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  • Application of SRK Framework to Game Mechanics

    [06.17.10]
    - Paul Goodman
  •  Introduction

    Raph Koster, in his book A Theory of Fun, describes games as "puzzles to solve, just like everything else we encounter in life" (Koster, 2005, p. 34s). Puzzles and games alike are built on the foundation of their game mechanics; the mechanisms and functions that individuals use to engage a game and its environment with the ultimate goal of completing the game and finding the puzzle's solution. A good game can attribute its appeal and success with players to its well-designed, usable and effective game mechanics.

    However, in the design of game mechanics, one crucial construct can often be overlooked in that individuals engage in different kinds of cognitive behavior when completing different kinds of activities and tasks. At their core human beings are "furious pattern matchers" (Reason, 1990, p. 66), and through daily life seek out the structure in all manners of activities, including playing games. In games, these structures and patterns take the form of game mechanics, and if a player is presented with a mechanic and is unable to process and understand its function in the overall structure of a game, they can get frustrated and give up (Koster, 2005, p. 25). As game mechanics today incorporate a wide variety of task and activities in the form of puzzles and obstacles to be overcome, they usually require different types of behavior and action from a player to complete them.

    The issue with human cognition being left out of the design process arises in the development of the mechanics designed for use in completing a game's puzzles and obstacles. If a game's mechanisms are too easy to grasp, the game may "grow boring when they fail to unfold new niceties in the puzzles they present" (Koster, 2005, p. 42); if they are too difficult or complex, it may lead to player frustration. This leads to the question, is there a way of including a method of examining player cognitive performance and errors in the design and modification of game mechanics?

    Skills, Rules and Knowledge Framework, a method which measures cognitive behavior and assists in determining what causes human errors, may be of potential use in the design and modification of game mechanics. In the first section of this paper both SRK framework and the types of human error will be detailed, along with examples of how SRK Framework has been applied since its initial development. The second section will focus on the definition and categorization of game mechanics, followed by a proposed application of SRK Framework to each category of game mechanic. Finally, implications for combining SRK framework with game design will be discussed with suggestions for future use.

    SRK Framework

    The Skills, Rules and Knowledge Framework (or SRK taxonomy as it is sometimes called) is a method of measuring human cognitive performance and determining at what cognitive level particular tasks and activities are being performed. Developed by Jens Rasmussen, it defines behavior across three separate levels: Skills, rules and knowledge-based. It also provides information on the kinds of human cognition conducted at each stage.

    Skills-based behavior is an activity or task that for the individual undertaking it, is a routine behavior. The task or activity is completed using "smooth, automated, and highly integrated patterns of behavior" (Rasmussen, 1987, p. 292), without the individual putting a significant amount of awareness or consciousness into the task or activity; it can be considered almost instinctual in nature. A fairly common example of a skill-based behavior would be riding a bicycle or driving a car. These are tasks that experienced individuals can accomplish without focusing too clearly on what they are actually doing. Instead, during a skill-based behavior, an individual's senses are focused on subconsciously keeping them oriented and informing them of changes in the environment (Rasmussen, 1987, p. 293) one's internal processes as to the progress of the Skills-based behavior, such as watching for road obstructions while driving a vehicle or riding a bike.

    Mistakes at the Skill-based behavior level can occur on two different levels, overattention and inattention. Overattention is an interruption "of an action sequence at a time when control is best left to the automatic 'pilot'" (Reason, 1990, p. 73). An individual focuses too heavily on their progress and how they are trying to complete a task, resulting in errors or mistakes during the process. A Guitar Hero player may have difficulty in hitting the correct buttons on the controller to properly match up to the chords of a song if they are focusing specifically on the placement of their fingers on the controller rather than the act of playing the guitar itself. Inattention is related to an omission or interruption of a step in a skill-based behavior. Opening an email account to check for new messages but then closing it before reading any of them is an example of an omission mistake in a skill based behavior; receiving a phone call during the process of checking's one email account and then closing the email account once the phone call is over without reading any new messages is an example of an interruption.

    Rules-based behavior is similar to Skills-based, in which the actions being taken to complete the task at hand are still, for the most part, commonplace to an experienced individual. However, there are additional checks and routines built in along with more cognitive and conscious effort placed on completing a task or action. Rules-based behavior is guided by a "stored rule or procedure...derived empirically during previous occasions, communications from other person's know-how as instruction" (Rasmussen, 1987, p.293) or through previous successes in problem solving and planning. While driving a car may be skill-based behavior for experienced individuals, other driving actions such as merging lanes or stopping at traffic lights fall under Rules-based behavior due to the additional cognitive and conscious effort required to successfully complete them.

