Keywords: clustering, kohonen network, leadership qualities, individualization of learning trajectory, mobile application
Mobile application for leadership development with intelligent individualization of learning trajectory
UDC 004.67
DOI: 10.26102/2310-6018/2024.46.3.028
The article discusses the development of a mobile gaming application for the formation and development of leadership qualities in high school students, college and technical school students. The educational gaming application corresponds to the concept of "innovative educational technology", that is, it includes a set of three interrelated components: modern content, modern teaching methods, modern digital learning infrastructure. The developed mobile application allows you to systematically develop such leadership qualities as self-confidence, responsibility, time management skills, creativity, the ability to act in a situation of uncertainty, and determination. The application logic is based on the principle of forming an individual educational trajectory. To build individual learning trajectories for each user, neural network clustering of questionnaire data is used. That is, when generating individual trajectories for the development of leadership qualities, not only questionnaire methods are used, but also the result of applying clustering methods to a set of questionnaires. Self-organizing Kohonen maps are used for clustering. The resulting division into clusters was analyzed by experts, several clearly defined clusters were identified, for each of which a model of individual change in the trajectory of development of leadership qualities was compiled. As a result of expert analysis of the clustering results, seven clusters were identified. A description of each cluster was compiled jointly with experts.
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Keywords: clustering, kohonen network, leadership qualities, individualization of learning trajectory, mobile application
For citation: Kuzmin A.K., Piminov D.A., Kumova S.V., Kuznetsova K.D., Dubova M.S. Mobile application for leadership development with intelligent individualization of learning trajectory. Modeling, Optimization and Information Technology. 2024;12(3). URL: https://moitvivt.ru/ru/journal/pdf?id=1597 DOI: 10.26102/2310-6018/2024.46.3.028 (In Russ).
Received 28.08.2024
Revised 10.09.2024
Accepted 25.09.2024
Published 30.09.2024