ỨNG DỤNG TRÍ TUỆ NHÂN TẠO TRONG ĐÀO TẠO TRỰC TUYẾN TẠI CÁC TRƯỜNG ĐẠI HỌC NGOÀI CÔNG LẬP Ở VIỆT NAM: THỰC TRẠNG, THÁCH THỨC VÀ GIẢI PHÁP CHIẾN LƯỢC

This article investigates the perspectives of Romanian academics on implementing Artificial Intelligence (AI) in Higher Education (HE). The article analyzes the pros and cons of AI in HE, based on the views of eighteen academics from five Romanian universities. There is a large and heated debate about the proliferation of AI in many domains, with strong supporters and determined deniers. Studies that research the implications of AI enrich the evidence-based literature on the advantages, disadvantages, threats, or opportunities that AI creates for us, for businesses, or for societies. Though many aspects are still less well known, attitudes toward AI are still under construction. HE is a domain where the implications of AI create passionate discussions. HE is, eventually, the sector that shapes the masterminds of societies’ leaders. There is a quest to find the perspectives of those who will apply AI, who will work with or for AI, and those who are opposed to or in favor of implementing AI in HE. The conclusions revealed by this study are in line with similar studies that exist in the literature. The positive aspects of AI implementation in HE are related, in the view of academics, to gains in the learning–teaching process, improvements in students skills and competences, better inclusion, and greater efficiency in administrative costs. Similarly, the negative aspects revealed by the research are linked to psychosocial effects, data security, ethical aspects, and unemployment threats. However, there are some aspects (mostly negative) related to implementing AI in HE that are less exposed by the interviewed academics, which are mostly related to the costs and efforts of implementing AI in HE. The possible explanation of this situation is related to the lack of strategic vision on what, in fact, the implementation of AI in HE means, what this process involves, and the fact that digitalization in Romanian universities (as well as in the Romanian economy) is in its infancy. The contribution of the results of this research is mainly empirical and practical. These opinions should be used as resources for managers of HE institutions to develop better policies concerning the implementation of AI in HE and for strategic vision toward AI, with the ultimate purpose of achieving progress and prosperity for the entire society.

The introduction and implementation of Artificial Intelligence (AI) in higher education has brought out new opportunities and obstacles. The utilization of AI will result in a significant transformation of the governance structure within global higher educational institutions. The potential use of AI involves exploring the educational implications of how teachers may enhance their teaching methods, how students can improve their learning experience, and how institutions of higher education can make more accurate and timely judgments. This is significant because the workload has significantly increased as a result of the widespread expansion of higher education. Given the circumstances, AI assistance is crucial. The implementation of artificial intelligence in higher education is a significant matter in this context. The objective of this study is to investigate the feasibility of individuals adopting it. To do this, we have formulated hypotheses and a conceptual framework, which we then validated through a survey by obtaining feedback from a total of 240 respondents. Research has discovered that the model can assist authorities in promoting the implementation of artificial intelligence in higher education. The outcome of this study will help practitioners understand the insights of people’s intentions and psychology in adopting AI in educational sectors.

Purpose This study aims to analyze the most frequently discussed topics in the scientific discourse on artificial intelligence (AI) in higher education using Natural Language Processing (NLP) techniques. Design/methodology/approach This paper analyzes 52 peer-reviewed articles published between 2017 and 2024, utilizing NLP techniques to identify prevalent unigrams, bigrams and trigrams related to AI in higher education. Findings The analysis identifies an emerging concern with utilizing AI tools to enhance educational processes, with “Higher education,” “artificial intelligence” and “generative AI” becoming ubiquitous terms in use. LLM and ChatGPT represent types of technology that evoke potential for personalized learning and enhanced practice in instruction. Research limitations/implications In review studies, samples with a post-secondary educational background usually restrict generalizability to school environments. Future studies can examine the long-term consequences of AI technology in extended academic environments, longitudinal studies and educational environments. Practical implications The frequency patterns from our analysis offer essential insights for educators and administrators regarding curriculum development and teaching practices. The high occurrence of terms like “artificial intelligence” (1,193 times) and “higher education” (824 times) highlights the need for incorporating AI literacy into curricula. This integration should include guidelines for responsible AI use and training programs for faculty. The frequent mentions of “teaching learning” (226 times) and “AI education” (319 times) highlight important implications for teaching practices. Educational institutions must establish frameworks that blend traditional methods with AI-enhanced strategies, including assessment plans that consider AI tools while upholding academic integrity. Additionally, institutions should prioritize investment in AI infrastructure and support systems. Social implications Our findings highlight important societal implications beyond education. The frequency analysis reveals concerns about educational equity, including disparities in access to AI-enhanced education, digital literacy gaps and economic barriers to adopting AI tools. Addressing these issues is vital to prevent the worsening of social inequalities. Additionally, our results emphasize the need for workforce development. Educational institutions should focus on equipping students with the AI competencies that employers demand and bridging the gap between academic training and industry needs. The policy implications of our findings are equally significant. Our analysis suggests the need for educational policies that address AI integration while establishing clear guidelines for ethical AI use in academic settings. These policies should include standards for AI tool evaluation and implementation to guide institutions' adoption decisions. The economic impact of these developments is also noteworthy, as our results indicate the potential for enhanced workforce preparedness through AI-integrated education, improved educational efficiency through automation and new opportunities for educational technology development. Originality/value This study contributes to the field by providing an overview of prominent trends in AI within higher education, discussing the practical application, future research opportunities, and challenges associated with the responsible and effective use of AI in education.

