Tag Archives: technology

“Make it work” in the FCL Lab

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If you’re a fan of “Project Runway,” you’re no doubt familiar with Tim Gunn’s signature phrase. He employs this particularly around the point in each week’s process, where the designers have chosen their fabrics and made at least their first efforts at turning their design into reality. It’s at about this time in the process where the designers have to forge ahead or take the last chance to start over and re-conceptualize.

 

 

This week, it feels like that’s where we are with the FCL Lab. We’re about one-and-a-half years into our five years of funding, and about a year behind on technology development. Which means, we’ve got the ideas, and the materials, but haven’t really gotten as far along as we’d like in the actual putting it together.

For us, it’s a bigger problem, too; the development (in this case, the video booth as well as the exhibit itself) is holding up the research. As Shawn put it to me, we’re spending too much time and effort trying to design the perfect task instead of “making it work” with what we have. That is, we’re going to re-conceptualize and do the research we can do with what we have in place, while still going forward with the technology development, of course.

So, for the video booth, that means that we’re not going to wait to be able to analyze what people reflect on during the experience, but take the chance to use what we have, namely a bunch of materials, and analyze the interactions that *are* taking place. We’re not going to wait to make the tsunami task perfect to encourage what we want to see in the video booth. Instead, we’re going to invite several different folks with different research lenses to take a look at the video we get at the tank itself and let us know what types of learning they’re seeing. From there, we can refine what data we want to collect.

It’s an important lesson in grant proposal writing, too: Once you’ve been approved, you don’t have to stick word-for-word to your plan. It can be modified, in ways big and small. In fact, it’s probably better that way.

Camera Housekeeping

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With all the new wave exhibit work, visitor center maintenance, server changes and audio testing that has been going on in the last few months, Mark, Katie and I realized that the Milestone system that runs the cameras and stores the video data is in need of a little TLC.

Next week we will be relabeling cameras, tidying up the camera “views” (customized display of the different camera views), and checking the servers. We’ve also been having a few problems with exporting video using a codec that allows the video to be played on other media players outside the Milestone client, so we’re going to attempt to solve that issue too. Basically we have a bit of camera housekeeping to attend to – but a good tidy up and reorganize is always a positive way to start the new year me thinks!

Before the holidays, Mark had also asked me to try out the newly released Axis network covert camera – which although video only, is much smaller and discreet than our dome counterparts, and may be more useful for establishment angles, i.e. camera views that establish a wider view of an area (such as a birds eye view), and don’t necessarily require audio. With the updated wave tanks going in, I temporarily installed one on one of the wave kiosks to test view and video quality. During the camera housekeeping, I’m going to take a closer look at its performance to determine whether we will obtain and install more. They may end up replacing some of the dome cameras so we can free those up for views that require closer angles and more detailed views/audio.

Source: axis.com via Free-Choice on Pinterest

 

“Reverse” ground-truthing

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We’ve recently been prototyping a new exhibit with standard on-the-ground methods, and now we’re going to use the cameras to do a sort of reverse ground-truthing. Over our busy Whale Watch Week between Christmas and New Year’s, Laura set up a camera on the exhibit to collect data on people using the exhibit at times when we didn’t have an observer in place. So in this case, instead of ground-truthing the cameras, we’re sort of doing the opposite, and checking what we found with the in-person observer.

However, the camera will be on at the same time that the researcher is there, too. It almost sounds like we’ll be spying on our researcher and “checking up,” but it will be an interesting check of both our earlier observations without the camera in place, as well as a chance to observe a) people using the new exhibit without a researcher in place, b) people using it *with* a researcher observing them (and maybe noticing the observer, or possibly not), and c) whether people behave differently as well as how much we can capture with a different camera angle than the on-the-ground observer will have.

Some expectations:

The camera should have the advantage of replay which the in-person observer won’t, so we can get an idea of how much might be missed, especially detail-wise.

The camera audio might be better than a researcher standing a ways away, but as our earlier blog posts have mentioned, the audio testing is very much a work in progress.

