Artificial Intelligence In Higher Education Research Articles

Attitudes of Instructors Toward the Use and Implications of Artificial Intelligence in Online Higher 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.

Mapping the Frontier: A Bibliometric Analysis of AI in Tertiary Education

This article presents a bibliometric analysis of research on artificial intelligence (AI) applications in higher education over the past decade. Through computer-assisted analysis of 412 documents from the Web of Science core collection, we shed light on publication trends, productivity patterns, and conceptual development. Despite this exponential growth in research output, there remains significant uncertainty about the long-term impact of AI on pedagogical practices, learning outcomes, and the overall structure of higher education systems. The results show an annual production increase of 31.8% in research publications on AI in higher education, signaling scientific recognition of the disruptive potential. The concentration in renowned specialist journals on the topic of technology-supported learning is offset by the distribution of these journals across 206 multidisciplinary sources. With 10 publications, the Chinese University of Hong Kong is the leading contributing institution. China leads in the number of publications on AI in higher education, with 62 articles, followed by the United States with 45 and the United Kingdom with 29. These regional anchors are driving progress in the field. Although there is strong collaboration, the research output remains spread across 1,182 scientists without established leaders, reflecting the diverse and emerging nature of the field. Topic modeling and keyword analysis mean an increasing examination of the connections to education systems, training, labor markets, and learning analyses. This highlights the tensions surrounding data ethics, academic integrity, and the disruption of the workforce as algorithms permeate admissions, advising, and teaching. Our examination of the anatomy of this rapidly growing field provides indispensable perspectives for guiding innovation. As techniques advance from theory to reality, continued empirical research to explore risks and opportunities will be critical to upholding humanistic educational values.

Research trends in the use of artificial intelligence in higher education

The latest technological advancements have greatly interested researchers in artificial intelligence (AI) in education. In parallel, researchers have expressed concern about using and applying AI in education. However, there is a shortage of research that comprehensively and holistically examines trends in the use of AI in higher education. Hence, this study aimed to comprehensively analyze and assess AI research trends in higher education. In the SCOPUS database, we conducted a bibliometric analysis of 1,563 articles on research on AI in education. Our results revealed that the use of AI in education has increased dramatically from 2004 to 2023. In particular, a dramatic increase and peak exist after 2019. We also found limited interaction among scholars studying AI. Furthermore, our findings indicate that most of the most influential institutions are located in developed countries. Moreover, our findings demonstrated that AI research primarily concentrated on comprehending the impact of AI-based instruction, with the majority of these studies taking place in engineering education between 2017 and 2020. We also noticed that research on medical education in higher education occurred between 2015 and 2017. In addition, before 2015, research used AI in medical education as a teaching method to implement problem-based learning in higher education.

Opportunities and challenges in higher education arising from AI: A systematic literature review (2020–2024)

With society’s continuous development and progress, artificial intelligence (AI) technology is increasingly utilized in higher education, garnering increased attention. The current application of AI in higher education impacts teachers’ instructional methods and students’ learning processes. While acknowledging that AI advancements offers numerous advantages and contribute significantly to societal progress, excessive reliance on AI within education may give rise to various issues, students’ over-dependence on AI can have particularly severe consequences. Although many scholars have recently conducted research on artificial intelligence, there is insufficient analysis of the positive and negative effects on higher education. In this paper, researchers examine the existing literature on AI’s impact on higher education to explore the opportunities and challenges presented by this super technology for teaching and learning in higher educational institutions. To address our research questions, we conducted literature searches using two major databases—Scopus and Web of Science—and we selected articles using the PRISMA method. Findings indicate that AI plays a significant role in enhancing student efficiency in academic tasks and homework; However, when considering this issue from an ethical standpoint, it becomes apparent that excessive use of AI hinders the development of learners’ knowledge systems while also impairing their cognitive abilities due to an over-reliance on artificial technology. Therefore, our research provides essential guidance for stakeholders on the wise use of artificial intelligence technology.

An Early Snapshot of Attitudes Toward Generative Artificial Intelligence in Physical Therapy Education

