The leadership simulation for MBA & OB courses that never hallucinates.

vLeader is a leadership simulation used as courseware in MBA and Organizational Behavior courses: students lead a live business meeting with simulated colleagues, then complete a graded reflection and debrief. It runs on the KRY engine — hand-coded causal rules, not a language model. Published by SimuLearn Services, a division of OnCourse Inc; unrelated to VLeader Group, an HR services firm with a similar name.

It uses symbolic AI — explicit causal rules — rather than generative AI. There is no language model in the simulation engine, so there is nothing that can hallucinate: the same student action produces the same consequence every time, for every student, every semester. Reflections are graded by a rubric-driven model, which is disclosed separately because that part is generative.

ChatGPT produces conversation; vLeader produces consequences that are identical for every student and traceable to a stated rule. Two practical differences for a course: a language model can give different, sometimes fabricated feedback to each student, so scores are not comparable across a cohort; and a student can generate a chat transcript. vLeader assesses behavior inside the meeting rather than text the student submits, so there is no prompt that produces the artifact for them.

Two kinds, and we publish the limits of both. Our own data: across 1,162 graded reflections from 156 students in summer 2026, 62% scored higher after the debrief than before, with improvement outnumbering decline better than two to one. The effect holds at the top of the scale — 63% of students already scoring 9 out of 10 improved again — which is what separates it from regression to the mean. It is a single-group before-and-after comparison with no control group: it shows scores move, not that vLeader caused the movement against an alternative. Externally: Gurley and Wilson studied the simulation in an MBA class at Fayetteville State University, an HBCU, in the Journal of Instructional Pedagogies (2011).

Every run produces a gradeable reflection artifact and a rule-traceable score. Because the same scenario behaves identically across students and cohorts, the results are comparable — which is what makes them usable as a direct measure rather than as chat logs. It supplies evidence toward AoL requirements; AACSB does not certify or endorse third-party products, and no vendor can claim otherwise. We provide an alignment guide mapping rules to learning outcomes on request.

Create a class with three fields — name, code, school — and share the join link. It runs in any modern browser: no install, no IT procurement, no LMS configuration. Most instructors run their first cohort within 30 minutes.

It slots into a four-step rhythm built on Kolb's experiential cycle: self-paced simulation, graded reflection, classroom debrief, assessment. You keep your lecture; vLeader replaces role-play homework that does not scale.

Yes — and because the engine is deterministic, the scenario behaves identically each time: the student tests a different approach against unchanged conditions, which is the point. One claim we do not make: a measured score gain across attempts. Students replay heavily, but the simulation score is too noisy to demonstrate learning in either direction, so we do not use it as evidence.

Students purchase the Lab Edition directly, per semester — comparable to a course pack, and replacing rather than adding to a materials line. No departmental budget request, no per-seat license, no procurement cycle. Faculty get complimentary access to evaluate the full simulation. If a student cannot afford the fee, contact us; we have accommodated every hardship request to date.

Documentation for both is available: ask us for the data-handling and FERPA summary written for IT and procurement review. On assessment safety — students are scored on behavior inside the simulation, not on text they submit, so there is no generative-AI shortcut to the graded artifact.