Displaying results 1 - 9 of 9 (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: 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: The purpose of this study is to explore the relations among elementary schools’ RTI (Response to Intervention) implementation and teachers’ awareness of RTI implementation and student outcomes.
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: Project FOCUS: Exploring RTI Implementation with a Focus on Students Receiving Tier 3 and Special Education
Description: These are data from 1000 teachers and 77 administrators. Data include demographic variables on teachers, and their perceptions of RTI implementation in their school. This is a cross-sectional dataset.
Dataset
Part of Project: Project FOCUS: Exploring RTI Implementation with a Focus on Students Receiving Tier 3 and Special Education
Description: These are data from 65 school administrators.
Document
Part of Project: Project FOCUS: Exploring RTI Implementation with a Focus on Students Receiving Tier 3 and Special Education
Description: This codebook accompanies the data set "Teacher Survey Data on School RTI components, and includes variable name, prompts, data type, and allowable values.
Document Type: Codebook
