Extending The Project Win Game™: Teaching Real Options and Moral AI Project Decision-Making

Abstract

This study addresses the following research question: What design principles enable a structured serious game canvas to operationalize complex quantitative and qualitative project management concepts as experiential learning environments? The concept for this work was inspired by observations of how practitioners engaged with The Project Win Game™, a board game designed to simulate project management decision-making. Building on this experience, the game was extended with two gameplay options for corporate training and adult education: Real Options Analysis (ROA) to support disciplined investment decisions under uncertainty, and moral AI. This unconventional pairing of a quantitative financial decision model and a qualitative ethics module within the same game framework expands the range of complex decision topics addressed through games. Conventional project management education often overlooks structured stop-or-scale decisions and the broader societal consequences of project outcomes. The first gameplay option integrates ROA, a financial modelling method that applies option-pricing to staged investment decisions under uncertainty. ROA is advanced for many project managers, so the game teaches it through gameplay. Players simulate phased investments, reassess continuation decisions, and manage downside exposure as project uncertainty unfolds. Serious games are particularly suited for teaching decision-making under uncertainty because they allow participants to experiment in a simulated environment where trade-offs and delayed consequences can be experienced directly rather than explained abstractly. The second gameplay option shifts from financial to ethical complexity and focuses on AI implementation projects in a healthcare context. Participants confront ethical risks arising from algorithmic decision-making, including bias, misidentification, and unintended harm. Through simulated project events, players identify ethical risks, evaluate stakeholder impacts, and recognize how early project decisions shape societal outcomes. The design approach was validated through pilot sessions and is illustrated through ROA and Moral AI extensions.