6-中英文翻译
When to Use Which User Experience Research Methods
By Christian Rohrer
Summary:
Modern day user experience research methods can now answer a wide range of questions. Knowing when to use each method can be understood by mapping them in 3 key dimensions and across typical product development phases.
The field of user experience, is blessed (or cursed) with a very wide range of research methods, ranging from tried-and-true methods such as lab-based usability studies to those that have been more recently developed, such as desirability studies (to measure aesthetic appeal).
You can't use the full set of methods on every project, but most design teams benefit from combining insights from multiple research methods. The key question is what to do when. To better understand when to use which method, it is helpful to realize that they differ along 3 dimensions:
?Attitudinal vs. Behavioral
?Qualitative vs. Quantitative
?Context of Website or Product Use
The following chart illustrates where several popular methods appear along these dimensions:
Each dimension provides a way to distinguish between studies in terms of the questions they answer and the kinds of purposes they are most suited for.
The Attitudinal vs. Behavioral Dimension
This distinction can be summed up by contrasting "what people say" with "what people do" (very often quite different). The purpose of attitudinal research is usually to understand, measure, or inform change of people's stated beliefs, which is why attitudinal research is used heavily in marketing departments.
While most usability studies should rely more on behavior, methods that use self-reported information can still be quite useful. For example, card sorting provides you with insights about users' mental model of an information space, which can help you determine the best information architecture for your site. Surveys measure attitudes or collect self-reported data that can help track or discover important issues with your site. Focus groups tend to be less useful for usability purposes, for a variety of reasons.
On the other end of this dimension, methods that focus mostly on behavior usually seek to understand "what people do" with minimal interference from the method itself. A/B testing only changes the site's design, but attempts to hold all else constant, in order to see the effect of site design on behavior, while eyetracking seeks to understand how users visually interact with interface designs.
Between these two extremes lie the two most popular methods we use: usability studies and field studies. They utilize a mixture of self-reported and behavioral data, and can move toward either end of this dimension, though leaning toward the behavioral side is generally recommended.
The Qualitative vs. Quantitative Dimension
The basic distinction here is that, in qualitative studies, the data is usually being gathered directly, whereas in quantitative studies, the data is gathered indirectly, through an instrument, such as a survey or a web server log. In field studies and usability studies, for example, the researcher directly observes how people use technology (or not) to meet their needs. This gives them the ability to ask questions, probe on behavior or possibly even adjust the study protocol to better meet its objectives. Analysis of the data is usually not mathematical.
By contrast, insights in quantitative methods are typically derived from mathematical analysis, since the instrument of data collection (e.g., survey tool or web-server log) captures such large amounts of data that are coded numerically.
Due to the nature of their differences, qualitative methods are much better suited for answering question about why or how to fix a problem, whereas quantitative methods do a much better job answering how many and how much type of questions. The following chart illustrates how the first two dimensions affect the types of questions that can be asked:
The Context of Product Use Dimension
The final distinction has to do with how and whether participants in the study are using the website or product in question. This can be described by:
?Natural or near-natural use of the product
?Scripted use of the product
?Not using the product during the study
? A hybrid of the above
When studying natural use of the product, the goal is to minimize interference from the study in order to understand behavior or attitudes as close to reality as possible. Many ethnographic field studies attempt to do this, though there are always some observation biases. Intercept surveys and data mining/analytic techniques are quantitative examples of this.
A scripted study of product usage is done in order to focus the insights in very specific ways, such as on a redesigned flow. The degree of scripting can vary quite a bit, depending on the study goals. For example, a benchmarking study is usually very tightly scripted so that it can produce reliable usability metrics.
Studies where the product is not used are conducted to examine issues that are broader than usage and usability, such as a study of the brand or larger cultural behaviors.
Hybrid methods use a creative form of product usage to meet their goals. For example, participatory design allows users to interact with and rearrange design elements and discuss why they made certain choices.
Most of the methods in the chart can move along one or more dimensions, and some do so even in the same study, usually to satisfy multiple goals. For example, field studies can focus on what people say (ethnographic interviews) or what they do (extended observation); desirability studies and cardsorting have both qualitative and quantitative versions; and eyetracking can be scripted or unscripted.
Phases of Product Development (the time dimension) Another important distinction to consider when making a choice among research methodologies is the phase of product development and its associated objectives.
1.STRATEGIZE: In the beginning phase of the product development, you are
typically considering new ideas and opportunities for the future. Research methods in this phase can vary greatly.
2.OPTIMIZE: Eventually, you will reach a "go/no-go" decision point, when
you transition into a period when you are continually improving the design direction you have chosen. Research in this phase is mainly formative and helps you reduce the risk of execution.
3.ASSESS: At some point, the website or product will be available for use by
enough users where you can begin measuring how well you are doing.
The table below summarizes these goals and lists typical research approaches and methods associated with each:
Art or Science?
While many user experience research methods have their roots in scientific practice, their aims are not purely scientific and still need to be adjusted to meet stakeholder needs. This is why the characterizations of the methods here are meant as general guidelines, rather than rigid classifications.
In the end, the success of your work will be determined by how much of an impact it has on improving the user experience of the website or product in question. These classifications are meant to help you make the best choice at the right time.
