Me, You, We:
by Pazit Levitan & Mark Friedman
“The most fascinating thing about Twitter is not what it’s doing to us. It’s what we’re doing to it”
(Johnson in TIME magazine, June 2009)
“The most fascinating thing about Twitter is not what it’s doing to us. It’s what we’re doing to it.”
(Johnson in TIME magazine, June 2009).
When we arrived to the Games, Learning and Society (GLS) Conference in June 2009, we expected a dominance of social network interactions. However, none of the group members expected “Twitter” to become the main communication channel throughout the conference, embracing idea exchange, stimulating real-time feedback and discussion, and acting as a game platform, all concurrent with the “traditional” learning opportunities resulting from conference interactions. Essentially, the Twitter-generated communication in GLS became a mini-conference in its own right, inviting a range of potential research and interesting observations.
Considering the three RTR cards that we received (“Behaviorism” as Theory, “Social Networks” as Topic, and “Statistics” as Method), we chose to investigate the nature of the tweet content tagged as #GLS and #GLS09. Specifically, we asked whether Twitter posts during 24 hours (one conference day from 2pm until 2pm the next day) refer to the self (“Me”), to another person’s speech or action (“You”), or both – a tweet of a community nature (“We”). In investigating the spirit of the social network content, we sought not only to observe the type of messages participants exchanged during a professional conference but also to examine, and possibly challenge, the common perception that Twitter is a platform for excessive ego blasting, manifested in self-display.1
Utilizing TweetGrid’s somewhat unknown feature of IRC (http://tweetgrid.com/irc), we were able to turn on “capture mode” for the two Twitter hashtags being used at the GLS Conference. Hashtags are a way to self-filter tweets by placing a descriptor of along with a # symbol. Users post their comments along with either #GLS and #GLS09 – the two hashtags we saw used at the conference. Once we had the two lists of tweets for the time period in date and time sequence, it was a matter of reviewing, analyzing and categorizing the tweets according to their content as “Me”, “You”, “We” or “Unidentified.”
Defining these four categories did not happen automatically. Our group chatted after dinner about how to classify the huge lists of tweets, which had been captured during the conference. After exploring a few ideas we defined the parameters for each category as follows:
A tweet expressing a personal action, thought or intention would be categorized as “Me”.
A tweet expressing another person’s action, thought, speech or intention would be categorized as “You”. In the #GLS and #GLS09 context, most of the “You” category consists of tweet content related to a session (or keynote) speaker.
A tweet expressing a call to action to others (i.e. “who would like to play later in the arcade?” or an RT (Response Tweet)2 would be interpreted as a community-natured content and would be categorized as “We”.
A tweet containing at least two of the above categories, or an ambiguous content, which is disputed among our group members would be considered as “Unidentified”.
Our hypothesis was that most tweets would be of “Me” nature and that many of the tweets, given the free-flow spirit of the Twitter social network, would fall under the “Unidentified” category. We were wrong in both predictions, ultimately leading to our Real Time Research (RTR) Award for “Most Surprising Findings”. Indeed, we were happy to be wrong, as our findings signify that Twitter enhanced the community-driven communications in GLS09.
Out of the 235 #GLS and #GLS09 tweets that we analyzed (June 10th at 2pm until June 11th at 2pm), we found that 50% (116) referred to the other (“You”), 29% (69) referred to the writer in a group (“We”), and only 18% (43) were tweets about the self (“Me”). Figure 1 provides a visual overview of these proportions.
Additionally, we identified some trends within the nature of the tweets:
“You” tweets were more prominent during conference sessions, especially during keynote sessions.
The day’s keynote speaker was James Paul Gee. “Gee” accounted for over 50% of the total day’s “You” tweets (note: Gee’s keynote address was 10:30am-noon, June 11, ‘09).
These two trends show that Twitter writers are interested in posting content that is being presented during the conference in real time. On the other hand, since Gee’s keynote address had a proportionally high weight in the results it would be interesting to research whether this type of “You”-dominated Twitter activity is typical for every morning session and/or whether a particular keynote speaker could “bias” the results. Additionally, it is possible that Twitter participants are more active in the morning presentations in comparison with evening keynote presentations. Such questions arose as we analyzed our findings. We agreed that would be interesting to explore through additional research.
Other interesting observations:
In the morning there were more tweets about the self (“me”). As the day progressed, and peaking in the evening and night, socialization messages increased in proportion, overall increasing the weight of the “We” (community) category.
As the GLS conference progressed, a community identity was formed, resulting in more “We” tweets. For example, the second half of the day had an overall larger “We” portion than the first half.
These two observations demonstrate that there is a difference in community engagement at different times of day as well as a difference in the community involvement process that takes place in (technologically-savvy) professional conferences, such as GLS 2009.
A bonus trend: Self-reflective tweets demonstrating aesthetic caring about the Twitter community:
“oops, sry for spam #gls09”
This type of message reminds us the Twitter mastery is sometimes developed within the context of a broader community. Here, a user who accidentally repeated a tweet is apologizing to the network collaborators for cluttering the network. We found that such an approach was more pronounced during conference sessions where participants used Twitter as a “back-channel” discussion. Overall community comfort level developed in such contexts over time.
In summary, we were intrigued to find multiple layers of patterns in Twitter use at the event. As we got deeper into the analysis, we realized that we would have liked to have extended our research beyond the place and time provided by the RTR limitations, which included: only one day of observation and only one conference as the context for research. The event itself was information-heavy, possibly increasing the proportional use of “You” category tweets. Moreover, we found a repetitive community of writers participated on Twitter, possibly not providing the full picture of the GLS conference communicators.
The most notable limitation, however, was that Twitter content was affected by a back-chatting game, which took place on Twitter simultaneously with our research. Specifically, the game incentivized players to tweet particular content in order to earn a higher score. Clearly this may have also affected the results of the “Me, You, We” research.
Conclusions & Next Steps
The “Me, You, We” research is merely a drop in the sea of possible investigations that could be done related to how social media is being used in conferences. Indeed, additional research is called for in order to examine Twitter communication and its social and cultural meaning deriving from its integration as part of professional conferences. On the other hand, our research suggests that there is emerging acceptance of the Twitter backchannel communication, exploring multi-layered interactions during the Games, Learning and Society conference (June, 2009).
With more time and resources, we would have extended the analysis to draw comparisons between different GLS09 days and between GLS and other conferences that take place around the same time and deal with similar topics (i.e. Games for Health, Games for Change, and DiGRA and Game Education Summit). This type of comparison would allow researchers to test the relationship between the “Me, You, We” categories in various conference settings, in multiple locations, cultures, and in under varying levels of integration of Twitter within the professional event itself. Additionally, breaking up categories into sub-categories (i.e. nature of the “You” content – is it a quote? Thought? Reply Tweet?) could clarify cause and effect relationships.
