On Learner-Game Content Interactions

On Learner-Game Content Interactions

by

Roel Cantada

1. Different types of learners interact differently with games in general, and with different genres of games. 
2. Different games afford learners different learning action due to differences in features and constraints. 

To state it another way, not all learners like playing games either for learning or entertainment. Not all learners like the same type of games. A single game cannot possibly afford all the learning action that will satisfy all learning objectives of a course (meaning predetermined by other than the learner) or the learner. There may be a need to combine different genres of games.

These variations are what I have learned from the educational games literature.  The first focuses on the learner, the second on the afforded learning actions of the game.  The latter insight is grounded on Affordance Theory.

Not All Learners Like to Play Games

Kurt Squire declares “games are not good for all learners” (2004, p. 411). Squire's dissertation provides a rich description of how students interact with a video game that teaches history.  Some of the students actually dropped out of his class because they did not find the game engaging or they found it too hard. Simon Egenfeldt-Nielsen had a similar experience. A group of students gave-up on his course within the first two weeks of the experiment. All these students had little experience with computer games and found the activity irrelevant to their studies (2005, p. 180).

Do learners learn from games?

The answer to this question is mixed and needs to be qualified by “what” they learn from games. If what they have to learn is how to play the game successfully then I think the literature is in agreement that games with the right design can teach a learner to successfully complete a game. In fact it was this perspective that Katrin Becker (2008) used in order to claim that good games embody good pedagogy. She said, “I'm pretending that what needs to be learned in the game is something that we care about and I'm going to identify how that game supports the player/learner so they can learn what they need to.”

Learners learn a lot from games. The question is whether what they are learning is valuable or not. Corollary to this question is “valuable to whom?”  James Paul Gee (2003) called this “the problem of content”. He illustrated this view with a six year old child who can play a rather complex game for hours. The child's grandfather remarked, “While it may be good for his hand-eye coordination, it’s a waste of time, because there isn’t any content he’s learning. (Gee, 2003, p. 20)” Recently, I heard a similar remark on national television from the head of the Philippine Department of Education who was complaining about internet cafes offering games to students, she said that students were wasting their time playing games instead of studying (DepEd , 2010).  In the Philippines, local governments are   forbidding computer games in internet cafes that are within a couple of meters (it varies from ordinance to ordinace; from 50 to 500 meters) from of a school.

I admit that games can teach something good and something bad, but so do printed material, videos, music and everything else we use in school. The problem of content is rooted in the belief that the only valuable thing to study is what is listed in the nationally mandated curriculum for primary and secondary education, or the facts in the established academic disciplines for higher education (Gee, 2003).   Another cause is the belief that learning is an acquisition of facts, embedded in what has been criticized as rote memorization.  This is particularly acute in teaching history wherein students are socialized to expect memorization of dates, names, and places as the primary activity in a history course. Squire (2004) and Egenfeldt-Nielsen (2005) observes this with their participant students who tend to devalue the history they learn from games as being not factual. Squire also noted that the game Civilization III teach many concepts (233 concepts) but fails to provide deep understanding of those concepts (2003). This may be a problem of breadth over depth.  Egenfeldt-Nielsen on the other hand reported that “...the learning outcome of students do not differ in relation to whether computer games are used or not. However, it seems that retention is better when using computer games and students are more intrinsically motivated despite criticism of the actual historical content of the course. (2005, p. 239)” In another subject matter, Richard Blunt (2006) found that the academic achievement of students who use games in class was higher than those who did not use games.  He operationalized academic achievement as test scores in the course. Unfortunately, Blunt's study is ex-post facto and we don't know how the games were actually used by the students.

