This session explores the Credential-to-Outcome Recognition Ecosystem (CORE), an AI framework transforming Prior Learning Assessment. CORE analyzes professional profiles, maps skills to academic requirements using standardized taxonomies, and identifies targeted microcredentials for competency gaps. Learn how this approach accelerates degree completion while maintaining academic standards and creating personalized pathways for adult learners.
Presenter(s):
Wendy Lin-Cook
Montclair State University
David Chun
Montclair State University
AI-Driven CORE: Revolutionizing Prior Learning Assessment and Microcredentialing
Category
Breakout Session
Description
Session Day: ,
Session Time: -
Learning Outcome 1) Understand how the CORE framework uses AI to transform the PLA process by mapping professional experience to academic requirements through standardized skill taxonomies
Learning Outcome 2) Identify strategies for maintaining academic integrity and quality standards while automating skill assessment through AI-enhanced processes
Learning Outcome 3) Recognize how targeted microcredential recommendations can address specific competency gaps, reducing redundant coursework and accelerating degree completion