Reflection for the 15th week.

Reading list:
1. Koster, R. (2004). A theory of fun for game design: What games aren't. Gamasutra, December 3.
2. Gee, J. P. (2004). Learning by design: Games as learning machines. Gamasutra, March, 24
3. Garneau, P-A. (2001). Fourteen Forms of Fun. Gamasutra, October 12.
4. Prensky, M. (2001). Fun, Play and Games: What Makes Games Engaging. Chapter 5 in Digital Game Based Learning. NY: McGraw Hill. (From the author's website)
5. Falstein, N. (2004). Natural funativity. Gamasutra, November 10.

Summaries:
Koster, R. (2004).

Kowster 's article is not colorful as the other pieces. He focused on a limited model of game: superficial graphical pattern vs. abstract logic underneath. In his discussion, fun is an important element of games. But he did not really develop fun and game in a harmonious pattern to help readers understand his points. To Koster, fun is an abstract that is hard to be defined, and fun is a phenomenon. He kind of discussed that fun is contextual. It will happen when several elements get in the right place: right time, attitude, engagement, etc. He also discussed that fun is a result of evolutionary process. However, his ideas about fun were spreaded widely but only circling around the periphery of the issue. What is fun is not clear in the first place in the article. I think this is actually the bottom line of this article without which it is hard to understand the author's stand.

Gee, J. P. (2004).

It is a fact that many individuals keep purchasing new video games. this article was trying to understand the question how do good game designers manage to get new players to learn long, complex, and difficult games? On one hand, some good games seem to be designed only for adept gamers. This is an explanation only helps us see a certain part of all gamers, old and new. On the other hand, the answer could be good games' designers applied profoundly good methods of getting people to learn and to enjoy learning. The author argued that under the right conditions, learning is biologically motivating and pleasurable for humans. Then, the author applied a list of good principles of learning that have been built into good games (computer and video) to explain, with examples of real video games, the practice of learning in games. In the end, the author discussed his observation that very few educational games apply the principles of learning. On the contrary, non-educational games for the young are using many good principles. This debate is worth to be extended to the administrators and researchers.

Garneau, P-A. (2001).

The goal of this article is to make a complete list of entertaining activities, forms of fun, at present in order to provide a tool kit for game designers. Garneau suggested that effective game design is the result of mixed forms. But combination of too many of these forms may do the opposite. It is a matter of balance. I tried to classify these fourteen forms of fun using the categories proposed by Falstein. Physical fun: Physical Activity, Competition, Application of an Ability, Immersion; Social fun: Love, Social Interaction, Comedy(?), Power; Mental fun/psychological fun: Immersion, Intellectual Problem Solving, Thrill of Danger, Creation, Advancement and Completion, Beauty, Discovery, Competition. There are a couple of forms classified repeatedly into different categories.

• Beauty: That which pleases the senses
• Immersion: Going into an environment different from one's usual environment by physical means or by use of one's imagination
• Intellectual Problem Solving: Finding solutions to problematic situations that require thought
• Competition: An activity where the goal is to show one's superiority
• Social Interaction: Doing things with other human beings
• Comedy: Things that make one want to laugh
• Thrill of Danger: Exhilaration coming from a dangerous activity
• Physical Activity: Activities requiring intense physical movements
• Love: Strong affection toward somebody
• Creation: To make exist that which didn't
• Power: Capacity of having a strong effect, of acting with strength
• Discovery: Finding something that wasn't known before
• Advancement and Completion: Going forward in, and eventually finishing, an activity
• Application of an Ability: Using one's physical abilities in a difficult setting

Prensky, M. (2001).

Like Garneau, Prensky also developed a list of elements that make video games engaging.

