Tutoring Process in Emotionally Intelligent Tutoring Systems: Tutoring Process in Emotionally Intelligent Tutoring Systems

Intelligent Tutoring Systems

ITSs are adaptive computer systems, which are based on the theory of learning and cognition. ITS-based learning process is very similar to the process when a student and a tutor interact in a one-to-one situation, therefore, an effective intelligent tutoring should simulate what good human-tutors do when implementing individualized instruction. The key feature of ITSs is their ability to adapt presentation of teaching material to a particular student by using methods of artificial intelligence (AI) to make pedagogical decisions and to represent information about each student.

Such systems allow implementation of a more natural learning process by adapting a learning environment (content, feedback, navigation, etc.) to characteristics of a particular student. Adaptation is possible because of a student diagnosis module that collects and processes information about the student (his/her learning progress, problem solving behavior, psychological characteristics, learning style, etc.) and of a student model that stores this information. Additionally to the mentioned components, the student diagnosis module and the student model, the ITS architecture includes (Anohina & Intenberga, 2008):

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  A pedagogical module that is responsible for implementation of the tutoring process and a pedagogical model storing tutoring model and strategies;

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  An expert module or problem domain module that is able to generate and solve problems in the problem domain and an expert model storing knowledge what must be taught to the student;

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  A communication module managing interaction among the system and the student through different devices.

The ITS architecture and interaction between system’s components is represented in Figure 1.

Figure 1.

Traditional architecture of intelligent tutoring systems