I guess a bullet list is easiest. Conferences for this year:
I decided to upload and annotate them on YouTube, including the admin frontmatter stuff since I figure PhD students who are defending in the years to come can get a sense of the format of a defense. My slides are available in a previous post.
This is part 3 in a series where I’m posting drafts of the dissertation chapter I’m currently working on. Much of this is wordy and stream-of-consciousness, but I figure putting it out there and soliciting feedback can only be a good thing.
The chapter is on how the introduction of a threat meter addon changed my raid group’s practice over time.
About four months into our raid’s life, in February [or March?] of 2006, we started using a new addon called “KLHTM” or “KTM.”
Created by a player named Kenco, KTM did the work of keeping track of which abilities a particular player used while fighting a monster, how much threat those abilities generated, and then visually displayed that information to that player. What’s more, any instance of KTM could talk to other instances of KTM installed on other people’s machines and thereby aggregate all of the threat data for all players who had the addon installed, displaying relational charts of everyone’s threat level to each player.
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This is part 2 in a series where I’m posting drafts of the dissertation chapter I’m currently working on. Much of this is wordy and stream-of-consciousness, but I figure putting it out there and soliciting feedback can only be a good thing.
The chapter is on how the introduction of a threat meter addon changed my raid group’s practice over time.
[Need an illustrative, hypothetical table here?]
Looking at Rogues in particular, since I know the game best from their point of view, having played a Rogue during my time with the raid group, I can say that we did not know exactly how much threat each of our abilities generated, but the Rogues did know that certain abilities generated much more threat than others. These were roughly correlated to the damage output of the various abilities. For example, we knew that our main attack, Sinister Strike (SS), generated a consistent, predictable amount of threat that was safe to use, whereas, Eviscerate generated much more threat since generally its damage output was much higher. Yet, the use of Eviscerate was balanced with the fact that we could not use it as often as SS.
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The Consortium for the Science of Sociotechnical Systems is holding their annual summer institute at Skamania Lodge this year. Since I’ve been leaning heavily towards actor-network theory, distributed cognition, and mangle of practice ways of looking at my data, and since it’s so close, I decided to apply. Here’s my research summary I wrote for the application:
Contributions to the Scientific Understandings of Sociotechnical Systems
I research the ecology of gaming and new media (Salen, 2008, Stevens, Satwitcz, & McCarthy, 2008). My dissertation focuses on ethnographic accounts of online gaming practice, documenting expertise development, teamwork, and collaboration in a World of Warcraft player group (Chen, 2009). Using actor-network theory (Latour, 2005) and distributed cognition (Hutchins, 1995), this work treats the group as a learning network that successfully enrolled various human and nonhuman resources to thrive in a high-stakes joint-task environment (Taylor, 2009). I find using an analytical lens that recognizes the mangle of gaming (Steinkuehler, 2006, Pickering, 1993) helps to see that distinctions between subject-object or player-game don’t adequately describe in-action learning across settings and time. Rather, a player group’s expertise trajectory is always collaborative and social, always contentious, and always drawing on both micro- and macro-level sociomaterial (Orlikowski, 2007) resources in complex, messy gaming spaces. Analyses of informal learning arrangements using a socio-technical lens are important for science and technology studies, learning sciences, and new media scholars as specific examples of the distributed nature of learning that may lead to a broader conception of everyday practice and learning with new media.
I combine this object-oriented ontology (Bogost, 2009) with other interdisciplinary ways of describing learning arrangements including how people position and are positioned into specific roles and relationships (Holland & Leander, 2004) across timescales (Lemke, 2000) in interdiscursive moments (Silverstein, 2007).
I hope to continue using these ideas to describe learning across all of life’s myriad settings (NRC, 2009). As I am just finishing my dissertation this year, I feel like my options are wide open. Possible future areas of study include continued work in online and offline gaming practices in different player communities to expanded sites of study. For example, one research interest I have is to study software and media piracy networks and the learning and expertise development within those networks.
- Bogost, I. (2009). What is object-oriented ontology? Retrieved February 25, 2010, from: http://www.bogost.com/blog/what_is_objectoriented_ontolog.shtml
- Chen, M. (2009). Communication, coordination, and camaraderie in World of Warcraft. Games and Culture, 4(1), 47-73.
- Holland, D., & Leander, K. (2004). Ethnographic studies of positioning and subjectivity: An introduction. Ethos, 32(2), 127–139.
- Hutchins, E. (1995). Cognition in the wild. Cambridge, MA: MIT Press.
- Latour, B. (2005). Reassembling the social: An introduction to actor-network theory. New York, NY: Oxford University Press.
- Lemke, J. L. (2000). Across the scales of time: Artifacts, activities, and meanings in ecosocial systems. Mind, Culture, and Activity, 7(4), 273-290.