• Games are a form of fun. That gives us enjoyment and pleasure.
• Games are form of play. That gives us intense and passionate involvement.
• Games have rules. That gives us structure.
• Games have goals. That gives us motivation.
• Games are interactive. That gives us doing.
• Games are adaptive. That gives us flow.
• Games have outcomes and feedback. That gives us learning.
• Games have win states. That gives us ego gratification.
• Games have conflict/competition/challenge/opposition. That gives us adrenaline.
• Games have problem solving. That sparks our creativity.
• Games have interaction. That gives us social groups.
• Games have representation and story. That gives us emotion.

In addition to this list he pushed further to relate the observation with learning and work. Like most of the articles for this week, Prensky focused on fun and play. He defined fun as the great motivator. The role of fun in the learning process is to create relaxation and motivation. Relaxation enables a learner to take things in more easily, and motivation enables them to put forth effort without resentment. He argued play as the universal teacher. Work and play are always overlapping with each other. Learning (children): similar to Falstein, Prensky applied the evolutionary view in understanding play. "Play is our brain's favorite way of learning things". Work (adult): more play will improve our learning and performance; making work playful reduces stress, and actually increases productivity.

How to transfer the abstract fun and play into actual experience through digital games is the central focus of this article. Prensky proposed six structural elements of games based on which the games can be engaging. Rules: are what differentiate games from other kinds of play; Goals or Objectives: differentiate games from other types of play, as well as from other non-goal-oriented games; Outcomes and Feedback: are how you measure your progress against the goals; Conflict/competition/challenge/opposition: are the problems in a game you are trying to solve; Interaction: interaction of the player and the computer vs interaction with other people (inherently social aspect). Representation: means the game is about something.

For the rest of this chapter, Prensky touched on wide topics on digital games comprehensively. He discussed different forms of interactivities (toys, narrative stories, and tools), talked about categories of games (Action Games, Adventure Games, Fighting Games, Puzzle games, Role Playing Games, Simulation Games, Sports Games Strategy), listed principles of good computer game designs (balance, creation, focus, character, tension, and energy). Then he discussed aspects that are affecting engagement of digital games (the rationale for this part is still to help designers for good game design): culture, age, gender, violence, language (or genre?).

Falstein, N. (2004).

Palstein saw the question of what makes a game fun as an elusive and subjective one. To answer this question, Falstein took an approach finding the underlying root of humans' fun. He tracked back to ancient time and even earlier to find evidence from human revolution. His point is that all human entertainment, including games, has a central premise of learning about survival and reproduction and the necessary associated social rules and behaviors. This learning is a life-long activity for humans, especially in the "modern fast-changing global culture". He classified humans’ fun into four categories (physical, social, mental, and blended). "By tying game play to these key aspects of hunting, gathering, exploration, social interaction and status, and pattern perception we can capture the interest of large numbers of players and make games more fun". Falstein tied his discussion with applying the fun theory, natural funactivity, into game concepts. Basically, I find this approach of understanding both gamers’ behaviors and game design reasonable and easy to master.

Focus question:
What are the possible reason(s) why more people do not play digital games?

It is necessary to see what kinds of people play games. To talk about gamers, there are people who are addictive to games, including the game fans and people who have video games as the most important entertainment in their life. There are also people who just occasionally play some games just for killing time. As we read and discussed, people play video games for fun. The video games are attractive and challenging. For those online games, gamers may also play for socializing, but not necessary. The population who play games has certain common characteristics. Here I try a couple of them. I do not have evidence to support my argument. My points are developed from my observation. So it might be biased, in which case more discussion might be generated. One characteristic is the majority people in the gamers' population are in young age: children, teenagers, and college students. The other characteristics is that they can afford to play: time (they have plenty of time) and money (sometimes money is not that important since there are many cheap or free games).

However, the fact is there are more people who do not play video games regularly than those who do. People who do not play games regularly do not possess either of the two characteristics mentioned above. These could count for two reasons. The third one, I think, could be people in this camp actually find that real life activities, sports, party, reading, movie, traveling, etc, are much more entertaining and have more fun than video games which is in-door activity and/or require to sit still for a long time, etc.

My questions from the readings and questions for Discussion in class:
1. From readings we can see professions have been thinking deeply about how to generate good concepts for games and design good games. Is there any case study of research testing those elements or principles in designing educational games? What are some limitations?