Becker (2008) seems to shed light on the problem of content when she used the idea of Collateral learning (things that are unintentionally learned) and Things we MUST learn in a game in her Magic Bullet design model of educational games. In relation we may be informed by the findings of Thorkild Hanghøj (2008). Some of his participants separated hard outcome, or pure subject matter content from soft outcome, which in Hanghøj “debate game's” case are discussing and arguing.  One student even said that the end result would be “a very, very stupid class of social studies students who don’t know much about social studies but are enormously good at arguing (2008, p.281)”. On the other hand experts in Wagner’s Delphi panel (2008) appear to be promoting soft-skills as part of the school curriculum.  They believe that “MMORPGs might be able to help students develop various 21st Century skills, as defined by NCREL and the Metiri Group”.  These skills include (Burkhardt, et.al. 2003):

1. Digital-Age Literacy
2. Inventive Thinking
3. Effective Communication
4. High Productivity

The third item in the above list would be considered soft-skills (Soft skills, 2010). The experts are encouraging schools to adopt a new set of skills in the curriculum rather than using games to teach existing subject-matter content.  This “change the school” or “change the game” issue is prevalent in the literature. The issue of how in-game and subject matter content may be interacted will be discussed in its own post later.

How long does it take for learners to learn from games?

Squire (2004) offers us a glimpse of the length of time before students get something relevant from games in his suggested curricular outline for Civilization III. The schedule is as follows:

Days
Game Play

1-3
Facilitate appropriation of game

4-7
Master game basics; go over common “failure points;”

8-11
Fostering purposeful game play & communities of inquiry

12-15
Recursive play and examining Civilization (game) as a simulation

16-18
Finish games


The schedule suggests that it will take seven (7) days before students can play a purposeful game, which I interpret as playing to learn history. One thing video games have in common with web applications and even a Learning Management System is that the learner has to master the game interface and rules before they are able to learn from it.  Since games are more complex than Learning Management Systems, it may even take longer for learners to learn to play a game before being able to learn.  The reader should also note that the length of game play varies among video games.  Some games can be played within minutes; others as in the case of MUVEs and MMOGs never end until the company that maintains them decides to end the game or go bankrupt. The latter are called persistent games (Blunt, 2006; Steinkuehler, 2005; Qian, 2009). I will discuss the problem of lock-step scheduling and the time needed for playing in the post on community-game content interaction.

Types of Players

Richard Bartle (1996) created a taxonomy of player types based on their styles of playing. He mapped four types of players on two axes of a graph. The axes of the graph represent the source of players' interest in a MUD (See Bartle, 1996 for the graph). The x-axis maps whether the players are interested in other players or the world. While the y-axis maps whether they are acting on or interacting with the players or the world.  The four types are the following (Bartle, 1996):

1. Achievers – interested in doing things to the game (acting on the world)
2. Explorers – interested in having the game surprise them (interacting with the world)
3. Socializers – interested in interacting with other players
4. Killers – interested in doing things to other people (acting on other players). This term is associated with games that allow players to fight each other.

The types above can be mapped to Michele Dickey's ways by which learners learn from video games (1999). The first two learn from the world, the last two learn from other people.

Another classification of players is that of Marko Siitonen (2007) who differentiates between casual players and competitive players.  Siitonen's category has more to do with the norms of gamers' community.  It can roughly be mapped to Bartle, as socializers and explorers may be considered casual players, while killers and achievers are competitive players. We can use these types when designing and implementing games for learners, by reminding ourselves that not all learners appreciate competition.

Steinkuehler (2005), using Bartle's taxonomy as a starting point, created different dimensions for axes of the graph which she elicited from MMOG players. She came up with a more complex graph, one example having 13 axes (Steinkuehler, 2005, p. 66). I am not going into detail of Steinkuehler's graph; suffice it to say that she advocates the development of taxonomies of playing styles based on a study of the community of players rather than forcing Bartle's model on the data. One thing that I have noticed  though is that her reproduction of Bartle's graph has the label interveners instead of killers (Steinkuehler, 2005, p. 59). Steinkuehler points out the difference between players who do good things to other people, (like helping other players in quests and giving them game items) and those that are player killers.

I more inclined to adopt Squire's interpretation of Bartle's taxonomy. Squire (2004) focused on the fact that the types of players are differentiated by their goals. He thinks that “motivation is better conceptualized as a series of goals”. Furthermore he observed how students changed their goals (and therefore their playing style) as they play the game. He came to the conclusion that “students who appropriated the game as a tool for learning history, repurposed the tool and changed the goal of the game”.

It appears to me that Squire focuses on the intentionality of the learner in game play when he speaks of motivation.  The literature appears to have consensus on the commonly known capability of games to motivate players.  I will now turn to this aspect of the interaction between learners and game content.

