MARCS: Facilitating Math Learning with Adaptive Reading Supports
Math and Reading Acquisition Co-Adaptive System (MARCS)
Learning to solve mathematics problems can be challenging enough for students, but for students with reading difficulties it can be particularly difficult. To address this, CAST and Carnegie Learning are developing and evaluating a set of individualized reading supports for middle school students embedded in Carnegie Learning’s adaptive mathematics learning system, MATHia. Leveraging artificial intelligence to analyze students’ interactions as they use MATHia, MARCS will estimate the extent to which students' reading challenges affect their math learning and determine when to provide or recommend particular reading supports and scaffolds. In addition, the team is designing adaptive supports for the associated teacher application, LiveLab, to alert teachers in real time when students are likely exhibiting reading challenges and provide recommendations for intervention.
Working closely with teachers and students in suburban and urban public school districts, investigators will iteratively co-design and evaluate adaptive supports during the first phase of the project. In phase two, the team will conduct a large-scale pilot study using a cluster randomized controlled trial with teachers and middle school students across suburban and urban districts to evaluate the efficacy of the set of supports identified as most promising during phase one.
The ultimate goal of MARCS is to develop and evaluate reading supports that can be embedded into digital math tools—including MATHia and LiveLab—to improve student performance and engagement by addressing reading challenges. To support the use of project findings, generated technical resources, such as design assets and adaptive rules, will be Creative Commons licensed and made freely available.
July 2021 – December 2024
For more information about this project, please contact Bob Dolan.