Artificial Intelligence In Higher Education Research Articles

Assessing AI Adoption: Investigating Variances in AI Utilization across Student Year Levels in Far Eastern University-Manila, Philippines

This study investigates the prevalent use of artificial intelligence (AI) among college students at Far Eastern University. Despite the risks, it aims to understand the primary reason behind the continuous use of AI. According to academics, the benefits of implementing AI in higher education include better inclusion, increased efficiency in administrative costs, and improvements in the learning-teaching process (Pisica et al., 2023). However, the extreme utilization of AI among students has led to cheating and plagiarism for many reasons that impact their personal lives and mental health. The researcher identified potential gaps while assessing possible solutions to lessen the student using Artificial Intelligence (AI) excessively. Moreover, the researcher used a quantitative method analysis involving 40 college students from 1st-year level to 4th-year level to explore the impacts of Artificial Intelligence on their academic tasks and learning styles. Thus, examining the utilization of AI from different year levels of Far Eastern University college students revealed that the researcher provides valuable insights into addressing the challenges posed by excessive dependency on AI while maintaining academic integrity and the need for the students to develop their critical thinking skills. After the researcher analyzed the collected data, it showed that the utilization of Artificial Intelligence (AI) for academic workloads varies among participants covering different college students, showing that first-year students rely on AI due to peer pressure. In contrast, the second-year students use it to improve their academic standing. Third-year students depend on AI because of time constraints, while fourth-year students use AI to minimize the possibility of human errors. The study conveys no significant differences in the probability of using AI for academic purposes, and it does not prevent the students from using AI regardless of their year level. Therefore, the researcher recommends proposing stricter AI checkers and educating the students on responsible Artificial Intelligence (AI) usage to mitigate academic misconduct.

The Prospects of Generative AI in Higher Education

Artificial intelligence (AI) has brought tremendous prospects and breakthroughs to a number of areas, including education. With an emphasis on the use of chatbots, analytics, generative AI, and personalized learning experiences, this research study offers a thorough analysis of the effects of AI on education. In order to shed light on the ethical implications, cultural considerations, language competence issues, and privacy concerns related to the use of AI in education, it explores the related limitations, obstacles, and concerns. Artificial Intelligence (AI) has the potential to completely transform higher education by promoting efficiency, creativity, customization, and engagement. Higher education could undergo a significant transition with the use of Generative Artificial Intelligence (GAI) tools as ChatGPT, Google BARD, and Bing Chat. But this integration also presents problems for avoiding plagiarism and upholding academic integrity. Within this In this work, we explore and evaluate useful strategies for effectively utilizing GAI's potential while also guaranteeing assignment integrity. We present the PAIGE (Promoting Assignment Integrity using Generative AI in Education) conceptual framework as a viable means of addressing these issues. This concept places a focus on the moral. The inclusion of GAI, encourages student engagement, and fosters chances for collaborative learning. Institutions of higher learning can efficiently use the promise of GAI while maintaining assignment integrity by utilizing the PAIGE framework. A responsible and prosperous future in education powered by generative AI is made possible by this strategy. The research report also explores the roles that parents, legislators, and educators play in minimizing the risks and optimizing the advantages of implementing AI in the classroom. Challenges with linguistic ability, privacy, and other factors related to using AI in education. Key Words: Generative AI, analytics, learning experiences, cognitive achievement, AI in the classroom, customized feedback

The influence of artificial intelligence in higher education based on four thematic axes: a bibliometric study

The article presents a structured bibliometric study examining the impact of artificial intelligence (AI) in higher education across four thematic axes: AI in higher education, AI in education review, AI in the teaching-learning process, and AI tools applied to higher education. Research productivity and impact indicators are analyzed using data from major databases like Scopus, Web of Science, and ScienceDirect. Results reveal a significant increase in AI-related research output, particularly in machine learning, data mining, and learning analytics. The study highlights China and the United States as leading contributors to AI research in higher education. The findings highlight AI's evolving role in transforming higher education and the need for multidisciplinary research approaches to address emerging challenges and opportunities. However, limitations include the reliance on quantitative measures, the narrow temporal scope, and the limited focus on high-production countries. Future research should incorporate qualitative methods to explore practical applications and social impacts more comprehensively, consider a broader range of geographic contexts, and discuss ethical considerations around integrating AI into higher education.

