Displaying results 1 - 20 of 46 (Go to Advanced Search)
Project
Description: In this study, we wanted to explore the support networks of instructional supervisors of beginning special education teachers and those of rural special education teachers, and how these networks relate to intent-to-stay in the field as a coach or special education teachers. We collected data across two waves.
Project
Description: Mentoring for clinical faculty in academic health centers offers numerous benefits; however, structured virtual mentoring remains understudied in this context.
Project
Description: Project KIDS aimed to rigorously combine data from several independent RCTs to explore individual differences in response to intervention, focused on cognitive, behavioral, contextual, and family history correlates of intervention response.
Project
Description: The purpose of this study is to explore the relations among elementary schools’ RTI (Response to Intervention) implementation and teachers’ awareness of RTI implementation and student outcomes.
Project
Description: In this study, we examined if data analytics gleaned from an online literacy application could inform teachers of student reading progress above and beyond their progress monitoring scores. Participants were all K-1 students in one elementary school in a southeastern state.
Project
Description: This project page describes the creation of a latent reading score created by combining data across 12 datasets available on LDBase. This variable is the product of an Integrated Data Analysis (IDA) which was modeled using a multiple-group measurement model described below.
Dataset
Part of Project: Mentorship Matters
Description: Survey data gathered from mentors and mentees after the conclusion of the Mentorship Matters program.
Dataset
Part of Project: Support networks for instructional supervisors and special education teachers
Description: These data include demographic information on the participating coaches (n = 15) and their coaching context. These data are crosssectional and include specific ego-IDs that can be used to merge with Alter and Tie datasets.
Dataset
Part of Project: Support networks for instructional supervisors and special education teachers
Description: These data contain perceived demographic data on named alters (by Ego) and perceived support provision. These data can be combined with Ego level data to make a nested set using key ID variables.
Dataset
Part of Project: Support networks for instructional supervisors and special education teachers
Description: These data are ties between alters in the network. These data are needed to visualize the complete network using ego and alter data as well.
Dataset
Part of Project: Project FOCUS: Exploring RTI Implementation with a Focus on Students Receiving Tier 3 and Special Education
Description: These are data from 1000 teachers and 77 administrators. Data include demographic variables on teachers, and their perceptions of RTI implementation in their school. This is a cross-sectional dataset.
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: Project KIDS
Description: These data are for each item on all achievement and behavioral assessments completed during the original intervention projects. The dataset is wide, with separate variable names for each wave of assessment. All participants (n= 4,038) are included. These data can be linked to the "total level" data using the PK_ID variable.
Dataset
Part of Project: Project KIDS
Description: This data set includes all total scores, demographics, home literacy environment, etc. for Project KIDS. Data are in wide format, with separate variables for each wave of assessments. All 4038 participants are represented in the data.
Dataset
Part of Project: Project KIDS
Description: These data include information on family demographics, home environment, health information, child diet and nutrition, BRIEF, SWAN, all at the item level. This is cross-sectional data. Data can be linked to other Project KIDS data through the PK_ID variable.
Dataset
Part of Project: Mentorship Matters
Description: Data gathered from both mentors and mentees prior to program launch
Dataset
Part of Project: Mentorship Matters
Description: Survey data gathered from Mentorship Matters mentors and mentees who were participating at the program's mid-point.
Dataset
Part of Project: Project FOCUS: Exploring RTI Implementation with a Focus on Students Receiving Tier 3 and Special Education
Description: These are data from 65 school administrators.
Code
Part of Project: Project KIDS
Description: This code accompanies the preprint Do Student Behavior Ratings Predict Response to Tier 1 Reading Interventions? (10.35542/osf.io/jfxz5). Code is for R version 4.2.1 (2022-06-23) )macOS Montery 12.5
Code Type: Analysis
