Work

Development of Intelligent Systems to Support Academic Staff in the Teaching Process

Year: 2025

Type: conference-paper

Abstract: This study focuses on the development of intelligent systems designed to support academic staff in the teaching process by improving instructional planning, assessment, and feedback. A mixed-methods approach was employed, encompassing system design, implementation, and pilot testing with university educators. The results revealed gains in efficiency, personalized instructional guidance, and enhanced decision-making capabilities. The findings emphasize the potential of intelligent systems to optimize teaching practices, alleviate administrative workload, and foster data-driven educational strategies, thereby contributing to more effective and adaptive learning environments.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17112936

Authors: Huda, Oksana, Lemesheva, Natalia, Litvina, Zlata

Institutions: Lutsk National Technical University, Ivan Kozhedub Kharkiv National Air Force University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W7081658032

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