Intelligent Tutoring Systems for Ill-Defined Domains - Philippe ...

John: By telling your mum, do you think this makes you a good son?
Yes
John: What If Gina’s was not your sister; will this make a difference in your decision?
No
John: Do you think by telling your mum you betrayed your sister’s trust?
No
The dialogue continues this way, at the same time the student model is updated after
each answer, but it is not used until the whole dilemma finishes and then it is used by
the pedagogical model to decide the next appropriate dilemma.
The main challenge at this stage is the feedback which is not possible to be in the
form of “your answer is right” and “your answer is wrong”. As we discussed before
the narrative environment offers the chance for the feedback to be tailored within the
context of the story. So the consequences of the student’s interactions with the
teaching moment are implicitly the kind of feedback needed in this educational
domain. The system is able to present the student with one of the possible outcomes
for this dilemma. For example, the above situation will end with the sister Gina upset
with the student and the mother being upset from the daughter and the daughter being
grounded. If the student chooses not to tell their mother, a guilty feeling will
accompany him and/or he may choose to advise the little sister not to repeat such an
action again. Through this experience the student will get the chance to reason more
deeply about those dilemmas and see what outcome satisfies him most. We intend to
extend the student model to include student beliefs that are updated through his
interaction with the system. These beliefs will help to evaluate what the students have
learnt from the activity.
6 Remarks and future work
Interactive Narrative and Intelligent Tutoring 20
In this paper we proposed an adaptive educational interactive narrative system. The
system is mainly a narrative-based system that incorporates intelligent tutoring. The
system is able to monitor the student’s actions and provide personalized teaching and
feedback. The system uses Kohlberg’s moral dilemmas as part of its domain. An
important issue is the agency of the student within the learning environment. We
proposed a technique that offers two types of agencies; a full and complete agency
outside the teaching moments and semi-controlled agency inside the teaching
moments.
As the next step in this research, we plan to evaluate AEINS internally and
externally. The internal evaluation will assess the inner workings of the intelligent
interactive narrative, i.e., it will check that the system is capable of offering a
continuous coherent story with the inclusion of the suitable teaching moments
according to the individual student/player. We intend to do external evaluation in the
near future via a user study with respect to the following two hypotheses: (1) Students
feel that an adaptive story is more engaging than a fixed story. (2) Students gain a