Overall, our research shows that the #GLS and #GLS09 tweets enhanced the depth of discussion around games, learning and society by allowing every writer to present their thoughts and challenge things presented officially on stage. This type of liberation and democratization of professional communication not only provides a platform to every participant (as well as those who could not make it to the conference in the first place, as seen in our “We” example above), but it also reshapes the presenter-participant power hierarchies that exist in traditional conferences.
As one conference-goer tweeted weeks after the event itself,
“One thing we noticed at #gls09 – if your presentation couldn’t produce Twitter one liners, it did not exist.” (@cstubbs, July 29th, 2009, personal communication)
How might this type of social network-driven approach to attending events affect professional conferences in the future?
We’d like to thank the other group members that did the initial research at the conference: Hal Scheintaub, Stephanie Richter, and Bonnie Saunders. It was a joy to work with them & their energy was key to the success of the activity.
1This view is common enough that we are assuming it here. For an example, see this view in blogs like Mapping The Web that make the case at www. mappingtheweb.com.
2 RT is a one-click direct reply feature on Twitter,
which is used frequently among Twitter communicators.
Table 1. Examples of each tweet category
About the writer
About someone else or event
About writer in a group
“Last final over...time to wrap up so I’m free to head to #gls09”
“Jim Gee: “Women’s play is central to the future of gaming.”
“Keep those #GLS09 updates coming. For those of us who couldn’t be there, it’s the next best thing!”
“can’t believe Javier “hurled” rather than “tossed the candy bars... #gls”
Table 2. Proportion of each category represented in the data corpus.
All I Really Needed
to Know I Learned
by Playing Games
by Brett Bixler, Dona Cady, Maryellen Ohmberger Wendy Huang, Tanya Joosten, & Turkan Karakus
What do people say they learn
from their favorite games?
What do people say
they learn from their
favorite Video games?
As part of the Real Time Research (RTR) project conducted at the Games, Learning, and Society (GLS) conference in Madison, Wisconsin in June of 2009, our research group was given a set of criteria within which to investigate a learning phenomenon related to games. The assigned criteria were: “constructionism” as a supporting theory, “survey” as a research method, and “problem solving” as the topic to investigate.
Constructionism, inspired by constructivist learning theory and connected to notions of experiential learning (see Piaget, 1955), asserts that learning occurs most effectively when individuals are active in making things that they can share (Papert & Harel, 1991). Although our theoretical criterion was constructionism, our research was situated more in a constructivistic paradigm. In explaining the difference between constructivism and constructionism, Papert (1991) explains “[t]he word with the v expresses the theory that knowledge is built by the learner, not supplied by the teacher. The word with the n expresses the further idea that happens especially felicitously when the learner is engaged in the construction of something external or at least sharable” (p. 3). We chose a more constructivist theoretical approach in that we wanted to explore the idea that the playing of games resulted in the building of knowledge by the learner. Therefore, we surveyed our participants, GLS conference attendees, about the most important game which he or she has played and what was learned from that game following a constructivist theoretical approach in order to discover if one of those skills learned through game play would be problem solving.
Specifically, we examined what games and what genre of games influenced practitioners and academics in the field of games and learning and what areas of knowledge playing these games created. As a metaphor, we chose to design a research theme based on Robert Fulghum’s best-selling collection of essays, “All I Really Need to Know I Learned from Kindergarten” (1986). We modified this theme to address what games, illustrating learning by doing, led to what types of knowledge creation (e.g., problem solving) by our participants. Being aware of the varying professional affiliations (educators, researchers, game designers) present at the conference, we wanted to explore the differences and similarities between these groups as well. Our research questions were:
1. What games have impacted GLS attendees?
2. What do GLS attendees believe they
have learned from games?
3. Is there a relationship between one’s
professional identity and the types of
games played and/or skills learned?
4. What game genres were most prominent
for which professional identities?
Our methodological approach consisted of surveying participants at the conference. It can be assumed that these participants had a professional affiliation in the field of games and learning based solely on his and her attendance at the conference.
We asked each participant to first classify his or her professional identity as either: Educator, Designer/Developer, Researcher, or Other. Individuals were then directed to choose the color of the Post-it note that best matched his or her professional identity (See Table 1). Post-it notes were used as a mode of data collection due to their ability to be completed efficiently, to limit the length of the response, and to be posted on a flip chart.
Participants were directed to write his or her responses to the proposed survey questions on the selected Post-it note. Specifically, participants were given written instructions to use one word to answer each of the following questions: “All I really needed to know I learned by playing X. What is X?” and “What did you learn?” Participants then placed their colored Post-it note anywhere across the four quadrants on the chart (See Figure 1).
The chart is a Cartesian grid presented on a flip chart with the X-axis ranging from Digital to Non-Digital and the Y-axis ranging from Entertaining to Educational (See Figure 1) resulting in four quadrants: Digital/ Entertaining, Non-digital/Entertaining, Digital/Educational, and Non-digital/Educational.
We strategically requested a one-word response in order to require participants to prioritize the games that they have played, the skills that they learned in their most significant game, and the most significant skill learned in his or her overall game play. Even though participants were instructed to use one-word responses, few were able to do so when describing the skills learned from playing a game.
We created two charts and positioned them in high-traffic areas within the conference space in order to gather the maximum number of responses from participants in the limited amount of time (See Figure 2). We collected responses over a 24-hour period.
Participants were solicited non-systematically based on their proximity to the flip charts. Given the focus of the conference, it was assumed that individuals in the area wearing conference nametags were conference attendees who were also professionals in the field of games and learning.
Once the data collection was complete and due to the time constraints of the RTR project, we transcribed the data from the flip charts into a data sheet based on professional identity, games, and classification of game. Later, we coded the games based on genre (e.g., action adventure, board game).
For our data analysis, we used Wordle word clouds using the Wordle software (Feinberg, 2009) to produce visual representations of frequency data to address research questions 1 and 3. These word clouds are an effective representation of these data because they do not represent simply a collection of responses, but rather, they illustrate how the group working together influences individuals and collectively creates understanding. Wordle was the most appropriate method of analysis due to the breadth of responses and ability to produce a visual representation of the data. Frequency charts could not capture the essence of the data for these research questions or illustrate the findings concisely. To address research questions 2 and 4, we entered the data into SPSS statistical package for further analyses. We produced frequency percentage pie graphs to address research questions 2 and 4.
Our participants were attendees at the Games, Learning, and Society conference (n=82). Their participation was completely voluntary. We did not collect demographic information from the participants beyond their professional affiliation. As seen in Table 2, the majority of participants classified themselves as “Researchers” (n=30), the second highest reported professional affiliation was educator (n=25), with the lowest reported professional affiliation being designer or developer (n=13). We did have a category of “other” (n=10) and we did have a few individuals that reported multiple affiliations (n=4).
