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利用生物测量法研究玩家体验的5点考虑

发布时间:2011-08-01 12:02:10 Tags:,,

游戏邦注:原文作者是PhysiologicalComputing网站编辑Kiel Gilleade,该网站文章主要是关于生理学信号(如心率)在游戏设计和用户评估中的运用。Kiel Gilleade个人的研究方向主要是生理交互式游戏机制的发展。

最近,我的同事Stephen Fairclough(他是利物浦John Moores大学的生理心理学家)发动了一场关于利用生理学来评估玩家体验的讨论。

以下是该讨论的后续文章的压缩版。本文旨在阐明,在已知涉及心理生理学的问题下,如何将基于玩家评估的生物计量研究技术推销给游戏开发商。

player experience valuation(from verticalslice.co)

player experience valuation(from verticalslice.co)

根据生理心理学在玩家体验评估上的运用这类文章及相关评论,我决定先展开一个想像实验。

想像一下,我供职于一个很大的软件工作室,那间工作室希望保证游戏销售量的同时,尽可能让产品(游戏邦注:每个版本的开发费用平均是3-5百万美元)质量过硬。工作室的高层之一询问我:“我们应该如何在用户体验的评估中运用生物计量学?这项技术不但实验设备昂贵,分析结果还要耗费大量人力,而且似乎没有人理解数据的含义。”(这种观点并没有夸大其辞,我曾经将一份相当模糊的生理心理学数据展示给另一名研究人员,他也深有同感地说:“生理学知识像巫术一样让人琢磨不透。”)

以下5点是生理心理学测量法的优越性所在,就当作是我对以上疑惑的回答吧。

1、在不干扰玩家的情况下,生理心理学方法可以对玩家行为进行持续性监测,然后传递数据。这种测量法比实时性(不打断实验)或按回顾标准进行的主观研究方法要优越。

这种测量法比单纯地监视游戏表现(游戏邦注:因为良好的表现在高低层次的生理心理学活动中均可达到)更敏感,且除了安上传感器,这种方法对玩家没有其他要求,从而避免了受干扰的风险。

2、使游戏公司明确生理心理学研究的作用。这种测量法不是对情绪、想法或心情的书面量化,也不是一种脑中探测器,而是研究记录了来自心脏、肺、皮肤、眼、肌肉和脑的人类神经系统的电子活动。

首先,我们如何预期一款好游戏带给玩家的感受?兴奋?专心?快活?受到挑战?让我们想想在实验术语中的这些生理学的陈述——现在利用生理学知识把这些词转换成人类神经系统的电子语言。例如,兴奋=交感神经活动增强=更高的心率、血压、更快的浅呼吸。但人们往往背道而驰,得出一些经不起推敲、以一对多的推论,如心率增加=兴奋/沮丧/不安/高兴。

3、为了定位相应测量法的选择,我们将焦点放在玩家体验的特定方面。这意味着在我们在能掌握的方围内,策略性地利用生理心理学测量法。如果我们希望测量留存率,即除了反复失败的体验外,是什么原因导致玩家离开游戏,我们可以观察对动机的生理学测量结果。如果我们想要捕捉训练或熟练过程中玩家的心理负荷,我们可以着眼于认知能力的测量。

我基本上赞成利用假设导向型方法来捕捉玩家的体验。我认为,在捕捉“体验”或“流动状态”或类似的难以下定义的现象时,生理心理学特别受易受到误解的干扰。

4、在进行测试前,我们能够仔细监控玩家的体验和技术级别。生理心理学反应对新奇的事物和习惯性非常敏感。根据游戏环境和他们对那种环境的经验水平,玩家的心理机能各不相同。为了补充和分析、根据经验水平来测试玩家是有道理的。

5、如果是在比较原型,我们能够认真控制游戏环境。为了获取明确的心理生理学反应,要利用游戏引擎,有条有理地操纵环境。不要同时改变过多变量,否则如果我们在游戏世界中拥有大量的互动变量,就会造成数据解析上的困难。(本文为游戏邦/gamerboom.com编译,如需转载请联系:游戏邦

5 items a game developer should consider before they use biometrics for player experience studies

by Kiel Gilleade

I’m co-editor at PhysiologicalComputing.net where we occasionally blog about using physiological signals (e.g. heartbeat rate) in game design and user evaluation. My particular research expertise is in the development of physiological interactive game mechanics among other things.

