A Personalized Emotional Intelligent Tutoring System Based on AI Planning

258 Pages·2012·3.33 MB·English

A Personalized Emotional Intelligent Tutoring System
Based on AI Planning
Dissertation zur Erlangung des Doktorgrades
Doktor der Naturwissenschaften (Dr. rer. nat.)
der Fakulta¨t fu¨r Ingenieurwissenschaften und Informatik
der Universita¨t Ulm
vorgelegt von
Heba Mohamed Atef Elbeh
aus Menoufyia, A¨ gypten
Institut fu¨r Ku¨nstliche Intelligenz
Fakulta¨t fu¨r Ingenieurwissenschaften und Informatik
Universita¨t Ulm
Institutsleitung
Prof. Dr. Susanne Biundo-Stephan
Ulm, Deutschland
June 2012
Amtierender Dekan der Fakulta¨t fu¨r Ingenieurwissenschaften und Informatik:
Prof. Dr.-Ing. Klaus Dietmayer
Vorsitzender des Promotionsausschusses:
Prof. Dr. Uwe Scho¨ning
Mitglieder des Promotionsausschusses:
Prof. Dr. Michael Weber
Prof. Dr. Wolfgang Minker
Die Gutachter der Dissertation:
Prof. Dr. Susanne Biundo-Stephan
Prof. Dr. Harald Traue
Tag der Promotion: 27 September 2012
A Personalized Emotional Intelligent Tutoring System
Based on AI Planning
A PhD thesis submitted to the Faculty of
Engineering and Computer Science, Ulm University
in fulfillment of the requirements for the degree of
Doktor rerum naturarum (Dr. rer. nat.)
by
Heba Mohamed Atef Elbeh
from Menoufyia, Egypt
Institute of Artificial Intelligence
Faculty of Engineering and Computer Science
Ulm University
Advisor
Prof. Dr. Susanne Biundo-Stephan
Ulm, Germany
June 2012
Dean of the Faculty of Engineering and Computer Science:
Prof. Dr.-Ing. Klaus Dietmayer
Chairman of the doctoral committee:
Prof. Dr. Uwe Scho¨ning
Members of the doctoral committee:
Prof. Dr. Michael Weber
Prof. Dr. Wolfgang Minker
Reviewers of the dissertation:
Prof. Dr. Susanne Biundo-Stephan
Prof. Dr. Harald Traue
Day of Conferral of Doctorate: 27 September 2012
ABSTRACT
The Intelligent Tutoring System(ITS) is a computer based learning system which assists stu-
dents in their learning process. It has the ability to be adaptable according to the needs of students.
In ITS, it is equally important to consider not only the cognitive level of the student but also the e-
motional state of the student. Psychological researches indicate that emotions have a deep influence
on the efficiency of memory storing and retrieving processes. Also, it is important to individualize
the learning process and to teach students according to their personality types. Thus, students with
various personality types differ in their cognitive capabilities, emotional and motivational states,
learning style, appraisal, and coping way with incoming events.
Although several approaches have been constructed for ITS, enhancing students emotional intel-
ligence has not been considered so far. Emotional intelligence (EI) is considered as an important
factor for increasing the student’s performance. The researches show that IQ (intelligence Quo-
tient) contributes only about 20% to success in life, the rest of 80% of success depends on the EQ
(Emotional Quotient). Thus, in our educational systems, we are not taught how to handle frustra-
tion, anxieties, stress, and failure or depression problems during the learning process. EI is defined
as the ability to recognize the meanings of emotion and their relationships, to reason about emo-
tions, to enhance thought.
With the consideration of previous factors, we present a novel framework for modeling an indepen-
dent authoring/course generation system named PANDA.TUTOR. This system allows the author
to prepare the course structure and content enriched with classification information without need
to define the adaptation rules or specify configurations for each student, aiming to keep all the
authoring effort low in terms of time and effort. The course generation system, which is basically
a hierarchical planning system, generates a personal course for the student. The system enriches
with different learning scenarios, teaching strategies and learning styles. The student’s personality
type in our system serves as a guide for selecting an appropriate scenario, a teaching strategy, and
a learning style in order to regulate with current emotional and motivational states of student. For
that purpose, we developed general ontologies for representing student module and course module
that can be used in different domains. These ontologies help the planning system to generate a
personalized course. In addition, in order to enhance the student’s emotional intelligence, we de-
veloped a dialog based HTN planning system. It is shown to improve the emotional intelligence
of the student. This can be done by grasping the student’s appraisal to build up an individual’s
interpretation of how external events relate to the student goal and desires, as well as overcoming
their emotional reasoning. Emotional reasoning is defined as a thinking error that occurs when a
student believes that his/her feeling is true regardless of the evidence, which prevents one looking
at alternative, more balanced information or evidence. Different styles of dialog can be generated
according to the student’s personality type. Moreover, we regard the student’s emotional appraisal
and coping to regulate his/her emotion during the dialog and course generation. Thus, the objective
of our approach is to teach the student during the learning process how to adjust or maintain the
emotion, motivation, and cognitive states. Therefore, the proposed system is able to understand
the student’s emotion and the reason behind this emotion to shape the students’ behavior.
ACKNOWLEDGMENTS
First of all, I would like to express my special appreciation and thanks to my advisor Prof.
Dr. Susanne Biundo-Stephan, you have been a tremendous mentor for me. I would like to thank
you for your continuous support and for all your invaluable guidance that makes this period of
study enjoyable. Regardless of how much and what she had to do, she was always available for
discussion and support, and a never dwindling source of ideas and suggestions.
Beside my supervisor, I would like to thank the rest of my defense committee for their guidance.
Special thanks to Dr. Bernd Schattenberg for his valuable support.
I am grateful for the fruitful discussions with our friends in the Artificial Intelligence department,
whose blessings and wishes have helped me come this far.
Words cannot express the profoundness of my gratitude to my husband Dr. Mohamed Elkawkagy,
my son Yousuf and my daughter Salma. Thank you for your support and patience during the whole
time of my thesis. Without them, I wouldn’t be standing here.
My sincere thanks go to my parents, sisters, for supporting me in everything, and especially I can’t
thank you enough for encouraging me throughout this experience.
Finally I thank my God, for letting me through all the difficulties. I have experienced Your guidance
day by day. You are the one who let me finish my degree. Thank you, Allah.
Ulm, Germany, 2012
Heba Elbeh
DEDICATION
To my parents, my husband and my kids (Yousuf and Salma).