Motivation

The dictionary definition of motivation is “the act or process of motivating; the condition of being motivated; or a motivating force, stimulus, or influence (Merriam-Webster Online Dictionary, 2010).” It is synonymous with drive and incentive. The literature on motivation does not seem to be arguing over what behaviour is motivated behaviour. The argument which is relevant to game design is whether the cause of that motivated behaviour resides in the agent (drive) or the environment (incentive) (Motivation in Wikipedia, 2010). The terms used for this division is intrinsic and extrinsic motivation respectively. Intrinsic motivation in relation to learning is motivation that is in the act of learning itself, without any need for external rewards. Its opposite is extrinsic motivation, where learning is done because of the expectation of external rewards (Malone & Lepper, 1987). Those who focus on motives that reside in the agent (intrinsic motivation) may be further divided between mind and body. Those who attribute motivation to drives like hunger and sex focus on the body, and those who attribute motivation to for example curiosity, honour, (Reiss, 2005) goals, and dislike of cognitive disequilibrium (Müller, Carpendale, & Smith, 2009, p.126) focus on the mind. The last—cognitive disequilibrium is a Piagetian concept that refers to discontinuities prompted by a disparity between what is believed to be true and what is actually true (Van Eck, 2006). Richard Van Eck citing Elliot Avedon and Brian Sutton-Smith said that “game playing is a voluntary exercise of controlling a system (i.e., the game) intended for a state of disequilibrium. In other words, game players continuously try out new methodologies and strategies during the game-playing process based on the system’s feedback until they achieve the game objectives or the equilibrium state (Van Eck, 2009, p. 1144)”.

Let me give a brief example of the motivation of players.  I have a six year old nephew just like the child in Gee's (2003) example mentioned above, who plays Lego StarWars (Lego Star Wars: The Complete Saga, 2010). He can play for hours and knows all the options, buttons, and menus needed to play the game. No one taught him how to play this video game. And this six year old child can't even read his score beyond three figures. I am amazed at the dexterity he displays with the controls but disappointed that the game is not teaching him how to read.  But then again this game is not designed to teach six year olds how to read. One time I was baby-sitting my nephew while he was playing a difficult level where you shoot a couple of red circles that is supposed to be part of a ship and every time he failed (which brings him back to his last position) he would jump up, cry and say over and over in Tagalog, “Why doesn't it work?”. After that tantrum he would sit back again with tears in his eyes and try again. He repeated this probably more than ten times. I remember when I was trying to teach this child how to read and he'd give up after the first mistake, but with games he appears to be displaying what Seymour Papert dubbed hard fun (Papert, 2002). Students find games fun because it’s hard.  They are engaged and motivated by it even though it challenges them to the brink of frustration (Wagner, 2008).

But not all games are motivating to all learners. A designer of educational games is interested in what makes video games fun, motivating, and engaging. He/she is interested in harnessing this power of games for teaching and learning. The designer needs to identify specific features of a game that will elicit particular motivations.  Difficulty is not the only feature of a game that makes it fun.

Among the theories of motivation two stands out in the literature, Thomas Malone and Mark Lepper's Taxonomy of Motivations (1987) and Mihaly Csikszentmihalyi's Flow Theory (1990).

Malone and Lepper constructed a taxonomy of intrinsic motivations that they hope “can be used in designing intrinsically interesting learning environments, not just in explaining why or predicting that some environments will be more interesting than others (1987, p. 224)”. Malone and Lepper's taxonomy or an earlier version had been cited by five (Becker; Egenfeldt-Nielsen; Squire; Vandeventer; Watson) of the dissertations on educational games that I have read. On the other hand flow theory had been cited by seven dissertations (Becker; Egenfeldt-Nielsen; Jamison; Squire; Steinkuehler; Wagner; Watson).

Below are the first two levels of Malone and Lepper's taxonomy (1987, pp. 248-249):

 1.Individual Motivations
   a) Challenge
   b) Curiosity
   c) Control
   d) Fantasy
 2.Interpersonal Motivations
   a) Cooperation
   b) Competition
   c) Recognition (See Malone and Lepper, 1987 for their Heuristics for Designing Intrinsically Motivating Instructional Environments checklist.)

