Displaying results 1 - 11 of 11 (Go to Advanced Search)
Project
Description: This longitudinal research study explores the perceived and physiological stress, stressors, and work characteristics of childhood educators in the Midwest across the academic year 2021-2022 (during COVID-19). Data collection occurred over four time points.
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: Early Childhood Educators' Work and Stress
Description: These data are from time point 1 of the study and are in wide format.
Dataset
Part of Project: Early Childhood Educators' Work and Stress
Description: These longitudinal data contain information about hair cortisol in the participants across the first two time points of the study. Data are in wide format.
Dataset
Part of Project: Early Childhood Educators' Work and Stress
Description: These data are from time point 2 of the project. The data are in wide format. Data contain constructs of work characteristics, income, housing, economic hardship, food insecurity, personal stress, personal self-efficacy, depression, anxiety, and hair cortisol confounders.
Dataset
Part of Project: Early Childhood Educators' Work and Stress
Description: These data are for time point 3 of the study. Data are in wide format.
Dataset
Part of Project: Early Childhood Educators' Work and Stress
Description: These data are for time point 4 of the study. Data are in wide format.
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.
Document
Part of Project: Early Childhood Educators' Work and Stress
Description: This is the codebook accompanying all datasets for this project. It includes the data dictionary, information on item-level variables, citations of assessments, and total scores for variables.
Document Type: Codebook