- National Research Council. (2009). Learning science in informal environments: People, places, and pursuits. Committee on Learning Science in Informal Environments. P. Bell, B. Lewenstein, A. W. Shouse, & M. A. Feder (Eds.). Board on Science Education, Center for Education, Division of Behavior and Social Sciences and Education. Washington, DC: The National Academies Press.
- Orlikowski, W. J. (2007). Sociomaterial practices: Exploring technology at work. Organization Studies, 28(9), 1435-1448.
- Pickering, A. (1993). The mangle of practice: Agency and emergence in the sociology of science. American Journal of Sociology, 99(3), 559-589.
- Salen, K. (2008). Toward an ecology of gaming. In The ecology of games: Connecting youth, games, and learning (1–17). USA: The MIT Press.
- Silverstein, M. (2007). Axes of evals: Token versus type interdiscursivity. Journal of Linguistic Anthropology, 15(1), 6-22.
- Steinkuehler, C. A. (2006). The mangle of play. Games and Culture, 1(3), 199-213.
- Stevens, R., Satwicz, T., & McCarthy, L. (2008). In-game, in-room, in-world: Reconnecting video game play to the rest of kids’ lives. In K. Salen (Ed.), The ecology of games: Connecting youth, games, and learning (41-66). USA: The MIT Press.
- Taylor, T. L. (2009). The assemblage of play. Games and Culture, 4(4). 331-339.
Here’s some of what I’ve written on a new paper/chapter. Feedback would be lovely. I mean to showcase data from some of the various fights in WoW, what it was like before threat meter, what changed after the addon was introduced, and especially how we actually adopted it and then used it to diagnose the Rags fight (and discover that threat wasn’t the problem).
The Enrollment of a New Actor and the Redistribution of Responsibilities in a World of Warcraft Raid Group
In World of Warcraft, each individual actor in a raid group is in charge of certain tasks and responsibilities. At one point in the life of the raid group I studied, a new actor was allowed into the group. This newbie rendered new services to the rest of the group. The services rendered were essentially rating the actions of the others in the group—that is, assigning a specified number value to their actions—and then remembering who did what to add up the ratings from each particular player. This newbie, though, didn’t actually care one way or the other if these services were used by the others, but if another decided to use them and have his or her rating displayed, that player had to abide by new rules associated with these new services. The newbie wouldn’t verbally announce others’ rating. Instead, a sign was held up and players had to manually look over to read what their ratings were. In that way, the newbie not only served but also demanded, not only taking on the burdens assigned with this new role but also prescribing new responsibilities on the others. Yet others in the raid group, first slowly then readily, came to adopt the use of these new services into their practice as the services’ benefits became increasingly clear. The group came to consider the new tasks as essential parts of its raiding activity, and players could barely remember a time when the rating-remembering services were not used. The newbie became one of them—not a newbie but a veteran—and the group merrily went on its way. But this veteran wasn’t one of them. In fact, it wasn’t even human. It was a technological device, a program, a construct, an “addon” modification to the game.
(More after the break.)
Recently, someone asked a question of the Association of Internet Researchers mailing list regarding the use of actor-network theory (ANT) with the analysis of why (WoW) gamers have a negative stereotype.
A flurry of activity occurred commenting about the use of ANT. It’s not a method but a framework, for example.
I was excited because I am thinking of using ANT to look at WoW raiding practice, and since I wanted to get feedback, too, I posted the following:
I’ve recently starting reading about ANT and have been toying with the idea of analyzing how a raid in WoW works through an ANT lens, though I am unsure what it’ll get me more than using distributed cognition (Hutchins) or just simply describing the learning arrangement between various humans and nonhumans to get the job done.
I guess my problem with ANT is that it seems boundless in terms of macro vs. micro analysis. As has been mentioned, an actor network can be made up of actor networks. Where does one start?
So, for example, I have a 40 person raid group that learns to kill a boss over several weeks. It seems like each person should be considered an actor that had to be translated into the network. We’ve also collectively used certain addons and tools within the game to help us manage cognitive load and to make transparent some of the underworkings of the game. Does each of these addons get counted? Does each iteration of an addon get counted (40 people running the same addon in slightly different ways, positioned on the screen differently, paying attention to different parts of the addon, etc.)? Do specific functions of the addon get separated as individual actors? Do different elements of the UI get separated? To back up, do specific people get broken down to mind-body-fingers?
Latour (writing as Johnson) briefly mentions that a door closer, an actor that’s been delegated the task of making a hole back into a wall, can be further broken down into the mechanisms in the whole object (egs. a spring, a metal cylinder). Is it completely arbitrary where a researcher draws the line?
In Reassembling the Social, Latour emphasizes tracing associations, which is possibly an answer to my above questions. I could concentrate on describing practice in the raid activity as I see it (which is pretty much what I’ve been doing for a while now), but pay particular attention to describing the functions of specific things as they relate to other things. Do this as they come up. In turn, these associations lead to other things that come up. Is that no longer considered ANT but after-ANT?
