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IES Grant

Title: ECHO: Prosocial and Positive School Climate
Center: NCER Year: 2021
Principal Investigator: Bergin, Christi Awardee: University of Missouri, Columbia
Program: Social, Emotional, and Behavioral Context for Teaching and Learning      [Program Details]
Award Period: 4 years (07/01/2021 – 06/30/2025) Award Amount: $1,999,793
Type: Development and Innovation Award Number: R305A210212
Description:

Purpose: The purpose of this project is to develop and pilot a model, ECHO: Prosocial and Positive School Climate, for building the capacity of teachers to increase students' prosocial behavior and create a positive climate at their school. This project addresses the research to practice gap in education, and addresses concerns about the lack of equity in access to high-quality professional development for teachers in isolated rural or under-resourced urban areas. The research team will adapt the ECHO model that has been effectively used in medicine as a tele-mentoring model for building the capacity of physicians in isolated rural and under-resourced urban areas to offer optimal, research-based care to their patients. Based on outcomes in the medical sector, the researchers will adapt the ECHO model to education to help improve school climate, improve teacher self-efficacy, reduce teacher burnout, support more positive teacher-student relationships, increase student prosocial behavior, in-class engagement, and improve student academic outcomes.

Project Activities: Over two years, the researchers will iteratively develop and refine ECHO: Prosocial and Positive School Climate. Iterations will be informed by feedback loops and quality improvement data. The researchers will conduct a one-year randomized controlled pilot study in which teachers will be placed in the intervention or wait-list control group to provide preliminary evidence of efficacy.

Products: Products will include a refined education ECHO model to close the research-to-practice gap, a professional development sequence for teachers to support prosocial behavior of their students, and a positive school climate that could be used by other ECHO teams at universities.

Structured Abstract

Setting: The project will take place in middle school across Missouri, with a focus on rural and under-resourced urban areas.

Sample: The project will involve approximately 200 middle school teachers and 26,000 students.

Intervention: ECHO is a tele-mentoring model in which a team of researchers at a university join with 20–25 practitioners to form a remote peer learning community around a specific topic (e.g., positive school climate), using accessible technology (Zoom and Box). The motto is "all learn, all teach" such that learning is deliberately bidirectional with researchers learning from practitioners, and vice versa. Monthly 1.5-hour ECHO sessions involve practitioners presenting authentic cases from their work, followed by group discussion of the cases and then a 20-minute didactic on cutting-edge research. ECHO has some elements found in existing professional development approaches (e.g., webinars, PLCs), but it is unique in that it combines the best elements of existing approaches into a single model that has proven effective in medicine. Teachers could benefit from adapting this approach to education. ECHO: Prosocial and Positive School Climate cases and didactics will focus specifically on strategies teachers can use to promote prosocial behavior among students to foster a positive climate.

Research Design and Methods: The research team will use mixed methods to develop, refine, and examine the intervention. In Year 1, the researchers will develop the materials for ECHO: Prosocial and Positive School Climate and launch the first ECHO group for middle school teachers (n=20 teachers). The team will collect data to improve the model. In Year 2, the researcher will conduct an "improved" ECHO model (n=60 teachers) and collect feedback for iterative improvement. In Year 3, the team will conduct a randomized controlled pilot study (n=120 teachers). In Year 4, the team will analyze data, conduct a cost analysis, deliver the intervention to the wait-list control group, and disseminate results.

Control Condition: Teachers randomly assigned to the wait-list control will continue with "business as usual" in Year 3 but participate in data collection. They will receive the intervention in Year 4 when data collection is completed.

Key Measures: In the development phase, quality improvement and implementation data will include (1) team reflection of each ECHO session, (2) transcripts, attendance logs, short pulse teacher surveys at each session, (3) semi-annual teacher feedback surveys, and (4) exit focus groups of teachers. In the pilot study, the team will measure similar outcomes for teachers as are found for physicians in medical ECHOs. That is, teachers' perception of (1) self-efficacy, (2) burnout, and (3) relationship with students. The researchers will also measure students' perception of (1) climate, (2) prosocial behavior, (3) engagement, and (4) belonging. The research team will also collect students' state academic proficiency test data. .

Data Analytic Strategy: Quantitative analysis will include descriptive statistics and group differences using t-tests and ANOVAs when appropriate. Qualitative analysis will include identifying patterns using the constant comparative method. The research team will also use multilevel modeling to analyze the data. The level-1 model will be at the student level and will model each student outcome within the teacher/classroom. The level-2 model will be at the teacher/classroom level.

Cost Analysis: During Year 4, the researchers will use the "resource cost method", which entails itemizing resources needed to provide services, calculating (or estimating) their costs, and then aggregating the costs to estimate overall program costs. The researchers will also conduct a sensitivity analysis varying cost assumptions to see if different choices (e.g., teacher time, number of participants served) would result in significant differences in the cost estimate.


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