How do you research how the unemployed find jobs? Surely they use their social networks. How do you research how to financial investors get advice from their community? How do you research consumer coffee drinking culture? How do you research how people shop for clothes? Shopping is one of the most social activities, even if it’s done alone. In fact the most social shoppers are elderly women: they shop with their deceased husbands in mind (“What would he have liked?”) and with their children in mind (“If I buy the cheaper shirt, I’ll have more to pass on to my daughter.”) But shopping for a dress might take several days to weeks before the purchase is actually made. What goes on in that time?

Okay, those are what I was referring to as “social design problems”. But what I care about is how we design for those things? I know very little about financial planners make decisions. I know my coffee drinking habits — but do I know yours? What about your shopping habits? Research is necessary to uncover all the nuances in our social behaviors, and is especially important to do right when working on such social design problems.

But how? Our user research methods have been fine tuned over the past decade so that we know exactly how to recruit the right sample, how to ask the right questions, and how many users to talk to to unveil most usability issues in an interface. I just don’t believe that we have the right methods yet for social interaction design issues.

How do we study a community that spans the online and offline world? How do we capture emotions, feelings, expectations, and privacy issues without biased research prompts. How do we understand social context?

I am not convinced that 5 users is enough for social interaction design issues — or for studying social interfaces. There are too many variations in people’s social behavior to capture everything in small samples. There are too many social contexts in which even the same user would respond differently. How many users is necessary? What is the best way to complement data metrics (quants) with qualitative user behavior?

I have been talking to several people about this recently and would love to hear from you. What social research methods do you use? How do you use them and what benefits do they provide? If you’re willing to share your methods, I am interested in collaborating with you to create a set of best practices here!

They were building upon (among other things) my work on asking and answering behavior on social networks (“Do your friends make you smarter“) and wanted to know more details about things like: why do people post questions, answer questions, and what motivates people to go the social search route over traditional search.

I want to talk about their conclusion here first: where they discuss the tradeoffs between using social networks and search engines. This was the most interesting part of the paper and is the part that has the most practical take-aways for the UX community.

Basically, for questions requiring trustful and personalized responses like for recommendations or opinions, social networks were strongly preferred over search engines. People occasionally perceived a delay in response time (but sometimes did not!) — and either way, this delay was not a downer since it saved people the effort of making multiple attempts on a search engine before getting the right answer back (if they ever did). Also, subjective questions got faster responses on social networks than objective questions!

Additionally, they talk about how being on social networks is fun for people. It’s too bad that they under-emphasize this point because it’s really important from a social interaction design perspective! People engage on social networks because it’s fun! There’s an emotional tie to the community that keeps bringing them back. When it comes time to ask a question, people turn to their friends for help because it keeps them connected with others, helps them to share information about themselves, and keeps them engaged in their community. Fun is an important element of design — and until Google, Facebook, Yahoo, Microsoft, or other search providers make the information seeking part fun, they will lose. It’s not enough to simply pipe in real-time Twitter results and expect that to be fun or more personalized!

That (above) is the juiciest part of the paper, but I do summarize the whole paper below for other nuggets of inspiration.

To start, the authors note that Q-A on social networks is unique (like unique from Q&A sites like Yahoo Answers) because:

• questions are posted with true identities (rarely anonymously)
• people’s audience is smaller (being only people’s direct contacts, or possibly friends-of-friends)
• status messages are short: so questions are succinct

Then they collected surveys from 624 Microsoft employees (1/4 were female) about their Q-A behavior on Facebook and Twitter mostly. The survey asked about:

Asking questions:

• whether they ever used their status messages to ask questions
• if yes, to share a recent example of a question they asked
• what kind of responses they received
• how often they logged onto social networking sites

And answering questions:

• whether they responded to someone else’s question (from a status update)
• if yes, to share a recent example of a question they answered

50% of people who replied to the survey did indeed use their status messages to ask questions! Sometimes they were silly questions (“Why are men so stupid?”) and sometimes they were serious (“Point and shoot camera just died — need to replace it asap. What should I buy? Think under $200″).

On asking questions

Questions took many shapes and forms. Some were targeted to “Anyone” in the social network; others were general statements put out to the network to interpret. Most questions were asking about recommendations (29%) or opinions (22%). Some were about facts (17%) and some were rhetorical (14%).

