For my experimental digital art class at Georgia Tech, I created this toy I call SoundPen. It’s a very basic version obviously (although I think some cool things could come from this idea).
The basic idea is to create music by clicking your mouse and placing balls that will bounce of the screen. There are 3 different types of balls (click and press either A, S, or D).
I used Jeff Swartz’s algorithm to change pitch of the sounds from the vertical balls. The more left the ball is on the screen the lower the pitch while the more right on the screen the higher the pitch.
Please be careful when using. If you place too many balls your computer might slow down rapidly. If you want to remove the last ball just press the backspace.
There are probably ways I could have fixed that problem (for example, using lower level PixelBender capabilities to process the sound); however, I don’t think it matters too much. You don’t want to put too many balls anyway because you’ll just hear noise.
The Internet has provided a new means of data expression. I decided to play with the idea of machine aesthetics by developing an application that creates images of images.
I first saw this effect a long time ago on a poster advertisement for the Truman show. I always wondered how they made the effect of compiling images together to form, when looked at a certain distance, an image. The program I made this week creates the effect by downloading Flickr images.
The algorithm is very straightforward (I also mention some ideas for expansion on the Flash). Basically the program downloads Flickr images either by the most recent, based on a search term, or from a username’s public photos via the as3flickrlib. While downloading, the application calculates and caches each photos average RGB color average (the main reason why my algorithm is fast). The program, based on the user’s supplied number of rows and columns, calculates the average RGB color of each divided cell and finds the image with the average color that has the closest 3D distance to the cell’s average color. The effect is pretty cool. I offer the ability to have a very high resolution (which basically expands the original image before running the algorithm to near the max of Flash Player 10’s bitmapData’s limit). The picture effect is best seen with the highest resolution.
A unit of measurement is defined as “any division of quantity accepted as a standard of measurement or exchange.” Units of measurement are critically important in associating meaning with quantities. One gallon of milk, one-hundred yards on a football field, or a thousand pages in a book are examples of a numerical multiplicity of units that have definite associations with their respective mediums. People identify with a gallon, yard, or page because each unit holds concrete meaning and magnitude.
In the context of video games, measurements of success are determined by evaluations of player experiences and presented as quantifiable units. Unfortunately, the units used in video games are often times simply “points” that are calculated from multiple dimensions of mathematical operations and offer little or no verisimilitude to the fiction in the game. The educational Apple II game The Oregon Trail, played in the late 1980s and early 1990s, while offering fictionally relevant death-screens, exemplifies the mistake of using incoherent and abstract “points” to evaluate the success of the player.
In this essay I will first briefly mention the method of score calculation and evaluation by non-digital games and the significance of their choices of score computation and units. Afterwards, I offer my explanation of why video games tend to stray away from the mechanics of score computation offered in non-digital games. I then introduce the Oregon Trail and the game design choices that relate to the pioneer life of the 1840s and 1850s. Next, I outline the problems of the evaluation mechanism of the Oregon Trail and how it regrettably detaches itself from the fiction. Lastly, I propose an alternative means of player assessment in the Oregon Trail and its benefits.
Part 1: Scoring without Computers
There are people who have careers in studying sports’ statistics. These statisticians predict un-played games via the analysis of played ones. The sheer quantity of logged statistics is overwhelming. In addition to points, basketball has a multitude of statistics for teams and players such as assists, rebounds, blocked shots, and turnovers. Baseball statistics consist of pitch count, balls, strikes, bunts, errors, batting average, earned-run-average, on-base-percentage, and the list goes on. However, while all these numbers are tracked, the only numbers that matter are runs, goals, or points. If a team has the most runs, goals, or points in a game then they are declared the winner. In these non-computers based games, the way of incrementing the unit of score of is typically single or low dimensional. For soccer and hockey, this causation is passing the ball/puck past the goal line to score a goal. For baseball the causation is stepping on the plate to earn a run.