When entering all data collected, including games reported and what was learned, into the Wordle software and not in any attempt to address our proposed research questions, games that were predominant in the word clouds were World of Warcraft (WoW) and Dungeons and Dragons (D&D). It also appeared that Civilization, baseball, and Risk were highlighted as slightly predominant (See Figure 3).
Prominent skills learned included “how to relax” and “patience” with other skills, such as “guts,” “creativity,” “strategy,” and “collaboration,” appearing as slightly prominent (See Figure 3). We did not find frequent reports that problem solving was a skill learned in playing games. In the following, we selected out data and continued our analyses to have a more clear illustration of the predominant games and skills to address our research questions.
Research Question 1:
What games have impacted GLS attendees?
When addressing our first research question, we entered the data, disregarding professional identity, including the games the participants reported. The word cloud as seen in Figure 4 illustrates the predominance of WoW and D&D as the games most frequently reported. Other games that were reported multiple times included Risk, Civilization and baseball. Also, we see that Sims (multiple versions) was reported frequently as well, but due to the multiple versions of the Sims game, the game did not appear from an initial analysis to be a dominant game reported.
In examining the data more closely, there were a high number of games participants reported (n=66). However, only five games, baseball, Civilization, D&D, Risk, and WoW had more than one response (See Table 3). The other 61 games only had one response each indicating a high diversity amongst games that impacted participants.
Research Question 2:
What do GLS attendees believe they have learned from games?
As Figure 5 shows, participants reported learning affective skills (23%) from games more than any other kind of skill. Management skills were the second most reported (15%) skill learned.
Research Question 3:
Is there a relationship between one’s professional identity AND the types of games played and/or skill learned?
In our study, among educators, WoW is the most frequently cited game. Further, we can see in Figure 6 that “strategy,” “guts” (bravery), and “collaboration are the most frequently cited skills learned.
Among designers and developers, WoW and D&D are the most frequently cited “games” and “strategy” is the most frequently cited skill learned
(See Figure 7).
Among researchers, WoW and D&D are again the most frequently cited along with “patience” and “how to relax” as the most frequently cited as the skills learned in games (See Figure 8).
Among participants classifying themselves as “other,” there were no clearly predominant themes (See Figure 9).
Research Question 4:
What game genres were most prominent for which professional identities?
Fourteen genres of games were coded (See Table 4). When examining the data set as a whole, role-playing (29%) was the most dominant genre of game reported by our participants. Action-adventure (15%), simulation (13%), and board game (12%) genres followed (See Figure 10). Note that the most dominant genres (role-playing and action-adventure) also describe the game titles most frequently reported previously (i.e. WoW and D&D).
As seen in Figure 11, when examining Educators and the most frequent genre reported, both board games (23%) and role-playing games (23%) were the highest reported. Outdoor games (19%) were reported second highest with platform games being reported the least (4%).
In Figure 12, when examining Researchers and the most frequent genre reported, role playing games (13%) was the most frequent and obviously the most prominent.
Finally, (see Figure 13), when examining Designers and Developers, we again see role-playing games (6%) as the most frequent followed closely by action and adventure (5%).
Role playing games were the most prominent across the professional identities. For each professional identity, educator, research, and designer and developer, role-playing was the most frequent reported genre of game.
Though initially surprising, a common pattern emerged among the games most frequently reported. World of Warcraft and Dungeons and Dragons were the most frequently cited games across all categories of profession. In retrospect, however, such results are not all that surprising. World of Warcraft is the most popular MMORPG (Massive Multiplayer Online Role Playing Game) to date, boasting more than 11 million subscribers as of 2008 (Blizzard Entertainment, 2008). Dungeons and Dragons is the most famous non-digital role playing board game ever created (Waters, 2004). It is no wonder, then, that these two game titles would be more frequently reported than any other game.
The findings of these frequencies should not be overstated. There were over 66 games reported with only baseball, Civilization, D&D, Risk, and WoW having more than one response with baseball, Civilization, and Risk only having two responses each. WoW and D&D were overwhelmingly the most frequently reported, but more importantly may be the number of different games that participants uniquely reported, 61 uniquely reported games. It is evident that games have an impact on our participants’ development of skills, but there is no clear evidence that any one game is the leader. The categorization of genre was then needed since no clear evidence could be drawn from the name of the game alone.
These data suggest that, while more or less everyone, regardless of profession, reports an array of games highlighting two popular games (i.e. WoW & D&D), what, specifically, individuals report having learned from them does vary somewhat based on professional identity. In fact, we were surprised at the vast number of individualized and highly nuanced “skills” identified by participants. For example, educators reported learning “strategy,” “guts,” and “collaboration.” Designers and developers reported learning “strategy,” and researchers reported learning “patience” and “how to relax.” This diversity could be attributed to the fact that participants often used more than one word to describe what they learned from playing a game. It is, indeed, interesting that participants had difficulty expressing what they learned in only one word. Perhaps this suggests that what is learned from games deeply resonates on many levels and is hard to precisely define.
It could also be that professional areas of expertise color perceptions of games via the affordances participants perceived in the games. Affordances are features the individual perceives in an environment that can be manipulated towards a desired end (Gibson, 1979) leading players to bring their real selves into a game (Gee 2007). Thus, different people will see the same game in different ways, take different actions, and possible learn very different things. In other words, because games are interactive and individuals perceive them in differently, what is learned from a game is not consistent across all people and all game play experiences. However, more research is needed to clarify these possibilities and the influence of professional identity.
In this project, the most frequently reported types of skills were affective skills followed closely by managerial skills (“leadership,” “how to run a business”). On the surface, the finding that many people learned affective skills from games is not surprising in that much of game play taps into strong emotions (“fun,” “fear,” “excitement,” “frustration,”), however, the wide range of affective skills reported suggests that playing games is somewhat of an introspective and personal adventure, regardless of how collaborative or public the game may be. Both WoW and D&D are intrapersonal, communicative and collaborative games, yet the skills participants report having learned from them are first and foremost introspective and personal and only second managerial and social.
It is not surprising that role-playing was the most reported genre of game across professional affiliations. Role-playing has been identified as a strategy for constructivist learning for years due to the experiential nature of role playing and its ability to not only promote cognitive learning, but also promote behavioral and affective learning (See Moradi, 2004; Smith, 2004). The known outcome of role playing as facilitating affective learning can also help us better understand the high reports of affective skills by our participants. Since most of the participants were reporting role playing games, it is only natural that they would also be reporting affective skills learned by playing those games, which can also lead us to better understand why there is sometimes resistance in educational institutions to implement games for learning. If the primary skills learned by playing games are affective and managerial skills, neither of these are tested to determine an educational institution’s success or effectiveness. Therefore, these schools have no motivation to implement experiential activities, such as role playing games, since it does not directly impact the measured outcomes of student performance on math, English, and reading in standardized testing, although a conclusion can be drawn that affective and managerial skills can be gained by playing games and are pre-requisite for certain professions (educators, researchers, and more).