Student perceptions on the impact of AI on their teaching and learning experiences in higher education

This paper provides evidence of student perspectives of Artificial Intelligence (AI) in Higher Education (HE). In contrast to the extant literature that uses large-scale survey data to gather the student voice, research methods that prioritise qualitative data collection are presented. The data responds to a gap in the empirical evidence, redressing the lack of qualitative data on students’ thoughts and feelings in response to AI within a UK context. The paper also compares categorisations of concern relating to AI in HE between that published by academics and that generated by students using their own frames of reference. Recommendations for HE institutions are provided in response to issues identified in the literature and the research data.

Combining human and artificial intelligence for enhanced AI literacy in higher education

This paper seeks to contribute to the emergent literature on Artificial Intelligence (AI) literacy in higher education. Specifically, this convergent, mixed methods case study explores the impact of employing Generative AI (GenAI) tools and cyber-social teaching methods on the development of higher education students’ AI literacy. Three 8-week courses on advanced digital technologies for education in a graduate program in the College of Education at a mid-western US university served as the study sites. Data were based on 37 participants’ experiences with two different types of GenAI tools–a GenAI reviewer and GenAI image generator platforms. The application of the GenAI review tool relied on precision fine-tuning and transparency in AI-human interactions, while the AI image generation tools facilitated the participants’ reflection on their learning experiences and AI's role in education. Students’ interaction with both tools was designed to foster their learning regarding GenAI's strengths and limitations, and their responsible application in educational contexts. The findings revealed that the participants appeared to feel more comfortable using GenAI tools after their course experiences. The results also point to the students’ enhanced ability to understand and critically assess the value of AI applications in education. This study contributes to existing work on AI in higher education by introducing a novel pedagogical approach for AI literacy development showcasing the synergy between humans and artificial intelligence.

Developing effective prompts to improve communication with ChatGPT: a formula for higher education stakeholders

The escalating integration of artificial intelligence (AI) technologies, particularly the widespread use of ChatGPT in higher education, necessitates a profound exploration of effective communication strategies. This paper addresses the critical role of prompt development as a skill essential for university instructors engaging with ChatGPT. While emphasizing the practical implications for higher education, the study introduces a novel two-layered AI prompt formula, considering both components and elements. In methodology, the research synthesizes insights from existing models and proposes a tailored approach for ChatGPT, addressing its unique characteristics and the contextual elements within higher education. The results highlight the formula’s flexibility and potential applications in diverse fields, from syllabus planning to assessment. Moreover, the study identifies limitations inherent in ChatGPT, emphasizing the need for instructors to exercise caution in its usage. In conclusion, the paper underscores the evolving landscape of AI in education, envisaging specialized versions of ChatGPT for academic settings and advocating for the proactive adoption of ethical frameworks in the use of AI in higher education. This study serves as a foundational contribution to the discourse on effective AI communication in educational settings.

Institutional Integration of Artificial Intelligence in Higher Education: The Moderation Effect of Ethical Consideration

This research study aims to examine the impact of institutional artificial intelligence (AI) implementation on students’ academic achievement considering the role of ethical considerations. A quantitative approach was employed and data was collected using a non-probability convenience sampling technique, targeting students from different universities in Bangladesh. A total of 214 valid responses were collected and the partial least squares-structural equation modeling estimation procedure was performed using WarpPLS software. The results demonstrate a positive correlation with the rising trend of AI utilization in higher education. Nonetheless, this connection weakens when ethical aspects are considered as a moderator that highlights the originality of this study.

