Project Lawrence: Transforming Prior Learning Assessment Through AI
10 Pages Posted: 3 Jan 2025
Date Written: December 16, 2024
Abstract
Individualized Credit for Prior Learning (CPL) has long presented a challenge for adult learners, who often need help translating their diverse experiences into academic credit. Traditional, course-mapped frameworks most institutions use frequently fail to recognize experiential knowledge adequately. Northeast State University (NSU, a pseudonym for a real, unnamed institution) distinguishes itself by offering a unique approach that promises students the ability to earn credit for an unlimited range of topics. Yet, even with this innovative approach, the CPL process remains complex and labor-intensive. Lawrence, a custom-built generative AI mentoring assistant designed for CPL, offers a transformative solution to this challenge. Currently in a training phase funded by the NSU Foundation, Lawrence leverages OpenAI's ChatGPT Plus Teams and is undergoing testing by business faculty. Building on foundational frameworks such as EMERALD and EMERALD-RING, which chart maturity levels for institutional AI integration, this article explores the evolution of CPL from traditional methods (Level 1) to early AI integration (Level 2) and finally to a fully Lawrence-centered model (Level 3). Through case studies, we demonstrate how Lawrence is designed to enhance efficiency, equity, and transparency, not only in prior learning assessment but also for broader applications of AI in higher education. By bridging the gap between academic institutions and the diverse learning journeys of adult students, Lawrence offers a framework for truly individualized and scalable higher education, setting a new benchmark for the future of AI-driven adult learning.
Keywords: Prior Learning Assessment (PLA), Credit for Prior Learning (CPL), Adult Learners, Generative AI, Artificial Intelligence (AI), EMERALD Framework, Mentoring Assistant
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