Recently my colleague and co-editor Stephen Fairclough, a psychophysiologist at Liverpool John Moores University, sparked a discussion on the issues involved in using psychophysiology to evaluate the player experience. A summary of this discussion can be found on Lennart Nacke’s Gamasutra blog from a few week’s back.

Below is a condensed version of a follow-up article to this discussion by Stephen that recently appeared on PhysiologicalComputing.net which I’m re-posting on Gamasutra. It presents a thought exercise on how, given the issues involved in psychophysiology, one would sell biometric based player evaluations to game developers.

Recent posts on PhysiologicalComputing.net have concerned the utility of psychophysiology (or biometrics) in the evaluation of player experience.  Based on those posts and the comments that followed, I decided to do a thought experiment.

Imagine that I work for a big software house who want to sell as many games as possible and ensure that their product (which costs on average $3-5 million to develop per platform) is as good as it possibly can be – and one of the suits from upstairs calls and asks me “how should we be using biometrics as part of our user experience evaluation?  The equipment is expensive, it’s labour-intensive to analyse and nobody seems to understand what the data means.” (This sentiment is not exaggerated, I once presented a set of fairly ambiguous psychophysiological data to a fellow researcher who nodded purposefully and said “So the physiology stuff is voodoo.”).

Here’s a list of 5 things I would push for by way of a response to this question.

# 1

Make the point that psychophysiological data provides continuous monitoring of behaviour that delivers quantitative data without the need to interrupt the player. This form of measurement is superior to subjective methods either in real-time (no need to break from experience) or on a retrospective basis (no memory bias).

It is more sensitive than simply monitoring gaming performance (because good performance can be achieved at low or high levels of psychophysiological activity) and besides the risk of intrusiveness due to actually wearing sensors, the approach makes no other demands on the player.

# 2

Educate the company about what psychophysiological measures do. It is not a literal quantification of an emotion or a thought or a feeling.  It is not an “inside-the-head-oscope”.  It is the electrical activity of human nervous system recorded from the heart, lungs, skin, eyes, muscles and the brain.

To begin with, how do we expect our best games to make the player feel? Excited? Engrossed? Exhilarated? Challenged?  Let’s think about those psychological states in experiential terms – now translate them into the electrical language of the human nervous system with some physiological know-how.  For example, excitement = increased sympathetic activation = higher heart rate, blood pressure, faster/shallow breathing.  Too often people work in the opposite direction and wind up with one-to-many inferences that don’t stand up to scrutiny, e.g. increased heart rate = excitement/frustration/anxiety/happiness.

#3

Make an argument that we focus on some particular aspect of the player experience in order to focus our selection of measures accordingly.  This means using the psychophysiological measures at our disposal in a strategic way – if we are interested in emotional experience, we focus on level of activation/positive affect experienced during game play.  If we want to measure persistence, i.e. what stops a player from tossing the handset aside due to repeated experience of failure, we may look at physiological measures of motivation.  If we want to capture the level of mental workload during the training/familiarisation phase, we would look at measures of cognition.

I would basically argue for a hypothesis-led approach to capturing player experience.  I feel that psychophysiology is particularly vulnerable to misinterpretation when tasked with capturing ‘experience’ or ‘flow states’ or similar phenomena that are poorly defined.

#4

Carefully monitor and control player experience and skill level prior to testing. Psychophysiological reactivity is very sensitive to novelty and habituation. The physiology of gamers will probably vary according to the gaming situation and their level of experience with that situation. It makes sense to test gamers according to experience/exposure for purposes of recruitment and data analysis.

#5

Carefully control the gaming environment if we are comparing prototypes.  Use the gaming engine to systematically manipulate the environment in order to obtain an unambiguous psychophysiological response.  Do not change too many variables at the same time – this tends to make data interpretation difficult if we have lots of interacting variables in the game world.(source:gamasutra


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