A systematic review of research on artificial intelligence in higher education: Practice, gaps, and future directions in the GCC

A systematic review of research on artificial intelligence in higher education: Practice, gaps, and future directions in the GCC

Higher Education’s Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania

Higher education is currently under a significant transformation due to the emergence of generative artificial intelligence (GenAI) technologies, the hype surrounding GenAI and the increasing influence of educational technology business groups over tertiary education. This commentary, prepared for the Special Issue of the Journal of University Teaching & Learning Practice (JUTLP) on “Enhancing student engagement using Artificial Intelligence (AI) and chatbots,” delves into the complex landscape of opportunities and threats that AI chatbots, including ChatGPT, introduce to the realm of higher education. We argue that while GenAI offers promise in enhancing pedagogy, research, administration, and student support, concerns around academic integrity, labour displacement, embedded biases, environmental sustainability, increased commercialisation, and regulatory gaps necessitate a critical approach. Our commentary advocates for the development of critical AI literacy among educators and students, emphasising the necessity to foster an environment of responsible innovation and informed use of AI. We posit that the successful integration of AI in higher education must be grounded in the principles of ethics, equity, and the prioritisation of educational aims and human values. By offering a critical and nuanced exploration of these issues, our commentary aims to contribute to the ongoing discourse on how higher education institutions can navigate the rise of GenAI, ensuring that technological advancements benefit all stakeholders while upholding core academic values.

Analysis of Artificial Intelligence in International Higher Education Field Based on Bibliometrics

Artificial intelligence (AI), as a significant feature of modern development, has changed the form of education, especially with a significant impact on higher education (HE). Clarifying the integration and infiltration of HE and AI is of great significance for the future development of AI in HE. The Citespace is used to make a quantitative and qualitative analysis of the indicators such as authors, institutions, nationalities, disciplines, journals, and highly cited articles of AI research literature -located at HE included in the Web of Science core collection database. The results show that in recent years, AI in the field of HE has received extensive international attention, and the research results are in a growing trend. In the field of international HE, AI focuses on hot topics such as parameter design, deep learning, machine learning human-computer interaction and hybrid learning. And deep learning, learning space simulation design, learning effectiveness measurement, etc. will become an important development direction of international AI research in the field of HE.

Enhancing Psychological Well-being in Higher Education Post-Covid-19 Pandemic. The Role of AI-Based Support Systems—Bibliometric Reviews

Psychological well-being is a cornerstone of student success in higher education. However, many students struggle with mental health challenges like stress, anxiety, and depression during and even after the Covid-19 pandemic. These challenges, often stemming from academic, personal, social, or career concerns, negatively impact student learning and development. This underscores the need for robust support systems within higher education (HE). Artificial intelligence (AI) emerges as a promising field in educational technology, offering students readily available guidance on their path to well-being. This research, guided by the PRISMA Statement 2015, provides an overview of AI applications in higher education through a systematic review. From an initial pool of 270 publications identified between year 2021 and 2023, finally, 24 articles met our inclusion criteria and were analyzed for the final synthesis. This paper revealed three key areas where AI-based systems can support student well-being: i) AI’s Advancement and Potential: Exploring the evolving capabilities and promise of AI in this context. ii) Building Effective AI Systems: Identifying crucial components for successful AI-based well-being interventions. iii) Barriers to Implementing AI in Higher Education: Addressing ethical considerations and challenges unique to academic settings. The conclusions and the road ahead from this research is the critical need for ethical, well-designed AI-based systems to overcome existing barriers and deliver exceptional student well-being support services. By prioritizing student mental health and providing them with the necessary tools and resources, we can empower them to achieve their full potential and thrive in their academic endeavors.

