Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

From classroom to industry

Developing universal competencies and AI integration in engineering education for technological advancements

Bibliographic Data

ID22188198
AuthorsZhadyra Konurbayeva (0000-0002-6457-392X, D. Serikbayev East Kazakhstan State Technical University), Oxana DENISSOVA (0000-0001-7899-500X, D. Serikbayev East Kazakhstan State Technical University), Madina Rakhimberdinova (0000-0001-9009-8686, D. Serikbayev East Kazakhstan State Technical University), Assiya Mashekenova (D. Serikbayev East Kazakhstan State Technical University)
Year2024
Volume8
Issue14
Pages9849
Publication date2024-12-06
Open AccessYes
TypeARTICLE
VenueJournal of Infrastructure Policy and Development (JOURNAL)
Journal identifiersISSN: 2572-7923 • E-ISSN: 2572-7931
PublisherEnPress Publisher (PUBLISHER)
DOI10.24294/jipd9849
OpenAlexW4405123176
LanguageEN

The purpose of this study is to develop strategies for enhancing higher and postgraduate education in Kazakhstan, with a focus on improving graduate readiness for professional roles and building predictive models to analyze and assess doctoral graduation rates in technical fields for 2023–2025. This research emphasizes a flexible framework that integrates universal competencies into engineering programs, adaptable to various institutional and national contexts. Active learning methods, including project-based tasks, problem-solving exercises, internships, and lab work, are employed to cultivate practical skills aligned with real-world engineering demands. The study also highlights the need for comprehensive assessment systems that extend beyond theoretical testing, incorporating continuous feedback and curriculum adjustments to align with labor market needs and scientific developments. Results reveal key areas for higher education reform, as outlined in Kazakhstan’s State Program for Education and Science Development (2020–2025). These include implementing a competency-based approach, optimizing interdisciplinary and practice-oriented teaching methods, and enhancing the global competitiveness of Kazakhstani universities. Additionally, through time-series analysis of doctoral graduation data, a trend model was created, showing a steady increase in graduates, tested for anomalies and trend adequacy, making it reliable for forecasting graduate numbers. The scientific significance of this work lies in its contributions to models that improve graduate training, fostering high-quality education to enhance Kazakhstani universities’ global competitiveness. By integrating AI-driven strategies and emerging technologies, the research provides an adaptive educational model to equip students with essential professional and universal competencies, essential for navigating the evolving labor market and supporting sustainable development

Curriculum · Engineering ethics · Engineering management · Internship · Knowledge management · Medical education · Pedagogy · Professional development · Computer Science · Educational Innovations and Challenges · Engineering · Engineering Education and Technology · Medicine · Psychology

Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae