evaluatingdesign.com

There’s a review of the PS3 game “Lair” that ties into some of our research at GMU.  Check the review: 

“Lair is a beautiful fantasy-action game with a good story and extraordinary music.Too bad it’s virtually unplayable.

This is because the Sony PlayStation 3 exclusive is one of the most difficult video games to control in recent memory.”

Ouch.

It seems that use of the six axis controller that leverages gestural control increases the difficulty of controlling your avatar (in this case, a dragon) in the air.

This isn’t completely suprising - several papers have noted that gestural control may be inappropriate for more complex actions.  This suggests that complex, symbolic actions should be mapped to specific buttons or keys.   Fair enough - no one wants to have to perform a complete loop with the controller when a “loop” button would suffice.  But do the gestural control problems seen with games like Lair translate into usability problems across all flight paradigms?

We’re currently investigating the use of gestural controls as a method of UAV control.  While automation is used with larger UAV’s, smaller UAVs can be hand flown for precision control.  We’re currently evaluating the use of joystick versus two different types of gestural control using a flight game (blazing angels).

Interestingly, early results indicate that users leveraging the gestural controls may be able to perform more accurately than their counterparts using joystick controls.  Which leads to the interesting question of exactly what symbolic actions should be encoded in button presses.  When we’re maneuvering around a 3 Dimensional space, when is maneuvering appropriate (per our study) and when is it not (like Lair?)

More on this as our research continues…

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While I try to hold this to vaguely serious postings, I was amused enough to include Cal State’s tribute to video games past. While painful to interpret many of the actions from upside down, it’s a whole lot of fun to trainspot the songs.

Here’s the video. Enjoy!

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Fox 5 reported on the dangers of interruptions while driving or flying - and including some shots of the simulator I used on my graduate research!

Check it out:

LINK

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An interesting article about an MIT initiative that dynamically maps action in a city, using information from cell phones, GPS devices, etc.

The concept is to be able to rapidly gain information about anything from “what bar is jumping” to “exactly where are the local buses right now?”

Aside from the coolness factor, imagine the possibilities for user centered design. Sure, mapping has been done quite a bit in the human factors realm, but usually we’re talking positioning information of known or unknown values. But expanding this information to visualize aspects of everyday life, such as motion and rate of Public transportation, location of crowds (or avoiding crowds, if that’s more your style). The possibilities are almost endless.

Here’s what the final product is currently looking like. As a user experience designer, what would you do with this?

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A great read about the validity of tertiary sources, from a Professor of History who found himself at the center of a Wikipedia controversy when he banned using Wiki’s as a primary source. This story broke in March of this year, but a new article this month in ACM Communications sheds some more light on a really interesting debate.

See the Article HERE.

Part of the issue is the relative polarity of both sides - those who don’t want Wikipedia cited frame the site as a fountain of populist, erroneous information, while many users who support the use of Wikipedia stress the democratization of the information process. Waters opinion makes a good point:

“It seems to me that there is a major downside to the self-reinforcing cycle of popularity. Popularity begets ease of use, and ease of use begets the “democratization”of access to information. But all too often, democratization of access to information is equated with the democratization of the information itself, in the sense that it is subject to a vote. “

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Here’s an interesting article on why Gears of War costs $60 - as in, where’s the money go?

The real show here, though, isn’t the article - it’s the pop-up window with a pie chart breakdown on what each dollar of the 60 is alloted for. Interesting stuff.

So my question is simple (and likely reflects what I don’t know about the industry) - where’s the budget for user testing and User Experience? Who foots the cost for user testing before a games goes out the door?

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They all come together to make a pretty good article.

Here’s the link:

http://www.wired.com/gaming/virtualworlds/magazine/15-09/ff_halo?currentPage=1

(Image from Wired)

Recently, one of our groups at GMU worked to used eye tracking for some of the smae types of problems noted in the article.

Which brings up a great example of eye tracking and usability. In the wired article, there’s a problem of a user not picking up certain grenades, with the conclusion that the grenades aren’t salient enough. But (as is the case in many video games), it sounds like there’s a whole lot going onscreen during that time. So how can we be sure that increasing saliency will help?

Practical experience and perceptual theory certainly argue in that direction - but simply increasing saliency may not capture the user’s attention. What you want to know is if the users is perceiving the current grenades at all - and that’s a great opportunity for eye tracking work. By examining whether the eyes ever fall on the grenades, we can verify if the user’s completely failed to perceive the grenades, or if they perceived the grenades, but failed to act on them - an important distinction for game designers.

For example, if a lack of perception is the culprit, the eyes should not land on the target (or within a degree or two of visual angle). If this is the case, make the item (grenades) more salient.

But, if the eyes fall on the target, and the users still do not use the item, there’s a more complex problem at hand. Here, there may need to be a auditory or visual prompt directing the user to the grenades.

We’re currently working in the GMU labs to provide specific, applied examples of how eye tracking can be applied to help clarify some of these issues. More on this soon!

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An interesting article about using physiological measures with game preference:
http://www.usatoday.com/tech/products/cnet/2007-08-21-video-game-brain-scans_N.htm

From the article:

“So game maker THQ tried an unusual research method last year to evaluate people’s early emotional response to its in-development shooter game Frontlines. Instead of asking a test group how it liked the game, as with most market research, the company hired technology specialist EmSense to measure people’s brain waves, heart rate and sweat responses while they played the military-theme game. Armed with that data, THQ took Frontlines in a whole new direction developmentally, said Bob Aniello, chief marketing officer at THQ.”

