Despite the attractiveness of massive online courses for learners, only a small part of the latter reaches the finish line. This situation arises due to the effects of different adverse factors on the learning process. Additional staff and “smart” assistants (educational chatbots) are used for reducing the impact of these factors by helping tutors in online learning management. Tutor’s assistants are engaged to perform checking free response works and identifying course problems connected with its content, and educational chatbots to guide students through a course and organize interactions between them. On every launch of the online course, a tutor faces a choice of a group of the most suitable assistants. In the existing research, different assistants’ features such as: scores, motivation, way of communicating, etc. are taken into consideration in this selection. However, in the former, the ability of assistants to properly assess and comment on the performance of free response works are not taken into account. To close the gap, a method of intelligent decision support for forming tutor’s assistant group for checking such works is proposed in the paper. The method was tested on one of the laboratory works on the course “Modeling” and allowed to form a group of assistants capable of assessing the work correctly.
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