Innovative algorithm optimized for multiple rounds and stateless assigning of tasks non-duplicate for the same subjects

Abstract

Optimization of selection of tasks or questions assigned to different subjects from a larger set of tasks is a problematic topic, often solved not only in schools. The article presents the principles and original algorithmic procedures of the new tool that approaches the solution in a completely innovative way. This tool directs pseudorandom value generators to maximize the efficiency of the tasks that are entered in electronically form. The multiplatform open source implementation of this algorithm can be directly linked to LMS Moodle, it can be used alone or integrated into an own application, for multiple rounds and stateless assigning tasks or questions randomly selected from multiple options so as to avoid premature duplicate selection in different rounds for the same subjects. The principles used in this algorithm and presented in the article may also be an inspiration not only for the implementation of future learning applications but also for further development of the theory of selection functions, whether in this or an entirely different science branch.