Digital network learning: cooperation, collaboration and pedagogical innovations

the new terms which have appeared in the field of modern education (including e-learning) are considered in the article. The author uses the method of critical semantic reflection and also the results of both his research work and teaching practice. The comparative analysis of the following concepts − e-learning, cooperative learning, collaborative learning, blended learning and inverse learning − are presented in the article. The issue of the legitimacy of including them in the educational innovations is brought up. Special attention is given to open distance learning in digital networks. The author emphasizes the fact that although today the development of computer providing allows everyone to receive education with the help of digital networks, nevertheless, the e-learning investigations show that successful learning on a one-on-one basis with a computer is a complicated process and not appropriate for everybody. Cooperation and collaboration are viewed as specific forms of interaction and partnership that might be used both in intramural and distance models of learning. The principles of cooperation learning are enumerated. Comparing the nature of radical (crucial, breaking-through) and incremental (gradual, step-by-step) innovations, the author comes to the conclusion that in modern education the innovations able to change principally (revolutionarily) the system of education having been developed in the millennia (the knowledge transfer from a teacher to a learner) are practically non existent. In order to identify the innovation in the process of learning the author proposes to define the features of «standard practice» and create the relevant system of evaluation to test the relative (comparative) advantages of a new educational practice in comparison with the «standard» norm. The article calls for discussion and will be of interest for the researches working in the field of the educational innovation theory and for the specialists engaged in developing the systems of network learning.