Introduction. Generative artificial intelligence (AI) is rapidly gaining popularity across health care, education, and society. The purpose of this study was to assess perceptions and use of generative AI in academic physical therapy (PT). Review of Literature. Generative AI became one of the fastest-growing technologies ever after the public release of ChatGPT in November 2022. Early data indicate that attitudes toward generative AI in higher education are mixed and rapidly evolving, with significant ethical concerns around use and potential misuse. There are no published studies investigating perceptions and use of generative AI in PT education. Subjects. A total of 175 surveys were completed and analyzed. Respondents included PT educators, administrators, and students. Methods. An anonymous, online survey on use and perception of AI was distributed through email and social media. Descriptive statistics and cross-tabulations were performed to analyze respondent characteristics and responses to survey questions. Results. Most respondents (61.1%) reported they did not use generative AI during the 2022-2023 academic year, whereas 35.4% were generative AI users. More than 40% of respondents were optimistic or very optimistic toward generative AI. Users of AI were more likely to report an optimistic or very optimistic disposition toward AI compared with nonusers. AI users were more likely to agree or completely agree that generative AI has more benefits than drawbacks compared with nonusers. Discussion and Conclusion. Results of this survey suggest that, despite the rapid uptake of generative AI in society, many PT educators and students harbor reservations and uncertainties toward its use. Artificial intelligence users were less likely to hold negative perceptions toward it and were more likely to find it useful. Understanding use and perceptions of generative AI in PT education may inform strategies to promote innovation, policy-making, and ethical integration of this new and rapidly evolving technology.

Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs

Faculty perspectives on the use of artificial intelligence (AI) in higher education are crucial for AI’s meaningful integration into teaching and learning, yet research is scarce. This paper presents a study designed to gain insight into faculty members’ (N = 122) AI self-efficacy and distinct latent profiles, perceived benefits, challenges, use, and professional development needs related to AI. The respondents saw greater equity in education as AI’s greatest benefit, while students and faculty members’ lack of AI literacy was among the greatest challenges, with the majority interested in professional development. Latent class analysis revealed four distinct faculty member profiles: optimistic, critical, critically reflected, and neutral. The optimistic profile moderates the relationship between self-efficacy and usage. The development of adequate support services is suggested for successful and sustainable digital transformation.

The Role of Artificial Intelligence in Higher Education

The integration of Artificial Intelligence (AI) in higher education has sparked a transformative shift in pedagogical methodologies, student engagement, and academic integrity across the UK and Ireland (Dogru, et.al, 2023). This qualitative study delves into the multifaceted implications of utilising AI in academic assignments from the perspective of higher education students, drawing on semi-structured interviews carried out with higher education students. The findings reveal a variety of perceived benefits, including enhanced study efficiency, personalised learning support (Hanaba et al., 2020; Yang, 2021), and the potential of AI to level the academic playing field for students with diverse needs. However, these advantages are in contrast with students’ perceptions of a wide range of significant concerns and challenges, notably the ethical dilemmas surrounding academic honesty, the potential for student dependency on AI leading to diminished knowledge and skill development, as well as the issue of equity in relation to students’ access to AI resources. Moreover, the study stresses a critical gap in institutional guidance regarding AI use, with students voicing a need for clear, consistent guidance from universities. This paper highlights the complex landscape of AI in academia, advocating for a balanced approach that harnesses AI's potential while addressing ethical, educational, and equity challenges. The study emphasises a need for immediate and more in-depth research into the use of AI in higher education from the perspective of both students and university staff in Ireland/UK.

A More-than-Human Ecology: Evolving Generative Artificial Intelligence in Higher Education

A More-than-Human Ecology: Evolving Generative Artificial Intelligence in Higher Education

AI in higher education: unveiling academicians’ perspectives on teaching, research, and ethics in the age of ChatGPT

ABSTRACT This study examines the potentials and challenges of integrating conversational AI (Artificial Intelligence) tools in higher education. Specifically, the study delves into how ChatGPT is reshaping teaching, learning, research, and student evaluation while addressing ethical concerns such as academic integrity. We employ a qualitative research design based on semi-structured interviews with 12 highly accomplished academicians from North America, Asia, and Europe’s higher education institutions. Our analysis reveals ChatGPT’s potential to uplift educational productivity, learning outcomes, creativity, and idea generation but raises apprehensions about academic honesty, authenticity, and over-reliance. While ChatGPT can enhance educational practices such as brainstorming, analysis, and skills acquisition, its unchecked use may impede learning, critical thinking, and research quality. The study advocates for the responsible AI use in academia, underscoring educators and policymakers to establish policies guiding conversational AI ethical applications. Thus, training faculty and executing institutional policies are essential for effective and ethical integration of ChatGPT and other AI tools in higher education. Finally, this research contributes to ongoing research on AI in education by providing valuable insights that can harness potential of these transformative tools while upholding academic integrity and standards.

Strengths, Weaknesses, Opportunities, and Threats Analysis of Integrating ChatGPT Into Nursing Education

Artificial intelligence (AI) is driving global change, and the implementation of generative AI in higher education is inevitable. AI language models such as the chat generative pre-trained transformer (ChatGPT) hold the potential to revolutionize the delivery of nursing education in the future. Nurse educators play a crucial role in preparing nursing students for a future technology-integrated healthcare system. While the technology has limitations and potential biases, the emergence of ChatGPT presents both opportunities and challenges. It is critical for faculty to be familiar with the capabilities and limitations of this model to foster effective, ethical, and responsible utilization of AI technology while preparing students in advance for the dynamic and rapidly advancing landscape of nursing and healthcare. Therefore, this article was written to present a strengths, weaknesses, opportunities, and threats (SWOT) analysis of integrating ChatGPT into nursing education, providing a guide for implementing ChatGPT in nursing education and offering a well-rounded assessment to help nurse educators make informed decisions.

