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misconceptions.
Analyzing the results of the student id 6 presented
in the previous section it can be verified that
no ‘vicious-cycle’ could be detected nor repeated
occurrences or permanence in the Q2 or Q3
quadrants. Therefore, specific actions of the
educational software would not be necessary or
advisable for the students used as example.
Tutorial intervention strategies also could be
based on the results of ModHEmo. These intervention
strategies should not be applied to students who are
interested or focused on the activity, even if some
mistakes occurs. Furthermore, for students with
constant signs of frustration or annoyance (quadrants
Q2 and Q3) educational software could try strategies
such as a challenged or a game trying to alleviate the
effects of these negative states .
It is important to note that the construction of
this proposal was focused on the educational field,
but it is supposed that this approach, with some
adaptations, could be applied in other areas like
games, for example.
As a continuation of this work we intend to
improve the accuracy rate by tuning ModHEmo
parameters and implement and test others fusion
techniques. It is also intended to evaluate the results
obtained when teachers or specialists (psychologists)
perform the data labeling task.
Future works could be developed with the aim
of expanding the information contained in the
physical and cognitive components. Information like
head movements or fixation of the eyes in certain
components of the screen could be included in the
physical component. In the cognitive component
information such as interaction patterns with the
interface or previous knowledge of the student could
be considered.
ACKNOWLEDGMENT
The authors thank the Instituto Federal de Educac¸
˜
ao,
Ci
ˆ
encia e Tecnologia do RS - IFRS and the
Universidade Federal do Paran
´
a - UFPR for financial
support for this work.
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