RMAIIG AI Member Showcase
CU Boulder
Ann and H.J. Smead Aerospace Engineering Sciences
AI Leveraged Learning

PACE
TheEcosystem
AI catapults 🚀 Vygotsky's (1978) Zone of Proximal Development (ZPD) seminal framework on learning from MKOs, More Knowledgeable Others.
AI-Leveraged learning is Personalized, Adaptive & CollaborativeÂ
- AI platforms can analyze learner interactions and performance data to dynamically group individuals with complementary skill sets, fostering peer-to-peer scaffolding within shared ZPDs.
- AI agents function as advanced MKOs, offering nuanced, adaptive feedback that evolves with the learner's progress, suggesting optimal challenges, and providing tailored hints or explanations precisely when and where they are needed.
AI extends collaborative learning beyond the limitations of human MKOs by offering continuous, scalable, and personalized support, effectively optimizing each learner's journey through their ZPD in a collective learning context.
Research
PACE model research
RMAIIG Member Showcase:Â
white paper
Ed.D. EdTech dissertation
Dissertation: Examining the Experiences of Online Professional Development: A Teacher Education Twitter-Based Professional Learning Network (2020).
Themes of collaborative learning, Communities of Practice, microlearning, mentorship and coaching, Professional Development and Leadership Development, mLearning, eLearning, social constructionism, constructivism.’
Curriculum
📘 Book as
the Framework
💻 Learning Lab asÂ
the Application & Learning Community



Iterative Curriculum & Learning Community

Rebecca Nusbaum, Ed.D.

Current state & future state
Personalized Adaptive Collaborative Ecosystem for Learning (PACE)
Evaluation lifecycle: