This paper presents a model of an intelligent computer network that provides real-time evaluation of students' performance by incorporating intelligence into the application layer protocol. Specially designed drills allow students to independently solve a number of problems based on current lecture material; students are switched to the most appropriate assignment level (regular, advanced, or simplified) based on computer evaluation of performance. The state of each network is defined as a function of a student's performance during the course of the drill. The analysis of a state of the nodes in real-time permits algorithmic reconfiguration of the network resources. As a consequence of this reconfiguration, the instructor will monitor only those students who are behind the schedule. This, in turn, allows the instructor to concentrate on the analysis of the students' problems and the ability to provide real-time help rather than attempting to identify those students who are experiencing difficulty. Figures present the matrix of student performance, graphs of a students' performance and overall class performance, and the algorithm of real-time performance analysis. (AEF)