Pedagogy-Driven Smart Games for Primary School Children% - 2nd International Workshop on Evidence-Based Technology Enhanced Learning - page 39

• The available choices may change from state to state of the game: at the begin-

ning all the choices are available; when the play starts, some choices may be-
come unavailable. The solutions for the game list the choices or their combina-
tion that form a correct solution to the game (correct), and those that do not
(wrong).

The feedback for the game is specialised into a consistency feedback (yes, no),
an explanatory feedback for finding a correct solution (for correct) or for spot-
ting what is wrong in the current solution (for wrong), and a solution feedback
(the correct solution).

•

• The states of the avatar in the gameplay are of two kinds: happiness for the cor-

rect solution, disappointment for the wrong solution. The resolution time is a
constant.

The Smart points are the points a learner with a specific reading comprehension level
can gain in a smart game. These points can be calculated using the IRT [7], so that the
more difficult a game is (assessed to be) for a learner, the more points the learner can
gain in resolving correctly that game. Relaxing games have relaxing points instead of
smart points. Relaxing points should be easy to cumulate, so as to motivate the learn-
er to keep on playing and, in so doing, earning attributes for the avatar.
Now, like points, rules are different for smart games and relaxing games.

• Smart rules , the pedagogical plan establishes requirements for the actions that the

learner can take, the states the system can be in, and constraints on them. In the
following, we sketch the actions, the states and the constraints for smart games:
The plan also recommends diverse types of feedback if the learner makes a
wrong choice: first, a no-consistency feedback for signaling that the solution is
wrong, and then an explanatory feedback are given.
The plan also suggests a solution feedback if the leaner chooses no solution
within the resolution time or the number of wrong solutions overcomes the
wrong attempts limit.
The main states the system can be in are as follows:
(i) the initial state, in which the learner score s and resolution time t are set
to 0, the smart points for the learner are computed as a function of the
learner ability in the game, all the choices are set as available, and the
number of wrong answers is set to 0;
(ii) a terminal state reachable via a correct action, in which a yes-consistency
feedback is given, the score is displayed and the avatar is in the happy status;
(iii) a terminal state reachable via a skip action, in which the solution feed-
back is given, the null score is displayed and the avatar is in the dis-
pleased status;
(iv) a state, reachable via a wrong action, in which a no-consistency feedback
is given, an explanatory feedback is given, the set of available choices is
updated, and the number of wrong answers is updated; and

(v) a terminal state reachable via a wrong action, in which the no-consistency

feedback is given, the solution feedback is given, the null score is dis-
played and the avatar is in the displeased status.