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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: Headsprout Data Analytics
Description: Data from the Headsprout data analytics project. This dataset includes student progress monitoring data (DIBELS, TOWRE, CELF), data analytics from their engagement in Headsprout, and information about their home literacy environment (UFLI Home Literacy survey.
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: 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: Longitudinal Study on Reading and Writing at the Word, Sentence, and Text Levels
Description: This document provides information regarding the naming of variables within the dataset, as well as information regarding the specific tests and subtests included in said dataset.
Document Type: Codebook
