You’re probably wondering: where the heck is Brynn Evans? Good question. I have been here and there and everywhere, but I haven’t been sitting idly.
I’ve been working with Ed Chi at PARC to understand search in enterprises, and specifically how/where social search may help. Our approach has been to collect critical-incident style survey responses from Amazon’s Mechanical Turk. The first survey, asking corporate/enterprise users about the last time they searched for digital information on their computers, has returned 100 good responses (and only 8 gibberish responses). A preliminary analysis of this data revealed that: 1) most people did not report having any problems with their search process (we were hoping for a few instances of failure); and 2) a surprising number of people interacted with colleagues and friends prior to the search act itself. Based on this, we decided to submit two additional surveys querying users to report specific instances of 1) search failures and 2) social interactions during search. These follow-up surveys have also received a decent response rate: failures = 45 good replies, 1 bad; social = 18 good replies, 1 bad.
The last two weeks has been filled with scouring the previous literature for work on collaborative search and information foraging and sensemaking. I’ve been trying to incorporate our findings with models others have proposed (Wilson ‘81, Russell et al. ‘93, Twidale et al. ‘97, Pirolli & Card ‘05, Morris ‘08, etc.) to get an idea of how/where/when/why social interactions may improve the search and sensemaking process. Ed and I are going to try to write this up as a 4-page note for the Computer Supported Cooperative Work (CSCW) conference (due Apr 18).
In addition, I’ve been working with my three wonderful (UCSD–second year project) research participants to finish up data collection. I’ve been asking participants to capture via screencasts (video recordings) portions of their online activity, especially as they interact with online social media tools to communicate and share information with others. Video recordings have included online and desktop (local) activities related to both personal and work pursuits. I expect to finish collecting recording files from subjects by the end of next week (first week in April).
As the files have been rolling in, Tim, Amanda, and I have been transcribing the activities/events observed in each subject’s videos. Nearly all the files have been coded once, and over half have been put through a “second read” to double-check, correct any errors, and add additional comments.
To better understand and interpret the behavior observed in the screencasts, I am also interviewing participants about their behaviors, interests, goals, etc. So far I’ve conducted one interview (each) with two of the participants, where I asked them to “walk me through” one or two of their video files, providing me essentially with a narrative overview about why they did (or did not do!) certain things. I also asked about their interaction with other members of the group, but I expect to probe more about this in future interviews.
One note about the interview process: I considered using an audio recorder that Ed Hutchins lent me, but that would have meant missing out on any desktop interactions, behaviors, searches, etc. that participants might perform as they walked me through their video files. Instead, I decided to use ScreenFlow to capture all of our desktop activity plus an audio track. (In fact, ScreenFlow is the screencast software that each of the participants has been using.) The biggest drawback to ScreenFlow is that the original files are in their native *.screencast format and exporting to *.mov takes quite a long time. However, the video and audio quality is excellent, and the benefit of having one file containing both video and audio tracks totally outweighs the export-time setback!
At this point, I plan to focus on getting out the CSCW note and wrap up 2nd year project data collection. I’ll be out of (San Diego) town for the first two weeks in April (going to CHI’08 in Florence!), but when I return, I will dive deep into 2nd year project data analysis.
2 Comments
I think your use of ScreenFlow is pretty interesting here. It might be useful to call out why your participants are using it instead of, say, iShowU, and maybe what platforms (Mac, Windows) folks are using? Is there a higher likelihood for sharing behavior to exist based on the fundamental design of these systems?
The mTurk stuff is also very interesting and surprising — I would not have expected such a mechanism to elicit such a positive response, but that’s great validation of the resource!
good summary