Thesis Description
My Digital Media thesis at Drexel University is research and development of a system which can procedurally generate physics-based puzzle levels which can continuously engage players with hopes of inciting some amount of learning within those players.
Alongside professor Stefan Rank, I have researched procedural generation in games, game-based learning, engagement/motivation, and replayability to support the ideology behind this project. Human: Fall Flat is a widely successful and popular physics puzzle platformer which has a level editing tool called Human: Fall Flat Workshop that operates directly within Unity. The access to this Workshop combined with the concepts and strength of the gamplay in Human: Fall Flat itself are why we decided to use this as a platform to visualize the system and put the ideas into practice.
The aim of the project itself is to create a system which can generate varied puzzle experiences of a few different physics puzzle types (i.e. ramp, pulley, or lever) within this Human: Fall Flat Workshop. Each puzzle type will have many parameters which can be modified to change the ranges at which objects are created and/or positioned within the scenario, while still providing a varied enough experience as to promote replayability with the system.