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Project
Description: This meta-analysis examined effects of intervention on the level and trend of text-writing sequences of students with disabilities and writing difficulties, in addition to potential moderating effects related to student demographics (i.e., disability status, age, gender, and race) and writing task (i.e., sentence, essay, and narrative).
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: 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.
