Implementing of artificial intelligence in a higher educational ecosystem

Background and Aim of Study: The use of artificial intelligence (AI) by students and teachers in higher education is becoming increasingly common. AI implementing in higher education started as a spontaneous process among all stakeholders. Strategies and models of implementation in higher education systems must now justify this. The aim of the study: to explore the benefits and challenges of using AI in academic university teaching, and to develop and justify a model for the optimal implementation of AI for the development of the higher education ecosystem. Material and Methods: The present study used several theoretical methods: analysis, synthesis, comparison, generalisation, systematisation, and classification to define the benefits and challenges of AI use by stakeholders; systems approach, modelling, and optimisation methods to develop a model for the optimal implementation of AI in a higher educational ecosystem. Results: The prospects of AI implementation for developing the higher education ecosystem are considered. The advantages and problems of using AI in academic university teaching are characterised based on the classification of directions of using AI in higher education. The model of optimal implementation of AI in the educational ecosystem of higher education, based on the systems approach, has been developed and substantiated. This model include structural (universities, faculties, departments, institutes, centres, doctoral schools, clinics, and labs) and functional (internal – content of education, forms and methods of teaching, diagnosing of learning outcomes, administering of educational service, and eternal – include academic achievement: levels of knowledge, skills, and competences) components. Conclusions: The study highlights the importance of implementing AI in higher education, as well as the need for collaboration between all university stakeholders in the digitisation of education. The results are essential for developing university strategies for developing educational ecosystem The curriculum should be relevant, meeting the interests of students and the current needs of employers. Education stakeholders are encouraged to use the available benefits of AI responsibly to address the challenges of student learning and teacher organisation in universities.

Authors

Publication Details

Journal
International Journal of Science Annals
Published
2025-03-07
DOI
https://doi.org/10.26697/ijsa.2025.1.1
Citations
1
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
3.25
Controls
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article

Implementing of artificial intelligence in a higher educational ecosystem

Yuriy Melnyk, I. S. Pypenko
1 citations
International Journal of Science Annals
Engineering Education and Technology
3.25
article

Implementing of artificial intelligence in a higher educational ecosystem

Yuriy Melnyk, I. S. Pypenko
article en
1 citations

Abstract

Background and Aim of Study: The use of artificial intelligence (AI) by students and teachers in higher education is becoming increasingly common. AI implementing in higher education started as a spontaneous process among all stakeholders. Strategies and models of implementation in higher education systems must now justify this. The aim of the study: to explore the benefits and challenges of using AI in academic university teaching, and to develop and justify a model for the optimal implementation of AI for the development of the higher education ecosystem. Material and Methods: The present study used several theoretical methods: analysis, synthesis, comparison, generalisation, systematisation, and classification to define the benefits and challenges of AI use by stakeholders; systems approach, modelling, and optimisation methods to develop a model for the optimal implementation of AI in a higher educational ecosystem. Results: The prospects of AI implementation for developing the higher education ecosystem are considered. The advantages and problems of using AI in academic university teaching are characterised based on the classification of directions of using AI in higher education. The model of optimal implementation of AI in the educational ecosystem of higher education, based on the systems approach, has been developed and substantiated. This model include structural (universities, faculties, departments, institutes, centres, doctoral schools, clinics, and labs) and functional (internal – content of education, forms and methods of teaching, diagnosing of learning outcomes, administering of educational service, and eternal – include academic achievement: levels of knowledge, skills, and competences) components. Conclusions: The study highlights the importance of implementing AI in higher education, as well as the need for collaboration between all university stakeholders in the digitisation of education. The results are essential for developing university strategies for developing educational ecosystem The curriculum should be relevant, meeting the interests of students and the current needs of employers. Education stakeholders are encouraged to use the available benefits of AI responsibly to address the challenges of student learning and teacher organisation in universities.

International Journal of Science AnnalsVol. 8(1)
Openalex Percentile: Top 11%
Engineering Education and Technology
3.25
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