Design of Educational Games: Game Critique 1

GerryMander

Developer: Good Egg Games

Platform: iOS, Android,

High-Level Instructional Goal: Political Science, Gerrymandering

Description:

GerryMander is a puzzle app developed and published in 2017. At the beginning of the game, you decide which party you want to “help destroy democracy”, red or blue. Then, you are faced with different map puzzles where you can draw fences around different colored characters with the goal of securing a majority vote for your chosen party. Depending on the type of map they lay out, the amount of people in each “district” will vary, but the main constraints are always constant. There is also a stopwatch at the top of the window, which incentivises speed: there are certain medals you can get based on how quickly you can complete each level. As you continue through each level, you face new challenges such as “doubled up” squares of 2 people too close to seperate.

The game features little descriptions of each map while it’s loading, and funny cartoonish “cackles” when the main instructional characters are speaking through speech bubbles.

Retro, old-school and pretty witty.

Learning Objectives:

A. I would guess that regardless of whether or not you knew what gerrymandering was, you would be able to understand the basic rules and mechanics of this game, probably enough to continue through each level without much of a disadvantage to someone who did. However, because one of the main purposes of this game is to understand the incentives for gerrymandering, that dark, comical side to political science would be lost on someone who had no idea what it was. There aren’t any super obvious clues that relate what is happening in the game to any current election, but with a basic sense of U.S. political party colors one could easily make that jump.

B. After playing for awhile, players are likely to gain a better understanding of the incentives behind gerrymandering. Because the game has so many witty quips and comments throughout, players will also pick up the idea that gerrymandering is undemocratic (granted, the name itself has a negative connotation, but then that’s probably why the designers kept the app title simple). The game is biased against it, and paints gerrymandering as this kind of dirty, blatant secret in modern politics. Players also pick up quick mental math skills and the ability to easily recognize the number of characters in a cluster, as well as a good awareness of how to map out the space according to the unique layouts of each particular puzzle.

C. As far as transferable knowledge goes, this is definitely a game that lives on the copy/character writing in order to enforce it’s point. Without all of the snide comments, I think it would remain just as a pretty basic puzzle game that tests counting and sorting skills under pressure, so those would be the only transferable skills that a player would gain. But because of the writing, I think players also pick up a definite bias against the process of gerrymandering, as well a (questionably realistic) understanding of the incentives and constraints that real life district designers deal with in their job.

Mechanics, Dynamics, & Aesthetics

Mechanics: The main mechanics are the ability to draw and remove fences around the different plots of “voters”, the highlight political party feedback you receive after you draw a complete district, and the positions/quantities of the various blocks of voters in a particular game. There is also an element of randomization when working on each map, as well as the ability to regenerate a new random map and undo and clear your work as you go. The main challenge is a time race, and you are incentivized to race against yourself to collect different time medals. There is also a way to collect coins, which I believe help you advance to future rounds (although I’m still unsure if there are other uses for these coins.

Aesthetics: There is a chunky, retro quality to both the visuals in the game and also the way certain actions respond to user input. Specifically, the option to draw fencing is constrained to a large grid size, so automatically the user is participating in adding to this cubic quality.

Another important part of the aesthetics is this idea of an individual mission. It’s a single player puzzle game, and the two political party representers are constantly talking to you as if you alone hold the fate of the election in your hands. You have a god-like control over the outcome of the characters, and as you progress through the levels you encounter more and more helpless people whose votes are completely in your control. I argue that this contributes to the aesthetic because it relates the real practice of gerrymandering to the familiar position as a user in a single-player puzzle game; reducing a an active practice in our electoral system to a video-game level further pushes the point that it’s evil and and sneaky.

Also, the sound effects are very evil and sneaky. There is a lot of snickering when you complete a level successfully.

Dynamics: I talked about this in aesthetics a little bit, but I think the most prominent dynamic between the mechanisms of this game and the aesthetics is this combination of having only yourself as a real opponent and ruling over tiny, pixelated, helpless humans with your decisions. This combination relates actual, modern gerrymandering in the U.S. electoral college to an old-school, easy to understand video game. The dynamic of solving this puzzle to create more evil feeds directly into the intended bias against gerrymandering.

Learning Principles:

This game is driven by fun: players are encouraged to continue to learn how to gerrymander a district because it’s fun to complete puzzles, and you get rewarded with coins and funny comments when you do. However, your skill increases as you continue playing mainly because of two learning principles: feedback and variability. When you draw fences, you are able to determine in real time whether or not the district they drew is red, blue or invalid. This feedback enables the player to quickly correct themselves, and decreases the time it takes to learn the puzzle rules and excel. Combined with this is the variability of the puzzle rules themselves, which change as you continue through the maps. Being able to apply skills learned in earlier levels to the changing challenges of higher levels teaches players to gain transferable skills that remain with them outside of a single level, and ideally outside of the game. Along this vein, GerryMander also incorporates anchored learning: this puzzle game is grounded in the real life practice of gerrymandering, so by playing this game and understanding this practice gives players the ability to better understand the U.S. political system.

Synthesis and Critique

I think that by exclusively looking at the EDGE framework principles in relation to each other, GerryMander is pretty strong. There is a strong, polished aesthetic language carried throughout the appearance and interactions, but behind all of this there is a concrete and challenging puzzle that is directly tied to real world examples. Although the main learning objective is to understand what gerrymandering is, the game doesn’t present itself as educational.

I think this game is a a really fun puzzle, but only a decent example of an educational game. I think that it’s fun to play with at home, but if my high school AP Gov teacher assigned it as a study tool I wouldn’t have been any better prepared for the test. The game is very well designed, but the educational potential stops at teaching the player what gerrymandering id, and inflicting bias against it. Political science is a giant field and there’s a lot of different dynamics that could be explored in a puzzle app, but this specific game doesn’t push it too far and probably sacrifices educational potential for just pure enjoyment.

Written by

Designer. Currently at Asana, previously at Khan Academy. Language + Data + Digital + Print.

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