Diverging perceptions of artificial intelligence in higher education: A comparison of student and public assessments on risks and damages of academic performance prediction in Germany

The integration of Artificial Intelligence (AI) into higher education, particularly through Academic Performance Prediction (APP), promises enhanced educational outcomes. However, it simultaneously raises concerns regarding data privacy, potential biases, and broader socio-technical implications. Our study, focusing on Germany–a pivotal player in shaping the European Union's AI policies–seeks to understand prevailing perceptions of APP among students and the general public. Initial findings of a large standardized online survey suggest a divergence in perceptions: While students, in comparison to the general population, do not attribute a higher risk to APP in a general risk assessment, they do perceive higher societal and, in particular, individual damages from APP. Factors influencing these damage perceptions include trust in AI and personal experiences with discrimination. Students further emphasize the importance of preserving their autonomy by placing high value on self-determined data sharing and explaining their individual APP. Recognizing these varied perceptions is crucial for educators, policy-makers, and higher education institutions as they navigate the intricate ethical landscape of AI in education. This understanding can inform strategies that accommodate both the potential benefits and concerns associated with AI-driven educational tools.

Attitudes and Perceptions Towards the Use of Artificial Intelligence in Higher Education: A Survey Study on a Sample of Academic Staff in Algeria

Attitudes and Perceptions Towards the Use of Artificial Intelligence in Higher Education: A Survey Study on a Sample of Academic Staff in Algeria

Applications of Artificial Intelligence in Higher Education: An Exploratory Study of a Sample of Professors from the Faculty of Economic Sciences, Commercial Sciences, and Management Sciences at the University of Médéa

Applications of Artificial Intelligence in Higher Education: An Exploratory Study of a Sample of Professors from the Faculty of Economic Sciences, Commercial Sciences, and Management Sciences at the University of Médéa

Institutional aspects of the use of artificial intelligence in higher education and science: The role and importance of compliance

Institutional aspects of the use of artificial intelligence in higher education and science: The role and importance of compliance

Artificial Intelligence in Higher Education: Enhancing Learning Systems and Transforming Educational Paradigms

This study ventures into the expanding role of artificial intelligence (AI) in higher education and its potential to revolutionize the learning experience. Through a qualitative approach, we investigate how advanced AI-driven educational tools can enhance learning systems through tailored learning experiences, AI-powered adaptive tutoring platforms, immersive digital learning environments, and AI-assisted assessment and feedback systems. From a theoretical perspective, we utilize the constructivist theory of learning as a study framework to explain the role of technology in AI-facilitated personalized and collaborative knowledge construction. This study was executed in three stages. First, we present a brief overview of AI and its recent impact on the education system, including its ethical considerations and implementation hurdles. In the second stage, we propose the potential implications for learning contexts through the constructivist lens, the process of AI-supported cognitive development, and the use of AI tools for optimizing educational processes through AI and transformation in educational paradigms and study work. The findings suggest that institutions can unlock new opportunities for efficiency, accessibility, and personalized learning by adopting AI technology, but they also highlight the need to address ethical considerations and implementation hurdles. This study also contributes to future studies by examining the impact of AI on student outcomes, teacher roles, and institutional practices in education, as well as exploring ethical and equity concerns in AI-driven educational settings.

Gender perceptions of generative AI in higher education

PurposeThis study explored the themes and sentiments of online learners regarding the use of Generative Artificial Intelligence (AI) or “generative AI” technology in higher education.Design/methodology/approachEnglish-language tweets were subjected to topic modelling and sentiment analysis. Three prevalent themes were identified and discussed: curriculum development opportunities, lifelong learning prospects and challenges associated with generative AI use.FindingsThe results also indicated a range of topics and emotions towards generative AI in education, which were predominantly positive but also varied across male and female users.Originality/valueThe findings provide insights for educators, policymakers and researchers on the opportunities and challenges associated with the integration of generative AI in educational settings. This includes the importance of identifying AI-supported learning and teaching practices that align with gender-specific preferences to offer a more inclusive and tailored approach to learning.

