Determining emotional intelligence standards by development and implementation of a software system using machine learning (ML) models

Автор: Amirkhanyan D.H., Tshshmarityan M.S., Asriyan E.V., Sargsyan S.G.

Журнал: Сетевое научное издание «Системный анализ в науке и образовании» @journal-sanse

Рубрика: Моделирование и анализ данных

Статья в выпуске: 2, 2025 года.

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During the educational process, students encounter a wide range of academic and non-academic challenges that significantly impact their performance, motivation, and level of engagement. Emotional intelligence (EI) is a crucial psychological resource that fosters the development of stable social connections, successful adaptation, and both professional and personal growth. This study presents a software system based on machine learning algorithms designed to assess students’ levels of emotional intelligence. The assessment is conducted using the validated Nicholas Hall Emotional Intelligence Questionnaire. Based on the results, the system generates personalized exercises aimed at developing EI components and enhancing students' emotional competence.

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Artificial Intelligence, Machine Learning, Emotional Intelligence, Emotional Quotient, Support Vector Machine, Neural Network, Python

Короткий адрес: https://sciup.org/14133176

IDR: 14133176

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