In a previous post, I arrived at three high-level research questions for my proposal (below; changed somewhat, again, from earlier posts).
I’ve posted about why I believe focusing on language is important, but I still need to write a similar “motivating post” about my focus on information structure and organization. Slowly but surely, I’m chipping away at the ideas that will be in my proposal.
What I’m trying to do next is make the (giant?) leap from the high-level questions above, and specific questions that I’ll try to answer. I think I am getting hung up on ideas I’ve had in the back of my mind for studies that I want to do, trying to reconcile them with these research questions. What I really should be doing is brainstorming from the questions, not trying to arrive (backwards) at the questions from the study ideas. Perhaps I’ve done a little bit too much exploratory data analysis with the delicious and ctools datasets, and it’s time to get back to basics, like actually having a research question BEFORE collecting the data. What a concept.
1. How do the information structure and organization of a user-contributed content system shape its evolution and use?
Two characteristics of user-contributed content systems are particularly relevant to this question. The first is that the information/content within the system is the point of using the system. Contributing and viewing or accessing content are the primary activities that take place in the system. The second is the content and structure present in the system at a given point in time constrains future use, in terms of what is available for them to access, what others choose to contribute, where they put the new content, and how they label or tag it. Small, individual choices accumulate into larger patterns that affect the choices and behavior of future users.
I want to know if there are patterns to be found in the process, for example, what might affect the growth of the system; what are people thinking when they make labeling or tagging choices at various stages in the development of the system; tracing the consequences and constraining effects of different types of changes on future usage; what information or cues do people attend to when trying to figure out where to” put” something, and how to find it (or re-find it); what aspects or “features” of the content make it into the labels or tags; how the “mental model” of one’s group members changes and develops over time; how and why conventions or explicit patterns form (is it really a kind of collective linguistic problem-solving?). Lots of questions, and the opportunity to compare-and-contrast among different groups in the field, using a particular system, would allow me to look for patterns at three different levels of analysis: individual, within-group, and between groups. Yay, data!
2. How do users establish common ground and negotiate meaning when contributing and seeking information asynchronously?
This question comes from the psychologist in me. I have a hypothesis that the processes at work when people use language to communicate might also affect language use in other situations that are not as obviously “communication”. Brennan (1998) suggested that we might react to computers as though they were human communication partners; she gave the example of a user of a command-line system who uses the command “ls” often to check on the status of the system, because system status is not provided automatically. I want to find out whether people’s language choices in a user-contributed content situation follow patterns that can be predicted from what we already know about language use in communication. Either way, the results will inform improved design choices, and also contribute to mediated communication theory. I intend to answer this question through lab experiments designed to identify various factors that contribute to tag, label, and description choices in user-contributed content systems.
3. How do information organization and language use affect information seeking and access in user-contributed content systems?
This question is about investigating outcomes for information consumers, in a more systematic way, once I’ve invented a design or other intervention and am ready to test it. Given my timeframe, this goes under the “future work” category.
It is not clear to me that you should always have a research question before collecting data. The perfect research question doesn’t help if the data is too hard to get at. Research is about balancing contributions with resource constraints. Getting the most “bang for your buck” so to speak. So it is valid to have some data (or know how to get some data) and try figure out what research questions can be answered with that data. Then possibly collect more data to help verify your answers. I’m fairly certain that the conventional wisdom of “question -> data -> results” isn’t necessarily the way that many researchers work, even if it is the “ideal.”
I think your intuition that some researchers (in the information field at least) often don’t have a specific research question or hypotheses when they collect their data is probably correct. Often i-school type research tends to be exploratory, so it is hard to know what to expect or even what to pay attention to before any data has been collected. However, having research questions and hypotheses is useful for two reasons: 1) it bounds the research activity and makes it easier to tell when you’re done, because you’ve answered the question; and 2) it demonstrates familiarity with past research and theory, and critical thinking in selecting what questions to pursue and how to set up the research. In cognitive psychology, there’s pretty much always a research question and hypotheses based on the work of others…
What I really need to do is analyze the CTools pilot interviews with question 1 above in mind, so I can make better predictions. It may not be entirely possible since I believe I don’t exactly have the right data, but I should give it a shot and include it in my proposal.