The camera angle, especially since it’s a single, fixed camera at this point, will be worse than the flexible researcher-in-place, as it will be at a higher angle, and the visitors may block what they’re doing a good portion of the time.

 

As we go forward and check the automated collection of our system with in-place observers, rather than the other way around, these are the sorts of things we’ll be checking for, advantages and disadvantages.

What else do you all expect the camera might provide better or worse than a in-person researcher?

 

Analyze this

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And now it comes to this: thesis data analysis. I am doing both qualitative analysis of the interviews and quantitative analysis for the eye-tracking, mostly. However, I will also quantify some of the interview coding and “qualify” the eye-tracking data, mainly while I analyze the paths and orders in which people view the images.

So now the questions become, what exactly am I looking for, and how do I find evidence of it? I have some hypotheses, but they are pretty general at this point. I know that I’m looking for differences between the experts and the non-experts, and among the levels of scaffolding for the non-experts in particular. For the interviews, that means I expect experts will 1) have more correct answers than the non-experts, 2) have different answers from the non-experts about how they know the answers they give, 3) be able to answer all my questions about the images, and 4) have basically similar meaning-making across all levels of scaffolding. This means I have a general idea of where to start coding, but I imagine my code book will change significantly as I go.

With the eye-tracking data, I’ll also be trying to build the model as I go, especially as this analysis is new to our lab. With the help of a former graduate student in the Statistics department, I’ll be starting at the most general differences, again whether the number of fixations (as defined by a minimum dwell time in a maximum diameter area) differ significantly:  1) between experts and non-experts overall with all topics included and all images, 2) between supposedly-maximally-different unscaffolded vs. fully-scaffolded images but with both populations included, and 3) experts looking at unscaffolded vs. non-experts looking at fully-scaffolded images. At this point, I think that there should be significant differences in cases 1 and 2, but hope that, if significant, at least the value of the difference should be smaller in 3, indicating that the non-experts are indeed moving closer to the patterns of experts when given scaffolding. However, this may not reveal itself in the eye-tracking as the populations could make similar meaning as reflected in the interviews but not have the same patterns of eye-movements; that is, it’s possible that the non-experts might be less efficient than experts but still eventually arrive at a better answer with scaffolding than without.

As for the parameters of the eye-tracking, the standard minimum dwell time for a fixation included in our software is 80 ms, and the maximum diameter is 100 pixels, but again, we have no standard for this in the lab so we’ll play around with this and see if results hold up over smaller dwell times or at least smaller diameters, or if they appear. My images are only 800×600 pixels, so a minimal diameter of 1/6th to 1/8th of the image seems rather large. Some of this will be mitigated by the use of areas of interest drawn in the image, where the distance between areas could dictate a smaller minimum diameter, but at this point, all of this remains to be seen and to some extent, the analysis will be very exploratory.

That’s the plan at the moment; what are your thoughts, questions, and/or suggestions?

Food for thought: Ethics of sharing video

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Question: should we make available some of the HMSC VC footage for viewing to anyone who wants to see it? I was thinking the other day about what footage we could share with the field at large, as sharing is part of our mandate in the grant. Would it be helpful, for instance, to be able to see what goes on in our center, and maybe play around with viewing our visitors if you were considering either:

a) being a visiting scholar and seeing what we can offer

b) installing such cameras in your center

c) just seeing what goes on in a science center?

Obviously this brings up ethical questions, but for example, the Milestone Systems folks who made the iPad app for their surveillance system do put the footage from their cameras inside and outside their office building out there for anyone with the app to access. Do they have signs telling people walking up to, or in and around, their building that that’s the case? I would guess not.

I don’t mean that we should share audio, just video, but our visitors will already presumably know they are being recorded. What other considerations come up if we share the live footage? Others won’t be able to record or download footage through the app.

What would your visitors think?

Right now, we can set up profiles for an unlimited number of people who contact us to access the footage with a username and password, but I’m talking about putting it out there for anyone to find. What are the advantages, other than being able to circumvent contacting us for the login info? Other possible disadvantages: bandwidth problems, as we’ve already been experiencing.

