IMPLEMENTATION OF ADAPTIVE LEARNING: METHODS AND TECHNOLOGIES

The research activities in the field of adaptive learning have began in the late 1990s [1, 2. p. 12] in TUSUR Laboratory of Instrumental Modelling and Learning Systems (LIMLS). However, its results were not widely implemented in the educational process due to the insufficient development of e-learning technologies. Further development of the ideas for adaptive learning in TUSUR was outlined in 2011 in the paper [3. 322]. Since then, the LIMLS continues the research of adaptive learning, resulting in a number of publications [4-10]. In this article, authors describe the approaches used in TUSUR for the implementation of the electronic adaptive course in the Computer Science discipline. The existing services of adaptive learning ([11-15], etc.) have not received a noticeable spread in the Russian market for various reasons. In general, it can be stated that in terms of university education, there are no such technical solutions that would allow integrating into the information and technical infrastructure of the university and implement adaptive learning along with the traditional one. The aim of TUSUR is to create a platform that will allow Russian universities to create and implement adaptive e-learning courses. One of the tasks within this line of development is the creation and testing of an adaptive course for the Computer Science discipline according to the proposed in [7. P. 117] methods and approaches. Practical implementation is represented by two basic stages. I. Methodical design and development of content The decomposition of general professional competence was conducted in the FreeMind program [16]. It resulted in a tree of 222 sub-competences. Modules have been designed to provide for these sub-competences. The result was formalized in text documents. II. Software implementation of the algorithm and add-ons for the distance learning system The article presents the results of the program implementation of the adaptive learning algorithm and presents examples of the client application: the start screen offers students to choose from certain modules, clicking on which proceeds to the training content (video or text). When the training is completed, students must pass a test. The system records the values of the sub-competence levels and calculates the forgetting curves in order to subsequently make decisions on the change of the learning path. Conclusion Studies of software implementation have shown that the time taken by the algorithm depends on the total number of modules and the number of sub-competences available in the course, as well as on the degree of variability of modules. The implemented system raises the requirements for the university computing resources, and without the profound modernization of the computer network, the introduction of this technology is hindered.

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