Game Based Lifelong Learning - E-Infrastructures and Technologies for Lifelong Learning - page 346

• Patterns for social interaction: these pat-

terns describe the specific properties of a
multiplayer gaming environment.

Boyle. Another point is that the reverse engineer-
ing of existing game-based learning scenarios may
elicit game elements that have already shown to
be of educational use and can then be mapped to
form the appropriate contextualized taxonomy of
game patterns for learning (Becker, 2007).
In our approach we focus on the social interac-
tion patterns, such as competitive patterns and
collaborative patterns.
Example: The “Cooperation pattern”: Play-
ers cooperate, i.e., coordinate their actions and
share resources, in order to reach goals or sub
goals of the game.
To form a game out of this starting pattern,
it is necessary to instantiate into more specific
patterns that state facts about how in detail the
cooperation is conceived. “Alliances”, “Team
Play” and “Shared Rewards” could be possible
sub-patterns.
Example: In juxtaposition of aforementioned
pattern, the “Competition pattern” is of relevance:
Competition is the struggle between players or
against the game system to achieve a certain goal
where the performance of the players can be mea-
sured at least relatively. This pattern for example
is instantiated with the “Enemies” pattern, “Player
Elimination” or “Incompatible Goals” patterns,
only to name a few self-explaining examples.
As pointed out above, an important element
is the reflection of the player's progress or status,
which can be achieved by making use of resource/
score patterns, raising the awareness of success
and failure, especially when it comes to social
comparison.
Finding the right selection of game design
patterns according to the classification mentioned
above (acquisition of information, practice of
skills, collaboration) can be systematized in con-
junction with the pedagogical processes relevant
to the learning scenario, and comparing these
requirements with the description of the game
design patterns in question. For example, the
acquisition of information (a process critical for
learning) can be reflected in-game by the “gain

• Patterns for Goals: these patterns are need-

ed for the end of a game or its subdivisions.
Once a goal is achieved a certain special
event occurs that indicates so.

• Patterns for Goal structures: goals can be

modified during gameplay, which is de-
scribed by these patterns.

• Patterns for Game sessions: these patterns

describe the overall characteristics of play-
er participation in a game.

• Patterns for Game Mastery and Balancing:

these patterns described the abilities and
kills of a player in the game.

• Patterns for Meta Games, Replayability

and Learning Curves: these patterns de-
scribe factors outside the game, such as
possible contextualizations.

As sketched in Figure 1, game design patterns
consist of different structural components. First,
the core of the pattern describes its functionality,
what element of a game it represents, how it is
used and what the consequences are. Also possible
conflicts with other game elements are indicated
lest they appear in the same game together. Relat-
ing to this, a metric of combination rules can be
applied: patterns can be combined by modulation
(one pattern influences the other), and instantiation
(the existence of one pattern leads to the coexis-
tence of another). In theory this construct leads to
“game based” compound learning objects, such
as described by Boyle, (2003), however in a less
concrete form. It is, however, important to stress
that a single game pattern does not suffice to cre-
ate a whole learning game. Therefore it should
be argued that the metrics for combination are of
paramount importance for a sound game design.
The specifics of software design, derived from
a conceptual design, can be extended to fulfill
the requirements for implementation by using a
layered composition of elements as suggested by