Questions also related to everything from technology (29%) to entertainment (17%), places (8%), current events (5%), and ethics and philosophy (2%). People said they’d generally avoid asking their network about topics like health, pornography, religion, and financial issues because those are too personal.

Another finding was that Twitter users were more likely to ask questions about technology, while Facebook users more likely to ask about home and family issues. This isn’t too surprising, but does show that the makeup of people’s networks affects what kinds of questions people will ask.

One looming question in this research is: why do people choose to ask their friends over searching on Google? In this study, people reported having more trust in their friends’ responses or that they thought traditional search wouldn’t work for them with this particular question. Sometimes it was obvious that their friends would know their history, family situation, and other preferences better than a search engine.

People also generally knew the makeup of their networks (meaning they could get targeted responses) and people wanted to advertise their current interests by way of asking questions of their friends.

What about answer speed or answer quality? There were mixed results, but often questions asked on social networks were not urgent so any delay was considered acceptable. It was also easier than sorting through tons of results on search engines and quite often more fun to engage with friends.

On answering questions

Almost everyone has answered a question on one occasion or another. And of the questions offered up in this survey — nearly every one received an answer! That’s kind of amazing considering Q-A sites in general have a much lower response rate, but it’s also likely due to the intimate make up of people’s social networks. Not to be an under-appreciated finding in this paper, however!

About one-quarter of questions got an answer in 30 minutes or less, and 90% were answered within one day. (I’d LOVE to see how Aardvark’s data compares here. I have several questions out to Aardvark that have never been answered; but of the ones that do get answered, it’s typically faster than 30 minutes.)

Yet people don’t seemed to be bothered by the 1-day response lag. Perhaps this is because replies from trustworthy friends are more valuable than junk search engine or Yahoo Answers responses?

Why did people respond to questions by others? Most often they were just trying to be helpful (37%) or had expertise in the area (32%). Those seem like good reasons to me, and ones that are often overlooked when thinking about how valuable personal social networks can be to people. At other times, people replied because they had a good relationship with the asker, were connected socially, or had some notion of social currency (that answering now may result in a favor later).

When people didn’t respond to questions by others, it was mostly because they didn’t know the answer! That’s pretty neat. But some said they’d prefer a personal request and ignored questions that were asked to the network as a whole. In fact, my research on Q-A in social networks revealed the very same thing — that people gave great responses when asked privately or one-on-one, even when they weren’t very knowledgeable about the topic.

Another interesting, but not very surprising finding, is that people who were more frequent social networks users received quicker responses! Why duh! People who are engaged with their communities have developed rapports and back-and-forths and social capital with folks — what goes around comes around. But it is cool to see this intuition confirmed in real data!

Unfortunately, this paper is weak on design recommendations. My colleagues and I have already suggested the very same ideas (e.g., surface your friends status messages on the results page — what I call “friend-filtered search” — or have a search engine post a question as a status message on your behalf.) Even as I say this, there are serious social interaction design issues with this approach. Expectations about search engine behavior, expectations about social network intrusion, privacy (obviously), interactions with online agents, etc. all come into play. I very much hope that these issues are being considered by the big search engine companies, but somehow I’m afraid they’re not.

“Het Googlen van de toekomst doe je met je vrienden”

translates to this:

“The Googling of the future that you do with your friends”.

If anyone out there speaks Dutch and wants to provide a translation for me, I’m quite curious what this article says! (where’s Xiha Life when I need it? maybe now is when I get an account!) I remember doing the interview with the journalist, Kahliya Ronde, but alas, I cannot understand the text. I’m pretty sure several of the quotes are about my research on social search — specifically these two papers on the cognitive benefits of talking to friends for help.

This is a pretty high-level summary (e.g., not that detailed) of how I create and run a new survey on Mechanical Turk. Since people have lots of different ways of using Mechanical Turk, this how-to may or may not be for you. I’ve also noticed that nearly every survey or questionnaire I put on Mechanical Turk requires different hacks

Creating A Mechanical Turk Task

Step 1: Select. You’ll start in the design tab, and either copy a template that exists (there are some default templates in there), or edit one of your saved drafts.

Step 2: Properties. Then you set the properties of your HIT. There are some more details like pay rate and automatic approval time at the bottom of this page.

Step 3: Layout. Next, you’re still under the global tab for Designing the hit, but you switch to a sub-tab for Designing the Layout. The other thing to note here is that you can adjust the “frame height” of your hit (which will determine how long the page’s scroll bar is and what users see “above the fold”).

