Building AI Feedback and Learning Ecosystem for Adult Learners at UMass Global

Preparing the Next Generation of Learners with Gen-AI Solutions

UMass Global, a nonprofit affiliate of the University of Massachusetts system, is recognized for its commitment to flexible, workforce-aligned education designed for adult learners. In 2025, UMass Global began a co-design process with LearnWise AI to build a fully integrated AI-powered ecosystem for teaching, feedback, and support, tailored to the institution’s competency-based education (CBE) model. The goal: deliver instant, personalized, and pedagogically aligned support without disrupting instructors’ workflows or compromising academic rigor.

This collaborative initiative is currently in development, with the shared goal of advancing equity, personalization, and mastery-based progression through thoughtful, transparent use of generative AI.

The Challenge: Empowering Adult Learners in a CBE Framework

Competency-based education (CBE) requires nuanced, formative feedback throughout a student’s skill development journey. But for institutions like UMass Global serving busy, working adult learners, delivering personalized, consistent, and timely feedback at scale can be challenging.

UMass Global identified several priorities:

• Improve formative feedback across stages of skill mastery
• Maintain academic integrity and discourage misuse of AI
• Reduce instructor workload in grading and feedback
• Ensure all learners receive actionable, growth-minded support even in asynchronous, self-paced environments

UMass Global serves a population of working professionals and nontraditional students who thrive on self-directed, purpose-driven learning. The design challenge? To create a scalable, cost-effective, and pedagogically sound system that:

• Supports Direct Assessment CBE: Helps learners demonstrate mastery of predefined competencies through authentic, objective assessments at their own pace
• Delivers High-Quality Feedback: Provides detailed, timely, and context-aware feedback on both formative and summative assignments
• Enhances Personalized Learning: Uses generative AI to guide each student through their own individualized learning journey—when and how they need it
• Promotes Transparency and Trust: Ensures students, faculty, and employers fully understand how AI is being used, and the educational value it brings
• Drives Cost Savings: Reduces instructional costs through automation and passing those savings on to students in the form of lower tuition

The Solution: A Co-Designed AI Ecosystem in Progress

UMass Global and LearnWise AI are collaboratively building and testing two key solutions:

1. AI Feedback and Grading Assistant

The LearnWise AI Feedback Assistant is being co-designed to provide rubric-aligned, instructor-reviewed feedback that supports mastery. The development process includes:

• Agent programming based on detailed rubrics and instructional tone
• Calibration using real student work samples and faculty input
• Ongoing faculty oversight and refinement during the early phases
• Future transition to fully automated, real-time feedback once quality is validated

The assistant is embedded directly into Brightspace’s grading workflow, ensuring ease of use and minimal disruption.

2. LearnWise AI Learning Guide

The Learning Guide is a closed-system AI tutor that draws exclusively from original course content and CC BY peer-reviewed resources. It is designed to:

• Support individualized remediation and skill-building
• Embed prompt engineering instruction into the curriculum
• Encourage learners to engage with active simulations, roleplays, and reflective exercises
• Help close knowledge gaps in real time, while reinforcing CBE principles
• Enable transparency and auditability, with rating and feedback mechanisms to guide continual improvement

This co-designed experience aims to help students develop AI literacy alongside their subject knowledge, an essential skill for the modern workforce.

Implementation Approach

The project is being developed in iterative stages, guided by close collaboration between instructional design, academic leadership, and the LearnWise AI team. Key principles of this co-design process include:

• Centering instructional design for skill mastery
• Prioritizing instructor review and quality assurance
• Emphasizing explainability and safe AI use
• Planning for scalable, cost-efficient deployment over time

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The Future of AI At UMass Global

Over the coming academic year, UMass Global will begin deploying early versions of the AI Feedback and Learning Guide tools across select CBE MBA courses, with plans to expand across additional programs in 2026.

Planned next steps include:

• Ongoing data collection and student/instructor feedback
• Continuous refinement of agents and instructional content
• Integration of dashboards for tracking progress and use
• Scalable deployment across additional assessments and programs

Long-Term Vision

UMass Global’s long-term goal is to build a fully adaptive AI learning companion that can:

• Deliver instant, personalized feedback across all assessments
• Continuously evolve based on student progress and feedback
• Accompany each learner across their educational, professional, and personal learning goals
• Award AI skills microcredentials and badges, motivating learners and recognizing progress across a structured skill continuum 

This approach reflects UMass Global’s commitment to delivering high-quality, high-touch, low-cost education, supported by trusted, responsible AI systems.

If you missed our lightning talk with UMass at D2L Fusion and want to see what we're building, join our webinar series, AI-Powered Assessment & Feedback in Canvas this coming 27th August 2025 | 11 AM EDT / 5 PM CET. Register here. 

Curious to learn more about our AI Assessment Feedback tool? Download our Whitepaper here.