These research findings suggest that, when prompted, game players can and do report having learned specific skills from the games they play supporting a constructivist theoretical foundation of learning by doing.
The topic of problem solving in gaming needs further investigation and could be well served by taking a constructionist perspective. Follow-up studies could investigate the pros and cons of this approach, by devising one study similar in nature and methodology to this one, and another where all participants’ contributions were done in the blind. Comparisons between the groups on pattern swarming (where later participants follow along with previous participants in a “me too” pattern), uniqueness of responses, and time for patterns to emerge could be performed.
Personal observation of the activity of the participants indicated that approximately 50% of participants contributed “blindly” to the study, not reading previous participant’s responses. The other participants did browse other’s responses, sometimes commenting to the researcher on their thoughts about previous participant’s responses. Also, some individuals perused other’s responses then left to “think about it,” returning later to participate. The difference in time delay between those who blindly and immediately participated, those who perused the board then participated, and those who perused the board, left for a period of time ranging from several minutes to a day, and then returned to participate, could have introduced a variable that is not accounted for in this document. Or, making the data collection private could control this variable.
The broadly reported games identified by our participants are interesting phenomena. Although there were some popular games reported with some frequency, there needs to be additional research in understanding why so many different games impacted our participants.
With the identification of role-playing games as the prominent genre of games across professional affiliations, we urge continued research into the impact of role-playing games on learning. Specifically, an investigation of the skills learned from role-playing, such as affective and managerial skills, on student success would be viable research.
We do not know clearly, based on these data alone, however, if the skills learned “transfer” to real-world situations in some way. The research on role playing would confirm this idea, but further research on the transfer of skills learned by role playing in games on all four of our quadrants is still needed.
Blizzard Entertainment. (Oct. 28th, 2008). World of Warcraft surpasses 11 million subscribers worldwide. Retrieved September 10, 2009, from http://www.blizzard.com/us/press/081028.html .
Feinberg, J. (2009). Wordle. Retrieved June 12, 2009 from http://wordle.net .
Fulghum, R. (1986). All I really need to know I learned in kindergarten: Uncommon thoughts on common things. New York: Villard Books.
Gee. J. P. (2007). Good video games + good learning. New York: Peter Liang Publishing, Inc.
Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton Mifflin.
Moradi, B. (2004). Teaching about diversities: The shadow/role-play exercise. Teaching of Psychology, 31(3), 188-191.
Papert, S. (1991). Mindstorms. Children, computers and powerful ideas. New York: Basic books.
Papert, S. (1991). Situating constructionism. In I. Harel & S. Papert (Eds.), Constructionism. Norwood, NJ: Ablex Publishing.
Piaget, J. (1955). The child’s construction of reality. London: Routledge and Kegan Paul.
Smith, N. S. (2004) Teaching for civic participation with negotiation role plays. Social Education, 68(3), 194-197.
Waters, D. (April 26, 2004). What happened to Dungeons and Dragons? BBC News Online. Retrieved September 10, 2009 from http://news.bbc.co.uk/2/hi/uk_news/magazine/3655627.stm.
Designer and/or Developer
Table 1: Correspondence Between Post-it Note Color and Professional Identity
Designer or Developer
More Than One Reported
Table 2: Frequency Table: Professional Affiliation
First person shooter
Action - Adventure
3D Virtual Environment
Table 4: Game Genre Frequency
Losing Track of Time in the GLS Arcade
by Anythony Betrus, Janet Beissinger,
Greg Casperson & Yoonsin Oh
How does a player’s perceived
game-playing time compare to a
player’s actual game-playing time?
How does a player’s perceived game-playing time compare to a player’s actual game-playing time?
This “Real Time Research” (RTR) study was conceived at the May, 2009 Games, Learning, and Society (GLS) conference at the University of Wisconsin-Madison. Our inquiry started when one of our group members (Betrus) read the description of the RTR session on the way to the conference. After some thought, he brought the idea of observing GLS attendees as they played a game to our randomly chosen group at the RTR session. The group expressed a mutual interest in Csíkszentmihályi’s (1990) theory of flow and discussed how we could do some basic measurement and observation to determine whether players had entered a flow state while playing.
Just as we were thinking about which game we would set up and where, one of the conference organizers (Steinkuehler) made the timely suggestion to use the games already set up in the conference arcade. Our UW-Madison hosts had set up a giant dream arcade with games of every different shape, size, and variety (along with free flowing kegs and unlimited ice cream). We all agreed that observing people in the arcade was a good idea.
For our RTR experiment, we decided it would be relatively easy to ask some simple questions about players’ perceptions of their experiences and to gather some basic demographic information after they finished playing a game. We found, among other things, that players were miscalculating their time played 95% of the time – a significant amount even for a quick test like ours.
& RTR Questions
Csíkszentmihályi’s (1991) book, Flow: The Psychology of Optimal Experience, is the seminal work in the area of flow. In it, Csíkszentmihályi describes “flow activities” as supporting enjoyment, and gave examples of play, art, pageantry, ritual, and sports. He then explained that flow activities “...transformed the self by making it more complex. In this growth of the self lies the key to flow activities.”
The achievement of flow through an appropriate balance between Anxiety and Boredom has since become a commonly accepted goal among researchers and scholars interested in improving the teaching/learning environment through the use of games. Csíkszentmihályi stated that:
“Although the operationalizations of flow diverge from one another, almost all flow measuring instruments include the challenge–skill dimension that has been argued to be the most important flow antecedent “ (Csíkszentmihályi, 1991, p.191).
Kiili (2006) divided the conditions described by Csíkszentmihályi (1991) into antecedents and the experience itself. Kiili (2006) outlined the antecedents as, “...challenges matched to the skill level of a player, clear goals, unambiguous feedback, a sense of control, playability, gamefulness, focused attention, and a frame story.” He sought to correlate these antecedents with the indicators of flow experience: “...concentration, time distortion, autotelic experience, and loss of self-consciousness” He concluded that that:
“The flow antecedents studied—challenges matched to a player’s skill level, clear goals, unambiguous feedback, a sense of control, and playability—should be considered in game design in order to produce engaging and enjoyable experiences for players” (Kiili, 2006).
In other words, he concluded that the basic descriptive characteristics of flow outlined by Csíkszentmihályi (1991) could be used as prescriptions for creating learning games that support flow experiences. In his conclusions he went on to state that:
“The results of the study supported the assumption that the concentration, time distortion, autotelic experience, and loss of self-consciousness dimensions can be considered indicators of the flow experience. The interplay of these dimensions facilitates the flow level experienced by players. Furthermore, the results indicated that the flow experience was independent of gender, age, and prior gaming experience” (Kiili, 2006).