The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives

In recent months, Artificial Intelligence (AI) has had, and will continue to have, a dramatic impact on Higher Education (HE). A study conducted by researchers at a leading university in Australia surveyed 30 of their teaching staff, drawn predominantly from their teaching academy, and interviewed eight of them regarding the impact of AI on HE. Data were analyzed using the procedures of Inductive Thematic Analysis and revealed a lack of any homogenous sentiment around AI in HE and much ambiguity regarding best practice regarding recent technological developments. The results indicate concerns exist around concepts relating to academic integrity, however, these concerns may be exaggerated. Almost half of the participants indicated they were using AI within their teaching roles with the most common design change being modifications to assessments. Less than a quarter of staff agreed the university has adequately equipped them for AI, and more than three quarters indicated they would like support. They unanimously assumed the technology will improve. Keeping in mind universities’ obligation to serve students by preparing them for industry, it is vitally important that the HE sector stays informed of developments in AI and commit to ongoing research and discussions regarding best practice in response to AI. However, anything regarding AI and future developments will be extremely difficult to predict.

Exploring the Fundamentals of Artificial Intelligence and its Impact on the Teaching of Higher Secondary and Higher Education, particularly in the Teach Health Sciences

These present assat show a principal findigns Artificial intelligence (AI) has emerged as a transformative discipline, mainley exploring the Fundamentals of Artificial Intelligence and its Impact on the Teaching of Higher Secondary and Higher Education, particularly in the Teach Health Sciences. Show the classification in Intelligence, is the intellective power, the faculty of knowing or understanding and Artificial, it is what is made by the hand and art of man. Present the Methodological Foundations of Artificial Intelligence, and The Impact of Artificial Intelligence in Higher Education.

Academic Integrity and Artificial Intelligence in Higher Education (HE) Contexts: A Rapid Scoping Review

Academic Integrity and Artificial Intelligence in Higher Education (HE) Contexts: A Rapid Scoping Review

AI in higher education: Booster or stumbling block for developing digital competence?

Since the Artificial intelligence (AI) revolution catalyzed by ChatGPT, the discourse of students’ digital competence has become prevalent in German higher education institutions (HEIs). While educators recognize the potential for using AI in higher education, concerns persist about students needing more necessary skills. This paper presents findings from a comprehensive lecturer survey that provides insights into educators’ perspectives on the opportunities and challenges associated with AI integration in HEIs. Furthermore, it addresses the conditions required for successful AI implementation in German HEIs to promote, rather than hinder, students’ digital competence and future skills.

A scholarly dialogue: writing scholarship, authorship, academic integrity and the challenges of AI

ABSTRACT Concerns about the role of technology and the quality of student writing in higher education are not new. Historically, writing scholars have been at the forefront of initiatives that scrutinise and integrate new technologies in higher education. This article contends that writing scholars are again uniquely equipped to assist students, teachers in all disciplines, and institutions of higher education in navigating the challenges created by the public availability of generative artificial intelligence (AI). Adopting a dialogical approach, the article brings together six scholars from diverse disciplinary backgrounds within the broad umbrella of writing studies. Through the lens of writing scholarship, this chorus of critical voices illuminates the important questions posed by, and possible responses to, AI in higher education. Although AI complicates key issues in higher education such as academic integrity, assessment, and authorship, writing scholarship provides an essential framework for educators to respond to these challenges. Collectively, these scholars map the history of writing scholars’ responses to technological change in higher education and suggest how writing scholars can contribute to the debates and discussions concerning the impact of AI on higher education.

Generative Artificial Intelligence in Higher Education: Exploring Ways of Harnessing Pedagogical Practices with the Assistance of ChatGPT

There is a growing interest in using generative artificial intelligence (AI) for educational purposes within the higher education environments, while AI applications (such as ChatGPT) can transform traditional teaching and learning methods. ChatGPT is an advanced AI tool that generates new content and human-like responses. The purpose of this paper is to use ChatGPT as a research assistant in order to explore ways AI can be harnessed to enhance pedagogical practices in higher education. This is a qualitative study, in which the output-responses generated by ChatGPT provided a starting point for the investigation. AI can be harnessed to enhance pedagogical practices in higher education in various ways including personalized learning, automated assessment and feedback generation, virtual assistants and chatbots, content creation, resource recommendation, time management, language translation and support, research assistance, simulations and virtual labs. Other educational affordances that can strengthen the teaching and learning experience regard collaboration and communication, accessibility and inclusivity, as well as AI literacy. When implementing AI tools such as ChatGPT in higher education, ethical considerations (e.g., data privacy, transparency, accessibility, cultural sensitivity), potential misuses and concerns need to also be addressed. Although ChatGPT can aid the generation of content-ideas for further exploration, it is a complementary-supportive tool, and its output necessitates human evaluation and review. The integration of ChatGPT and other AI tools in the higher educational process/practices has implications for educators, students, design of curricula, and university policy makers.

