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Tuesday, Aug 10, 2010
“In the final analysis, a critique of performance practices must ask: Who gets to play?"

One of the reasons that Johan Huzinga’s book Homo Ludens has such an important place in gaming culture is that it writes a blank check for game studies. If the play element can potentially be found in any part of culture, then any part of culture can be discussed from a gaming perspective. Mary Flanagan’s book Critical Play is an examination of that concept from the perspective of social activism. Often involving artists and poets, it outlines the play element of several cultural movements and how they used games to raise awareness and accelerate social change. Like many games today, a lot of the games that Flanagan discusses are difficult to understand unless you’re playing them. I picked out examples that I thought I could communicate effectively, but it is a massive topic that can’t be fully accommodated on a blog. So, bear with me here.


Flanagan proposes several overarching guidelines for critical play and how it works. She writes, “Critical play means to create or occupy play environments and activities that represent one or more questions about aspects of human life . . . . Criticality in play can be fostered in order to question an aspect of a game’s ‘content,’ or an aspect of a play scenario’s function that might otherwise be considered a given or necessary” (6). A basic example of this process occurring naturally is playing with dolls. Often used to enforce gender roles and stereotypes, many young girls today and in the early days of the doll industry would use dolls to subvert social roles. Violent fantasies, macabre funerals, and other forms of changing the way play worked with dolls provides a striking example of critical play in its natural form. Flanagan writes, “The enactment of critical play exhibits at least three kinds of action: unplaying, re-dressing or reskinning, and rewriting” (32). “Unplaying” is acting out forbidden scenes with the doll. “Re-dressing” is changing the doll’s appearance or items for darker play, like making funeral items and caskets. “Rewriting” is fan fiction and the proliferation of people writing stories about the doll funerals.


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Tuesday, Aug 3, 2010
At the end of the fourth season, LOST abandoned mimicking the content of video games and instead focused on how they characterize space.

An excellent article at PopMatters by Elwyn Palmerton details the many similarities of the first four seasons of LOST with adventure games. One of the show’s creators, Damon Lindelof, has noted that the game Myst was a big inspiration, and it makes sense. A remote island filled with unexplained mechanical gadgets, the slow process of gaining access to these areas, and other video game plot devices are scattered throughout the show. Keys and objects are often the focus of the plot, characterization occurs during the static flashbacks, and much of the show is spent moving from different locations. The show’s first four seasons so heavily resemble a classic adventure game narrative that several spoofs have appeared suggesting what a Lucasarts version would be like. There are a few other video game aspects of the show that I thought were worth pointing out, particularly ones that develop after the period of the show that Palmerton’s article covers. At the end of the fourth season, LOST abandoned mimicking the content of video games and instead focused on how they characterize space.


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Tuesday, Jul 27, 2010
A multiple choice exam is looking for a sweetspot of a certain percentage passing, not too high and not too low.

The multiple choice question may be one of the most despised games ever conceived. The purpose of a multiple choice exam is to exclude people in a quantitative manner, be it for admission into schools, licensing professionals, or limiting the number of high grades in a class. Assessing a person on their individual merits is a time consuming process, and once a school or class hits a critical mass of students, it isn’t economically reasonable to scrutinize all of them. Let’s say you’ve got 1000 participants and five people reading their results. You can cut time and costs by figuring out a way to neatly get rid of 500 because they scored under a certain amount. A multiple choice exam cannot be so difficult that you exclude an excessive number of applicants. Most law schools, for example, have a minimum LSAT score that you must score below for automatic denial and a high score for automatic acceptance. Applicants in between those scores are then addressed on an individual level and other factors are introduced. The problem with such a system is that to ensure a multiple choice test produces the right number of passing scores, you have to keep changing the questions.