Is it more useful to describe cognition and memory and material resources within an entity a la dcog than use ANT? (Though my prob with dcog is more that it seems like a snapshot-in-time where I am trying to document the change in practice. ANT seems like it inherently considers instability and change through the act of translation.) Is ANT reserved for bigger arguments about societal relationships? About translation being the leveraging or convincing of other actors to share tasks? Or maybe a dcog analysis is the way to use an ANT lens using my ethnographic mehod…
Lots of questions. Maybe better suited to a blog post, as I’m just throwing ideas out there without much experience with ANT and such… But I thought I’d throw them out since it seems to that me the fastest way to learn something is to make transparent what you don’t know. And my digital ears perked up when I saw Tamara’s first message in this thread. ANT and MMOGs!
NO ONE replied except Bonnie Nardi off list! 🙁
And even then, she gave me some good pointers to articles I should read without any editorial comments of her own. Gah, more reading! :p
Was it not clear enough? I don’t explain distributed cognition at all. I don’t explain ANT at all because I assume the people who were talking about it know more about it than I do. I don’t explain WoW raiding, either, but I thought they’d all know what I was talking about. Also, I didn’t want to make the email even longer than it was…
Ah well… I guess I’ll keep reading.
So, this year instead of being an instructor for the Teacher Education Program (TEP) here in the College of Education at the University of Washington (UW), I’m an RA (research assistant) for a National Science Foundation (NSF) funded Science of Learning Center (SLC) called LIFE (Learning in Informal and Formal Environments). (How many acronyms can I put in there? 🙂 )
There are six SLCs:
- Center of Excellence for Learning in Education, Science, and Technology (CELEST) – most brainy
- Learning in Informal and Formal Environments (LIFE) – most “everything is about life, dude”
- Pittsburg Science of Learning Center (PSLC) – most original name
- Spatial Intelligence and Learning Center (SILC) – most visual
- Temporal Dynamics of Learning Center (TDLC) – quickest, yet slowest
- Visual Language and Visual Learning (VL2) – most spatial
This past weekend the UW branch of LIFE (which also has branches at Stanford and SRI) hosted the second annual grad student and post-docs inter-center conference. It was pretty cool meeting all these other learning sciences students and hearing about their research. We were able to share tools and resources, findings, methods, theories and ideas, and some good drink and company at local bars after each day’s events.
There were a number of us interested in games for learning, from the use of virtual environments for studying the effects of 1st person vs. 3rd person POV on learning (Robb) to testing social vs. non-social feedback for navigation tasks (Dylan Arena), from task oriented vs. social oriented cultural learning goals (Amy) to collaborative activity-based multiplayer mouse control (Neema).
The first day, Sarah Walter from Stanford arrived early so we could meet and brainstorm proposals for upcoming conferences. She does almost the same research as me except that:
- I am focusing on trying to map the way a raid group works to an ANT or distributed cognition model where she’s focusing more on specific collaboration practices.
- My data only includes what players were already doing (chat logs, video, web forum threads), while Sarah’s got some interview and survey data in addition to what I’ve done.
- I’m looking at a 40-person raid in World of Warcraft, while Sarah’s group is a 12-person raid in Lord of the Rings Online.
We quickly saw that it would be easy to start using the same coding scheme and collaborate on analyses so we could compare our settings and findings. We’re writing abstracts to submit to IR10 (Milwaukie, Oct) and DiGRA (London, Sept). Prob will also submit to GLS (Madison, June 10-12) but she’s going to be at CSCL in Greece (lucky!) at the same time as GLS.
On Friday, we had a full day of poster sessions and then workshops on inter and intra center collaboration. We need a match.com for researchers, one that pushes info to participants when something new of interest (maybe tag based) gets added rather than depending on us to go visit a site routinely. Does that exist?
Afterwards, dinner at Portage Bay Cafe was pretty good. Met Vanessa who researches media realism and its effects on arousal.
On Saturday, we had presentations and workshops on current research and tools. The workshop I went to was the video analysis one and ELAN (presented by Sarah Fish and Naomi Berlove of VL2) looks great!
On Sunday, the conference was technically over, but I spent the day working at a cafe with Sarah Lewis (also from Stanford), lunch with Turadg, Erin, Ruth, and Ido (all from CMU), and working at a different cafe with Turadg. Sarah and I talked a bit about our programs and profs and politics. Very informative. 🙂
Turadg showed me some cool stuff he’s been working on that might help me with my chart creation… using python and pickling and a make file and such rather than going through all the crazy manual steps I’ve been doing with a text editor, excel, sql, flash, and photoshop. He’s also working on a collective web tool for learning that I’ve agreed to help with (though honestly, I only have a fuzzy image of what it is) and runs the Open Education Research blog.