Academic – Mentor126.AI

Role-Playing in Today’s Enterprise Environment: Bridging Theory and Practice

by Ben RollenhagenAcademic, Learning Science February 4, 2025February 13, 2025No Comments

Sales and Sales Development Representatives (SDRs) operate in high-stakes, high-variability environments, where adaptability, communication, and problem-solving are key to success. AI-driven role-playing simulations enable scalable, realistic, and adaptive training environments that mimic real-world challenges.

Common Role-Playing Scenarios for SDRs

Below are common role-play scenarios in sales training, along with how Agentic AI enhances these experiences:

Effective Uses of Role-Playing in Learning and Development

by Ben RollenhagenAcademic, Learning Science January 7, 2025February 6, 2025No Comments

Part 2 in 3 part series on AI Role Play Introduction Role-playing is a powerful application-based learning tool that enables learners to demonstrate their understanding of a subject by engaging in realistic, interactive scenarios. Unlike passive forms of learning, role-playing requires individuals to actively apply knowledge, adapt to dynamic conditions, and refine their skills in …

Harnessing the Power of Role-Playing in Education: Foundations, Benefits, and Emerging Applications.

by Ben RollenhagenAcademic, Learning Science December 3, 2024February 6, 2025No Comments

Part 1 of 3 part series on Role Play Theoretical Foundations of Role-Playing Experiential Learning and Active Engagement The effectiveness of role-playing is well-supported by foundational learning theories. Kolb’s Experiential Learning Model (1984) underscores the significance of active, hands-on experiences in fostering deep cognitive engagement and long-term knowledge retention. Learners progress through a cycle of …

Bespoke Learning | Mentor126.ai Learning Science

by Ben RollenhagenAcademic, Learning Science October 1, 2024February 5, 2025Comments are Disabled

Rethinking Upskilling-Leveraging Agentic AI for Scalable, Bespoke Learning

For over five decades, EdTech has promised to revolutionize learning, yet enterprise workforce training still struggles to meet the individual needs of learners in a scalable and impactful way. Most solutions tackle surface issues like engagement and gamification but miss in addressing the deeper challenges of delivering adaptive, meaningful, and personalized learning at scale. The result is a one-size-fits-all approach that leaves learners unfulfilled, experts experience boredom, novices experience anxiety with learning, workplace managers want to reduce time away from work to learn and L&D teams overstretched in today’s rapidly evolving workplace.

Generative AI presents a pivotal opportunity to change this paradigm—but deploying AI and focusing it on a corpus of knowledge alone isn’t enough. The true potential lies in creating adaptive learning systems that respond dynamically to individual learner progress, goals, and preferences. Mentor126 rises to this challenge by harnessing agentic AI to enable scalable, bespoke learning experiences that are based on proven learning science principles and support lifelong growth instead of temporary engagement.

At Mentor126, we believe in moving beyond flashy and superficial personalization experiences to transformative education that evolves alongside the learner. Our “Just in time. Just enough. Just for Me.” philosophy ensures learners receive precisely what they need, when they need it, fostering autonomy and long-term success that uses a distributed framework that enables anytime, anywhere availability of upskilling like electricity offers ubiquity.

For enterprises seeking meaningful change in their workforce training, this approach delivers both scalable efficiency and 1:1 upskilling impact—turning the promise of EdTech into a reality.

Bloom’s Taxonomy in the Generative AI Age

by Ben RollenhagenAcademic, Learning Science September 3, 2024February 5, 2025Comments are Disabled

Unlocking the Future with Bloom’s Taxonomy

In a world where generative AI promises to transform industries, EdTech faces a pivotal moment, where it can leverage the foundational principles of educational psychology to deliver on its breakthrough potential of upskilling learners and usher in transformative learning experiences.

The key lies in reconnecting today’s proven learning science-based tools with foundational learning theories like Bloom’s Taxonomy, which offers a roadmap for moving learners from basic knowledge acquisition to higher-order skills like critical thinking and creativity.

Too often, EdTech focuses on scalability at the expense of depth, emphasizing memorization over meaningful engagement. Yet, modern AI platforms can invert this trend, enabling adaptive, personalized pathways that reflect Bloom’s vision for mastery and 1:1 learning. By leveraging the full spectrum of Bloom’s hierarchy, EdTech can enhance learner outcomes, address disengagement, and improve the relevance of workforce training.

Grounded in decades of educational research, this paper offers a framework for integrating classic theories with cutting-edge tools. For leaders shaping the future of learning, it outlines strategies to transform training systems into dynamic, learner-centric platforms that not only engage but empower.

If your goal is to align state-of-the-art Agentic AI technology with learning science to achieve transformative upskilling outcomes, this article provides the blueprint.