Occam’s razor applies in scoring in non-digital games. Giving bonus points to teams that score a bicycle kick or subtracting points for missed questions in a trivia game would add unnecessary complexity. In the context of score culture, players discuss or use secondary units of metrics in games for comparison. Obviously, there is a direct proportion to secondary statistics to primary statistics. Baseball teams with better batting averages tend to win more games. Sports fans use secondary statistics as reasons why their favorite team is better than the other. But those interpretations are always subjective and speculative. At the end of the day, the primary statistic is what matters. Who cares if the team’s batting average is the highest in their division if they aren’t making the playoffs? As the late German soccer coach Sepp Herberger famously told his team, “The ball is round, the game lasts 90 minutes, everything else is… theory.” There is no justice in giving extra points to teams with higher batting averages either. Games that apply weight to specific secondary statistics risk ruining the balance of the game and cultivate an unanticipated culture of community assessment.
Part 2: Cultural Effects of Assessments
Evaluation is an embedded part of our lives. Capitalism, by definition, encourages competition and evaluation. Exams in schools rank our performance with tests and assignments. Importantly, test grades are often calculated with a single dimensional computation: percent of questions answered correctly.
More important, especially in relation to video games, is the concept of score inflation and deflation. While a test grade of C implies average, a class full of D students may consider a C above average. In games the same process applies. Both game designers and teachers attempt to predict average results of a game in order to assess player experiences. However, game designers that fail to predict accurately force players into creating community-based assessments. Scoring five goals in a soccer game is considered abnormally high because of the outcome of previous games. Game designers don’t have the luxury of previous gameplay data; consequently, most video games don’t have built-in interpretations of the players’ experience. Comparisons are often absent in video games and the gaming community itself turns the scores into meaning. Interpretations are usually best left to the community; games sometimes catalyze community comparisons with scoreboards. “You’ve made the high scores!” is the typical embedded evaluation of a player’s experience. Yet, what typically happens is that the community ignores the points and focuses on the experiences themselves as sources of evaluation. This phenomenon is evident in many action games via conversations players have with one another in society. “I just beat the second boss!” or “Oh yeah? I reached the third boss and killed him with only a knife!” The experiences become the metrics, and the units of measurement used in the game are disregarded.
Most of the time failure is attributable to the incoherence between the metric and the fiction. “Points” is a commonly used yet linguistically abstract term with little relevance to the fictions it represents.
These points are often calculated in a meaningless way. Games tend to have a multitude of methods in computing score which have little or no coupling to the player’s experience. In Pac-Man the player amasses points throughout the levels by eating ghosts and collecting dots; however, the Pac-Man competitive culture became more about “What fruit did you get to?”; a reference to the various types of fruits the Pac-man encounters in later levels. The fruit became more significant to the players than the points because the fruit had a tighter coupling to the player’s experience.
Besides encouraging replay and competition, one of the reasons video games have propensity to add loosely-coupled, computationally complex scoring components is the obvious ability of the computer to process and store information. Non-computers based games left storage upon the players rather than on the system itself. The popular game of Tic-Tac-Toe is a perfect example. What if Tic-Tac-Toe had a rule that if a player waits more than 3 seconds on their turn, then the other player is declared the winner? One can only imagine the arguments players would have over the amount of time a player waited. The choice of leaving this rule out is not coincidental. Requiring the use of a stopwatch during play would be ridiculous. However, the computer provides many affordances for games; one of those affordances is the ability to track time length. Consequently, this additional rule can be added to the game without destroying the physical experience of playing the game. But in game design, the consensus has generally pointed toward justice and balance rather than coherence; consequently, multiple added rules can deter the meaningfulness of the score.
For instance: a player may kill fewer 100 aliens in a first person shooter but could receive a score of 3104 depending on the number of headshots, amount of ammunition used, etc. Unfortunately, while this approach may be seem competitively fairer, the unfortunate fact is that players have a difficult time understanding their score during gameplay when score computations are multidimensional. Only the computer, due to its procedural nature, can keep track of the scores.
