Evaluating Classroom Lessons Within the Common Core Context: Testing Automated Alignment Using Machine Learning

• In Event: 18.069 - Learning-Centered Online Environments and Assessing Online Information

Abstract

Forty-two states and the District of Columbia have adopted the ELA (English Language Arts) Common Core State Standards. Teachers are now expected to align their instruction to the Common Core, but many lack the resources to do so effectively. The Automated Alignment Project is an effort to develop a tool that uses machine language learning techniques to determine alignment of lesson plans and associated materials to Common Core standards. The tool evaluates teacher lessons electronically rather than by hand. Ultimately, this will allow teachers to quickly and economically determine whether lessons are aligned to the Common Core, helping them to deliver instruction in their classrooms that supports students in meeting Common Core Standards.

Authors

• Stephanie Levin, IMPAQ International, LLC

• Fannie Tseng, Berkeley Policy Associates

• Trevor Selby, Preva Group

• Derek Soike, Preva Group