Use Of Artificial Intelligence In Education Research Articles

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.

Course Success Prediction and Early Identification of At-Risk Students Using Explainable Artificial Intelligence

Artificial Intelligence (AI) is increasingly used in online education platforms to provide valuable insights into students’ performance and success. However, the complexity of AI models makes it challenging for educators to interpret the specific factors that influence whether a student is going to pass or fail. Utilizing the Open University Learning Analytics Dataset (OULAD), this study employs various machine learning and deep learning techniques for predicting students’ success, along with SHapley Additive exPlanations (SHAP) as an Explainable Artificial Intelligence (XAI) technique, to understand the key factors behind success or failure. Unlike traditional statistical methods that explore variable relationships, this AI-driven approach uses advanced deep learning techniques to identify patterns and insights, allowing for a better understanding of the factors influencing student success. Additionally, this study focuses on identifying students at risk of failure using XAI techniques, specifically SHAP, to interpret model outputs by breaking down how specific factors contribute to a student’s success. This method enables targeted interventions to support their success. Results reveal that student engagement and registration timelines are critical factors affecting performance. The customized models achieve up to 94% accuracy for the designed tasks, outperforming traditional approaches. This study contributes to the use of AI in education and offers practical insights not only for educators but also for administrators and policymakers to enhance the quality and effectiveness of online learning.

Teaching and Learning in an AI-powered world

In a world where artificial intelligence (AI) is increasingly used, education is undergoing profound transformations, as AI inevitably changes the paradigm of teaching and learning. Teachers have already begun to use AI for student-centred learning, data analysis, or improving assessment through standardized systems provided by AI. Although these new technologies promise efficiency and personalized education, AI is not yet developed enough to truly understand the mechanisms underlying learning. Excessive dependence on technology can reduce the teacher’s role and the importance of human interaction, while certain ethical issues may arise regarding data confidentiality and security. To address these challenges, teachers and decision-makers must carefully integrate AI, emphasizing transparency and ethics, to ensure that technology will indeed have a positive impact on society. This article explores the issues and concerns related to the use of AI in education, also examining the potential disadvantages and fears associated with it and providing an overview of the challenges that teachers face when integrating AI into education.

Elevating STEM Learning: Unleashing the Power of AI in Open Distance eLearning

The integration of Artificial Intelligence (AI) into Open Distance eLearning (ODeL) represents a significant evolution in STEM education, offering transformative benefits in teaching, learning and administrative processes. This conceptual paper explores how AI-driven platforms are revolutionising ODeL by providing personalised learning experiences, real-time feedback, adaptive assessments and immersive simulations through technologies like Augmented Reality (AR) and Virtual Reality (VR). These advancements not only enhance student engagement and understanding but also support the development of critical thinking and problem-solving skills. The paper highlights successful case studies from institutions like Carnegie Mellon University and Stanford Online High School, showcasing practical implementations of AI in STEM education. However, the integration of AI also brings forth challenges, particularly concerning data privacy, security and the need for equitable access to technology. As AI continues to advance, it promises to play an important role in lifelong learning, offering modular and just-in-time educational opportunities. The paper concludes with a call for robust ethical frameworks to guide the responsible use of AI in education, ensuring that the benefits are maximized while potential risks are mitigated.

Artificial Intelligence in Education Management: Opportunities, Challenges, and Solutions

