Timetable Model For Self Regulated Learning Based On Student Agent Level Restrictions Resolving

Individualization of education at the university is key factor of digital transformation. Individualization of training involves considering the personal characteristics of students, providing them with services for choosing educational activities in the educational space of the university. There are technologies for construction of the educational space in now days: intelligent tutors; educational games; collaborative and project learning; personalized and adaptive learning; tools for learning analytics and educational data mining; ontologies for learning skills mining. Timetabling is key services for planning resources such as rooms, teachers, students. Multi-agent approach allows describe independent behavior of actors - student, dispatcher, course owner in self-organizing system of courses planning and selection. The model and services for events markup by the dispatcher and student courses selection and conflict resolving by the student are under review in this paper. The results of testing services at Ural Federal University are presented. The Ural Federal University has more than 36,000 students studying in 480 educational programs. The departments of 13 schools are involved in timetabling process four times in the year. The smart scheduling IT service is used for dispatch loads between 3000 teachers and thousands of rooms.