying results 1 - 8 of 8 (Go to Advanced Search)
Project
Description: By leveraging technology, new knowledge will be gained on the linkage between teacher stress, teacher talk, teacher-student relationships, and pre-academic and social-emotional outcomes in Black and Latine students, paving the way for more efficacious interventions to reduce teacher stress.
Project
Description: Purpose: The special needs of young children (birth to 36 months) are not unidimensional. Early interventionists are challenged in developing interventions that fully address the needs of young children with developmental delays in multiple domains.
Project
Description: Word knowledge is critical for speaking, reading and writing, yet a substantial proportion of children with language impairment demonstrate poor word learning and consequently poor vocabulary. Because vocabulary has a causal relationship with reading comprehension, this presents a significant national health concern.
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: Profiles of Working Memory and Word Learning for Educational Research (POWWER)
Description: This dataset incudes data from 248 second graders (7- to 8-year-olds) with typical development from three states. One hundred sixty-seven were monolingual English-speaking and 81 were dual Spanish- and English-speaking.
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.