Education management, as an integral part of management science, encompasses core functions such as organizing, planning, coordinating, and controlling educational resources, which closely align with the management concepts used in business administration. Whether in the field of education or business, managers need to improve organizational performance through effective strategy development, resource allocation, and decision-making support. The emergence of Artificial Intelligence (AI) has profoundly transformed several industries, and its impact on education is progressively gaining prominence.This paper explores the opportunities, challenges, and solutions associated with the integration of AI in the education sector. AI offers substantial benefits such as personalized learning experiences, automated educational management, and global access to shared educational resources, revolutionizing the traditional educational landscape. However, its application also presents significant challenges, including concerns over data privacy, the widening of the digital divide, and the evolving role of teachers.Through an analysis of both opportunities and challenges, this paper emphasizes the need for strategic measures to ensure the ethical and equitable use of AI in education. These measures include stronger policy frameworks for data protection, comprehensive teacher training programs for AI integration, and the promotion of global cooperation to bridge technological gaps in underdeveloped regions. Furthermore, the paper projects the potential future developments in AI-driven education, highlighting the importance of balancing technology with human interaction in the learning environment.By addressing both the benefits and risks associated with AI, this paper provides actionable insights for educators, policymakers, and technologists, aimed at creating a more inclusive, efficient, and innovative educational system. Future research should continue to examine AI's ethical implications and strive for solutions that ensure education remains accessible and fair in an increasingly AI-driven world.

The Use of AI in Improving Student's Critical Thinking Skills

The use of artificial intelligence (AI) in education has the potential to significantly enhance students' critical thinking skills. This study explores how AI tools can improve critical thinking among students majoring in English Education at X University. Utilizing a mixedmethods approach, the research combines quantitative surveys and qualitative interviews to assess the frequency and contexts of AI usage and its impact on critical thinking. Survey results reveal that 64% of respondents use AI tools several times a week, predominantly in educational settings. A smaller percentage of respondents use AI daily (14%), while another 14% use AI rarely, and 7% use it several times a month. Interviews with frequent AI users indicate that AI assists in expanding ideas and providing deeper insights, but its effectiveness depends on the users' ability to ask precise questions and critically interpret AI-generated content. The findings highlight that while AI can significantly aid in developing critical thinking skills through personalized learning experiences and interactive simulations, challenges such as potential biases and the need for foundational understanding persist. Ultimately, this research underscores the importance of thoughtful and critical use of AI in education to foster improved critical thinking skills.

Influence of artificial intelligence tools on higher order thinking skills: a meta-analysis

ABSTRACT The use of artificial intelligence (AI) has received scholarly attention and is becoming a common trend in the field of education, while the cultivation of higher order thinking (HOT) skills still remains as one of the crucial educational objectives. Recent years have seen substantial amount of research exploring the influence of Artificial Intelligence in Education (AIEd) use on each HOT skills of students, which necessitated a systematic review to amalgamate the findings quantitatively. This meta-analysis study set out to explore the effect of AIEd on students’ separate HOT skills and identify the effect of potential moderator variables. The analysis included 29 articles with a total of 2.966 participants between the years of 2000 and 2023. This research confirmed the use of AIEd had a medium positive effect on skills classified as HOT skills. The findings suggested that instructional settings which incorporated AI technologies enhanced students’ HOT skills 9.3% higher. This review also found that the variables of country, year of publication and AI tool/agent moderated the magnitude of effect sizes significantly. The findings offer extensive examination of AI technologies in educational settings and contribute to understanding of how and to what extent they influence students’ HOT skills.

Navigating the Grey Area: Students' Ethical Dilemmas in Using AI Tools for Coding Assignments

<div align="center"><table width="100%" border="0" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="605"><p>Integrating artificial intelligence (AI) in higher education, particularly in coding assignments for Information Technology (IT) students, represents a rapidly evolving research area with significant implications for academic practices and integrity. This study focuses on the ethical challenges faced by IT students when using AI tools like ChatGPT for coding assignments. Despite the growing use of AI in education, there is a notable gap in understanding how students perceive and navigate the ethical dilemmas associated with these technologies. To address this gap, this study employed a thematic analysis of qualitative data collected from interviews with IT students. The results reveal a complex landscape of ethical considerations, including issues of originality, academic integrity, and the potential for misuse of AI tools. Students reported challenges in balancing the benefits of AI assistance with the need to maintain independent learning and adhere to ethical standards. The implications of this research are significant for educators, institutions, and policymakers. Understanding the ethical challenges students face can inform the development of more effective teaching strategies, assessment methods, and institutional policies. This study contributes to the ongoing dialogue about AI ethics in academia, providing valuable insights for creating an educational environment that leverages the power of AI while upholding the principles of academic integrity and meaningful learning.</p></td></tr></tbody></table></div>

