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Challenge: Goals. Simple games should provide an obvious goal. Usually the more obvious and compelling the goal is, the better. Goals can be made obvious or compelling by the use of visual effects or fantasy. (Malone, 1980). Challenge: Goals.
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Challenge: Goals Simple games should provide an obvious goal. Usually the more obvious and compelling the goal is, the better. Goals can be made obvious or compelling by the use of visual effects or fantasy. (Malone, 1980)
Challenge: Goals A complex environment without built-in goals should be structured so that users will be able to easily generate goals of appropriate difficulty… Unless beginners have some suggested projects of the right difficult level, they might easily pick tasks that are discouragingly difficult. (Malone, 1980)
Challenge: Goals The best goals are often practical or fantasy goals (like reaching the moon in a rocket) rather than simply goals of using a skill (like doing arithmetic problems). (Malone, 1980)
Challenge: Goals The players must be able to tell whether they are getting closer to the goal. (Malone, 1980)
Challenge: Uncertain Outcome • Variable difficulty level: Good computer games should be playable at different difficulty levels. The choice of difficulty level can be either: • determined automatically by the program according to how well the player does • chosen by the player • determined by the opponent's skill. (Malone, 1980)
Challenge: Uncertain Outcome • Multiple level goals: Good computer games often have several different levels of goals. • Score-keeping. With this feature, the metagoal is to get as high (or as low) a score as possible. The score can reflect the number of tries, the number of successes, the difficulty of the successes, the resources expended, etc. • Speeded responses. With this feature, the meta-goal is to do something as fast as possible, or faster than a deadline, or faster than one's opponent. (Malone, 1980)
Challenge: Uncertain Outcome Hidden information: Many games, especially guessing games, make the outcome of a game uncertain by hiding information from the player or players and selectively revealing it. This feature seems to provoke curiosity and well as contributing to the challenge of the game. (Malone, 1980)
Challenge: Uncertain Outcome Randomness: A final way of making the outcome of a game uncertain is to introduce randomness. Many gambling games seem to succeed almost entirely on the basis of this principle, and randomness can be used to heighten interest in many other kinds of games (Malone, 1980)
Challenge: Self esteem Goals and challenges are captivating because they engage a person's self-esteem. (Malone, 1980)
Fantasy Extrinsic fantasies: One relatively easy way to try to increase the fun of learning is to take an existing curriculum and overlay it with a game in which the player" progresses toward some fantasy goal, or avoids some fantasy catastrophe, depending only on whether the player's answers are right or wrong. To a great degree, the fantasies used in this kind of game are interchangeable across subject matters. (Malone, 1980)
Fantasy Intrinsic fantasies: Not only does the fantasy depend on the skill, but the skill also depends on the fantasy. This usually means that problems are presented in terms of the elements of the fantasy world. (Malone, 1980)
Fantasy Emotional aspects of fantasy: Fantasies in computer games almost certainly derive some of their appeal from the emotional needs they help to satisfy the people who play them. One obvious consequence of the importance of emotional aspects of fantasies, is that different people will find different fantasies appealing. (Malone, 1980)
Curiosity Sensory curiosity involves the attention attracting value of changes or patterns in the light, sound, or other sensory stimuli of an environment. (Malone, 1980)
Curiosity Cognitive curiosity can be thought of as a desire to bring better "form" to one's knowledge structures. In particular, I claim that people are motivated to bring to all their cognitive structures three of the characteristics of well-formed scientific theories: completeness, consistency, and parsimony. (Malone, 1980)
Curiosity • Informative feedback: • To engage a learner's curiosity, feedback should be surprising. The "easy" way to do this is by using randomness. A deeper way to do this is to have environments whose underlying consistency is revealed by things that seem surprising at first. • To be educational, feedback should be constructive. In other words, the feedback should not just reveal to learners that their knowledge is incomplete, inconsistent, or unparsimonious, but should help them see how to change their knowledge to become more complete, consistent, or parsimonious. (Malone, 1980)