There are a few things to note for when you do dive into the HTML editor:

1. Mechanical Turk is a full-on HTML enabled. Anything you can do with HTML/CSS, you can do to style your survey here.

(See the sample HTML code below for: an embedded survey and an HTML/CSS-created survey)

2. This includes embedding objects (like images or iframes if you are linking to a Google Form or Survey Monkey survey that’s hosted elsewhere).
3. You cannot embed Javascript directly, but you can use Javascript with your HIT. I did this by creating a Javascript snippet and saving it on an external site, but then linking to the external site from Mechanical Turk. There may be other ways to accomplish this as well that I don’t know of.
4. Last I checked, you have to have some variable and associated variable list (the “Input File”) linked to your HIT. This is typically used if you want to test, say, 100 images, but where each user only tests 10. So you have to cycle through the first 10 for the first user, the second ten for the second user, etc. Even if your HIT doesn’t use this method AT ALL, you have to include some fake variable and link a fake variable list (see Step 6).

Here’s my dummy variable line which I always leave at the end of the HTML script:

<p id="${dummy}">&nbsp;</p>


Step 4: Preview. Finally, you’ll preview what your HIT will look like to Turkers. If things look funny, go back to Design Layout to tweak them.

Step 5: Begin Publishing. When you’re done there, you’re taken to the Publish page. Your latest HIT will be highlighted in yellow.

Step 6: Choose Input File. After you Select your HIT, you have to list your variables file (“Input File”). Recall that I mentioned this before? It’s wacky when you’re not using variables (like placeholder images), and this file has to exactly match what your put in the HTML of your HIT. If you’re just doing simple surveys, feel free to use my dummy variable line in your HTML and attach this file (exactly as is, since the Windows formatting was also required) — you’ll be fine!

Step 7: Final Preview. You’ll have one last chance to preview your HIT:

Step 8: Pay and Confirm. And then confirm all the settings, including your final estimated cost. It’ll tell you if you don’t have enough money, and if you click there to add more funds, it’ll pop you back into your workflow here when you’re done.

Here’s some sample HTML code which I used for two surveys recently:

Embedding a survey
<p>Please complete the embedded survey (within the black box). Be sure to his SUBMIT at the bottom of that form, and then SUBMIT for the Mechanical Turk form!</p>

<p>Enter that <u>CONFIRMATION CODE</u> here to receive payment! Thank you!</p>
<p><textarea rows="1" cols="30" name="Name"></textarea></p>
<h4>If you have any comments or feedback, please leave them below!</h4>
<p><textarea rows="3" cols="80" name="comment"></textarea></p>
<p id="${dummy}">&nbsp;</p>
</div>

Styling the survey with HTML/CSS within Mechanical Turk
See the code snippet on Pastie.

If you want additional samples (like with using Javascript), please email me separately.

All my comics can be found on my scribd account.

How Usability Studies are Like a French Meal

What is social interaction design?

Social interaction design (SxD) is the practice of designing for person-to-person interactions mediated by a computer interface, going beyond pure usability and human-computer interaction. Even fairly solitary experiences like editing a Wikipedia page occur in a social context in which other users’ past interactions influence what new editors contribute.

“It’s the the interactions among users that informs design” (Adrian Chan).

What’s a good example of an SxD problem?

Vark.com is a question-answering service that routes users’ questions to people in their extended networks who may have relevant knowledge of the topic. The original service operates through IM, Twitter, and email; more recently an iPhone app has been developed.

Let’s consider the difference between the mobile and desktop experiences of Vark.com. Both asking and answering activities work rather well in desktop email and IM. In contrast, responding on-the-go is awkward—more often than not, we’re distracted, hurried, or unable to type a coherent answer without bumping into a fire hydrant.

There’s also an assumption that the answer resides solely in our heads, when in reality, providing an answer often requires sharing links or performing a quick search—that is, we may not have the answer immediately on hand, but we know where to look.

Furthermore, successful answers often manifest as conversations on the desktop (example above), in which messages are exchanged in a back and forth manner so that the questioner can clarify her question and the answerer can refine her response. This type of sustained interaction is much harder to establish with on-the-go users.