Csíkszentmihályi (1991) described losing track of time as a common description of flow experience. He explained that most people mentioned time went faster than it actually did, but there is also the opposite case, and used an example of a ballet dancer who thought time went slower while performing a difficult turn. He concluded from his observation that, “The safest generalization to make about this phenomenon is to say that during the flow experience the sense of time bears little relation to the passage of time as measured by the absolute convention of the clock.”
Based on our understanding of flow, we suspected that some people would enter a flow state in which time perception becomes distorted. For our study, we focused somewhat narrowly on this particular aspect of flow, which is about losing track of time. Our primary research question was “How does a player’s perceived game-playing time compare to a player’s actual game-playing time?” We further compared that to basic information about the person playing and the game he or she was playing. We looked at whether they lost track of time, the game was challenging, and whether players had fun while playing.
We hypothesized that as players played for longer periods of time, they would be more likely to enter a flow state and would therefore evidence a correspondingly greater discrepancy between perceived time and actual time played. We also wondered if the aggregated data would reveal some sort of statistical “break point,” where before that point there would be less time distortion and after it there would be greater time distortion.
We conducted our research in the GLS arcade throughout the conference (2 days, 2 evenings). Participants were a convenience sample chosen from those playing in the GLS arcade. They were observed without their knowledge and clocked from the time they started playing a game until they quit the game. Immediately afterward the players were asked to estimate the amount of time they had just played the game. Then they were interviewed based on a short seven-item protocol (Appendix A) that included questions about whether they enjoyed the game and whether they found it challenging, as well as their age, gender, and prior game experience. We also asked whether they had checked the time during game play to know whether their estimate was a true guess or based on a clock.
Given the limits of the study and the difficulty in controlling variables, over-analyzing the data would not be appropriate or useful. We looked mainly for general patterns.
Here is some basic data about the participants:
• 25 males & 15 females participated
• Age range was 8 to 54 with a mean of 33.2.
• Games played: Rock Band, Dance Dance Revolution, Conspiracy Code, Flower, Samba De Amigo, Guitar
Hero, Team Fortress 2, & Left 4 Dead.
• 50% were playing a game they had never played before.
• On average, players rated them- selves a 3.0 on a 5-point Likert scale, with 1 being a non-gamer and 5 being a hardcore gamer.
We found that most players (84%) estimated time played by guessing, while 16% used some other reference to help estimate time such as counting how many songs played in Rock Band and multiplying it by average pop song length of three minutes and thirty seconds, glancing at time during or just after play, or estimating based on when a previous conference session ended and the next started. So for most players, the time reported reflects their own perception of time.
In regards to our main research question of “How does a player’s perceived game-playing time compare to a player’s actual game-playing time?” 47.5% of participants underestimated the time they played, 47.5% of them overestimated, and 5% of them answered exact playing time (Figure 1). The range of difference in perceived time went from an underestimate of 15 minutes to overestimates of 70 minutes, and the average player was off in their estimation by 39%. We found the average absolute time difference between perceived and actual time was 9 minutes 4 seconds. However, we did not see any pattern between actual played time and this time distortion (longer play did not seem to correspond with greater or less distortion).
Of the three most commonly played games, Rock Band players underestimated time played by 17%; Conspiracy Code players underestimated 23%; on the other hand Dance Dance Revolution players overestimated by 22%. Players who did not think the game was challenging underestimated time played by 2%. On the other hand, those who found the game challenging overestimated time played by 11%.
Other findings: 75% of participants were playing in a group (2 or more), 75% percent of participants rated their game as fun, and 75% rated their game as challenging. 57.5% found their game to be both challenging and fun.
Future Research Questions
Although our initial goal was to investigate whether players experience a flow state while playing games, we are limited in what we can conclude. There were so many uncontrolled variables in our study that it is hard to attribute errors in time reporting necessarily to flow. While some players seemed to engage in the games, the testing environment hampered this possibility for others. Players had constraints of upcoming sessions or social distractions from colleagues or others in the gaming environment. Additionally, half were playing the game for the first time, which may affect ability to reach a flow state. Finally, we do not know how well participants would be able to estimate time passage during other activities. Correctly estimating time might just be a difficult thing to do regardless of the activity.
We were hoping to observe whether players entered into a state of flow, primarily comparing their perception of time played with their actual time played. We found in general that players did not accurately report their time played (95% of participants), and they did have a distorted sense of time. We found it surprising that only 5% accurately estimated time played and those players’ time estimates were an average of 39% off. These findings may have been inflated somewhat due to some shorter game play times for which estimates were often rounded to the nearest 5-minute increment. However, even in longer playing situations, there were similar differences between times played and estimated time played. Either people entered a state of flow rather quickly in game play and lost track of time or else people have a poor sense of time in general.
It is interesting that the game that required moderate physical activity (e.g., Dance, Dance, Revolution) was also the game that had the highest overestimation of time played (by 22%), and that in general as players rated games more challenging they overestimated their time played. We wonder if this is similar to the case Csíkszentmihályi (1991) described in which a ballet dancer’s perception of time was slower while performing a difficult turn.
Although all players who played Dance, Dance, Revolution reported that the game was challenging, there were mixed reports from players on overestimation and underestimation compared to their actual play time. It would be interesting to see if there is a relationship between overestimation of time and increasing challenge level of an activity. In future studies one might start with the assumption that flow is not an absolute, but a relative concept. In other words, a player could be at the very limits of flow, just before the challenge of the game increases to the point where it pushes the player from a flow state to a state of anxiety. Alternatively a player could be in a flow state on the verge of boredom. In any case, the intersection and relationships among skill level of the player, the challenge of the activity, and time distortion is certainly an interesting area to examine in future research.
We are also interested in finding if there are differences in the people we talked to, such as background, immediate contextual variables, or personality that, if measured, could predict whether someone would overestimate or underestimate their time played.
“Do people engaged in video games lose track of time?” “Does the time distortion change (increase or decrease) if they enter a flow state?”
“Does a person’s perception of time while playing video games differ any more or less than their perception while doing other more mundane activities?”
We would also observe players in more natural settings. We would control for variables in our sample, such as game genre, actual amount of time played, and prior experience with game. We would also need to determine how accurately participants keep track of time doing other activities.
To finish this study, our RTR team met every day during conference, informally in the morning and afternoon, and formally in the evening. We spent one particularly long night analyzing data and preparing our presentation. While this was not what any of us had in mind when we went to the conference, somehow, the sense of accomplishment we got from working together made it worth the time and effort.