2. Is there any statistical information of the distribution of the gamers? What are some common features they share, like age, profession, education background, socio-economic status?

Reflection for the 14th week.

Reading list:
1. Avery, A. (2005). Beyond P-1: Who plays online?. Digital Games Research Association 2005 Conference: Changing views- worlds in play, Vancouver, 16 - 20 June 2005, Vancouver, British Columbia, Canada: Digital Games Research Association.
2. Paras, B., & Bizzocchi, J. (2005). Game, motivation, and effective learning: An integrated model for educational game design. Digital Games Research Association 2005 Conference: Changing views- worlds in play, Vancouver, 16 - 20 June 2005, Vancouver, British Columbia, Canada: Digital Games Research Association.
3. Yee, N. (2007). Motivations of play in online games. CyberPsychology and Behavior, 9, 772-775.

Summaries:
Avery, A. (2005). There is a wide range of phenomena that need to be discovered for the impacts and roles of virtual games in people's life, behavior, and social construct, both offline and online. Alix focused on serious gamers of online games. He wanted to understand what actual elements of video games that people like (I think this is more useful for game developers/designers than educational researchers) and what kind of games people play most. Then people could know what kind of preference gamers hold when they play games and help to predict the games they like or dislike. Because of the way they collected data, the study only reflected people who play games regularly (from two hours per week to 25 hours per week). the findings could also be used to predict the characteristics and preference for players who do not regularly play games. As summarized by Alix, there first four popular archetypes of gamers were Warriors (like to fight in combat and other military themes), Narrators (like to imagine and think), Strategists (like to play with complex strategies and master over game and other players), and Interactors (like to compete and cooperate with other players).

However, as Mike mentioned in the forum, even one possesses many characteristics of a gamer, he or she could still not be a gamer because of many other reasons, such as motivation, attitude toward games, and personal experiences, etc. This fact reflects the limitation of this study. The reasons of the limitation could be the population the research tried to study. Or the limited research method which only depends on self-reflection of individuals.

Paras, B., & Bizzocchi, J. (2005).
Paras and Bizzocchi, on the other hand, took the path of the motivations of gamers and tried to integrate their findings with a model of educational game design. They focused on the flow theory and reflection on learning process. They proposed a sequence to discuss how learning happens via gaming: games, play, flow, motivation, and learning. In this sequence, motivation is the joint of gaming and potential learning. On the other hand, the authors talked about active learning phenomena that could link gaming with learning. Reflection based on active learning is not new and has been well discussed and learned by researchers. However, the essay is soft in discussing the possible explanation of how games could be designed to meet educational purpose. It is good to link flow, motivation, and reflection with gaming experiences. But without solid research on the topic and the model, valuable and valid issue of this model will be remained questionable.

Yee, N. (2007).
Yee's essay also talked about motivation issue in gaming. The essay started from the fact that millions of players are active in MMORPGs daily. Obviously, this is a phenomenon deserving more understanding and modeling. Yee applied factor analysis method developing a motivation model for gamers. A sample of 3000 MMORPGs' players were selected for this study and a forty questions survey was conducted for data collection. Yee classified the motivations into ten subcomponents (Advancement, Mechanics, Competition; Socializing, Relationship, Teamwork; Discovery, Role-playing, Customization, Escapism.) under three main theme: Achievement, Social, and Immersion. Besides, Yee also discovered the demographic variables (age, gender, and usage patterns) and their relationship with motivation. Male players scored significantly higher on Achievement while female scored significantly higher on Relationship. The pattern study also confirmed that the pre-existing depression or mood disorder are common among users who develop problematic usage with online games.

Focus question:
How does your gaming demographic and your reasons for playing fit in with the research?