The purpose of this study was to assess the attitudes and perceptions of instructors toward the use and implication of artificial intelligence (AI) in online higher education spanning bachelor’s through doctorate level classroom instruction. 104 online higher education instructors were recruited through LinkedIn and the Colorado Technical University Teaching & Learning Center to complete a survey. Nonparametric statistical analysis was used to assess close-ended question responses and open-ended question responses were categorized. A significant difference in instructors’ concern for being displaced by AI in the next 2 years compared to the next 5 to 10 years was found at the bachelor’s level (p=0.04846). At the doctorate level, support for the use of AI in higher education was moderately correlated with concerns for being displaced by AI (rho=0.493, p=0.01058). Support for the use of AI in higher education by the instructor was moderately correlated with support for use of AI in the classroom by students (rho= 0.58199, p<0.001). Instructor support for allowing students to use AI in the classroom was not found to be dependent on the perception of the university employer providing instructors with the policies, procedures, and training to appropriately and ethically adapt to AI in the higher education classroom (p=0.7336). However, most participants recommended that the university develop strong policies regarding the use of AI. The findings indicate a positive preference toward the use of AI by both faculty and students, with some significant exceptions. Support and research toward adopting AI in the classroom are recommended.

The application of Artificial Intelligence (AI) in higher education continues to experience rapid development along with the digital transformation in various aspects of life. Universities are required to adapt to technological advances in order to strengthen institutional competitiveness and reputation. This study aims to analyze national education policies in the digital era related to the implementation of AI in universities to build institutional reputation. The methods used are policy analysis and literature study, with the help of Publish or Perish software for searching scientific articles, and VOSviewer for visualization and bibliometric analysis. Results of the study show that national education policy has created a basis for the use of digital technologies such as AI by encouraging adaptive learning, increasing administrative efficiency, and adjusting education services. However, several challenges still hinder the implementation of AI in higher education. To support digital transformation in education, the government, universities, and the industrial sector must work together by creating a supportive ecosystem. Implementation of AI use in higher education can change the paradigm of digital-era education in Indonesia into a more inclusive, responsive, and data-based system.

This paper seeks to address the challenges of underdevelopment bedeviling the African continent in general and Zimbabwe in particular on the integration of Artificial Intelligence (AI) in higher education. Universities in Africa have over the years produced many graduates in Science, Technology, Engineering, and Mathematics (STEM) related learning areas but continue to grapple with underdevelopment both economically and intellectually. Part of the problem has been identified as a lack of quality in the education system that is not able to produce graduates with adequate 21st-century skills for the achievement of the Sustainable Development Goals (SDGs) to fulfil the Global Agenda 2030. Achieving this is possible if Africa moves a step forward and embraces modern technologies like the integration of AI in her education system. A technologically astute graduate would be able to apply their knowledge in achieving the much-needed sustainable economic development. This article highlights how the implementation of AI in higher education can foster a turnaround in Africa’s education systems and lead to industrialisation and innovation. Pivotal aspects of AI like the Turing machine test, cloud computing, big data, and machine learning are explored in an attempt to add value to the current education discourse. This study is situated in the interpretive paradigm, the qualitative approach was employed to gather data using several methods like e-questionnaires (open-ended), document analysis, and review of journals and other academic publications. Purposive sampling of STEM educators from a renowned university in Zimbabwe was undertaken to gather information on the ground and the data was thematically analysed. The article argues that Africa has the potential to be a leader in Industrialization and commerce should the continent fully embrace AI in higher education.

