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Project
Description: The data within this project comprise a four year longitudinal study assessing various aspects of literacy including decoding, fluency, vocabulary, reading comprehension, listening comprehension, working memory and writing. Participants were tested on all measures once a year, approximately one year apart.
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: Longitudinal Study on Reading and Writing at the Word, Sentence, and Text Levels
Description: This dataset is longitudinal in nature, comprising data from school years (2007/2008-2010/2011) following students in grade 1 to grade 4. Measures were chosen to provide a wide array of both reading and writing measures, encompassing reading and writing skills at the word, sentence, and larger passage or text levels.
Dataset
Part of Project: Preschool Social and Emotional Development Study
Description: These data are children ages 2 through 5, includes preschool, child, and family demographic characters, social and emotional skills, cognitive skills, early math, early reading, and other indicators of kindergarten readiness (e.g., approaches to learning). Data were collected via director child assessments and teacher report.
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.