An article by the National Center for Fair and Open Testing explains, “multiple-choice items are an inexpensive and efficient way to check on factual (“declarative”) knowledge and routine procedures. However, they are not useful for assessing critical or higher order thinking in a subject, the ability to write, or the ability to apply knowledge or solve problems” (“Multiple-Choice Tests”, Education.com). It’s for that reason that a multiple choice question is always limited in scope: it can only be about basic knowledge of a topic. The formula is to have two answers that are blatantly wrong, one that is kinda right, and one that is the most right. One instructor during a review session for the BAR pointed out that on average a student will know the correct answer immediately to 25% of the problems, have no clue on 25%, and be able to boil it down to the right and kinda right answer for the other 50%. So the way that you evaluate the difficulty of a multiple choice question is how similar the right and kinda right answers are. A person who can’t boil it down to those two doesn’t know the basic material and shouldn’t pass.


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Tuesday, Jul 20, 2010
The art of video game AI is in making a player think that they’re interacting with something more sophisticated than it really is.

Video game artificial intelligence is a fascinating merger between programming and artistic deception. Richard Bull, lead AI programmer for Empire: Total War explains in an interview, “the AI academics are your wizards and we’re your stage magicians—it’s all smoke and mirrors with game AI” (Ben Hardwidge, “How AI in Games Works”, bit-tech, 5 March 2009). An academic trying to simulate a human brain has a massive super computer devoted to the task of thinking, while an AI programmer for a video game is instead working with a small percentage of processor power. The majority of the computing power in games is instead going towards depicting graphics, sound, physics, and cow bell type things. For example, technically the AI in Halo 3 is less sophisticated than in Halo 2 because most of the processor has to be devoted to graphics. A giant, open world game will inherently have stupider AI because there just isn’t enough power to go around. So the art of video game AI is in making a player think that they’re interacting with something more sophisticated than it really is.


The first and most obvious technique for making an AI look smart is just keeping it alive long enough for the player to even notice it. An in depth discussion of the AI in Halo points out that the main difference between playing the game on Easy versus Legendary is that everything has more health and the player has far less (Alex J. Champanard, “Teaming Up With Halo’s AI: 42 Tricks To Assist Your Game”, AIGameDev.com, 29 October 2007). Play testers were more complimentary of an AI when they were able to observe it perform various tasks as opposed to just killing it on sight. Consistency is also an important factor, it’s important to not curve difficulty by dumbing down the machine or reducing its abilities. Once you see an AI behaving stupidly, the impression is permanent. Once a person is observing the AI, it’s also important to make sure that it’s broadcasting its conduct back to the player as much as possible. The Brutes seem smart in Halo 3 because we hear them shouting, “Flank him”, before they execute an otherwise simple AI command. Grunts seem like they’re responding to us because they shout “Run away”. Getting the player to even notice that the AI is doing something besides shoot is the first step to making it look good.


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Tuesday, Jul 13, 2010
The perception of challenge in a game is always contextual and based on prior experiences in the game space.

In the now lengthy Castlevania series, Order of Ecclesia should rank as the second best of the Metroidvania styles. First place should go to Symphony of the Night by a very slight margin and third to Aria of Sorrow. The funny thing about even saying one Castlevania game is better than another is that very little changes in any of them. Plots are almost non-existent and characterization even less so. You’re always there to kill Dracula or someone is trying to be Dracula. Like its sci-fi sister Metroid, you spend most of the game exploring a map or collecting abilities that let you explore more regions. The RPG system is a fairly basic leveling up routine with variety added only through how you collect abilities. The biggest difference amongst the titles is how each Castlevania game handles difficulty.


When I refer to difficulty, I don’t mean it in the abstract sense of the word. I mean the player’s quantifiable ability to ignore the game design’s desire to kill them through the use of health potions, overpowered weapons, being immune to damage, and general button mashing. Common sense indicates thst you should go soft on the player in this department while they learn the ropes and then eventually put your foot down and force them to actually play the game. Difficulty is then perceived because I have to change the way that I am playing the game in order to continue it.


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