So, chew over this food for thought on this Christmas eve, and let us know what you think.

Tech notes

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Here’s a roundup of some of our technology testing and progress lately.

First, reflections from our partners Dr. Jim Kisiel and Tamara Galvan at California State University, Long Beach. Tamara recently tested the iPad and QuestionPro/Survey Pocket, Looxcie cameras and a few other apps to conduct surveys in the Long Beach Aquarium, which doesn’t have wifi in the exhibit areas. Here is Jim’s report on their usefulness:

“[We] found the iPad to be very useful.  Tamara used it as a way to track, simply drawing on a pdf and indicating times and patterns, using the app Notability.  We simply imported a pdf of the floorplan, and then duplicated it each time for each track.  Noting much more than times, however, might prove difficult, due to the precision of a stylus.  One thing that would make this even better would be having a clock right on the screen.  Notability does allow for recording, and a timer that goes into play when the recording is started.  This actually might be a nice complement, as it does allow for data collector notes during the session. Tamara was unable to use this feature, though, due to the fact that the iPad could only run one recording device at a time–and she had the looxcie hooked up during all of this. 

Regarding the looxcie.  Tamara had mixed results with this.  While it was handy to record remotely, she found that there were many signal drop-outs where the mic lost contact with the iPad.  We aren’t sure whether this was a limitation of the bluetooth and distance, or whether there was just too much interference in the exhibit halls.  While looxcie would have been ideal for turning on/off the device, the tendency to drop communication between devices sometimes made it difficult to activate the looxcie to turn on.  As such, she often just turned on the looxcie at the start of the encounter.  It is also worth noting that Tamara used the looxcie as an audio device only, and sound quality was fine.
 
Tamara had mixed experiences with Survey Pocket.  Aside from some of the formatting limitations, we weren’t sure how effective it was for open-ended questions.  I was hoping that there was a program that would allow for an audio recording of such responses.  She did manage to create a list of key words that she checked off during the open-ended questions, in addition to jotting down what the interviewee said.  This seemed to work OK.  She also had some issues syncing her data–at one point, it looked like much of her data had been lost, due in part to … [problems transferring] her data from the iPad/cloud back to her computer.  However, staff was helpful and eventually recovered the data.
 
Other things:  The iPad holder (Handstand) was very handy and people seemed OK with using it to complete a few demographic questions. Having the tracking info on the pad made it easier to juggle papers, although she still needed to bring her IRB consent forms with her for distribution. In the future, I think we’ll look to incorporate the IRB into the survey in some way.”
Interestingly, I just discovered that a new version of SurveyPocket *does* allow audio input for open-ended questions. However, OSU has recently purchased university-wide licenses from a different survey company, Qualtrics, who as yet do not have an offline app mode for tablet-based data collection. It seems to be in development, though, so we may change our minds about the company we go with when the QuestionPro/SurveyPocket license is up for renewal next year. It’s amazing how the amount of research I did on these apps last year is almost already out of date.
Along the same lines of software updates kinda messing up your well-laid plans, we’re purchasing a couple of laptops to do more data analysis away from the video camera system desktop computer and away from the eyetracker. We suddenly were confronted with the Windows 8 vs Windows 7 dilemma, though – the software for both of these systems is Windows 7-based, but now that Windows 8 is out, the school had to make a call as to whether or not to upgrade. Luckily for us, we’re skipping Windows 8 for the moment, which enables us to actually use the software on the new laptops since we will still go with Windows 7 for them, and the software programs themselves for the cameras and eye tracker won’t likely be Windows 8 ready until sometime in the new year.
Lastly, we’re still bulking up our capacity for data storage and sharing, as well as internet for video data collection. I have recently put in another new server to be dedicated to handle the sharing of data, with the older 2 servers as slaves and the cameras spread out between them. In addition, we put in a NAS storage system and five 3TB hard drives for storage. Mark assures me we’re getting to the point of having this “initial installation” of stuff finalized …