Enhanced Decision Tool for Peer-Mediated Personalized Learning

Enhanced Decision Tool for Peer-Mediated Personalized Learning is sponsored by IES. Creates an AI-driven tool to assist teachers in differentiating instruction and improving mathematics learning outcomes.

Enhanced Decision Tool for Peer-Mediated Personalized Learning | IES Enhanced Decision Tool for Peer-Mediated Personalized Learning From Seedlings to Scale Grants Program American Institutes for Research (AIR) (09/30/2025 - 09/29/2026) The purpose of this project is to develop a prototype of an enhanced decision tool (EDT) that leverages artificial intelligence (AI) to streamline and expand a validated instructional differentiation program that uses interim assessments already available to teachers and data-driven pedagogical strategies.

The goal of the EDT is to address several common barriers to implementation of effective personalized mathematics instruction. First, the EDT uses assessment data already available to teachers. Second, it provides teachers with technology to support their productive and efficient use of assessment data to differentiate and target instruction to improve mathematics learning.

Finally, the EDT will be designed for use in any general education instructional classroom and does not require the adoption of a new program. The prototype will be developed for mathematics instruction in the late elementary grades, but, if successful, the EDT will be scaled to support teachers and students across a range of grade levels, academic content areas, and settings.

The first stage of Phase 1 research and development will be need sensing, in which the team will aim to understand stakeholder needs in peer-mediated learning and data-driven instruction. To do this, the team will perform a literature scan to refine understanding of available resources and teacher needs and use those to develop a working problem concept and theory of action.

The team will convene an advisory board and teacher panels to improve understanding of teacher needs and interests surrounding new solutions to support peer learning. The team will refine the problem concept iteratively based on the literature scan, teacher input, and feedback from the advisory board. The second stage will include the creation of a draft proof-of-concept report.

In this stage, the team will translate the solution concept into prototype design documents and visual representations, incorporating stakeholder feedback and testing into the design. The team will identify and define the technical requirements of the prototype, create wireframes and clickable mockups, and conduct user testing and feedback gathering.

In the third stage of the project, the team will develop the prototype using an agile development approach, an iterative process of gathering frequent feedback, testing, and adaptation. The prototype developed will be an AI-driven Python and Django application with corresponding user documentation.

Finally, informed by Phase 1 activities, the team will finalize the proof-of-concept report, and an initial plan for further implementation, research, and development of the prototype in Phase 2. People and institutions involved Commissioner of Education Research Co-principal investigator Co-principal investigator Questions about this project?

To answer additional questions about this project or provide feedback, please contact the program officer. Questions about this project? To answer additional questions about this project or provide feedback, please contact the program officer.

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