I think my current experience only deals with participating virtual community, such as forum, but gaming and it does not have any educational purpose embedded. To answer this question, I can only reflect from my former experience with video games. The games I played were offline ones. So there is definitely no "social" motivations related. I see my case could fit in either stereotypes of "warrior" or "strategist" depends on the games I played. Or, if applied the model of Yee, I may fit more in Achievement. For the gaming demographic, my case support Yee's finding that Male players scored significantly higher on Achievement.

My questions from the readings and questions for Discussion in class:
1. In Paras and Bizzocchi's article, they mentioned "Looking at the 'effort' expelled during the learning process will help determine whether learners are motivated." By using "effort", did the authors mean the energy and time the players put into gaming? or something else?
2. Still in the same article, the authors mentioned "While in flow state, the learner is completely motivated to push their skills to the limit." I just wonder is this push-to-limit always happen when individuals experience flow? Is this push-to-limit phenomenon necessary in flow experience?

Reflection for the 13th week.

Reading list:

Rosen, D., Woelfel, J., Krikorian, D., & Barnett, G. A. (2003). Procedures for Analyses of Online Communities. JCMC, 8 (4). Available at http://jcmc.indiana.edu/vol8/issue4/rosen.html

Williams, D. (2006). On and off the 'net: Scales for social capital in an online era. Journal of Computer-Mediated Communication, 11(2), article 11.

Ling, k., Beenen, G., Ludford, P., Wang, X., Change, K., Li, X., Cosley, D. Frakowski, D., Terveen, L., Rashid, A.M., Resnick, P., & Kraut, R. (2005). Using Social Psychology to Motivate Contributions to Online Communities. Journal of Computer Mediated Communication, 10(4).

Summaries:
Rosan, et. al. (2003)
This paper started with a comprehensive review of research methods scholars have been using to study online communities on social aspects and structure of online interaction, spatial movement, nature of users' coordination, impression, and emotions. Rosen et. al. studied the phenomena of online non-threaded interaction, specifically chat-room conversation. The tool they used for the study is Catpac(TM) package. They chose SciCenter, a three-dimension online environment, to carry out their study. the purpose of SciCenter is to provide cyberspace playground for teens to create knowledge space in after-school programs. Data showed that mentor for the conversation dominated the interaction. According to the semantic network analysis, there was obvious gender difference in the content of chatting record. But one thing was shared by both males and females participants: their interest in scientific research seems to increase in three-dimension virtual world.

Williams (2006)
Noticing that the Internet accomodates different way of social interaction with a parallel and conjunct manner with offline life, Williams proposed a framework based on social capital (SC) to measure bridging and bonding for online and offline contexts. The scale he introduced was Internet Social Capital Scale, or ISCS. In this study, Williams treated social capital as outcome. In this article, Williams criticized that the perception and research approach for old media like TV is not applicable to Internet which is interactive and mobile in nature as a communication channel. Williams developed a two-dimension scale pairing bridging & bonding, and online & offline. He used criteria based on Putnam's work (2000) to develop bridging SC measurement. The criteria are: 1) outward looking; 2) contact with a broader range of people; 3) a view of oneself as part of a broader group; 4) diffuse reciprocity with a broader community. Also he discussed criteria used for developing bonding SC measurement as: 1) emotional support; 2) access to scarce or limited resources; 3) ability to mobilize solidarity; 4) out-group antagonism. Here is the list of final scale item (* adapted from Cohen & Hoberman, 1983).

