The process of creating Lovebug was, in my opinion, the most difficult of all of this course’s projects. To begin, it was a bit difficult for me to conceptualize what a systems game is — it seemed like such a broad category of games. Once I eventually wrapped my head around the concept, it then became even more complicated. How were we to accurately model a system faithfully while also making a game fun? Balancing these two things further complicated the already complicated process of game creation.
Playing Lovebug, I believe our game affords a social deception-esque learning type of fun. Through the cohesion of our game’s early 2000s theme, coupled with the mechanics that modeled the spread of the ILOVEYOU virus, our team made a game that both implicitly teaches about a global hacking phenomenon as well as allows for social deception fun.
By allowing players to send mail, build new contact connections, and open and delete mail from their inbox, we accurately simulated the basic mechanics of our system and the dynamics that would allow for, or prevent, infection from spam emails.
From this experience, I learned that it’s difficult to distill a system to its core elements. Picking and choosing what systems to retain, which to dispose of, and which to abstract, is a very difficult process. While changing some elements of the system may add more fun and functionality to the game experience, it also departs from a faithful depiction of the system.
Though this game was not explicitly a learning game, as I watched people play, I was particularly interested in how interested they were in the origin system (the Love Bug) and how much they learned from our game. Personally, I measured our ability to create a good systems game through how much people were interested in the core system and the context of its creation.
