The Student

---

Intelligent tutoring systems are built for students, so the students should be the focus when developing any intelligent tutoring system. When students come to the learning process, they come with many individual differences, such as unique learning styles, different motivational levels, different backgrounds, different levels of expertise, and different expectations. The question is how to develop an intelligent tutoring system that identifies these individual differences and adapts the instruction to meet learners’ individual needs. A well-designed intelligent tutoring system will be able to cater to learners’ individual needs in a distributed environment.

As researchers, we need to build tutoring systems to benefit students and help students learn. Students learn more effectively when they are active in the learning process. Active learning results in a deeper level of processing, which results in better storage in long-term memory (Craik & Lockhart, 1972). Active learning is crucial for affective and psychomotor skills development so that learners can practice and achieve the required levels of performance. Shang, Shi, and Chen (2001) proposed an intelligent distributed environment for active learning, where learners can be involved in reflective learning and dialogue with others. They proposed three strategies that should be included in intelligent systems to promote active learning. These strategies are as follows: expand the learning experience to include dialogue and further processing, provide opportunities for interaction with other students and experts in the field, and allow students to apply what they learn. To provide the content for the learning, the intelligent tutoring system must contain a domain module. The domain module is described in detail in the next section.

---