    Rule-based mistakes occur when an individual's stored rules are either sufficient to complete a task or solve a problem, but are misapplied and used incorrectly. It may also occur when the stored rule is actually insufficient or inadequate to assist in completion of an activity, but an attempt is still made to use it. An experienced individual, having dealt with a particular situation several times, may rely on their current set of rules that have allowed for that individual to achieve an acceptable outcome in the past- such as double checking mirrors when merging with traffic on a busy highway. The more and more successful traffic merges using that rule will lead to that rule becoming stronger, and the "stronger the rule, the less it will require in the way of situational correspondence" (Reason, 1990, p. 77) for that rule will be used. A mistake using a strong rule can occur when that rule is used incorrectly; an internally developed rule of double-checking one's mirrors before merging into traffic could lead to the failure of that task if applied at the wrong time or if distances between other vehicles on the road are misgauged while the mirrors are being checked.

    The application of bad rules occurs when the rules being used to complete a task are inadequate to successfully complete that task, or the particular rule being implemented is inadvisable to the situation at hand. As an example of a rule being inadvisable, imagine the 'check engine' light of an individual's personal vehicle is active when they first turn on the ignition. If they turn the vehicle off, and then on again to see if the indicator goes away, and if it does, they assume the vehicle is perfect working order, that individual may potentially be making an inadvisable rule-based error. The problem that set off the 'check engine' light in the first instance may not have been resolved by the restart, even though the indicator itself is no longer active. Such a rule-based behavior isn't necessarily wrong in the sense that it "generally achieves its objective, though it may violate established codes or operating procedures" (Reason, 1990, p. 84), it's just not recommendable because of the potential to cause more problems.

    Knowledge-based behavior occurs primarily when the activity being engaged in is a task an individual has never engaged in before. The individual has exhausted all of their options and problem-solving routines at the Skills or Rules-based level, and therefore has to use "slow, sequential, laborious and resource-limited conscious processing" (Reason, 1990, p. 57). In other words, the individual has to (either mentally or physically) research and experiment to find the best way to complete a task or achieve a particular goal. While an experienced individual may be able to operate a car with little effort and then navigate that car through traffic, if they have never undergone a road trip travelling cross country before, they would have to engage in conscious planning in order to successfully travel from point A to B. A goal would have to be established, based on the analysis of the environment and any objectives the individual may have, they would also need to develop a plan, either through trial and error in a physical sense, or more conceptually through understanding an environment's functional properties in addition to predicted outcomes of the plan being formulated (Rasmussen, 1987, p. 293). The same concept can be applied to experienced video game players; an individual that has been dedicated to playing games under the first-person shooter genre, and are unfamiliar with any kind of massively multiplayer online role playing game, would engage in knowledge based behavior in order to understand that game's systems and architecture.

    Knowledge-based mistakes are somewhat more difficult to predict than either rules or knowledge based errors, particularly due to the fact that it involves solving a problem or completing a task an individual has little to no experience in handling as "uncharted territory" (Reason, 1990, p. 58). Usually errors at the knowledge-based level are centered on how an individual interprets the problem or task facing them. A type of knowledge-based error is the concept of 'out of sight, out of mind', in which an individual will use "only information which is readily available...to evaluate the situation" (Embrey, 2003 p. 8) when completing an unfamiliar task or trying to solve a problem. An example can be found in a 1978 study of how individuals can troubleshoot problems using 'fault trees' (an organized representation of the various explanations for a situation, usually in the form of a diagram). Fischoff et al (1978) gave their subjects an example scenario of a vehicle failing to start, presenting them with various versions of a fault tree diagram depicting all the potential reasons for why the vehicle might be malfunctioning. The subjects were instructed to examine the diagrams and judge them on if they considered all of the possible explanations for the hypothetical vehicle's issue. One of the more unique results of the study found was that subjects often overlooked the removal of branches in the various versions of the fault tree diagrams used, some of which had exclusions of very likely potential explanations such as 'battery failure' or 'ignition failure'. One of the possible reasons given was that subjects may have been ignorant; "there is no way to consider something that one has never heard of and that is not mentioned" (Fischoff, et al., p. 343). As both experienced mechanics and college students were interviewed, it's quite possible that many subjects committed a knowledge-based error because they relied primarily on the information they were given as to the hypothetical failure of a car, instead of considering additional factors which may have also been a cause.

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