  The learning process is a process of communication and interaction between
the teacher and his students on one side and between the students and each
others on the other side. Interaction of the teacher with his students has a
great importance in the process of learning and education. The pattern and
style of this interaction is determined by the educational situation, trends
and concerns, and educational characteristics. Classroom interaction has an
importance and a big role in increasing the efficiency of the learning process
and raising the achievement levels of students. Students need to learn skills
and habits of study, especially at the university level. The effectiveness of
learning is affected by several factors that include the prevailing patterns of
interactive behavior in the classroom. These patterns are reflected in the
activities of teacher and learners during the learning process. The
effectiveness of learning is also influenced by the cognitive and non cognitive
characteristics of teacher that help him to succeed, the characteristics of
learners, teaching subject, and the teaching methods. This paper presents a
machine learning algorithm for extracting knowledge from student model. The
proposed algorithm utilizes the inherent characteristic of genetic algorithm
and neural network for extracting comprehensible rules from the student
database. The knowledge is used for discriminating male and female levels in
logical reasoning as a part of an expert system course.