Flow's characteristics or what Csikszentmihalyi dubbed as the elements of enjoyment are the following:

1. The experience usually occurs when we confront tasks we have a chance of completing. 
2. We must be able to concentrate on what we are doing. 
3. The concentration is usually possible because the task undertaken has clear goals 
4. The concentration is usually possible because the task undertaken provides immediate feedback. 
5. One acts with a deep but effortless involvement that removes from awareness the worries and frustrations of everyday life. 
6. Enjoyable experiences allow people to exercise a sense of control over their actions. 
7. Concern for the self disappears, yet paradoxically the sense of self emerges stronger after the flow experience is over.
8. The sense of the duration of time is altered; hours pass by in minutes, and minutes can stretch out to seem like hours. (Csikszentmihalyi, 1990, p. 49)

Csikszentmihalyi further states that “the combination of all these elements causes a sense of deep enjoyment that is so rewarding people feel that expending a great deal of energy is worthwhile simply to be able to feel it (1990).”  Video games had been observed to induce this flow experience, and even lead to addiction.

Interpretation of flow theory emphasizes the need for matching available skills and the task challenges (De Freitas, 2009 p.56-57). Malone and Lepper had subsumed this theory under their category of challenge. They said “activities that are trivially easy or impossibly difficult will be of little intrinsic interest. Activities that provide some intermediate level of difficulty and challenge will stimulate the greatest intrinsic motivation (Malone & Lepper, 1987).”

Matthew Peter Jacob Habgood in his study "The effective integration of digital games and learning content (2007)" studied the effect of integrating learning content in a game to intrinsic motivation among primary school children aged 7-9 years old. The single-player game used was Zombie Division. It was used to teach division in mathematics. Habgood questions the value of fantasy in Malone and Lepper's taxonomy and prefers game mechanics to explain intrinsic motivation. He also used flow theory in his study. His guidelines for creating intrinsic integration and extrinsic learning content are worth mentioning.

Habgood's theoretical guidelines for creating intrinsic integration in video games are the following:

1. Deliver learning material through the parts of the game that are the most fun to play, riding on the back of the flow experience produced by the game, and not interrupting or diminishing its impact. 
2. Embody the learning material within the structure of the gaming world and the player’s interactions with it, providing an external representation of the learning content explored through the game’s core mechanics. (Habgood, 2007, p. 43)

While his guidelines for creating extrinsic learning content in video games are:

1. Keep the learning material separate from the parts of the game that are the most fun to play, avoiding the distraction of the flow experience produced by the game. 
2. Separate the learning material from the structure of the gaming world, providing a direct mapping of the learning content that must be completed in order to proceed with the game play. (Habgood, 2007, pp. 43-44)

Using learning content as the independent variable Habgood studied its effect on motivation, deep learning, reflection and transfer. He said that there are two ways to measure motivation. One is through self-reporting and the other is time-on-task. But he also considered there is more to intrinsic motivation than increasing time-on-task (see also Gentile, 2009; Charlton & Danforth, in press; albeit in relation to pathological behaviour). He found that intrinsically integrating learning content in a game is motivationally and educationally more effective than the extrinsic equivalent.  He also suggests the possibility of using video games for assessment aside from teaching/learning.

I am sceptical about the generalization of Habgood's study to college students in a distance education environment. I disagree with his devaluation of fantasy. He believes that as long as the game mechanics are the same the fantasy elements can be arbitrary and would not have much effect on the learning process. Thus he said he would have gotten the same effect had he substituted futuristic weapons for archaic weapons in his game. I don't think this would apply if he was teaching history. I can just imagine the confusion that will be brought about by teaching World War II using futuristic weapons like laser swords. Nonetheless, Habgood's study of motivation is a good starting point and his tabular breakdown of the design features of his game, as well as his well documented steps will be a good reference point for my project.