Artificial intelligence in education – opportunities and threats

The article aims to present a comprehensive view of the current state and future of artificial intelligence (AI), with particular emphasis on its opportunities and threats in the context of education. The first section introduces the topic, highlighting the revolutionary nature of AI in today’s world, and discussing the complex definition of artificial intelligence. It then outlines the opportunities for the use of AI in education, such as individualization of the learning process, customization of teaching materials, and support for students with special educational needs. An analysis of potential threats is also conducted, including ethical issues, student data security, algorithmic biases, and the risk of students becoming dependent on AI-based tools. Finally, the article emphasizes the need for a responsible approach and the necessity of regulation, ethical guidelines, and supervision to effectively harness the potential of artificial intelligence in education. The article also encourages further research into the effectiveness of AI implementation in education, especially in the Polish context.

Fairness, Bias, and Ethics in AI: Exploring the Factors Affecting Student Performance

The use of artificial intelligence (AI) as a data science tool for education has enormous potential for increasing student performance and course outcomes. However, the growing concern about fairness, bias, and ethics in AI systems requires a careful examination of these issues in an educational context. Using AI and predictive modelling tools, this paper explores the aspects influencing student performance and course success. The Open University Learning Analytics Dataset (OULAD) is analysed using several AI techniques (logistic regression and random forest) in this study to reveal insights about fairness, ethics, and potential biases. This dataset has been used by hundreds of studies to explore how educational data mining can provide information on students. However, potential bias or unfairness in that dataset could undermine the results and any conclusions made from them. To gain insights into the dataset's properties, this was analysed using a typical data science methodology, which included data collecting, cleaning, and exploratory data analysis using Python. By applying AI-based predictive models, this study aims to detect potential biases and their impact on student outcomes. Fairness and ethical considerations are central to the analysis as the representation of various demographic groups and any disparities are evaluated in course results. The goal is to provide useful insights on the proper use of AI in education, while also maintaining equitable and transparent decision-making procedures. The findings shed light on the complicated interplay between artificial intelligence, fairness, and ethics in the context of student performance and course success. As artificial intelligence continues to influence the educational landscape, this study will provide useful ideas for encouraging fairness and minimising biases, resulting in a more inclusive and equal learning environment.

Pemanfaatan Artificial Intelligence (AI) Pada Penyusunan Aksi Nyata Paltform Merdeka Mengajar di SDN 02 Medalkrisna

This training program is designed to enhance the competency of elementary school teachers in developing practical actions on the Merdeka Mengajar Platform (PMM) by utilizing Artificial Intelligence (AI) technology. Through the use of Turnitin for plagiarism checks and Gamma for document preparation, the program aims to ensure that the work produced is original and well-structured. The training involves teachers in intensive sessions that include the introduction and use of Turnitin to detect plagiarism, as well as Gamma to assist in preparing practical action documents that meet Kemendikbud's validation standards. The results of the training show a significant improvement in teachers' ability to produce creative, innovative, and compliant practical actions according to the assessment criteria. Teachers participating in this program can produce more professional and plagiarism-free documents, thanks to the constructive feedback from AI. Furthermore, the resulting practical action documents have a clear and attractive structure, facilitating the validation process. This program also encourages the formation of a learning community among teachers, where they share best practices and support continuous improvement. Thus, this training program not only enhances teachers' digital competence but also contributes to the overall improvement of education quality. The use of AI in education becomes an important step in preparing teachers to face challenges in the digital era.

