Collective Intelligence Algorithms in Pedagogical Practice

The article considers the ideas of using artificial intelligence algorithms in pedagogics. It presents methodology so-called collective pedagogical megasystem. introduction such an ephemeral construct is necessary only to understand system, formulate it a model, find out its operation patterns and laws obeys. would contribute predicting processes phenomena formulating new laws. objective demonstrate application practice for effective didactic decision-making. matter that real educational process, besides well-known set conditions, there are some random unpredictable reasons factors hard foresee or anticipate. Due their stochastic nature, they occur spontaneously. These single make minor impact on teaching methods selection, but aggregate influence gets so strong can upturn prognostic conclusions. problem also focuses identifying ensure highest efficiency productivity studies among known (expected) (unexpected) reasons. For these purposes, most suitable algorithm selection training ant which, one hand, randomness parameters, other, ensures steady high productivity. A certain example was selected process applying reveal best hierarchy conditions (factors) determines optimum choice method. authors conclude human distributed integrated at same time, yield decisions