Another affordance of computers over humans is the abilities of processing and memory. Humans playing multidimensional scoring games rarely know how much their score will increase because of human mind limitations in determining rationality of the numbers. Games that dispense thousands or even millions of points for random achievements are easy examples of games in which the points’ computation lose meaning. Unfortunately, games that fail to offer a coupled, low-dimensional scoring mechanism risk ruining the player’s ability to improve their performance. A player is expected to master a game after receiving feedback and modifying future game decisions based on that feedback. Yet, multi-dimensional feedback is nearly always more bias due to the selections of the weight of each attribute in the score formula. Score justice is a consequently unattainable achievement due to score bias. Especially for fiction games, implementing every possible parameter into a final score is typically an impossible task; consequently, designers must choose specific attributes they deem important. This process of selection creates the score bias. Additionally, score justice is circumvented via “score loopholes”; players may find strategies of racking a high score by performing a specific gameplay process repeatedly. An example of a score loophole is found in the 1985 MECC game The Oregon Trail which I discuss later. The Oregon Trail is an example of a game that attempts to justifiably evaluate player performance with a confusing, zero-coupled, multidimensional scoring computation.
Part 3: The Oregon Trail (1985)
The Oregon Trail, originally conceived in 1971 and produced by MECC in 1974 before released to public in 1985, is a heavily fiction based game about pioneer life on the real Oregon Trail in 1848. The player undertakes the role of a banker, farmer, or carpenter that leads a family across North America on the Oregon Trail. Starting in Independence, Missouri, where most pioneers began their migration, the player manages food, clothing, oxen, money, and hunting bullets throughout a long and eventful voyage to Oregon.
The Oregon Trail has tight couplings with its 1850s fiction during most of the playing experience. Nearly every event and action has coupling to the fiction presented in the game; consequently, the game became a very successful teaching tool in elementary schools. Some events include members of the wagon party obtaining various sicknesses or injuries or thieves randomly come at night to steal supplies; these events were faced by travelers along the real Oregon Trail. Choices are also relevant: at the cost of health, food rationings and wagon pace can be modified in dealing with shortage of supplies. Even the character death results are particularly verisimilar. In addition to the removal of the wagon member from the group, the player has the option of placing custom engraved tombstones at the place of the death. Later players will have the option of viewing these tombstones on their own journeys.
However, strangely enough, The Oregon Trail fails miserably in the win-state department. While most explanations or outcomes of the game are relevant toward the life of the pioneers in 1848, the final screen simply shows a numeric score; the result of a series of irrational mathematical operations.
From Wikipedia: “Points are awarded according to a formula weighted by the profession chosen (points are doubled for a carpenter and tripled for a farmer), the number and health of surviving family members, remaining possessions, and cash on hand.”
Surprisingly, the only difference between vocations in The Oregon Trail is the bonus multiplier associated at the end of the game. Instead, the game should have offered different affordances for each role. A banker should have better bargaining skills in buying items and trading, farmers should be able to keep the oxen alive longer and have better hunting skills (in The Oregon Trail hunting mini-game the character is unable to carry more than 100 pounds of killed animals back to the wagon), and carpenters should be able to repair broken parts more quickly than the other two roles. Instead, The Oregon Trail chose to simply alter the amount of starting money for each role and change the bonus multiplier. The Oregon Trail lazily uses vocation selection as a “difficulty mode” selection.
The scoring’s multidimensional complexity, in addition to confusion, affixes gameplay bias. The game says that an “Odysseus” pioneer with more food at the end of the trail is ranked higher than a pioneer with less food but more surviving family members. The Oregon Trail argues that a wagon leader’s goal is to balance supplies and money by the end of the trail… and to also be a farmer. The Oregon Trail subjectively applies value to specific vocations and decisions instead of linking the performance to the pioneer narrative.
