The simulation platform
your students deserve.
Apex Manufacturing is our flagship simulation for higher education — eight weeks in the CEO seat, every rubric published, every criterion visible to students before they answer.
The professor view
Built for the way you actually teach.
Transparent rubrics, AI-graded decisions, and a dashboard that respects your time.
The Problem
Case studies weren't built
for the AI era.
Management education faces a persistent "Relevance Gap" between academic theory and organizational practice.1 Traditional cases are static snapshots — they can't capture the messy, evolving complexity of leading through technological transformation.2
Experiential Learning6
Students make consequential decisions over 8 simulated weeks and see the organizational ripple effects — implementing Kolb's learning cycle iteratively to address concerns about single-iteration designs.
Productive Failure8
A risk-free environment where strategic mistakes become powerful learning moments. Kapur's research shows students who struggle with complex problems before instruction outperform those who receive instruction first.
Actionable Knowledge4
Moving beyond theory to create the data-driven rigor required by the academic community while delivering the engagement students demand.
Radical Transparency
Every rubric visible.
Every criterion published.
Unlike "black box" AI tools that obscure evaluation logic, FWA uses transparent, rubric-based assessment.9 Students see the exact same criteria used by the AI grader — displayed on every weekly simulation page.
Want to see every scoring band, the 5-step evaluation process, and how we calibrate against exemplar responses?
See our complete AI grading methodologyAssessment
AI-powered grading.
Instructor authority.
The grading module evaluates student essays against the published rubric, providing detailed formative feedback — while the instructor retains full override authority on every score.
LLM Rubric Evaluation
Scores across all 4 criteria with specific feedback per dimension
Bulk CSV Upload
Paste from Blackboard, Canvas, or any LMS — grade entire classes at once
Optional Curved Scoring
Opt-in statistical normalization adjusts for week difficulty across the class
Instructor Override
Every AI score labeled formative — review, adjust, add comments, finalize
The grading module is available to enrolled instructors and administrators.
Adaptability
3 difficulty tiers.
One platform.
Whether you're teaching introductory management to undergraduates or running a rigorous MBA seminar, the simulation adapts — implementing Vygotsky's Zone of Proximal Development10 by progressively reducing scaffolding as student capability increases. Difficulty affects consequence severity, financial complexity, and rubric expectations — all configurable by the instructor.
Continuous Improvement
Built-in student feedback.
AI-analyzed insights.
Every week, students rate the simulation across six dimensions. The instructor dashboard aggregates responses into trend charts, radar analysis, and AI-generated recommendations — so you can iterate based on real data, not guesswork.
Immersion
17 stakeholders.
Quantifiable personalities.
Each stakeholder has a rich backstory, professional history, and four measurable traits that directly affect simulation difficulty and decision outcomes.
Institutional Trust
Privacy-first.
Compliance-ready.
Privacy Mode enables completely anonymous enrollment — no student names, emails, or PII collected. Instructors map pseudonymous IDs to real records offline.
The Journey
8 weeks of escalating
complexity.
A structured arc from initial AI assessment through full organizational transformation.
Instructor Toolkit
Everything you need
to run the simulation.
A complete suite of tools for managing simulations, grading at scale, and iterating based on real student feedback.
AI-Powered Grading
LLM rubric evaluation with bulk CSV upload from any LMS
Optional Curved Scoring
Opt-in statistical normalization with configurable class curve targets
Student Feedback Surveys
6-dimension ratings with AI-analyzed results dashboard
Content Editor
Manage weekly briefings, research, and decisions with AI assistance
Activity Logs
Track every student action, engagement metric, and participation
People Management
Team creation, enrollment, role assignment, and progress tracking
Intel Articles & Research
WSJ, HBR, McKinsey-style case materials with citation codes
Phone-a-Friend Advisors
9 specialized advisors with audio guidance and strategic counsel
Injectable Situations
Alter simulation dynamics mid-semester with special events
Easter Egg Bonuses
Reward students who reference research in their decisions
Role Preview System
Experience the platform as a student or educator before deployment
Content Validation
Verify all content consistency against canonical source data
Modules
Scenario-based learning
across strategic challenges.
The Future of Work
AvailableLead Apex Manufacturing through 8 weeks of AI adoption decisions balancing automation, workforce transformation, union relations, and stakeholder management.
Get Started
See it for yourself.
Get instant 30-day demo access — no scheduling required. Or reach out for a personal walkthrough.
Academic References & Research Library
Read the full White Paper →1 Hay, G., & Heracleous, L. (2009). Bridging the scholar-practitioner divide. The Journal of Applied Behavioral Science. doi:10.1177/0021886309336780
2 Ungureanu, P., & Bertolotti, F. (2022). Dynamic stereotyping across occupations. The Journal of Applied Behavioral Science. doi:10.1177/00218863221084149
3 United Nations Development Programme Eurasia Regional Hub. (2025). Listening to 200 young people about work. UNDP. undp.org
4 Argyris, C. (2009). Actionable knowledge. In H. Tsoukas & C. Knudsen (Eds.), The Oxford handbook of organization theory. Oxford University Press. doi:10.1093/oxfordhb/9780199275250.003.0016
5 United Nations Development Programme. (2025). Future of Work Academy: Green & digital transitions. UNDP. undp.org
6 Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice-Hall.
7 Bartunek, J. M., & Rynes, S. L. (2014). Academics and practitioners are alike and unlike: The paradoxes of academic-practitioner relationships. Journal of Management, 40(5), 1181-1201. doi:10.1177/0149206314529160
8 Kapur, M. (2016). Examining productive failure, productive success, and unproductive failure in learning. Educational Psychologist, 51(2), 289-299. doi:10.1080/00461520.2016.1155457
9 Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7-74. doi:10.1080/0969595980050102
10 Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89-100. doi:10.1111/j.1469-7610.1976.tb00381.x
11 Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81-112. doi:10.3102/003465430298487
12 Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32-42. doi:10.3102/0013189X018001032
13 Mitchell, R. K., Agle, B. R., & Wood, D. J. (1997). Toward a theory of stakeholder identification and salience. Academy of Management Review, 22(4), 853-886. doi:10.5465/amr.1997.9711022105
14 Shermis, M. D., & Burstein, J. (Eds.). (2013). Handbook of automated essay evaluation: Current applications and new directions. Routledge.
15 Kayes, D. C. (2002). Experiential learning and its critics: Preserving the role of experience in management learning and education. Academy of Management Learning & Education, 1(2), 137-149. doi:10.5465/amle.2002.8509336
16 Future Work Academy. (2026). AI transparency & prompt documentation [Internal technical audit]. FWA.
17 Future Work Academy. (2026). Security & compliance documentation [FERPA alignment]. FWA.