Artificial Intelligence in Higher Education: Bridging the Gap for Students with Disabilities

Students with disabilities experience (SWDS) difficulties in learning due to limitations placed on them by their defect. To meet their learning needs distinguishing educational provisions from regular education were introduced into educational system which consist of special teachers and modification of curriculum, instructional procedures, methodology, instructional materials and learning environment contingent on category and magnitude of disabilities. Similarly, given that learning has to be effective; inclusive education in regular educational institutions was introduced. Nevertheless, while those who cannot benefit from inclusive education due to the severity of their handicap; provisions were made to accommodate them in special classes and special schools. These provisions are indeed beneficial to SWDs. However, introduction of Artificial Intelligence (AI) in tertiary institutions personalizes and has been found to enhance learning for SWDs. Moreover, its use is not without challenges which need to be addressed to enable them benefit maximally from this novel and unique technology. This paper, therefore, through evaluative and prescriptive methodology using google search on the theme, concepts and keywords examines the type of AI technologies used by SWDs in higher education, benefits and challenges. Finally, the paper offers some suggestions on overcoming these challenges to enable SWDs benefit maximally from the usage.

Conversational Artificial Intelligence: A Catalyst for Rethinking Assessment in Higher Education

Conversational Artificial Intelligence has disrupted higher education by fundamentally altering its landscape. Fuelled by natural language processing and machine learning this technology has gained widespread adoption particularly since the release of ChatGPT in November 2022. As universities embrace digital transformation, assessment practices must evolve to align with the capabilities of Artificial Intelligence-driven chatbots and virtual assistants. This paper explores how conversational artificial intelligence impacts higher education, in particular, student assessment. A fundamental shift in assessment and evaluation of student competencies is necessary to not only consider knowledge retention but also critical thinking, communication, and adaptability skills. A review of the literature was conducted to understand how assignments should change due to the emergence of this disruptive technology. Conversational Artificial Intelligence and its application within the higher education context is uncertain, with disparate practices—in terms of ethical consideration and understanding—across the sector. A case study was conducted in which MSc Management students undertaking a specific module were tasked to use three Artificial Intelligence tools in their report writing of a business, to verify the sources and content provided by the Artificial Intelligence tool, and to critically evaluate the process as well as the output received for each prompt. The paper proposes a collaborative approach to navigate the ethical implementation and utilization of conversational Artificial Intelligence in higher education, advocating for the co-creation of guidelines through forums like Knowledge Cafés, stressing the need to rethink student assignments and its assessment and the adoption of artificial intelligence technologies by students for assignments.

Risks of AI Applications Used in Higher Education

As artificial intelligence (AI) tools become more widely used in higher education, we must pay attention to the risks that can emerge. AI projects, whether applied in classroom learning or used for decision-making regarding admissions, financial aid allocation, or hiring, must include attention to governance and compliance issues, regardless of the project’s scope and scale. Concerns highlighted in this work include transparency, user privacy, data confidentiality, data integrity, and system availability, however, we note that this is a non-exhaustive list of risks. In this paper, risk assessment is defined, and two examples of risk management frameworks, namely the United States National Institute of Standards and Technology Artificial Intelligence Risk Management Framework and the non-profit humanitarian effort ForHumanity’s Independent Audit of AI, Algorithmic, and Autonomous Systems are briefly described. We identify characteristics of AI applications that need to be assessed for vulnerabilities they may present, such as bias and discrimination. This paper aims to facilitate discussion among stakeholders about the risks that may be encountered from using AI in higher education, as well as to suggest ways developers, decision-makers, and users can mitigate these risks. Much discussion and published literature has focused on risk management frameworks designed for large organizations or enterprises or frameworks that do not consider risks specific to AI. We hope that decision-makers carefully consider the risks, perform due diligence when implementing AI applications, and create a plan for mitigating the risks. This research supports e-learning practice because students and faculty are embracing AI applications. Leaders and decision-makers in higher education need to be proactive in protecting their varied stakeholders. The paper asks what risks may be encountered by institutions of higher education when using AI tools and products in the classroom and for various aspects of decision-making and if published frameworks can mitigate these risks.

ВНЕДРЕНИЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ПРАКТИКУ ВЫСШЕЙ ШКОЛЫ

The article provides an analysis of domestic and foreign publications on the use of artificial intelligence in higher education. The question of the possibility of using artificial intelligence technologies in higher education is raised. The possibilities and risks associated with the introduction of artificial intelligence into the educational process are noted. Among the main threats to the education system are issues related to the ethical use of technology, academic dishonesty on the part of students, a decrease in their motivation, ability to reason, and the emergence of intellectual laziness. The results of surveys of teachers and students devoted to the study of attitudes towards the possibilities of using new technologies in the learning process are presented. Students tend to have a more positive assessment of the use of artificial intelligence in higher education, while concerns, skepticism and fear are noted on the part of the teaching staff. Teachers assess their knowledge and skills in the field of artificial intelligence as insufficient and are ready to improve their skills in this area. The ambiguous attitude of the university administration to the use of artificial intelligence in writing scientific and diploma projects is shown, from a categorical ban on the use of these technologies to experiments on the best application in the form of competitions with incentives for students.