用户体验研究方法的选择：什么时候用哪个
摘要：
用户体验研究当前已经可以解答相当广泛的问题。通过在一个三维坐标系以及典型的产品开发阶段中列出各种可用的研究方法，可以了解到什么时候应当使用哪种方法。
用户研究领域有着相当广泛的研究方法，这是件好事（没准也是件坏事）。从那些已经广泛验证的方法，例如可用性实验室研究，到那些近些时候才发展出来的方法，比如合意性（desirability）研究（用来测量审美需求）
你不能在所有的项目中应用所有的方法，但是大部分设计团队受益于多种研究方法结合的洞察力。关键问题是什么时候应该用什么。为了更好的理解什么时候使用什么研究方法，把各种研究方法根据以下三个维度区分会很有帮助：
?态度与行为
?定性与定量
网站或是产品使用的背景
下面的图表描述了几种常见的方法在坐标系中的位置
每个维度都是一种区别不同研究的方法，他们回答不同的问题，也适合不同种类的目的。
态度—行为维度
这个方面的区别可以被归纳为人们说什么和人们做什么（经常是相当不同的）。态度研究的目的经常是理解，测量或者是获知人们特定的观念，这就是为什么态度研究在市场部门被经常使用。
虽然大部分可用性研究应该更多地依靠行为研究，使用自我报告方法获得的信息依然是很有用的。例如，卡片分类研究能让你深入了解用户在某种信息空间里的心理模型，这可以帮助你决策什么才是最适合你网站的信息架构。调查方法测量态度，或是收集自我报告数据，能够帮助跟踪或是发现你网站中重要的问题。因为种种原因，焦点小组在可用性研究中已经逐渐没什么用处了。
在坐标轴的另一端，那些关注行为的研究方法经常用来试图了解“人们做什么”，并尽量降低研究方法本身对研究结果的干扰。AB测试仅是改版网站的设计，但是努力保持其它因素不变，以便于观察网站设计对用户行为的影响，眼动研究用来了解用户与网站界面设计的视觉交互。
在两个极端之间的是两种我们最常用的研究方法：可用性实验室研究和现场实地研究。他们结合了自我报告和行为数据，并且可以偏向于坐标轴的任一端。但是一般推荐倾向于行为研究的那一段。
定性－定量维度
这两者基本的差别在于：在定性研究中，数据经常被直接收集，相反的，在定量研究中数据是被间接收集的，通过一种工具，例如一个调查问卷，或是Web 服务器日志。在现场研究和可用性实验室研究中，例如，研究者直接观察用户如何使用技术（或者是没有使用）来满足他们的需求。这可以让他们有能力去问问题，探查行为，或者可能调整研究方案来更好地满足目标。数据的分析也经常不是十分精确的。
与之相比，定量研究中的洞察力典型地来源于精确的数学分析，因为数据收集的手段（例如调查工具或是Web服务器日志）捕获海量的数字编码的数据。
由于它们本质上的区别，定性研究方法更适合回答关于为什么或是如何解决一个问题。相反，定量研究可以在回答有多少和有多少种问题上做的更好。下面的图表描绘了前面两个维度是如何影响研究方法可以回答问题的种类的。
产品使用背景维度
要做的最后一个区别是在研究中，是否使用产品，或是如何使用产品。可以被描述如下。
?自然地或是接近自然地使用产品
?脚本化使用产品（按照预先安排的方式使用）
?在研究中不使用产品
?以上各项的混合
当选择在研究中自然使用产品时，目的是尽力降低研究本身对结果的影响，以便于尽可能了解真实的行为或态度。很多人种学实地研究致力于此，但是依旧总是出现一些观测偏差。拦截访问调查（Intercept Survey）和数据挖掘/分析技术是定量研究中这类使用产品方式的例子。
产品使用的脚本化研究(Scripted Study )是为了集中观察非常细节的情况，例如在重新设计流程的时候。脚本化的程度根据不同的研究目标可以相当多样化。例如，一个基准研究（benchmarking study）通常相当严格地脚本化，于是可以产出相当可靠的可用性标准。
那些不要求使用产品的研究用来检查比使用和可用性更广泛的问题，例如品牌研究和跨文化的行为。
混合的研究方法使用一种创新的形式使用产品来达成目标，例如，参与式设计允许用户与设计元素交互，并重新排列那些设计元素，并且讨论为什么他们要做出那样的选择。
图表中的大部分的研究方法能够在一条或者多条坐标轴上移动，并且在一些研究中两个方向是很平均的，经常是为了同时满足多种目标。例如，现场研究能够关注人们说什么（人种学面谈ethnographic interviews）也可以关注人们做什么（拓展观察extended observation）；合意性（desirability）研究和卡片分类都有定性和定量两种版本；并且眼动研究也可以是脚本化的或者是非脚本化的。
产品开发阶段（时间维度）
另外一个在选择研究方法时需要考虑的重要的区别是产品研发阶段，和其相关的目标。
?计划阶段：在产品开发最开始的阶段，一般的情况下，你需要考虑新的主意和未来的机会。这个阶段的研究方法相当多样化。
?优化阶段：终于，你将会到达一个“干还是不干”的十字路口，你过渡到一个时期，在这个时期，你要在你选择的方向上不断的提升自己的设计。
在这个阶段，主要的研究方法是结构化的，并且帮助你降低执行的风险。
?评估阶段：在某个时间点，网站或是产品被足够多的用户使用，你可以开始评估你做的怎么样了。
下面的表格汇总了这些目标，并且列出了典型的研究途径和方法，和它们之间的联系。
艺术还是科学？
虽然很多用户体验研究方法来源于科学研究实践，但它们的目标并不是纯科学，并且需要调整来符合投资人的需求。这就是为什么这些方法的描述都是很简略的(只是一般的指导原则)，而不是严格的分类.
最后，你们的工作是否成功决定于提升网站或是产品的用户体验能带来多大的效果。这个分类的意义在于能够帮助你在恰当的时间做出最好的选择。