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Project
Description: In this study, we wanted to explore the support networks of instructional coaches 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: Language processing accounts posit that spoken and written word predictability processes facilitate language comprehension, and prior research on contextual facilitation effects shows that individuals’ processing of a constrained word is faster and more accurate than that of an unconstrained word.
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.
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.
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.
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: Florida Longitudinal Study
Description: This is the data set for the Florida Longitudinal Study
Dataset
Part of Project: Support networks for instructional coaches 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 coaches 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 coaches 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: 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.
Code
Part of Project: Sentence Context Effects on Word Processing Among School-Aged Children in Honduras
Description: This SPSS code takes the raw data posted as "SCE_Data".
Code Type: Analysis
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
Code
Part of Project: Project KIDS
Description: This code calculates internal consistency for 6 ISI projects. Including alpha for the total sample, and by project. This code accompanies "Examining differential intervention effects: Do Individualized Student Intervention effects vary by student abilities and characteristics?"
Code Type: Analysis
Code
Part of Project: Project KIDS
Description: This code generates descriptive statistics, Mplus input files for MNLFA models, multiple imputation, and multi-level quantile regression models that accompany the paper "Examining differential intervention effects: Do Individualized Student Intervention effects vary by student abilities and characteristics?"
Code Type: Analysis
Code
Part of Project: Support networks for instructional coaches and special education teachers
Description: This code includes everything necessary to replicate analyses in the Instructional Coaches Typology paper (see preprint).
Code Type: Analysis
Code
Part of Project: Project KIDS
Description: This code takes 4 different datasets generated through the R code (EC_IDA_QR) and runs the MNLFA procedures in Mplus. All aspects of MNLFA are included, CFA, initial measurement variance, calibration, and scoring. Each section should be run separately in Mplus. There are 47 individual Mplus files included.
Code Type: Analysis
Code
Part of Project: Project KIDS
Description: This code takes 4 different datasets generated through the R code (EC_IDA_QR) and runs the MNLFA procedures in Mplus. All aspects of MNLFA are included, CFA, initial measurement variance, calibration, and scoring. Each section should be run separately in Mplus. There are 24 individual Mplus files included.
Code Type: Analysis
Document
Part of Project: Project KIDS
Description: This is the accepted Stage 1 registered report version of the paper "Examining differential intervention effects: Do Individualized Student Intervention effects vary by student abilities and characteristics?".
Document Type: Preregistration
Document
Part of Project: Project FOCUS: Exploring RTI Implementation with a Focus on Students Receiving Tier 3 and Special Education
Description: This codebook accompanies the data set "Teacher Survey Data on School RTI components, and includes variable name, prompts, data type, and allowable values.
Document Type: Codebook
