Student Outcomes for a Statewide High-Impact Tutoring Initiative

• In Event: Thursday Roundtable Session 12:40 pm
  In Roundtable Session: Dismantling Educational Injustices: Outcomes of Implementing Statewide High-Impact Tutoring (Table 13)

Abstract

1. Objectives

This session aims to present the results of an 18-month analysis of the data. Preliminary data collection for the began in fall 2022 and continues through the present, with data collection each semester (fall & spring). This session will examine the various student data collected as part of the , including participation data, demographic data, and outcomes in the form of standardized achievement data.

2. Framework

The paper is framed in the increasing need for practical, scalable solutions to combat learning loss and generations of educational inequities. High impact tutoring is grounded in equity, student safety, and cohesion among program elements. Based on the framework provided by National Student Support Accelerator (NSSA, 2021), high impact tutoring includes five research-based tutoring characteristics that result in more positive student outcomes than traditional tutoring.

3. Methods

The study methodology is a non-experimental design, including collecting quantitative data on participation rates, student demographics, and various district-specific, standardized achievement data.

4. Data Sources

After each session, tutors collect data and entered an online portal developed by and implemented in the fall of 2022. The individual school districts provide school-level achievement data. Statewide, six regional areas (comprised of numerous school districts) participated in the initiative. The current study includes over 3,500 students in grades 3-8 receiving tutoring via the initiative and control groups of students within each participating school who are not receiving tutoring services.


5 Results/Findings

The results will include an analysis of the demographic student data, including program participation, race/ethnicity, socio-economic status, special education status, English language learner, region, district, and school. In addition, a repeated measures analysis of variance (ANOVA) of the achievement data over three, possibly four, semesters will be presented. Depending on the final study samples, multivariate analyses of variance (MANOVA) will be conducted to analyze the impact of multiple independent demographic variables on student achievement scores.


6. Significance

The ongoing analyses of the outcome data from the are significant to various constituent groups, including the participating schools and districts, the state of Illinois (funding agency), and nationally as the results and findings from the initiative can help inform the implementation of successful tutoring initiatives.

Authors

• Steven B. Mertens, Illinois State University

• Christy Borders, Illinois State University