Using soft computing methods for the functional benchmarking of an intelligent workplace in an educational establishment

Abstract

The article describes a method developed for assessing the functional proximity of an intelligent workplace (IWP) of a student with the best available examples based on a fuzzy multiple attribute decision-making method. The developed method is aimed at evaluating the success of the learning process and consists in aggregating individual indicators of the reviewed functions. The proposed method demonstrates the possibility of adapting the standard integral score method used to estimate the IWP to fuzzy initial data, thus providing a number of major advantages. In particular, the proposed method allows us to change the entire complex of the studied functions and their parameters depending on the study goals and objectives without substantially reworking the model. Besides, we can adjust the weights of parameters to match the sectoral and territorial specificity of the university or to comply with the expert assessments; bring together quantitative and qualitative estimates of the IWP indicators with the corresponding estimates of several intelligent learning tools selected as templates.