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All Journal Proceedings Series of Educational Studies International Journal of Advances in Artificial Intelligence and Machine Learning
Ergashevna, Burieva Kibrio
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Computer Science & IT Education

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FORMATION OF PROTECTIVE MECHANISMS IN THE PERSONALITY OF A TEENAGER Omonovich, Khimmataliev Dustnazar; Ergashevna, Burieva Kibrio
Proceedings Series of Educational Studies 2024: The 3rd International Conference on Educational Management and Technology (ICEMT) 2024
Publisher : Universitas Negeri Malang

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Abstract

The purpose of this study is the formation of protective mechanisms in the personality in adolescence. In this study, an observation method was used - with the help of this method, the daily educational activities of students were systematically monitored, and the information collected was recorded in a special diary as well as psychological tests: the methodology for determining the protective mechanism of personality (developed by the cheat),а questionnaire to determine the nature of subjective local control (developed by S.R.Panteleev, V.V.Stolin), determination of the nature of personality aggressiveness by the Bass-Darky method. This study was conducted to obtain accurate data, the data collected on the basis of the studied literature and the results of the conducted research contributed to the identification of protective mechanisms in the personality of a teenager. Also, the generalization and systematization of sources obtained from experimental work on personal protection mechanisms contributes to the improvement of the younger generation, who are brought up in educational institutions, as a necessary member of society. Based on this, teenagers can be effective tools in solving various problematic situations, the ability to rationally get out of them. The findings can be widely used in their work by practical psychologists, parents and employees of an educational institution. the relationship between the two variables. The results showed that the occurrence of aggressive states in adolescence may be associated with emotional states in them. Because if we look at the situation based on the psychological characteristics of adolescence, this period is the most dynamic in personal maturation, saturated with emotions and determined by the power of aggression. Therefore, it is necessary to form emotional management skills in the personality of a teenager. And this, in turn, will help to avoid various aggressive situations that arise in the personality of a teenager. Keywords: the personality in adolescence, protective mechanisms, the formation, problematic situations
Development of a WebXR-Based Collaborative LMS System with 3D Virtual Features and Artificial Intelligence Padmasari, Ayung Candra; Azizan, Ahamad Tarmizi; Ergashevna, Burieva Kibrio
International Journal of Advances in Artificial Intelligence and Machine Learning Vol. 2 No. 2 (2025): International Journal of Advances in Artificial Intelligence and Machine Learni
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijaaiml.v2i2.448

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Background of Study: The advancement of immersive technology and artificial intelligence (AI) offers new opportunities for creating more adaptive and interactive learning systems. However, higher education institutions still face challenges such as limited industry-standard facilities and the high cost of multimedia equipment.Aims and Scope of Paper: This study aims to develop a prototype of a WebXR-based Collaborative Learning Management System (LMS) equipped with 3D virtual features and AI integration to enhance student learning experiences.Methods: The research employed the Multimedia Development Life Cycle (MDLC) method, which consists of six stages: conceptualization, design, material collection, assembly, testing, and distribution. The study involved 30 Multimedia Education students from Universitas Pendidikan Indonesia selected through purposive sampling.Result: Feasibility testing using a Likert-scale questionnaire revealed that the system achieved a highly feasible category with average scores of 81,7 % for Learnability 85,6 %, for system performance 76,93%, for Efficiency 79,9%, for memorability 74,2%, satisfaction 85,4 %. Resulting in an overall feasibility of 81.7%. Semi-structured interviews confirmed that AI integration significantly supported learning personalization and provided content recommendations, although the AI feature was limited to text-based responses.Conclusion: The results indicate that combining WebXR and AI in an LMS can address the challenges of industry-based learning by providing immersive, adaptive, and accessible learning experiences. This system demonstrates strong potential as a future-ready digital learning solution, with future research suggested to evaluate its impact on learning outcomes and improve AI capabilities for deeper contextual interaction.
Co-Authors Ayung Candra Padmasari Azizan, Ahamad Tarmizi Omonovich, Khimmataliev Dustnazar