Issues about motivation

Intrinsic motivation had been emphasized by the educational games literature over extrinsic motivation. But Steven Reiss is critical of the concept of intrinsic motivation. One of his arguments is that the dyad intrinsic-extrinsic does not capture the multifaceted nature of motivation (Reiss, 2005). He also argues against the emphasis on enjoyment or pleasure (Reiss, 2004). He said that enjoyment is an effect rather than a cause. He proposes 16 basic desires or motives to explain motivated behaviour. The 16 desires are the following:

1. Power – desire to influence
2. Curiosity – desire to be autonomous
3. Status – desire for social standing
4. Social contact – desire for peer companionship
5. Vengeance – desire to get even
6. Honour -desire to obey a traditional moral code
7. Idealism – desire to improve society
8. Physical exercise – desire to exercise muscles
9. Romance – desire for sex
10. Family – desire to raise own children
11. Order – desire to organize
12. Eating - desire to eat
13. Acceptance – desire for approval
14. Tranquillity – desire to avoid anxiety, fear
15. Saving – desire to collect, value of frugality (Reiss, 2004)

I have yet to see a research on video games that apply Reiss' theory, but it seems to elaborate Malone and Lepper's fantasy category. For example the popularity of the game Tamagochi, where the player takes care of a virtual pet may be explained by a desire to raise your own children. And there is an endless collecting in many adventure games.  I keep wondering why players would endure repetitive task to collect virtual items that only differ in colour or shape.
I feel though that Reiss had severed the individual from his environment.  His theory focuses on the agent rather than the agent's interaction with the environment.

Another issue with the power of video games to motivate people that parents are concerned with is the so-called “video game addiction”.  Scary stories like the death of a South Korean for excessively playing an online game (S Korean dies after games session, 2005) are picked up internationally despite being isolated cases, and without full investigation of other circumstances affecting the deceased.

After reading the relevant literature I found the term “internet addiction” is misleading. Internet addiction is not listed in the Diagnostic and Statistical Manual of Mental Disorders (DSM IV) (AMA Council on Science and Public Health, 2007). In the literature it is not associated with substance abuse addiction, but rather with impulse-control disorders particularly pathological gambling (Charlton & Danforth, in press; Gentile, 2009).

The inclusion of the term was proposed to be included in the next version of the DSM, but was rejected by the American Medical Association (AMA Council on Science and Public Health, 2007).
A report by the AMA’s Council on Science and Public Health used the term “video game overuse” instead. The report did recognize potential detrimental health effects of videogame overuse like light-induced epileptic seizures and short-term increase in aggressive behaviour. But it called for further research.

A problem with accurately diagnosing “video game overuse” is a question of what symptoms to be included. The use of pathological gambling diagnosis has been shown by John Charlton and Ian Danforth (in press) to misdiagnose highly engaged video game players as being addicted. They identified six criteria associated with pathological gambling. The criteria are defined as follows: “salience – domination of a person's life by the activity; euphoria – a buzz or a high is derived from the activity; tolerance – the activity has to be undertaken to a progressively greater extent to achieve the same buzz; withdrawal symptoms – cessation of the activity leads to the occurrence of unpleasant emotions or physical effects; conflict – the activity leads to conflict with others or self-conflict; relapse and reinstatement – resumption of the activity with the same vigour subsequent to attempts to abstain (Charlton & Danforth, in press).” They found that the criteria cognitive salience, tolerance and euphoria are poor indicators of overuse. Overuse may be diagnosed with the criteria conflict, withdrawal symptoms, relapse and reinstatement, and behavioural salience. In other words pathological game use is not all about excessive play or high engagement (Gentile, 2009).

This discussion is important in that it should remind educators who use video games to do two things. Filter out learners who will potentially overuse games in a course that uses educational games by being explicit with warnings and using diagnostic tests. And/or provide counselling support and debriefing during and after the use of games in teaching and learning.

Neuroscience research appears to me to have had found physiological evidence for intrinsic motivation while playing video games and learning. Koepp et.al. (1998) found out that specific parts of the human brain releases dopamine while playing video games. They suggest that dopaminergic neurotransmission may be involved in learning, reinforcement of behaviour, attention, and sensorimotor integration. Dopamine is a chemical that naturally occur in the human body and has been associated with feelings of pleasure (Dopamine in Wikipedia, 2010). Dopamine increase is also known to be involved in substance abuse addiction but the processes are different from the natural release while playing video games and learning.

