The Effects of Small-Group Virtual Math Tutoring for Upper Elementary Students

• In Event: The Impact of High-Dosage Tutoring on Student Achievement Outcomes? Evidence from Four Randomized Controlled Trials

Abstract

While individual and small-group tutoring has been widely shown to be effective at supporting literacy development among young students, the research base in support of math tutoring for older elementary students is less robust. Moreover, recent evidence highlights that tutoring programs are often less effective at scale (Kraft et al., 2024). One challenge with scaling tutoring programs includes the identification, recruitment, and oversight of tutors spread across a large geographic area. This study presents an evaluation of a Cignition, a high-impact virtual tutoring program, for upper elementary students who are below grade level in math.   

In this study, we ask the following research questions: 

1. 
   

   What is the impact of access to Cignition’s virtual small-group math tutoring on math achievement for upper elementary students? 

   
   


2. 
   

   What is the impact of receiving a full-dose (120 session) of Cignition’s virtual small group math tutoring? 

   
   


3. 
   

   How does this impact differ by key student subgroups and programmatic context?

   
   

At the start of the 2024-2025 school year, 462 students in 3rd through 6th grade from four elementary schools in New Jersey and Ohio, were randomly assigned to either receive Cignition’s small group virtual math tutoring, or to receive the “business-as-usual” math instruction and supports provided by their school. Randomization occurred within school-by-grade level blocks. Students in the treatment group were assigned by their schools into small groups of 3-4 students to receive Cignition tutoring in doses of 30 minute sessions, three or four times per week. 

The primary outcome is the standardized math scaled scores on the state accountability assessment at the end of the study year. Exploratory outcomes include standardized scores on district/school benchmarking assessments (e.g. MAP, iReady, STAR), and ratings of engagement, identity, and self-efficacy for treatment group students. We will estimate an intent-to-treat effect of being assigned to the Cignition group, using a linear regression that controls for the random assignment block, student demographic characteristics such as gender, race/ethnicity, IEP and EL status, and, if available, FRL status. We will also include a pre-test measure of math achievement from the previous academic year. Standard errors will be clustered at the school-by-grade level to account for differing random assignment ratios across strata and the lack of independence between students in the same school. 

We are also in the process of collecting student-level information, from both the treatment group and the control group, about the total amount and nature of math instruction and support that they are receiving. We will use this information to form a robust description of the treatment-control contrast, which will inform our exploratory analyses about variation in program impact. 

Authors

• Catherine Armstrong Asher, University of Michigan
  Non-Presenting Co-Author

• Robin T Jacob, University of Michigan Ann Arbor
  Presenting Author