Finally, iPhone prompts (below) often lack enough information about the nature of the question or your relationship to the questioner. One reason for Vark’s success is that it seeks out answers from people within an extended, personal network, naturally building trust and accountability into the system. But without knowing how you know the questioner, the iPhone app experience feels instead intrusive and disruptive, and lacks any strong social motivator to respond.

Why is remote research useful for SxD?

Traditionally, user-centered designers conducted field studies or shadowed someone to learn more about their practices. The digital space complicates matters—not only is it difficult to shadow someone, but people’s actions are so fluid and varied that it’s hard to isolate specific behaviors in order to study them.

Remote research has emerged as a great way to do needs-finding for SxD, for three reasons:

First, it’s hard to recreate interactions between two or more people in a lab setting. Last year when I was studying user interactions during social search tasks, I realized that I needed to talk to multiple people: both the user who posed the question as well as the people who provided replies. I started by observing the questioning process: how the question was phrased, which communities or individuals were questioned, the historical relationships between the parties. Then I explored the answering process: answerers’ perception of the request, why they chose to reply, if they had a history of interacting like this.

What’s interesting is that answers provided over social networking sites (like Twitter and Facebook) were mostly jokes or “nudges” to attract the user’s attention (“Hey, remember me?”). But answerers in private channels (email, IM, phone) were more serious and thoughtful because people were contacted directly and had longstanding relationships with the user (“She asked me personally, and she’s helped me in the past”).

Second, social interactions unfold over time, and their repercussions aren’t always apparent in a hour-long lab study. I recall one user in my social search study who asked a question on ping.fm. He received a prompt reply which “seemed right”, so he reported it as his “final answer”. I followed up two days later to see if he had received any other replies. In fact, the conversation thread on ping.fm had progressed, and the community had collectively concluded that the earlier reply was incorrect. This observation was only made possible by the passage of time.

Third, social interactions are best understood within the context where they occured. Not just physical location, but also past history (between the people interacting) and reasons for having the interaction. For example, my sister tweets about her new startup, but I’m not familiar with her a field and don’t have a professional relationship with her, so I seldom reply to her tweets. However, when she emails, calls, or writes on my Facebook wall, I reply instantly—even on an unfamiliar topic. If you were only studying my Twitter use, you might wrongly conclude that I’m an ingrateful sister, but this interpretation would be taken out of the full context of my relationship with her.

Thus, whether you’re designing for healthcare, fitness, games, dating, or online privacy, it’s critical to gain insight into where, when, and why people to act the way they do. Community engagement through social media will differ substantially depending on people’s personalities, reputation, location, local culture and rules, nature of their relationships, and history of the community. Remote research methods—like experience sampling, remote observations, and critical incident surveys—are great tools for understanding the many facets of social behavior, and suggest productive avenues for pursuing SxD.

Additional resources:
Social interaction design salon (group blog)
Digital ethnography for social interaction design (slide show)

[Guest author: Brynn Evans is a digital anthropologist, design researcher, and author who studies social interaction design and social search. She extends a thousand thanks and a bear hug to Tony Tulathimutte for help in editing this post!]

Is design thinking really that hard? There is obviously a growing acceptance of the notion behind design thinking as the previous essays and comments pointed out. But it remains that there is no formula for design thinking, and because of that, design thinking may alienate business leaders, managers, or even UX practitioners.

Consider the following quotes:

• “Design thinking is not about solving design problems, it’s about solving problems with design.” –Paula Thornton
• “It’s not just thinking. It’s a structured approach to organizing design.” –Gayle Curtis
• “Good design is at the intersection of business and human goals. It’s not just about users, and it’s not just about business—it’s about balancing both.” –Jess McMullin

A natural reaction to this is: Great! Sign me up! P.S. I have no idea where to begin.

Even as the essays on this panel have hit the nail on the head in how design thinking can be used for innovation in businesses, it still feels like an elusive process that faces many barriers in actual organizations. I’ve been noticing this with one of my clients. After introducing some new user-centered, user-driven design, marketing and sales invariably rework it to echo their time-tested sales pitch, causing it to bloat with extraneous options, text, and check boxes. In the end, we’ve made only an incremental improvement in our design.

Yet, I’ve also noticed a theme emerge across the many articles on design thinking recently. Bruce MacGregor talks about the importance of gaining insights early. Venessa Miemis mentions Tim Brown’s book which outlines an “inspiration phase” (disclosure: I have not read the book myself). And Peter Merholz continually reminds us that users are the central to the design process.