Simply put, the idea is that an increase in dopamine in the brain motivates learners, unchanged dopamine release does not.  In a study of monkeys, Jeffrey Hollerman and Wolfram Schultz found that dopamine increases in the brain when there is an error in the temporal prediction of reward during learning (1998; see also Schultz, 2000). My reading of their report is that the neurons that are responsible for releasing the dopamine are keeping track of this prediction error. They said that these neurons are “activated by rewards, and because they are activated more strongly by unpredicted than by predicted rewards they may play a role in learning. (Hollerman & Schultz, 1998)” Furthermore they suggest that “many behaviours are affected by rewards, undergoing long-term changes when rewards are different than predicted but remaining unchanged when rewards occur exactly as predicted . (Hollerman & Schultz, 1998)”

The findings above seems to contradict Reiss' argument against hedonistic (pleasure seeking) interpretations of motivation. On the other hand it supports the ideas of Malone and Lepper (1987) about challenge and curiosity. They said that the certainty of achieving or not achieving a goal is not a challenge. In addition they stated that some models of motivation specify that motivation will be maximal when uncertainty is maximal i.e., when the probability of success is exactly one half (McClelland, Atkinson, Clark, & Lowell as cited in Malone & Lepper, 1987). They listed four techniques to make computer games unpredictable:

1. Variable difficulty levels 
2. Multiple levels of goals 
3. Hidden information
4. Randomness (Malone & Lepper, 1987, p. 232)

Nevertheless, I feel that dopamine increases cannot explain everything about motivation. After all a study found that different dopamine releasing neurons react differently to the same stimuli among monkeys (Matsumoto, 2009). In relation, Csikszentmihalyi (1990) does not only emphasize enjoyment but also discuss the outcome of flow, that is, complexity. He said:

Following a flow experience, the organization of the self is more complex than it had been before. It is by becoming increasingly complex that the self might be said to grow. Complexity is the result of two broad psychological processes: differentiation and integration. Differentiation implies a movement toward uniqueness, toward separating oneself from others. Integration refers to its opposite: a union with other people, with ideas and entities beyond the self. A complex self is one that succeeds in combining these opposite tendencies (Csikszentmihalyi, p. 41).

Neuroscience has a lot to offer in support of and against educational theories.  But we should be careful in using its findings as we may be reading more than what neuroscientists are willing to say (Weisberg, Keil, Goodstein, Rawson, & Gray, 2008). I guess the best approach is to think of the neuroscience findings as metaphors in educational research, pending unequivocal assertions about neurons and learning from neuroscience. Neural networks is one of the metaphors in the learning theory supported in this blog--Connectivism.

Another issue regarding motivation to be considered is that raised by Michael Young (2001). He questions the existence of motivation as a variable. He suggests that motivation may be an epiphenomenon. An epiphenomenon is “the result of presuming such a variable exists and asking people to rate how much of it they have (Young, 2001).” It is a secondary phenomenon that is a by-product of another phenomenon (Zheng, 2005). Young reinterpreted motivation “as an on-going momentary personal assessment of the match between the adopted goals for this occasion and the affordances of the environment.” To him then the primary phenomena that explain motivated behaviour or action are goals and affordances. We keep coming back to affordance theory which I discussed in another post in this blog.

What is important with Young's interpretation of motivation is his belief that learners can change their goals during the learning process.  They could adopt new goals, generate new goals, or modify existing ones.  Malone and Lepper (1987) recognize the dynamism of goal setting with the idea of “emergent goals” under their category “challenge”. They defined “emergent goals” (also Csikszentmihalyi, 1990, p.56) are goals that people can easily generate for themselves. They warn though that people may generate goals that are too difficult for their level of ability. This could lead to frustration and giving up.

The task then of instructional designers according to Young is to develop “contexts that induce students to adopt goals that will be afforded by the learning contexts they design”. But at the same time “instructional designers should not be surprised when the actions students take in a designed learning context appear unanticipated from the perspectives of the original designers” (Young, 2001). This takes us full circle to Squire's observation of students changing their goals as they play (2004). In fact players may create a whole new game from an existing game that was never the intention of the designers. This is called meta-gaming (Squire, 2004; Steinkuehler, 2005, p.114; Wagner, 2008).

