Using a cyclic model of knowledge transfer for the development of transdisciplinary learning environments Klavdiya Bochenina, Irina Boukhanovskaya, Anna Bilyatdinova, Alexey Dukhanov, Anna Lutsenko Department of High Performance Computing ITMO University St. Petersburg, Russian Federation k.bochenina@gmail.com , ilbuh@mail.ru , a.bilyatdinova@gmail.com , dukhanov@niuitmo.ru , anna.lutsenko@gmail.com Abstract— The requirements for a knowledge economy raised new challenges for higher engineering education. Modern learning processes are characterized by the continuous growth of both diversity and the amount of data that should be understood by the student. Taking into account the rapid obsolescence of information, the focus of knowledge-intensive educational activities shifts toward the formation of competencies for life-long learning. In this paper we propose a methodological basis for the development of computer-aided transdisciplinary learning environments to induce a student’s intrinsic motivation for education and research. A cyclic model of knowledge transfer is invariant for all subjects of the joint scientific and educational processes and can be implemented in academic centers of excellence to acquire and create knowledge through the partnership of students, teachers, and researchers. Furthermore we describe our experience with the deployment of a transdisciplinary environment based on the knowledge transfer cycle in the annual scientific course ‘Technologies of High Performance Computing and Computer Simulation’ (ITMO University, Russia). Keywords— knowledge transfer; knowledge management; learning environments; transdisciplinary education I. INTRODUCTION A global transition from a post-industrial economy to a knowledge economy raised new challenges in the area of higher engineering education. A knowledge worker (as the main human resource of the novel economic model) produces ideas and information instead of goods and services. Modern social and economic processes are characterized by an intensification of information flows and their rapid obsolescence. As a result, the competitive value of an engineering expert is defined not only by technical skills, but also by the abilities to find, understand, use, transform and create new sources of knowledge. These competencies ultimately determine the place a specialist will take in the global “skills race”[1]. Therefore, the traditional role of an educational establishment – propagation of codified knowledge – is supplemented by a variety of functions in order to teach the student how to obtain, assimilate, and systematize information in a field of interest. Furthermore, alumni will become members of global professional communities generating new knowledge from existing data in order to effectively participate in the processes of a network economy. Modern universities are centers of excellence in gaining knowledge, so they can be considered as a place to create novel trends, not only in education, but also in knowledge management. The formation of learning environment should be carried out while taking into account the answers to the following general questions. Q1. What are the foundational properties of knowledge societies? Q2. What key competencies should be achieved in order to become a competitive specialist in a knowledge society? Q3. How can we describe modern students as educands? In other words, all engineering specialists are involved in the continuous, lifelong process of the improvement of professional skills. A life-long learning environment (a combination of educational institutions, professional, and informal networks) is a part of the knowledge society, so it inherits most of the fundamental properties (Q1). Educators can use this inner similarity to organize such conditions so that students can perform the important transition from passive perception of scientific facts to conscious self-development within subject field. The purposeful formation of a learning environment becomes possible only if its creators have gained a clear understanding of preferred qualities (or, more specifically, competencies) for a trainee (Q2). An additional point is that the student is a part of an informal knowledge society. Due to this, the student has his or her own patterns of information recognition, mostly formed before admission to a university; so we should take into account the educable property as an intelligent agent (Q3). In this work, we propose an approach to the development of transdisciplinary learning environments based on a cyclic model of knowledge transfer. The latter concept was formulated during the analysis of typical information processes, which take place in knowledge-intensive systems. We have attempted to consider the stages of these processes and to determine key roles and motivation factors for the participants of the cycle. We also describe the principles of the development of integrated learning environments on the basis This work was financially supported by the Government of the Russian Federation, Grant 074-U01.