At the same time, I saw this surprising graphic last week: that “science” only makes up a sliver of the design thinking process. Really, I thought? What about the aforementioned importance of understanding users—isn’t that like a “science”? Maybe this is partly explains the uncertainty and confusion around design thinking.

[via http://www.kaplusa.com/blog/2009/12/the-role-of-intuition-in-design/ ]

I prefer the way that David Gillis describes the tradeoff between science and art as more of a continuum. Even still, where does design thinking fit in? A notch closer to the art, or to the science?

[via http://www.teehanlax.com/blog/2010/01/20/the-art-science-of-evidence-based-design/ ]

Taken together, I wanted to write a piece on the “science” in the design thinking process, to reiterate the importance of user-centered design and try to illustrate how this is not just a black box. Hopefully there’s some stuff in here that will help companies grasp exactly what we mean when we talk about “innovation” and “design thinking.”

One way to think of the innovation process is as a funneling of ideas across various stages—stages that span needs-finding, synthesis, ideation, prototyping, and iterating. Of course, this is a cyclical and dynamic process so it’s somewhat misleading to represent it as a sequential progression.

[via http://www.slideshare.net/mikeyk/intro-to-design-thinking ]

Gillis represents this process slightly differently, but still captures the same basic design phases:

[via http://www.teehanlax.com/blog/2010/01/20/the-art-science-of-evidence-based-design/ ]

Now, I prefer to think in terms of craft and creativity rather than science and art. By craft, I’m referring to the well-defined and established process of user-centered design. Creativity is the art, shiny design-y, intuitive part—the window dressing if you will. And to an extent, all these phases can be said to involve both craft and creativity.

It’s the craft part of design thinking that I want to elaborate on in the rest of this post, since the craft can be taught to a greater extent than the intuitive, experiential, creative part. Afterall, there are books and workshops out there teaching contextual and user-centered design. One great resource is IDEO’s Human Centered Design Toolkit.

Investigate / Observe:

Remember that the point of user-centered design is to gain clues about unmet user needs—needs that users themselves may be unable to articulate. The only way to gain this insight is to embed yourself in the community and practice of the people you’re designing for.

To do this, you must first scope your project and define various goals and hypotheses (what IDEO calls a brief).

Next, you talk to end users directly to learn about how they think, act, and engage, either with your product or in the space where you want to design a new product. This involves conducting contextual interviews, field studies, or otherwise observing users in their natural environments (not in the lab). If you’re designing an e-commerce checkout application, watch a user’s entire purchasing process from start to finish. If you’re redesigning your own site’s checkout flow, watch your users’ purchasing process. This is not a usability study. You’re not looking for feedback on specific features of your checkout process; you’re looking holistically at what your users’ goals are, what they’re doing to address those goals, where breakdowns occur, where confusion arises because expectations were violated, and importantly, how they feel (emotions! emotions! emotions!)

Synthesize:

There are number of established ways for documenting and synthesizing your insights. For example, interpretation sessions should be run as soon as possible after gathering user data, and they should always be done with other people—both people who were at your observation sessions as well as people who weren’t. Although it sounds counterintuitive, people who weren’t “in the field” with you often see the problem space from a different perspective, which causes important questions to be raised that might otherwise have been overlooked.

Some of the methods to use in interpretation sessions include building affinity diagrams, modeling workflow and cultural influences, and generating personas. Not all of these activities will be performed in the first interpretation session, but they are all part of the craft of synthesis in the design thinking process.

What you should be left with after this is a set of design principles in which you can begin to think about how to innovate on your product.

Ideate / Brainstorm:

Ideation and brainstorming is as critical to design thinking as is the collection of user data. After you’ve gathered your design principles, the goal is to generate ideas about how to create a product, service, or experience based on those principles. Gayle Curtis has an excellent talk on how to run such brainstorming sessions. Again, it’s a craft to structure the session— although what it generates is intended to be very creative, exploratory, and experiential. The more ideas the better.

Another excellent way to ideate is through what Dennis Schleicher calls a Issue Board. Issue Boards are, in fact, quite structured while still being visually evocative. They are generally built by one or two individuals, but subsequently used in larger brainstorming sessions to generate ideas.

