Displaying results 1 - 11 of 11 (Go to Advanced Search)
Project
Description: Raw data files on test statistics of students in our SBL class of 2022.
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: The purpose of this Hub was to deepen insight into an understudied and vulnerable subset of students with learning disabilities (LD), students with comorbid difficulty across reading comprehension (RC) and word problem solving (WPS) and whether text structure intervention in one domain transfers to the other domain.
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: Vanderbilt University Learning Disabilities Innovation Hub: Word Problems, Language, & Comorbid Learning Disabilities
Description: Nesting variables, treatment condition, demographics, pretest and posttest reading and math variables, text-structure knowledge for second-grade children with comorbid learning difficulty .
Dataset
Part of Project: Vanderbilt University Learning Disabilities Innovation Hub: Word Problems, Language, & Comorbid Learning Disabilities
Description: Nesting variables, treatment condition, demographics, pretest and posttest reading and math variables, text-structure knowledge for classmates of second-grade children with comorbid learning difficulty
Dataset
Part of Project: Vanderbilt University Learning Disabilities Innovation Hub: Word Problems, Language, & Comorbid Learning Disabilities
Description: This dataset includes the observations to determine the fidelity of implementation of the treatment conditions in the study.
Document
Part of Project: Simulation Based Learning (SBL): an engineering course on Chao Phraya River’s salinity forecasting by Mathematical Modeling
Description: This document is a paper submitted to a Hindawi journal of education.
Document Type: Journal Contribution
Document
Part of Project: Vanderbilt University Learning Disabilities Innovation Hub: Word Problems, Language, & Comorbid Learning Disabilities
Description: This codebook applies to the three datasets associated with this study:
1-Transfer between Reading Comprehension and Problem Solving
2-Classmates - Transfer between Reading Comprehension and Problem Solving
3-Fidelity - Transfer between Reading Comprehension and Problem Solving
Document Type: Codebook