Bonding Subscale

1. There are several people online/offline I trust to help solve my problem.*

2. There is someone online/offline I can turn to for advice about making very important decisions.*

3. There is no one online/offline that I feel comfortable talking to about intimate personal problems. (reversed)*

4. When I feel lonely, there are several people online/offline I can talk to.

5. If I needed an emergency loan of $500, I know someone online/offline I can turn to.*

6. The people I interact with online/offline would put their reputation on the line for me.

7. The people I interact with online/offline would be good job references for me.

8. The people I interact with online/offline would share their last dollar with me.

9. I do not know people online/offline well enough to get them to do anything important. (reversed)

10. The people I interact with online/offline would help me fight an injustice.

Bridging Subscale

1. Interacting with people online/offline makes me interested in things that happen outside of my town.

2. Interacting with people online/offline makes me want to try new things.

3. Interacting with people online/offline makes me interested in what people unlike me are
thinking.

4. Talking with people online/offline makes me curious about other places in the world.

5. Interacting with people online/offline makes me feel like part of a larger community.

6. Interacting with people online/offline makes me feel connected to the bigger picture.

7. Interacting with people online/offline reminds me that everyone in the world is connected.

8. I am willing to spend time to support general online/offline community activities.

9. Interacting with people online/offline gives me new people to talk to.

10. Online/Offline, I come in contact with new people all the time.

Williams proved the validity and reliability of the scales by using a sample of 884 volunteers dominated by white males across the US. Williams discussed that the entry and exit SC cost for all Internet communities is relatively lower than offline ones. This help to partially explain why people turn to online community. At the end Williams proposed some potential problems that ISCS can help to explore, such as Do online groups provide the same kinds of psychological, emotional, and practical support as their real-world counterparts, even without the power of face-to-face interactions? Do Internet users feel the kinds of reciprocal bonds that would lead them to contribute to their online communities?

Putnam, R. D. (2000). Bowling Alone: The Collapse and Revival of American Community. New York: Simon & Schuster.
Cohen, S., & Hoberman, H. M. (1983). Positive events and social supports as buffers of life change stress. Journal of Applied Social Psychology, 13 (2), 99-125.

Ling, et. al. (2005)
Ling et. al. investigated the contribution for online communities using social psychological theories, especially social loafing and goal-setting. I agree with their vision that online activities are part of social phenomena. Social psychology is primarily a behavioral science. Its goal is to determine unambiguously the causes for social phenomena and explain them. I think this article started with a strong rationale to interpret the phenomena of online communities with social psychological lens. This current study was an integration of four field experiments. The hypotheses of the four experiments are:

• People will contribute more to an online community when they think their contributions are likely to be unique and when they like the community more. (supported)

• Users will contribute more when the personal benefit or the benefit they provided to the community is salient as a result of their contribution. (supported)

• Members' contribution will increase more if they receive messages that enhancing the salience of intrinsic motivation compared to members who receive messages that do not enhance the salience of intrinsic motivation. (not supported)

• Members with assigned challenging/specific numeric goals (supported) or individual goals (not supported) will contribute more (rate more movies) compared to members with non-specific goals or group goals.

• members with exceedingly difficult specific goals will contribute less than the ones with difficult specific goals. (weakly supported)
  

Focus Question:

What do you see as *the* most important impediment or problem for online socializing?

My answer could be limited, because I do not have many experiences of online socializing. The answer is more like prediction. Actually, Akesha raised many good points for problems of online socializing (http://msucep956.blogspot.com/). I have one more thought to add to the list.
The most important problem for online socializing could be the lack of authority. I mean there is no structure or social resources to help people to trust the information they get, the individuals they encounter online, or the relationship they have online. As Williams discussed in his article, the cost of social capital to entry or exit the online community is much lower than in offline ones. It is easier for individuals to join online community and get involved on their call. Individuals have bridging experience more than bonding experience in online experiences. I doubt people can really get bonding experience in online community. Even it happens, it should be experience extended from a relationship from offline life. The authority line vanishes in online community. Even though there are administrators in online community for either technology support or community regulation, they have less power affect online socializing. In a community with less orders, socializing could have a ceiling effect because of the lack of trust. I see this is the most important problem for online socializing.

My questions from the readings and questions for Discussion in class:

The readings for this week are fairly new and could represent some trend of research of online community. My question is for researchers of online community, is there a debate for if or not researchers should perceive the online community as part of people's real social life? Another question is related to my discussion of the focus question. Is there any research studying the credibility of online socializing and the trust issues of online communication? If there is, what instrument the research used and theory the researchers applied (social psychology, personal psychology, or communication theory, etc)? What is the finding?