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Project
Description: Language sampling is a critical component of language assessments. However, there are many ways to elicit language samples that likely impact the results. The purpose of this study was to examine how different discourse types and elicitation tasks affect various language sampling outcomes.
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: The Meadows Center for Preventing Educational Risk (MCPER) partnered with the University of Houston, The University of Texas Health Science Center at Houston, Texas A&M University, and Florida State University to improve the reading comprehension of students in grades 7 through 12.
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: Impact of Discourse Type and Elicitation Task on Language Sampling Outcomes
Description: These are the data for 1037 K-3 students who contributed oral academic language samples. https://doi.org/10.1044/2023_AJSLP-22-00365
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: 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: Promoting Adolescents’ Comprehension of Text (PACT)
Description: In the 2013-14 school year, two PACT social studies RCTs were conducted, both with Grade 8 students. One study focused on schools with a higher percentage of English learners. The second study focused on struggling readers and provided a more intensified version of the PACT program.
Dataset
Part of Project: Promoting Adolescents’ Comprehension of Text (PACT)
Description: Students were in Grades 11 enrolled in general education social studies or in Grades 7-12 and enrolled in general education English/language arts classes. Data were collected using measures of reading and other academic skills, attitudes, and student characteristics. All students participated for one school year only.
Dataset
Part of Project: Promoting Adolescents’ Comprehension of Text (PACT)
Description: Students were in Grade 11 enrolled in general education social studies or in Grades 7-12 and enrolled in general education English/language arts classes. Data were collected using measures of reading and other academic skills, attitudes, and student characteristics. All students participated for one school year only.
Dataset
Part of Project: Promoting Adolescents’ Comprehension of Text (PACT)
Description: The Vocabulary and Comprehension (VoCo) project was a small study involving 44 struggling readers in Grade 9. The treatment was a multicomponent reading intervention delivered over 80 sessions during one school year. Data on measures of reading comprehension and fluency were collected at pre-test and post-test.
Dataset
Part of Project: Promoting Adolescents’ Comprehension of Text (PACT)
Description: Students were in Grades 8 or 11 and enrolled in general education social studies or in Grades 7-12 and enrolled in general education English/language arts classes. Data were collected using measures of reading and other academic skills, attitudes, and student characteristics. All students participated for one school year only.
Dataset
Part of Project: Promoting Adolescents’ Comprehension of Text (PACT)
Description: Students were in Grades 8 enrolled in general education social studies or in Grades 7-12 and enrolled in general education English/language arts classes. Data were collected using measures of reading and other academic skills, attitudes, and student characteristics. All students participated for one school year only.
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 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 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