According to Wagner, a metagame is a “broad term usually used to define any strategy, action or method used in a game that transcends a prescribed rules set, uses external factors to affect the game, or goes beyond the supposed limits or environment set by the game (2008, p. 9).”

Transferability to Distance Education

The focus of this subsection is the interactions between learners and games. The literature shows that learners learn from games. They are motivated by games to learn. But not all learners will be motivated to learn from games. Among those who will learn from games there are different types of players with different learning goals and motivation. There may be problems with what learners are willing to learn from games, but there may also be a solution through integration of learning content in games. Using games in education will result in longer time schedules due to the overhead of learning to play the game, so there is a need to determine the cost and benefit of additional time and effort invested in the game as oppose to what will be learned. Problems of overuse need to be addressed through counselling support and debriefing.

Despite the fact that these studies were conducted on face-to-face learning, I think their findings are general enough to apply to distance education. I have also learned useful concepts, techniques, and instruments that can be used in modelling students for my project. Modelling students is necessary because design and development is very long and in formal schooling we are unable to assess students before the start of classes.  So a designer can only anticipate learner-player characteristics in designing games. I have also affirmed the necessity of using more than a single genre of games in teaching in order to be able to provide a rich assortment of features to address the variation in student types and motivation.

Before proceeding let me point out that the adoption and use of video games in education has barriers (Klopfer, Osterweil, & Salen, 2009; Egenfeldt-Nielsen, 2005, p.181), the same goes for distance education that uses other web tools. Noriko Hara and Rob Kling identified sources of students' distress with a web-based distance education course (2000). Two sources of frustration that stood out are technological problems that are exacerbated by the lack of technical support; and lack of prompt feedback and ambiguous instructions from the teacher. The first may be worst for games as games typically require more powerful computers to work properly. The provision of demonstration games for preview and testing of equipment and internet connection should be implemented before enrolling students in a distance education course that use games as primary approach to teaching. The second lies with the teacher and will be discussed in the next post. Unfortunately, as Habgood have said about how teachers use games in the classroom, “...educational computer games have been traditionally used by classroom teachers as a ‘hands-free’ mode of teaching: an individual reward for completing work, or simply just a way of keeping a class occupied while attending to other priorities (2007, p.246).” In the next post I will be discussing the role of teachers in the use of educational games in the classroom.

References

AMA Council on Science and Public Health. (2007, June). Emotional and behavioral effects of video game and Internet overuse. Retrieved June 23, 2010, from http://www.ama-assn.org/ama1/pub/upload/mm/443/csaph12a07-fulltext.pdf.

Bartle, R. (1996, April). Hearts, clubs, diamonds, spades: Players who suit MUDS. Retrieved February 13, 2010, from http://www.mud.co.uk/richard/hcds.htm.

Becker, K. (2008, January). The invention of good games: Understanding learning design in commercial video games. Unpublished doctoral dissertation, University of Calgary, Alberta, Canada. Retrieved May 19, 2010, from http://www.minkhollow.ca/becker/papers/becker_thesis.pdf.

Blunt, R.D. (2006, August). A causal-comparative exploration of the relationship between game-based learning and academic achievement: Teaching management with video games. Unpublished doctoral dissertation, Walden University, Minnesota, USA . Retrieved, March 23, 2010, from http://www.rickblunt.com/phd/blunt_richard_dissertation_final.pdf.

Burkhardt, G., et.al. (2003). enGauge 21st century skills: Literacy in the digital age. Illinois, & California, USA: North Central Regional Educational Laboratory and the Metiri Group. Retrieved May 9, 2010, from http://pict.sdsu.edu/engauge21st.pdf.

Charlton, J.P., & Danforth, I.D.W. (in press). Distinguishing addiction and high engagement in the context of online game playing. Computers in Human Behavior.

Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: HarperCollins.

De Freitas, S. (2009). Massively multiplayer online role-play games for learning. In R.E. Ferdig (Ed.),  Handbook of research on effective electronic gaming in education (pp. 51-66). Hershey: Information Science Reference.

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