Without some static and continually observable stimuli to document for empirical repeatability gauging entertainment value and gameplay intensity becomes far more challenging. Clearly those with the resources to record data on the matter with a high degree of reliability as far as their recording techniques go have the upper hand. However there are a few starting points and tools that can be used to get a better sense of what is more entertaining and optimally challenging.
An intuitive conception of what sort of notion is worthwhile as far as entertainment goes is inquiring whether the user has stopped playing the game prior to the typical length of time one remains attentive to a task that requires learning. In long-winded games, for instance, a user that stops playing twenty minutes into gameplay is likely not a satisfied one and most likely one who has not completed the game. The same user can play a different game for hours, and through data it can easily be shown that the characteristics and preferences of the player matter little as compared to the entertainment value of the game, measured in this case by the duration of play. Thus there is something to say about the quantification of entertainment as a value and there are some distinct indicators that can be adjusted to compliment gameplay as needed.
On the elementary level a risk-and-reward system must be created in order to take advantage of the primitive behaviors which partially undergird game interaction. Thus there must be a clear way in which the player interacts that offers a risk or punishment mechanism and a reward mechanism. These systems vary greatly but the evident value of a game dissipates without one or the other. Imagine, for instance, a shooter game where nobody dies or a football game where nobody keeps score. Chiefly among the characteristics which influence the understood value of an interaction is timing. Various parts of the brain contribute to risk-and-reward and participate in recording delays in some manner, such as the frontal and parietal cortex, the amygdala and the striatum . Generally, the greater the delay in reward the less of a response is given to stimuli acting as reward-predictors. However in the case of the amygdala, for instance, neuronal response varies based on the population of neurons and the probability of instantaneous reward. Despite the complications the primary obvious issue is the relevance of timing in a reward system and the variation of the response according to the duration of the delay before the reward is given. Any game whose rules force the delay between action and reward to last far beyond the duration of the activity should not be expected to have the same type of satisfaction as those that moderate the proportion of investment value to delay.
Alongside this ought to be taken into account the relevance of user-control and the degree of control, since this appears to have a relationship with entertainment value or compliance; data showed that, comparatively, a more user-controlled environment lead to greater compliance measures than an automated environment . Providing freedom and efficacy within the constraints of a game should generally lead to a more engaged player. This includes such seemingly inconsequential details such as the choice of reward and operation of play within the rules of a game.
There is also something to say about the juncture between the risk-and-reward system and the level of intensity or challenge of the game, as dopamine may be relevant in relation to gameplay performance . Perceived difficulty has been recorded to increase monotonically (consistent increase) with measured difficulty and there is a threshold beyond which the goal of the game in question is rejected by the majority of users . Thus the best sure method of intensity optimization is experimentation with a group of individuals within the population of the target audience. The design objective is to maintain a challenging encounter and goal acceptance and a high probability of success while conceding some leeway when it comes to probability of success.
In most cases it is not possible for designers operating on a small scale to gather the resources to experiment with control groups of a population so as to optimize gameplay performance and entertainment value but there are various human-universal characteristics which may contribute to the creation of a foundation on which smaller-scale testing can occur.
 Bermudez, M. A., & Schultz, W. (2014). Timing in reward and decision processes. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 369(1637), 20120468. doi:10.1098/rstb.2012.0468
 Nagle, A., Riener, R., & Wolf, P. (2015). High User Control in Game Design Elements Increases Compliance and In-game Performance in a Memory Training Game. Frontiers in psychology, 6, 1774. doi:10.3389/fpsyg.2015.01774
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