Support for the personalization of master’s studies based on a fuzzy competency model (on the example of data analysis disciplines)

Author:

Gaibova T V

Abstract

Abstract Competence models for evaluating important teaching tools for personalizing educational content. This problem is of particular importance for studying in the master’s program, the teacher of each discipline needs the diversity of the educational trajectories of the master’s students and create an adaptive educational environment for both those who deepen their profiling, continuing their education in the previously chosen direction of training, and for those who have changed the vector of professional development. The aim is to demonstrate a fuzzy model for assessing competence using the example of this organization of training in data analysis. It is developed on the basis of the integration of cognitive modeling and fuzzy logic and is distinguished by the ability to analyze the mutual influence of the concepts of the considered area of knowledge of the target level of learning and is the basis for determining the area of acceptable educational trajectories. The implementation of the proposed model will provide high-quality personalization of semi-structured educational content. The author analyzed the modern skill sets of specialists in the field of data science and analytics, as well as methods and tools for competence assessment in the context of learning adaptation. The requirements for the developed concept of soft learning in the context of personalization of learning in the master’s program are determined, the structure of a fuzzy cognitive map is proposed, which allows one to assess the semi-structured competencies of various groups and determine the priority of mastering the concept of the proposed educational content. The proposed approach will make it possible to systematize the process of identifying permissible educational trajectories at the discipline level, depending on the available knowledge and accumulated professional experience, as well as on the student’s career aspirations, thereby expanding the range of possible educational strategies and increasing the level of organization of the educational process on the part of the teacher and the level of self-organization on the part student.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference31 articles.

1. Competency Measurement Model;Russo,2016

2. The role of artificial intelligence in achieving the Sustainable Development Goals;Vinuesa;Nat Commun,2020

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