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College of Education

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Think and Do The Extraordinary
Support the College

Building a Next Generation Diagnostic Assessment and Reporting System within a Learning Trajectory-Based Mathematics Learning Map for Grades 6-8

Project Team: PI-Jere Confrey 

Sponsor: National Science Foundation

Project Total: $2,999,785

Description:

The 3-year project contributes a critical, missing element to the range of existing formative, interim, and summative assessments by creating and refining a next generation diagnostic assessment, built around learning trajectories and the underlying research in the learning sciences. The level II project in grades 6-8 mathematics leverages a learning map organized around nine big ideas, and 24 related learning clusters. Associated to the map and the CCSS-M standards, the diagnostic assessments map student progress in terms of levels of proficiency in the learning trajectories. The district and school partners, Freehold County Schools (NJ) and Harnet County Schools (NC), assist in refining and testing the diagnostics within programs of competency-based education and personalized learning.

The project involves a collaboration among the research team and two middle schools at a high-performing district in NJ with district leadership mentored in competency-based learning and personalization, and with a brand new middle school in North Carolina serving a large percentage of students on free and reduced lunch, where the process of implementing digital 1-1 learning is in its infancy. The project builds on a current NSF and Bill and Melinda Gates funded project where first version assessment items were written and field-tested to calibrate individual items. The partnership seeks to address four major goals: 1) revising and strengthening the diagnostic assessments by adding new item types and dynamic tools for data gathering and analyzing student solution strategies, 2) studying alternative ways to use measurement models to assess student progress over time using the concept of learning trajectories, 3) investigating how to assist students and teachers to effectively interpret reports on progress, both at the individual and the class level, and 4) engineering and studying instructional strategies based on student results and interpretations, as they are implemented within competency-based and personalized learning classrooms.