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Generative Artificial Intelligence in Higher Education: Challenges, Opportunities and Future Course of Actions to Achieve Sustainable Development Goals

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Title: Generative Artificial Intelligence in Higher Education: Challenges, Opportunities and Future Course of Actions to Achieve Sustainable Development Goals
Language: English
Authors: Nazir Ahmed Jogezai (ORCID 0000-0003-0849-5282), Diana Koroleva (ORCID 0000-0001-5296-8708), Ivan Ivanov (ORCID 0000-0001-5036-8899)
Source: International Journal of Educational Management. 2026 40(1-2):133-157.
Availability: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Peer Reviewed: Y
Page Count: 25
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Foreign Countries, Higher Education, College Faculty, Artificial Intelligence, Computer Attitudes, Goal Orientation, Teacher Attitudes, Reliability, Technological Advancement, Sustainable Development, Technology Integration
Geographic Terms: Russia
DOI: 10.1108/IJEM-12-2024-0786
ISSN: 0951-354X
1758-6518
Abstract: Purpose: This study explores the challenges, opportunities and future course for the use of generative artificial intelligence (GAI) in higher education to attain the targets of the sustainable development goals (SDG4). Design/methodology/approach: A phenomenological approach within the qualitative research tradition was adopted. Data were collected through semi-structured interviews with 11 purposefully selected university faculty members. A hybrid data analysis procedure was employed, combining the application of a GAI model (ChatGPT 3.5) with validation by the researchers. Findings: The findings revealed several challenges and opportunities that may negatively affect higher education institution (HEIs) in attaining SDG4. The study has also identified significant opportunities and has proposed future courses to align GAI with the purposes of education and attain SDG4. Research limitations/implications: Equitable access to GAI-driven education requires collaboration between governments, academia and private enterprises (Target 4.3). Research-based policies must ensure AI enhances learning without undermining critical skills (Target 4.4). Inclusive AI design can improve accessibility for diverse learners while mitigating biases (Target 4.a). Educators should be empowered to integrate AI while maintaining human-centered learning environments (Target 4.c). Finally, ethical AI guidelines are crucial for fostering global citizenship and sustainable development (Target 4.7). This study underscores the need for strategic policy frameworks to maximize AI's potential in education. Originality/value: This study provides original insights into the educational use of GAI, particularly its facilitation and impediments to HEIs' efforts to achieve SDG4. The findings offer valuable contributions to the ongoing discourse on the integration of emerging technologies in higher education and their alignment with global development objectives.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1503078
Database: ERIC
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  Data: Generative Artificial Intelligence in Higher Education: Challenges, Opportunities and Future Course of Actions to Achieve Sustainable Development Goals
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  Data: <searchLink fieldCode="AR" term="%22Nazir+Ahmed+Jogezai%22">Nazir Ahmed Jogezai</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-0849-5282">0000-0003-0849-5282</externalLink>)<br /><searchLink fieldCode="AR" term="%22Diana+Koroleva%22">Diana Koroleva</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5296-8708">0000-0001-5296-8708</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ivan+Ivanov%22">Ivan Ivanov</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5036-8899">0000-0001-5036-8899</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Educational+Management%22"><i>International Journal of Educational Management</i></searchLink>. 2026 40(1-2):133-157.
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  Data: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22College+Faculty%22">College Faculty</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Attitudes%22">Computer Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Goal+Orientation%22">Goal Orientation</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Attitudes%22">Teacher Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Reliability%22">Reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Technological+Advancement%22">Technological Advancement</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainable+Development%22">Sustainable Development</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Integration%22">Technology Integration</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Russia%22">Russia</searchLink>
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  Data: 10.1108/IJEM-12-2024-0786
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  Label: ISSN
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  Data: 0951-354X<br />1758-6518
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: This study explores the challenges, opportunities and future course for the use of generative artificial intelligence (GAI) in higher education to attain the targets of the sustainable development goals (SDG4). Design/methodology/approach: A phenomenological approach within the qualitative research tradition was adopted. Data were collected through semi-structured interviews with 11 purposefully selected university faculty members. A hybrid data analysis procedure was employed, combining the application of a GAI model (ChatGPT 3.5) with validation by the researchers. Findings: The findings revealed several challenges and opportunities that may negatively affect higher education institution (HEIs) in attaining SDG4. The study has also identified significant opportunities and has proposed future courses to align GAI with the purposes of education and attain SDG4. Research limitations/implications: Equitable access to GAI-driven education requires collaboration between governments, academia and private enterprises (Target 4.3). Research-based policies must ensure AI enhances learning without undermining critical skills (Target 4.4). Inclusive AI design can improve accessibility for diverse learners while mitigating biases (Target 4.a). Educators should be empowered to integrate AI while maintaining human-centered learning environments (Target 4.c). Finally, ethical AI guidelines are crucial for fostering global citizenship and sustainable development (Target 4.7). This study underscores the need for strategic policy frameworks to maximize AI's potential in education. Originality/value: This study provides original insights into the educational use of GAI, particularly its facilitation and impediments to HEIs' efforts to achieve SDG4. The findings offer valuable contributions to the ongoing discourse on the integration of emerging technologies in higher education and their alignment with global development objectives.
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  Data: 2026
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