Role of Artificial Intelligence in Higher Education- An Empirical Investigation

The importance of artificial intelligence (AI) is growing in all economic sectors and thus also in higher education. In recent years, there have been significant developments in this concept of "Artificial Intelligence in Education (AIED)". The purpose of this study was to find out how the concept of artificial intelligence can be applied to teaching and learning in higher education and the implications of the use of artificial intelligence in higher education. The impact of the development of technologies on learning is often studied on the methods and scope of learning and teaching. Artificial intelligence enables higher education services to become easily accessible with extraordinary speed, not only in the classroom but also outside the classroom. This report seeks to explore how AI will become an integral part of universities and seeks to examine its immediate and future impact on various aspects of higher education. The challenges of implementing AI in these institutes were also explored. As artificial intelligence (AI) research in education increases, many researchers in the field believe that the role of teachers, schools and leaders in education will change. In this regard, the aim of this study is to investigate which are the possible scenarios for the arrival of artificial intelligence in education and what impact it can have on the future of schools. In this research, it confirmed that artificial intelligence has been widely adopted and used in various forms in education, especially educational institutions. Artificial intelligence was initially implemented in the form of computers and computer-related technologies, moving to web-based and web-based intelligent educational systems, and finally with the use of embedded computing systems and other technologies such as humanoid robots and web-based chatbots teachers & tasks and assignments independently or with tutors. With these platforms, teachers could perform various administrative tasks such as grading and Work more effectively and efficiently and achieve higher quality in your learning activities. On the other hand, because the systems use machine learning and adaptability, the curriculum and content are adapted which improved uptake and retention, which improved the student experience and the overall quality of education.

The educational value of artificial intelligence in higher education: a 10-year systematic literature review

Purpose This paper aims to consolidate empirical studies between 2013 and 2022 to investigate the impact of artificial intelligence (AI) in higher education. It aims to examine published research characteristics and provide insights into the promises and challenges of AI integration in academia. Design/methodology/approach A systematic literature review was conducted, encompassing 44 empirical studies published as peer-reviewed journal papers. The review focused on identifying trends, categorizing research types and analysing the evidence-based applications of AI in higher education. Findings The review indicates a recent surge in publications concerning AI in higher education. However, a significant proportion of these publications primarily propose theoretical and conceptual AI interventions. Areas with empirical evidence supporting AI applications in academia are delineated. Research limitations/implications The prevalence of theoretical proposals may limit generalizability. Further research is encouraged to validate and expand upon the identified empirical applications of AI in higher education. Practical implications This review outlines imperative implications for future research and the implementation of evidence-based AI interventions in higher education, facilitating informed decision-making for academia and stakeholders. Originality/value This paper contributes a comprehensive synthesis of empirical studies, highlighting the evolving landscape of AI integration in higher education and emphasizing the need for evidence-based approaches.

The Impact of Artificial Intelligence on Higher Education and the Economics of Information Technology

This article explores the influence of Artificial Intelligence (AI) on higher education and the economics of information technology. The rapid advancements in AI have the potential to revolutionize the way universities deliver education and how the IT industry operates. This study employs the IMRAD method to investigate the current state of AI in higher education, its economic implications, and future prospects. The findings suggest that AI can enhance teaching and learning experiences, streamline administrative processes, and open up new revenue streams for universities. However, the adoption of AI also presents challenges, such as the need for significant investments in infrastructure and the potential for job displacement. The article concludes with recommendations for universities and policymakers to harness the benefits of AI while mitigating its risks.