Prototype / Evaluate / Validate:

I’m specifically lumping the prototyping and evaluative phases of design thinking together, to emphasize the point that prototypes are intended to solicit feedback. Yes, prototyping is an activity that can involve lots of creativity and visual aesthetics. But prototypes are not simply a beautifully-packaged, first generation version of your product—prototypes come in all shapes and sizes (from conceptual mockups to paper prototypes to high-fidelity interactive products).

In order to use prototypes to generate feedback, you must be open to testing your ideas early and often. Explore some conceptual mockups, and get feedback from a few users; then move onto paper prototypes and get quick feedback again; etc. This can also involve something like participatory design, whereby users are directly involved in the development of your prototype. There’s a good example of this in the Design Thinking for Social Innovation article: IDEO worked with children directly to develop a comprehensive vision care system for VisionSpring (the local provider).

…

As most will agree, design thinking is no panacea, even when combined with business thinking. Perhaps organizations become fearful of its outcome; or the numerous stakeholders and deep-seated traditions make it difficult to use design thinking in practice. One way to deal with this problem is to create an emotional connection with business leaders and UX professionals, in much the way we want to create an emotional connection with our users.

To do this, we must continue sharing examples of design thinking across a range of problem areas (which I have not succeeded in doing, but which unstructure has placed a call for). Sooner or later there will be a compelling example that resonates with every industry! We must also providing the necessary resources for others to embark on the design thinking process themselves. The goal for this essay was to do just that: illustrate how to put the craft in design thinking.

I consider this to be a work-in-progress of methods for studying cultural and social behaviors in online, mediated spaces. Please share the methods that you have used or found to be useful so that we can continue the conversation around best practices.

If you’ve written a rebuttal before, you may be familiar with some of these techniques. I used these strategies for writing a clear rebuttal and dealing with the review process:

Filed under writing a clear rebuttal:

1. Organize your rebuttal by issues related to the methodology, analysis, and design implications separately. I gave them section headers.
2. Itemize your points and give your points titles.
3. Then address each one next to its title. Stick to the facts and don’t apologize. You will make the following changes in the revision.
4. Mention which reviewer(s) brought up each issue. This will make them feel good, and will show your attention to details.
5. Address all points, even little minor ones. A typo in my paper was mentioned by several reviewers — I addressed it in the rebuttal.
6. Avoid telling reviewers how stupid and pig-headed their comments were. (This is where you cry and sleep on it.) Instead tell them how much you love them. You might even tell them that twice.

Filed under dealing with the rebuttal process:

1. Complain on Twitter. I found lots of comrades when I did this.
2. Write a blog post. Last week several good ones were written (and got exposure, comments, etc.) by James Landay and Gene Golovchinsky.
3. Draw a comic! I am actually in the process of drawing my second (ever) comic on what’s wrong with the academic review process. Stay tuned!**

**Isn’t it ironic that I had to write my rebuttal before I could dedicate time to illustrating what’s wrong with the process. However, the writing of the thing also gave me good fodder for the comic

I’d love to hear your thoughts about what other strategies you employ in writing rebuttals (either similar or different from mine here)! Good luck to everyone who’s still writing!

This question struck me as I was editing a paper where I was describing a survey (or is it a questionnaire?) that we used to collect data from Mechanical Turk. I was about to use the terms interchangeably when it occurred to me that they might mean slightly different things (and of course I’d be ridiculed for the rest of my adult life if I screwed this one up). The replies I received had both different and similar perspectives, at times, on the difference between a survey and a questionnaire. Here are a few of their comments:

One is a superset of the other [questionnaire :: survey]:
“A questionnaire is a survey but a survey doesn’t have to be a questionnaire.”

A survey is more relevant to people within a community of practice:
“A questionnaire is more open to outsiders while a survey is for people inside the relevant community.” This, too, hints that a questionnaire is more broad.

A survey allows for solid conclusions:
“‘Survey’ feels like something for a rigorous statistically oriented outcome; ‘questionnaire’ feels aimless, a fishing expedition.” And another: “My understanding is that survey generates quantitative data; questionnaires, qualitative”.
Again this suggests that a survey is more focused (questionnaire more general).

“Maybe a difference is the end goal of the information?” No further clarification on this one. Which is which?

Yet others thought that a survey would produce more general findings: “My gut feeling is that the data from a “survey’ is intended to be studied in the aggregate (e.g. 60% of coffee drinkers…), whereas the data from a questionnaire is linked to the individual—and perhaps to other data that the individual provides (e.g. the more people report liking coffee, the faster they are at some other task).”

What do you think?