An Intelligent Multiagent Tutoring System (IMATS) in Artificial Intelligence (AI) is presented in this paper. The authors describe
ways of improving the quality of teaching AI through the use of agent technology. An interface agent, an authorization agent, an
SQL agent, and a student agent can be integrated into the intelligent learning environment. These agents can guide and assist
students as needed, probe their understanding, and promote learning and retention. They also exploit the natural human tendency
to respond socially to computing systems. Here a brief historical perspective of intelligent learning environments is discussed and
followed by an explanation of the IMATS framework. Next, a detailed description of the intelligent tutoring system, IMATS, is
given. Then the results of usability evaluation, effectiveness evaluation, and satisfaction level evaluation of the software system are
presented. The IMATS framework incorporates an incremental approach to obtain the dynamics of knowledge accumulation in the
domain of interest and the learned knowledge content over time.
關聯:
International Journal of Engineering Education Vol. 27, No. 2 pp. 248-256
如有問題歡迎與系統管理員聯繫 
