Dissertation Blog #5
Citation of the Day
Squire, Kurt. Video Games and Learning: Teaching and Participatory Culture in the Digital Age. Teachers College Press, 2011.
This book explains that the educational value of video games has less to do with their realism or complexity and more more to do with how they inspire interest, creativity, and social interaction. Games are ideological worlds that instantiate ideas through implicit rules sets and systems, make value judgments about what is and is not important, and create meaning through representations. (Chapter 2 paraphrasing)
The more complex a model is, the less useful it is for learning -- models have to be simplified if they are to be understood. Games are not predictive models; they are idea models. To counterbalance the simplification necessary to make a good game, you can ship it with modification tools that allow the player to experiment with complexity. (Chapter 2 paraphrasing)
Squire makes the important point that moment-to-moment gameplay must be polished to perfection, or else it won’t matter how thoughtfully designed a game's macro systems are. The designer's goal is to engineer memorable moments: when player intentions, game systems, and representations converge to produce transcendent emotions. (Chapter 5 paraphrasing)
Design and Mechanics
I spent most of the past few years preoccupied with the macro systems of Field of Cures, because that is the part of the game in which I want the player to explore ethical issues. But building version 0.3 made me realize that the moment-to-moment gameplay of Field of Cures is in dire need of a redesign.
In each version I have prototyped so far, the core gameplay is to choose a flower to collect pollen from, choose another flower to pollinate and gain seeds from, and then choose which of the seeds to plant. Each seed gets half its genes from each parent flower at random. By understanding the model of the game, the player can maximize their odds of getting the offspring they want, but it is never fully in the player's control.
I believe the problem with this gameplay is that the model is too abstract. Genes pass from the parent flowers to the offspring seeds automatically -- the algorithm chooses which genes in a "black box" where the player can't see the logic. This also makes the game primarily a tedious exercise in hoping you get the randomized results you want.
My idea for version 0.4 is inspired by the card game Memory. The genes of each parent flower will be represented as six playing cards, and the full pool of 12 cards with be shuffled together face-down during cross-breeding. To determine the genes of each offspring seed, the player will select six cards from the pool. The crucial twist will be that the offspring can only get one gene for each trait from each parent. For example, a flower carries two color genes. When the player selects one of that pair of color genes, the other card in the pair will automatically be burned. This is because the offspring's other color gene must come from the other parent.
I believe this gameplay will strike a balance between illustrating the randomness of genetic inheritance in nature, and giving the player interesting choices to make during crossbreeding. More important, this metaphorical representation of cross-breeding will make the game's model of genetics easier to understand.
I suppose I have not yet stated the obvious in this blog: I'm currently working on my dissertation half a year into the COVID-19 pandemic, which has killed more than 180,000 Americans at the time of this writing, and with two months to go before the presidential election between a Democratic moderate and a piece of reality TV trash who now leads a proto-fascist cult.
I'm trying my best to stay positive, Dear Reader.