Constructing things is fun and helps learning. (Plass and Homer, 2009)
Strong Narratives provide sufficient incentive and clear goals to solve hard puzzles/problems. (Plass and Homer, 2009)
Time and resource constraints make games fun and can improve learning. (Plass and Homer, 2009)
FPS do not automatically provide incentives to learn. (Plass and Homer, 2009)
Games can be engaging without stunning visuals. (Plass and Homer, 2009)
Different levels of incentives (e.g., based on player statistics) increase fun and engagement. (Plass and Homer, 2009)
Kids will engage in rote tasks for small incentives when it leads up to larger incentives later. (Plass and Homer, 2009)
Scaffolding can be used to make games adaptive to learners’ specific needs (prior knowledge, abilities, ...) (Plass and Homer, 2009)
Different levels of incentives (e.g., based on player statistics) increase fun and engagement. (Plass and Homer, 2009)
Games can be engaging, even addictive, without being always fun. (Plass and Homer, 2009)
The stronger the intrinsic motivation of the game content the less extrinsic motivation is required to engage players. (Plass and Homer, 2009)
A social component (collaboration, competition) makes games fun/engaging. (Plass and Homer, 2009)
Design educational action games by turning simulations into simulation games. (GTT Team, 2003)
Move from parameters to "power-ups". (GTT Team, 2003)
Design game contexts by identifying contested spaces. (GTT Team, 2003)
Identify opportunities for transgressive play. (GTT Team, 2003)
Using information to solve complex problems in simulated environments. (GTT Team, 2003)
Provide choices and consequences in simulated worlds. (GTT Team, 2003)
Differentiate roles and distribute expertise in multiplayer games. (GTT Team, 2003)
Reduction Make a complex task simpler. (Fogg, 2003)
Tunneling Lead people through predetermined sequence of actions/events step by step. (Fogg, 2003)
Tailoring Provide information relevant to individuals to change their attitudes or behaviours or both. (Fogg, 2003)
Suggestion Suggest a behaviour at the most opportune moment. (Fogg, 2003)
Self-monitoring Allow people to monitor themselves to modify their attitudes or behaviours to achieve a predetermined goal or outcome. (Fogg, 2003)
Surveillance Allow one party to observe another to modify behaviour in specific way. (Fogg, 2003)
Conditioning Use principles of operant conditioning to change behaviours. (Fogg, 2003)
"Psychosocial Moratorium" Principle Learners can take risks in a space where real-world consequences are lowered. (Gee, 2003)
Committed Learning Principle Learners participate in an extended engagement (lots of effort and practice) as an extension of their real-world identities in relation to a virtual identity to which they feel some commitment and a virtual world that they find compelling. (Gee, 2003)
Identity Principle Learning involves taking on and playing with identities in such a a way that the learner has real choices (in developing the virtual identity) and ample opportunity to meditate on the relationship between new identities and old ones. There is a tripartite play of identities as learners relate, and reflect on, their multiple real-world identities, a virtual identity, and a projective identity. (Gee, 2003)
Self-Knowledge Principle The virtual world is constructed in such a way that learners learn not only about the domain but also about themselves and their current and potential capacities. (Gee, 2003)
Amplification of Input Principle For a little input, learners get a lot of output. (Gee, 2003)
Achievement Principle For learners of all levels of skill there are intrinsic rewards from the beginning, customized to each learner's level, effort, and growing mastery and signaling the learner's ongoing achievements. (Gee, 2003)
Practice Principle Learners get lots and lots of practice in a context where the practice is not boring (i.e. in a virtual world that is compelling to learners on their own terms and where the learners experience ongoing success). They spend lots of time on task. (Gee, 2003)
Ongoing Learning Principle The distinction between the learner and the master is vague, since learners, thanks to the operation of the "regime of competency" principle listed next, must, at higher and higher levels, undo their routinized mastery to adapt to new or changed conditions. There are cycles of new learning, automatization, undoing automatization, and new re-organized automatization. (Gee, 2003)
"Regime of Competence" Principle The learner gets ample opportunity to operate within, but at the outer edge of, his or her resources, so that at those points things are felt as challenging but not "Undoable”. (Gee, 2003)