A personalized emotional intelligent tutoring system based on AI planning

The Intelligent Tutoring System(ITS) is a computer based learning system which assists students 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 emotional 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 intelligence 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 Quotient) 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 frustration, 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 emotions, to enhance thought. With the consideration of previous factors, we present a novel framework for modeling an independent 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 developed 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.