For many years, psychologists have investigated the relationship between subjective preference and physiological data, with some conflicting results. There is a relationship between arousal and subjective preference (in many cases, arousal can increase subjective preference for unrelated decisions - see the following article on arousal and partner preference.)

Heart rate and galvanic skin response can be used to measure arousal, making physiological measures appropriate.

It’s important to recognize, however, that several limitations of physiological data make it a questionable sell for discerning subjective preference. Consider the following issues with physiological data:

1. Sometimes, there’s no correlation between physiological data and subjective preference.
   In Heart and Emotion(Myrtek, 2003), several studies show differences in heart rate - but do not show differences in subjective preference. Further, differences may be moderated by the user’s experience level - for example, experts may actually show no difference in heart rate but still show increases in game preference. Similarly, novices may show a difference in heart rate that may not be correlated with actual game preference.
2. Physiological measures can be slow to respond to external stimuli.
   Heart rate is slow; Skin response is even slower. Earlier this week, I was talking with a fellow researcher about the potential of using HR with changes in camera angles. The issue? Changes in angles occur quickly - far too quickly for HR to “catch up”.
3. Teasing apart differences in physiological data can be difficult (and sometimes misleading).
   Heart rate can be affected by a number of issues - the individual’s age, amount of physical activity, etc. If a subject had caffeine earlier, their heart rate can be affected. What participants do outside of the experiment can affect the results that occur in the experiment. More to the point of this study, subtle changes may not be immediately obvious from physio data (see point #2 on the time lag of stimuli and physio response).

This is just to illustrate the very real challenges that occur in interpreting physiological data, and trying to incorporate it into preference data. Consider the procedure used with THQ:

“THQ is looking to EmSense for more information on how people respond to its content before it hits stores. The game maker will test an early-in-development game, or “pre-alpha,” by creating a minute-long CGI video that captures the essence of the game. Showing the clip to a small audience, THQ gets a read on the general response of would-be players, without them actually playing the game. In later stages of development, THQ might evaluate player responses to the game by exposing them to 20 minutes of play.

THQ struck a deal with EmSense last year; and with the technology, the company gets insight on play up to 50 minutes of the game, with comparisons to games in its genre.

“The tests helped us position the game — it was originally a cooperative-play, squad-style military game and now it’s more of an open world, multiplayer game.”"

I’m especially interested to see how physiological measures pointed towards a drastic design change. For now, a promising start might be in more controlled, incremental steps. One study we’re currently collecting data on at GMU is evaluating the effect of cinematics on both arousal and subjective preference. If we can show a significant difference using a very small measure, we may be able to begin to quantify the effect of different aspects of games and their impact on physiological measures.

More on this as our research develops.

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Here’s an interesting article about a Visa survey where our interactions with technology change our behavior - in this case, our fast food consumption.

During my time at Motorola, I remember an early test on RFID-enabled credit cards resulted in significant increases in purchase amount per visit. When our interaction with technology changes, our behavior in response to that interaction changes as well - often creating social and/or economic phenomena like the story above.

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I was reading an article about a recent survey on kids and usability which reported an interesting finding: According a survey by Microsoft and Viacom about kids and technology, children in developed countries don’t “like” technology, (though they do use it). Interestingly, children in Brazil, India, and China are much more likely to report “liking” the technology they use.

This has been interpreted as reflecting the integration of children and technology; a kind of merging of the concept with children’s lives so that one is not discernable from the other. This is borne out in the article by Andrew Davidson:

“Young people don’t see “tech” as a separate entity - it’s an organic part of their lives,” said Andrew Davidson, vice president of MTV’s VBS International Insight unit.

There is a danger here of interpreting the null. In statistics, we often set up a null hypothesis (for example, “Children don’t like technology” could be our null hypothesis). Assuming we have used the correct measurements for our construct, we can evaluated whether there is a significant difference from the null hypothesis to argue that children actually “like” technology.

If our null is not disproved, however, we can not immediately jump to say that the null is true (or for our example, that children don’t like technology). We can only say that the opposite of the null is not true (i.e., Children do not appear to “like” technology). The reason why the null is disproved could be many; it could be they didn’t collect enough data (likely not true for the MTV survey), or that the measure was not sensitive enough to pick up on what kids really like.

This last item crystallizes a real challenge within the usability community: as perceptions of technology change, how do we continue to create survey measures that accurately assess aspects of user’s perception? Will terms like “ease of use” develop new meaning? Or, more to the point of the study above, what will “like” mean? As perception changes, so do the effectiveness of terms that can be used to measure user experience.

Without the data (which we’re not going to get), it’s hard to say how the survey came to the conclusion that kids don’t “like” technology. But this report does bring up the question of how the term technology was defined. Even if technology is perceived as a tool to be used, it could still be something that users like (I imagine there are plenty of people who like their Black and Decker tools, or those who like their iPod). If technology was defined as an abstract term, however, it may have been that it lacked the face validity necessary for kids to understand what the survey was attempting to measure.

More on this as more information comes to bear. What I’d really like to see along with this results, however, is exactly how technology was defined and presented to their user group.

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