This research aimed to analyze the importance of artificial intelligence and sustainability in higher education according to the literature in the field and to present the relationships of this context with the United Nations Sustainable Development Goals (SDGs). The adopted research strategies included bibliometric analysis using VOSviewer software and literature review, considering the Web of Science scientific database. The bibliometric analysis resulted in the clustering of four groups. The blue cluster highlighted the emergence of interest in studies on AI and sustainability in higher education following the Covid-19 pandemic. The green cluster emphasized the importance of more efficient teaching methods adapted to the demands of higher education, as well as the need to empower teachers to use artificial intelligence in developing students' skills and competencies, emphasizing sustainability. The yellow cluster indicated the presence of artificial intelligence in higher education based on the triad of sustainable education and innovation, aiming to prepare students for future challenges. The red cluster emphasized the impact of artificial intelligence in higher education, focusing on student learning, efficiency, and sustainable performance. Finally, the literature analysis identified the main AI technologies in higher education and their relationship with the United Nations SDGs. The reflections presented here can contribute to expanding discussions on the relationship between artificial intelligence and sustainability in higher education. From a practical standpoint, it can serve as a foundation for university managers aiming to promote the integration of AI into their teaching processes, considering the context of sustainability.

This study explores the integration of Artificial Intelligence (AI) in higher education, with a particular focus on Kosovo’s transitional educational system. It investigates the students’ perceptions, the challenges they encounter, and institutional policies related to the AI use in learning practices. This research employed a mixed-methods design, including both quantitative and qualitative data. The qualitative data were assessed through thematic analysis, while quantitative data were processed using Statistical Method using SPSS. A questionnaire was designed based on SATAI (Student Attitudes Toward Artificial Intelligence) and Student Perspectives on AI in Higher Education: Student Survey, to gain insights into students’ perspectives. A total of 554 students participated from public and private universities in Kosovo. The results indicated a significant positive correlation between AI and positive students’ attitudes ( r = 0.813, p < 0.001)–students who used AI often tended to view it positively and use it more. Conversely, students who lacked AI training and experience reported significant challenges in use. Furthermore, the findings revealed that positive perceptions of institutional policies are associated with increased AI use ( B = 0.13, p < 0.001). However, gender and age differences didn’t have a significant influence on attitudes and the use of AI. The overall results highlight the critical need to construct clear policies, comprehensive and effective training to maximize the benefits of AI in the academic context.

The development of Artificial Intelligence (AI) in higher education has created new opportunities while presenting major challenges. This research aims to explore the impact of AI on higher education, both in terms of benefits and risks that may arise in the future. AI has opened up opportunities to personalize learning experiences, automate administrative processes, and support innovation in curriculum development, potentially improving educational effectiveness. However, there are also concerns regarding the digital divide, data privacy, ethical considerations, and the readiness of educators and institutions to deal with these technological changes. This research uses a literature review approach by analyzing current research on AI implementation in higher education institutions. It also compares case studies from several developed and developing countries to gain a broader picture of the global influence of AI in the education sector. The results show that while AI can have a positive impact in terms of more efficient learning and more effective operations, challenges in terms of equitable access and transparency must be addressed. The novelty of this research lies in the comprehensive analysis of the long-term implications of AI on higher education, as well as the strategies that institutions need to implement to maximize the benefits of AI and minimize the risks. This research makes an important contribution to education stakeholders in understanding the importance of responsible AI adoption to create an inclusive and sustainable educational environment.

The integration of artificial intelligence (AI) in higher education represents a transformative shift in the way teaching and learning are approached, offering unprecedented opportunities to enhance educational outcomes. One significant issue is the potential for bias in AI algorithms, which can perpetuate existing inequalities if not carefully managed. The objective of this study is to explore and evaluate the integration of AI in higher education to enhance teaching and learning processes. The study aims to identify the most effective AI tools and strategies for improving educational outcomes, assess their impact on student engagement and achievement, and provide actionable recommendations for educators and institutions. To effectively assess the integration of AI in higher education, a multifaceted data collection approach is essential. To ensure the successful integration of AI tools in higher education, a structured implementation plan is crucial. Enhancing teaching and learning involves a comprehensive approach that includes meticulous data collection, rigorous data analysis, strategic implementation and continuous improvement. The implementation phase requires thoughtful planning and execution, with a focus on refining AI systems based on feedback and performance metrics to ensure they effectively support educational goals. The findings show that AI integration in education has improved average grades to 88%, increased retention rates to 85%, and achieved 92% in content customisation and implementation using Python software. The future scope for integrating AI in higher education includes developing advanced AI tools that offer personalized and adaptive learning experiences, enhancing predictive analytics for student performance and retention, and fostering innovative pedagogical approaches through AI‐driven insights.

