Methods and Software Tools for Automated Synthesis of Adaptive Learning Trajectory in Intelligent Online Learning Management Systems

This paper presents a new methodology for synthesis of individualized educational trajectory for intelligent online learning management systems in engineering education. It is based on case-based reasoning and self-study methods and production-based model of knowledge representation. Such quality indicators as relevance of synthesized adaptive learning trajectory, integrity of adapted learning material, quality of knowledge assessment, quality of new material absorption, student achievement goal setting, adequacy of the model of forecasting academic achievements, usability of user interface, automation of structuring and importing of educational material, teachers workload, use of equipment, response time, data recoverability, knowledge base integrity, and compatibility were studied. In the paper we present the results of the use of the synthesized individual educational trajectory in the form of quality indicators of students’ educational achievements. In this paper we report the methods for evaluating of the probability of achieving the educational goals based on parameters of the student model and the lesson model.