Part 4: Narrative Evaluation Alternatives
A better alternative to the irrelevant scoring system used in The Oregon Trail is revealing the player’s family/party upon outcome after settling in Oregon. Instead of attaching a number to the player’s performance, simulate the post-journey result of the family. Historically, settlers arriving in Oregon sent letters east to other families and friends describing their happiness and state in Oregon. In replacement of showing score calculation, the game could display a letter sent by the player’s family to a fictional family or friend back home in Independence, Missouri describing their state in Oregon. Depending on the resulting supplies and cash, the letter is written with a different tone and result.
Money is dispersed at the beginning of the game but not earned through the adventure. Sequential checkpoints increase the price of supplies; consequently, players stock supplies early on to save money. If the player has no money at the end of the trip, the player’s letter home can contain information regarding how “money has been tight” and that their house is “small” and their kids attend “poor” schools. The more money the player saves the better the schools and larger the land they own. If the player keeps less clothing the letter can read how winters have been tough. If they kept oxen the letter can write how they’ve been able to use their oxen to travel to town to buy supplies such as clothing to manage with the winter. Depending on the vocation of the player the letter can read differently as well. If the player is a banker, depending on the other variables he or she has found a specifically ranked job from “unemployed” to “President of a National Bank” (Congress passed (1863) the National Bank Act, which provided for a system of banks to be chartered by the federal government). The Oregon Territory was acquired in 1848, the year the player in the game begins the journey and Oregon became part of the United States in 1859. Farmers could write in the letter their poor or strong harvests. Carpenters can also become architects with varying positions.
This custom “alternative ending” approach would help fix the deficient narrative of the end game. Pioneers in the 1850s journeyed to Oregon for a better life. Integrating those dreams and aspirations with the game adds agency. In reality, all the attributes and parameters of the trip are still being incorporated into the final assessment of the player’s experience; however, instead of showing a number, the game shows a narrative in the form of a letter.
In relation to the competitive aspect of the game, narratives do not provide the ability for unbiased comparison. The Oregon Trail from 1985 has a high score table feature to rank players according their numeric score. An overall rating is given to each player such as “greenhorn”, “adventurer”, or “travel guide”; a value determined by the score. Since my
“letters back home” proposition employs narratives that can only be subjectively evaluated, a ranking system based on those narratives is unfeasible as different players may view varying narratives as more “successful” than others depending on their personal definitions of success and failure. However, instead of eliminating the “Oregon Trail Top 10” scoreboard, the scores should be replaced to a simple number of days taken to reach Oregon. There is already a direct proportion in days taken to reach Oregon and the numerical score. The better the player manages their supplies and health, the faster the player will reach Oregon. In fact, there is a more direct proportion to the management of the entire experience in days taken than there is in the current formula for score calculation. The current scoring formula only applies to the result of the trip rather than the progress. For instance, suppose a player travels the trail with “good” health. Consider if player’s health at the very end of the trip, right before reaching Oregon, falls to “fair.” The player’s score will be comparatively lower than that of a “good” health ending player even if the “good” health ending play held “fair” health through entire trip. The Oregon Trail, as with all games with multidimensional scoring systems, suffers from these unexpected “score loopholes.” The narrative endings solve the problem of point bewilderment and loose-coupling and as well as encourages varying gameplay experiences to see different endings.
Evaluations tend to be quantitative instead of qualitative. Consequently, their evaluations are often ignored by players. Using abstract and extraneous formulas and bonuses damage coherence, agency, and ultimately immersion. To retain verisimilitude in player experiences, performance evaluations necessitate low dimensionality and fictional relevancy.
The following is a prototype of an example end screen letter a player may see. Modify the inputs to see varying outcomes.
1. P. University, “WordNet Search Dictionary,” Book WordNet Search Dictionary, Series WordNet Search Dictionary, ed., Editor ed.^eds., Princeton University, 2006, pp.