We focused on generating research questions and producing results that could lead to future research. For you, the reader, we hope the process worked. Through our reflections of the deficiencies in our research process, we are in turn identifying potential areas of inquiry to be explored. Ultimately, in our inquiry we were seeking to determine the circumstances and factors responsible for getting people into a flow state and similarly to look at what keeps it from emerging. In the end we hope that our study helped to accomplish the muse-like goals of the RTR project itself –that is, to foster dialogue and conversation about research in the domain of learning games and to propose next-step research questions and areas of inquiry.
We thank everyone who participated in our research at the GLS 5.0 conference. We also thank to GLS committes who had basically set up a giant dream arcade with games of every different shape, size, and variety (along with free flowing kegs and unlimited ice cream). It was simply amazing. We appreciate organizers for the real-time research, Eric Zimmerman, Constance Steinkuehler, Kurt Squire, and Seann Dikkers for making this research happen. They were warm, friendly, responsive, and really do have genuine interest in our collective studies. Their feedback and support for the research helped us to finish this study within such a short period time. And finally, thanks again to Seann Dikkers for his very gentle proddings to get the chapter drafted.
Anthony Betrus (State University of New York at Potsdam, firstname.lastname@example.org), Janet Beissinger (University of Illinois at Chicago, email@example.com), Greg Casperson (Michigan State University, firstname.lastname@example.org), Francois Emery (Ubisoft, Francois.email@example.com), and Yoonsin Oh (University of Wisconsin-Madison, firstname.lastname@example.org).
Csíkszentmihályi, M. (1991). Flow: The psychology of optimal experience. New York, NY : Harper Perennial.
Kiili, K. (2006). “Evaluations of an Experiential Gaming Model”. in Human Technology,Volume 2 (2), 187-201.
by Carol Rees, Laurie Hartjes,
Yoonsin Oh, Amy Adcock & Kae Zenovka
What roles do players take in offline
What roles do players take in offline social
At the first Real Time Research (RTR) session at the Games, Learning and Society (GLS) conference in July 2008, we were invited to design a research project that would be conducted, analyzed, and presented by the conclusion of the two-day conference. We accepted this challenge as a group of strangers with diverse disciplinary backgrounds, which included a grade school science teacher, a college professor, an instructional designer and researchers from the fields of nursing and education. In order to begin the process, index cards representing theoretical perspectives, research methodologies and data analysis techniques were selected randomly by each RTR group. Using the selected cards as a starting point, we began our quest for a research topic by seeking common interests in gaming research. Not surprisingly, we all shared a passion for games and learning. This collective interest led us to a conversation about the games that we had observed and/or played in the GLS arcade the night before. We were curious about the apprenticeship (Lave & Wenger, 1991) that seemed to be developing around some of the games and how the GLS arcade offered an easily accessible venue for observing the sociocultural nature of learning (Vygotsky, 1978), including the conversations that go on around games (Squire & Jenkins, 2004).
Much of the research done on the topic of learning through social interactions during game play examines the learning that happens when individual learners interact with other people in an online gaming space (Nardi, Ly, & Harris, 2007; Steinkuehler, 2004; Thomas, 2009). Fewer studies have described the apprenticeship around games in offline environments (Reed, S., Satwicz, T., & McCarthy, L., 2008). We decided to take advantage of the opportunity offered by the GLS arcade to conduct an RTR study of offline learning through social interactions around games.
Our initial research question was: How do conference participants experience offline social interactions in the GLS arcade and learn through them? We further refined this to two more specific questions:
In offline interactions, what roles do conference participants take during game play within the GLS arcade: players, lurkers, or mentors?
How do participants of the study who have taken on different roles (players, lurkers, or mentors) describe their comfort level and experience with the game?
Choice of Methodology
For our RTR project, we were asked to select a research methodology from one of several possibilities offered to our group. We selected “phenomenology” as the best fit because in a phenomenological study the researchers begin with a question that is important in their own lives (van Manen, 2002a). It was our shared learning experiences interacting with some of the new games in the GLS arcade that motivated our inquiry. Phenomenology is by its nature is not a methodology to be rushed, but our time constraints dictated a compressed reflection and validation process. We collected data for the purpose of reflecting on the meaning of these experiences for participants.
We chose two methods for gathering information for our study that are consistent with a phenomenological approach (van Manen, 2002b).
Close observation: “Close observation involves an attitude of assuming a relation that is as close as possible while retaining a hermeneutic alertness to situations that allows us to constantly step back and reflect on the meaning of those situations” (van Manen, 2002b, paragraph 2, line 9).
Interviews: Interviewing allows the researcher to “borrow” other people’s experience to help develop understanding. In an extended phenomenological study, researchers write questions that explore the meaning of that experience for individuals and ask them to share their lived experiences. Because of the abbreviated research time, basic questions that provided immediate description of the experience were developed.
Choice of Games
We limited our study to a subset of the games available at the GLS arcade. We selected the games, Wii Sports and Wii Fit (released 2 months before the conference), since they were new, drawing larger numbers of participants, and we had all enjoyed them personally.
Selection of Participants
Study participants were individuals playing Wii Sports or Wii Fit or individuals observing or waiting their turn to play the game. Participation was largely limited to breaks between conference sessions with a few running over into the start of a new session. We selected all willing participants who were available for conversation during the limited time frame.
Definition of Player, Lurker, and Mentor
Players were actively involved in the game play; lurkers were observing others play, but were not actively involved in the game. Mentors were guiding other players either through conversation as lurkers or through joint game play with other players.
In order to structure our observations and to document our findings, we constructed a data collection sheet (See Appendix A). We collected data between 10:30 am on Day One of the Conference and 3pm on Day Two of the Conference, primarily using session breaks, when the population in the GLS arcade was the most active, to make observations and conduct interviews. During session breaks, one or two researchers from our group approached conference attendees who were either playing or observing at the Wii Sports or Wii Fit area. We explained our RTR project and then invited the conference attendees to become participants.
To address our first research question we engaged in close observation of the game play, this sometimes led researchers to involve themselves in the game play (van Manen, 2002b). We closely observed participants and classified them as players, lurkers, or mentors. We also noted the conversations that were occurring between participants as they involved themselves in the game.
To address our second research question, we conducted brief interviews with participants (see questions in Appendix A), asking players and mentors to indicate their comfort level with the game in the following simple terms: level 1 = very comfortable, level 2 = okay, and level 3 = frustrated.
We compiled the data from our data sheets by first counting the number of participants who were players, lurkers and mentors. Next we counted the number of participants who had assigned themselves to each comfort level. Finally, we examined the interview data for themes, which were established by consensus after reviewing our interview notes (Appendix A).
Of the 400 GLS conference attendees, 35 (8.8%) participated in this study. The age range was 19-64 years. When examining behavior in this public social context, our data showed that 20 participants were players only, 13 were lurkers, 2 were mentors (see Figure 1). Interestingly, both mentors were also playing the games we observed, although for ease of category assignment, we did not include them in the player category.