Higher education is currently undergoing significant digital transformation, with artificial intelligence (AI) emerging as a key innovation shaping this change. This research elaborates on the implementation and impact of AI in the context of higher education. The discussion encompasses the influence of AI on the learning process, improvements in administrative efficiency, and shifts in the education paradigm. The research also explores specific AI applications, such as adaptive learning, sentiment analysis, and data management, which substantially enrich student learning experiences and support decision-making in higher education institutions. While the benefits are substantial, the research also highlights challenges and issues that may arise, including privacy concerns, data security, and the integration of technology into academic curricula. In conclusion, the implementation of artificial intelligence in higher education has the potential to be a cornerstone in shaping students who are prepared for the demands of knowledge-based societies and contributing to the development of a more adaptive and innovative education system.

In the rapidly evolving landscape of technology, innovation, and sustainability, integrating Artificial Intelligence (AI) in higher education presents significant opportunities to enhance learning, teaching and assessment, streamline administrative processes, and promote sustainable educational practices. Despite a vast amount of literature on AI in education, comprehensive use cases that can inform effective implementation of AI in higher education remain scarce. This chapter aims to fill this gap by exploring in-depth the AI applications in higher education, addressing key areas of AI integration such as curriculum design and content development, pedagogical strategies and learning environments, evaluation mechanisms and feedback systems, process streamlining and efficiency enhancement, learning analytics, academic research and ideation, and student support and services. As such, this chapter contributes to the broader goal of sustainable development in the context of education thus aligning with the themes of the SMART conference. This research may inform sustainable solutions, policy, and governance mechanisms in the context of AI-driven education.

The article analyses the theoretical foundations of using artificial intelligence (AI) in higher education. It shows that the AI system as a strategic technology provides many benefits for the lives of people and society as a whole and also symbolises a new stage not only in the history of digital technologies but also on a global scale of development of modern civilisation. The article provides an overview of the policies of European and global organisations, including the United Nations Educational, Scientific and Cultural Organisation (UNESCO), the European Union, the Organisation for Economic Cooperation and Development, the European University Association, etc. on the effective use of AI in everyday life and, in particular, in education. Based on the analysis results, the article systematises ethical principles (human-centred values, governance, transparency, accountability, sustainability, proportionality, confidentiality, safety, security, and inclusiveness) that should be applied in using AI. The SWOT analysis helped identify strengths and weaknesses, opportunities and risks of using AI in higher education. The article examines the regulatory framework for the implementation of AI in the Ukrainian educational area and identifies the peculiarities of AI application in the educational process of higher education institutions. It analyses statistical data for identifying the risks and threats of using AI in HEIs under the Open Science, obtained in 2023 by researchers of the Institute of Higher Education of NAES of Ukraine in the all-Ukrainian survey “Open Science in Higher Education Institutions of Ukraine,” more than 1.5 thousand respondents participated. The article also substantiates practical recommendations for developing and implementing AI in higher education at the national, institutional and individual levels.

This study explores the ethical factors that influence teachers in the use of artificial intelligence (AI) in higher education. Employing a mixed methods approach, which includes a Systematic Literature Review (SLR), two focus groups involving IT teachers, a survey, and four interviews, a total of 37 ethical factors were identified through the SLR & focus groups. The ethical factors identified from the literature review and focus groups highlight the nuanced perspectives surrounding the use of AI implementation. The results from the survey and interviews provide an initial step toward further exploration and generalization of the research findings. The findings contribute to a refined understanding of ethical considerations in AI use for teachers, offering valuable insights for higher education stakeholders. The study not only enhances ethical knowledge in AI implementation but also underscores the importance of diverse perspectives in shaping ethical decision-making within the higher education landscape.

The increasing prevalence of Artificial Intelligence (AI) in higher education underscores the necessity to explore its implications on ethical, social, and educational dynamics within the sector. This study aims to comprehensively investigate the impact of AI on higher education in Saudi Arabia, delving into stakeholders’ attitudes, perceptions, and expectations regarding its implementation. The research hones in on key facets of AI in higher education, encompassing its influence on teaching and learning, ethical and social implications, and the anticipated role of AI in the future. Employing a quantitative approach through an online survey questionnaire (N = 1113), this study reveals positive attitudes toward AI in higher education. Stakeholders recognize its potential to enhance teaching and learning, streamline administration, and foster innovation. Emphasis is placed on ethical considerations and guidelines for AI implementation, highlighting the imperative need to address issues such as privacy, security, and bias. Participants envision a future characterized by personalized learning experiences, ethically integrated AI, collaboration, and ongoing support for lifelong learning. Furthermore, the results illuminate the intricate interplay between AI usage, purposes, difficulties, and their impact on attitudes, perceptions, and future implications. Accordingly, the research underscores the necessity for a comprehensive understanding of AI integration, considering not only its technical aspects but also the ethical, social, and educational dimensions. By acknowledging the role of AI uses, AI usage purposes, and addressing associated difficulties, educational stakeholders can work towards harnessing the benefits of AI while ensuring responsible and effective implementation in teaching and learning contexts.