In our player category, eighteen out of twenty players identified their level of comfort with the games (see Figure 2). Of these 18 players, eight were very comfortable with this game experience, seven felt okay, and three felt frustrated. Both mentors classified themselves as very comfortable.
One of the questions that lurkers were asked is whether they planned to play. Of the 13 lurkers, three planned to play, seven preferred to watch, two said maybe, and one did not answer.
To elucidate themes from our interview data, we focused on the player and lurker roles because we collected more data from individuals in these two roles. Players described their experience predominantly in the terms shown in Table 1; it was fun, cool, engaging, and learning was intuitive in most cases (Table 1).
In addition to these general comments, specific comments on Wii Sport - Golf and Wii Fit were collected. Responses to Wii Sports - Golf were mixed with some players describing it as fun while others described it as frustrating, remarking that it was not like the real sport or otherwise expressing dislike for the title. Responses concerning Wii Fit were more consistently positive although one player found the balance board in Wii Fit - Ski Slalom uncomfortable. Examples of comments from lurkers on the reason they watched but did not play included: no time, liked watching, preferred to watch, just observing, heard about it, want to see what was new, play it all the time, not interested, interested in other games, sometimes watch, sometimes play. Players were observed encouraging lurkers to play with mixed results, while mentors offered tips and comments to the players that facilitated learning new skills and reinforced successes.
CONCLUSIONS & NEXT STEPS
Conclusions can be drawn from both the micro-level about what can be learned from the findings of this one example of an RTR study and the macro-level concerning the feasibility of doing RTR at a gaming conference more generally. Although the sample size in our RTR study was small (n=35) and our data were preliminary, we had three findings that lead to ideas for further work. First, we found that all mentors were players, but not all players were mentors. This raises interesting questions about the characteristics and motivations of those players who were also mentors. Second, another interesting finding concerns the different experiences of players with the games. For example Wii Sport-Golf elicited contrasting reactions (intuitive versus frustrating) from different players. It would be informative to extend the study and investigate explanations for these different reactions to this game. Third, an unexpected finding from our study was the high proportion of lurkers (13 out of 35). This finding suggested another interesting research avenue for further investigation on lurking.
We began this study with the objective of observing how participants responded to a recently released game in the GLS arcade, however we did not collect data focused on what study participants learned. Next steps for research would be to conduct a study of the teaching/learning process in a gaming arcade such as this one. Additionally, we noticed that a fairly consistent population of conference attendees entered the arcade during the break periods over this 2-day time frame. We would like to explore the reasons reported by conference attendees for entering or not entering this on-site play space.
On the macro-level, our process demonstrated that five professionals, previously unknown to one another, are capable of pulling study design characteristics “out of a hat” and then doing rapid prototyping to arrive at specific methodology and population of interest. We see value in doing RTR rapid prototyping in providing a forum for informal knowledge generation, in collecting preliminary data that can be used to generate new research questions, and in enabling feasibility testing for various methodologies. For example, we discovered that individuals in the GLS arcade were willing participants in a study of game play, easily accessible, and generally open in their behaviors while engaged in game-play. This made the experience of collecting data less cumbersome and more meaningful for the investigators and provided an added benefit to their conference attendance. The nature of the RTR process is highly creative, collaborative, and it offers opportunities to ask questions that might otherwise not arise in game and simulation research.
Lave, J., & Wenger, E. (1991). Situated Learning: Legitimate Peripheral Participation (Learning in Doing: Social, Cognitive and Computational Perspectives). New York, NY: Cambridge University Press.
Nardi, B. A., Ly, S., & Harris, J. (2007). Learning conversations in World of Warcraft. Paper presented at the System Sciences, 2007 HICSS 2007. 40th Annual Hawaii International Conference on Education.Waikoloa, HI.
Reed, S., Satwicz, T., and 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. The John D. and Catherine T. MacArthur Foundation Series on Digital Media and Learning. Cambridge, MA: The MIT Press, pp. 41–66.
Steinkuehler, C. (2004). Learning in massively multiplayer online games. Paper presented at the Sixth International Conference on Learning Sciences, Santa Monica, CA.
Squire, K., & Jenkins, H. (2004). Harnessing the power of games in education. Insight, 3 (5), 7-33.
Thomas, D. (2009). Scalable learning: from simple to complex in World of Warcraft. On the Horizon, 17(1), 35-46.
van Manen, M. (2002a). Writing in the Dark: Phenomenological Studies in Interpretive Inquiry. Althouse Press, University of Western Ontario.
van Manen, M. (2002b). Inquiry: Observing experience Retrieved September 11, 2009 from: http://www.phenomenologyonline.com/inquiry/29.html.
Vygotsky, L. S. (1978). Mind in Society: Development of Higher Psychological Processes. Cambridge, MA: Harvard University Press.
Table 1. Terms used to describe theirWii Sport & Wii Fit experience
Wii Sports (Golf)
Easy, Cool, Neat (Yoga)
Uncomfortable on the balance board (Ski Slalom)
Love it, like it
Don’t Like That
Different from real game.
Data Collection Sheet
Gender: Male / Female
1 (very comfortable) 2 (okay) 3 (frustrated)
Player / Lurker / Mentor:
(Space allowed for notes on sheet)
1) Have you played Wii before?
2) Played this sport in real life before?
3) 1-3 words on their experience
1) Played Wii before?
2) Are you planning on playing?
3) Why or why not?
by Michelle Aubrecht, Yoonhee Lee,
& Monica Martinez-Gallagher
What happens when viral notebooks
are used as a research collection
method at a conference?
WHAT HAPPENS WHEN VIRAL NOTEBOOKS ARE USED AS A RESEARCH COLLECTION METHOD AT A CONFERENCE?
This was the question that we formed after we much discussion. Determining our question was difficult for our group. We had three cards to help guide our formulation of a research question: Activity Theory, Social Interaction, and Ethnography. Michelle wrote ideas on a large piece of paper as our team threw around ideas. We began to focus on data collection methods and lit upon the idea to use small notebooks, each with a question written on it, and ask people to answer a question on the notebook and then pass it along to someone else. This method of collecting data used the idea of social interaction and was a not to general ethnography (participant journals). Theory was not a strong component of our research question.
We wrote two questions on five notebooks each for conference participants to answer. The topic of the question, albeit interesting, was not relevant to our research question per se. Rather, we wanted to focus primarily on the data collection method itself. Since we were attending a conference about games, we assumed that many of the attendees would be game players. The Questions:
1. What character class do you usually choose and why?
2. What is your favorite game and why?
There were ten notebooks divided into two piles of five, with question one on one set and question two on the other set of five. We wrote the question on the top half of the cover of the notebook. The directions were written on the lower half of the front cover and read: “Please return to the GLS info desk by 9 pm Thursday.” A box was placed on the counter at the conference’s information desk for notebook return.
It was the first night of the conference (Wednesday) during a poster session. Our notebooks were ready. Monica and Michelle each answered a question in order to provide an example. Monica and Michelle then went to the poster session area and asked people to take the notebook and answer the question, giving no further instructions.
The following morning (Thursday), we noticed that there were no notebooks being passed around. We found some in the game room. By the following evening (Thursday evening) before the plenary session, Michelle gathered as many as she could find because none had been returned to the designated box.
Rather than being passed around, the notebooks appeared to have been abandoned and left in various places or lost. Because so little data had been collected, (the notebooks were nearly empty at that time), we decided to deviate from our original protocol and directly approached approximately 15 people to take a notebook with Question #2 on it and answer the question. We waited while the person answered the question and then Yoonhee took the notebook back.
That evening, we gathered to tabulate and analyze the data we were able to obtain. For each of the two questions posed to participants, we counted the number of notebooks returned and noted how many responses were in each notebook. We also considered the number of responses relative to the number of conference participants.
Estimating the total number of GLS attendees to be around 300, we received responses from approximately 16% of the attendees (see Figure 1). If we subtract the 15 solicited responses, then that participation drops to approximately 11%.
Generally we found that when we asked people to answer the question in the notebook, they were very willing to participate. We did, however, ask people who appeared to be relaxing or standing around. Table 1 shows the overall response rate. Actual responses can be found in the Appendix.
#1 Character Class & Why?
#2 Favorite Game & Why?
The fact that, when asked directly, individuals were consistently willing to respond to the questions indicates that there was some degree of willingness to participate in this research project, yet overall we found that people were not willing to pass the notebook along to someone else or to return them to their drop box.
CONCLUSIONS & NEXT STEPS
In conclusion, we found that asking people to take responsibility for a notebook during a conference was unsuccessful, perhaps because it was perceived as interfering with the conference attendee’s reasons for being there. While willing to participate if asked, they were not willing to pass the notebook or return it. It was interesting however, that they were willing to write in it and leave it on a table. There could be other explanations for why the data collection method did not work. Perhaps participants needed better directions. Maybe the notebooks were too plain looking or people needed an incentive to participate.
These speculations led us to ask: How do viral notebooks become a game? What is fun about anonymous interaction? Why would someone participate, or not? Would more playful & intriguing questions make a difference? Perhaps, making the covers more colorful or decorating in them in someway to generate interest would have made the project more successful.
Would this make a good research study on a large scale or for follow up? After looking over the data collected, we concluded that although there maybe ways to make this a more viable project, the reason for collecting the data should be a more integral part of the project. The lesson learned is that personal requests for information are effective in gathering data. Asking people to take responsibility at a conference for passing a notebook is not. We concluded that we made too many assumptions about how our questions would be interpreted and about people’s willingness to participate.
Raw Data (for the lulz)
Q1: Which Character class do you
usually choose and why?
Hi (drawing of hand waving Blood elf They are pretty (smiley face)
Tourist, because the credit card and camera are AWESOME!
Elf- aesthetic appeal, Tolkein fetish!
Night Elf- Hunter, Hunter & Native relationship
Wizard- Brains before brawn
Disco Bandit (Kingdom of Loathing) Why chosen? Gaining a skill of ambidextrous Funkslinging-- and ranged weapon specialty.
Ranger/Hunter - Killer but nature friendly :)
Heavy, Pyro, Engine- Truly playing a real game.
I usually play a healer. First, if none available I play mage. I like the idea of using your intelligence to attack a problem instead of brute force. I especially like healing, as I feel like the other players will appreciate me.
I usually play Rogue, I like to infiltrate and all the strategy associated to it.
Q2: What is your favorite game & why?
My favorite game is Tex Murphy’s Pandora’s Directive. A very compelling story and way to integrate puzzles in a 3D adventure & a revolutionary hint system. I was hooked.
Legend of Zelda (Original) Great, Simple RPG type game that had a vast world to explore, I pulled some all nighters way back when when it first came out.
Zelda- Twilight Princess Why? because it is on Wii and I love sword fighting with the Wii controller.
Currently my favorite game is Battlestar Galactica Board Game. It has elements of a card/board game while requiring a good “poker face” in order to properly play the Cylon characters.
Rez- It’s pushing the boundaries between visual presentation & audio presentation to the point that what you see & what you do produces a unique musical experience. God of War I, II, & III (soon) b/c its the shit and I like Greek mythology and Kratos Fuckin’ Rock!!
City of Heroes I love the avatar creation + customization. I find it really satisfying to fine-tune the appearance of my characters
I really enjoyed Final Fantasy 9 back in the day. Just the right mix of fantasy & corny elements.
Galaxy Trucker - way random but you think you have some control/skill. Way fun!
God of War- it unleashes my psychopath.
Titanic, Adventure Out of Time b/c the characters were fun and I’m a history fan.
Kingdom of Loathing- It uses Bartles 4 Gaming Types well- very engaging.
Hide & Seek- I like to find what hides/ is hidden
Soccer- I like the physical play, complexity & teamwork.
Okami0 Love the twist an characterization & game goals.
Shadow of the Colosus- Tragedy in a digital game(? difficult to read,)
Civilization Series- Depth, complexity & one-move turn syndrome
I (heart) Green Tentacle
Earthbound for SNES - Psychick Youth ov Amerika!
Laura Bow 2: The Dagger of Amon Ra
I’ve never played a video game
WOW- My last game was Monopoly and WOW’s a whole lot better!
World of Warcraft- the only MMORPG I Play. I like meeting many different people who I would not meet IRL. Real friendships and bonds are formed from the construct of combat and cooperation.
World of Warcraft- large player base, Eve Online Complex, Prince of Persia (The first one) Unique
My favorite game right now is Runescape because I don’t know anyone there, so it feels like an open frontier.
Madden 2009 for Xbox 360
Phantasysta-Globalonia! Backgammon, World of Goo
Sex (in general) (not a videogame) Why- very exciting, good rewards, collaborative, sortoa.not.only.casual, Social, Excellent graphics/sound, immersive, & EDUCATIONAL (+ good for you!)
Kingdom of Loathing - Humor, hidden learning.
Battlestar Galactica The Board Game Intrigue, Poker Face, Strategy, always good to see if the humans will win. May change next month.
I like many games, but NOT drinking games. I take my drinking game seriously, and its a meditative process making it a game misses the point and out Herod’s Herod. Non-participant.
Paper-Scissors- rock: Basis of many games.
Team Fortress 2: Aesthetic Appeal
Civilization Strategy, Engagement, History