Towards Education 4.0: The role of Large Language Models as virtual tutors in chemical engineering

Recent years have seen the rise of Artificial Intelligence (AI) powered generative chatbots, such as OpenAI’s ChatGPT or Microsoft’s Copilot. These tools have simultaneously positively surprised and taken aback people worldwide, raising the question of whether they can or should be used in education, as well as how to properly guide students and teachers on using them safely and ethically. To this end, this work provides (i) a brief overview of the current applications of AI in Higher Education (HE), (ii) a discussion of the ethical and societal concerns associated with the usage of AI models, (iii) the initial steps of the implementation of a chatbot used at the Technical University of Denmark (DTU) able to perform audits for Good Manufacturing Practice (GMP), and (iv) an investigation of the need and opportunities of AI in chemical engineering education. The latter is achieved through quantitative and qualitative analyses of the responses given by both Master’s students and academia/industry practitioners on the introduction and use of AI in education. This paves the way for discussing current perceptions, expectations and concerns of AI models, as well as their limitations and the opportunities they could provide.

An Experiential Journey: A Year of a Professor Using AI in the Classroom and Research

This paper explores the integration of artificial intelligence (AI) in education and research, highlighting its potential to transform traditional teaching methods and enhance academic inquiry. The use of AI in education is examined, focusing on its ability to streamline administrative tasks, provide personalized instruction, and support teacher professional development. The benefits and challenges of AI adoption in the classroom are discussed, including its impact on teacher burnout and the potential disruption of teacher-student relationships. Additionally, the paper explores the applications of AI in scientific research, emphasizing its role in data analysis, literature review, predictive modeling, and collaborative research. The experiences of a professor who integrated AI into their classroom are shared, and the decision-making process, adjustments made, and the importance of balancing AI-driven instruction with interactive in-class activities are discussed. The paper highlights the need for ongoing evaluation, adaptation, and human-AI collaboration to ensure AI's responsible and effective integration in education and research.

Maximizing the Benefits of ChatGPT with FIRST-ADLX Framework: Promoting Responsible, Ethical, and Impactful AI Integration in Education

In the era of fast technological advancements and the inclusion of Artificial Intelligence (AI) in education, it is more important than ever for educators to have a pedagogy that embeds this technology. A humanistic approach to education is demanded. The focus on the individual student and their emotional and spiritual needs is essential if an active deep learner experience is to be created.This paper aims to explore the integration of Chat Generative Pre-Trained Transformer (ChatGPT) within Focusing, Interacting, Reviewing, Sequencing, Transforming-Active Deep Learner eXperience Framework (FIRST-ADLX Framework) and investigate the framework’s capacity to effectively incorporate the latest technology while prioritizing the learners’ needs and promoting responsible and ethical use of AI in education. By embedding ChatGPT within a comprehensive, holistic, and humanized Framework that prioritizes pedagogy over technology and focuses on the learner rather than on the digital tool, it becomes possible to create an immersive and impactful ADLX. This ensures that the technology used enhances the learner’s experience and does not overshadow it. Furthermore, the study shows how the implementation of the domains and principles of FIRST-ADLX Framework can maximize the benefits of ChatGPT in particular, encourages facilitators and learners to embrace AI technologies as valuable tools and resources, and supports both in utilizing AI ethically, responsibly, and appropriately.The study adopts a qualitative auto-ethnographic approach where data is collected from the facilitator’s personal diary, observations, participants’ comments, and assessments furthermore, this study offers a more objective perspective and embraces descriptive quantitative methods to analyze the results of formative quizzes and the final summative assessment. This approach aims to emphasize the importance of integrating AI within a comprehensive and humanistic framework, avoiding its random use and ensuring alignment with student-centered principles.

TRAINING FUTURE COMPUTER SCIENCE TEACHERS TO USE ARTIFICIALINTELLIGENCE TECHNOLOGIES IN THE EDUCATIONAL PROCESS

The article discusses the training of future computer science teachers to use artificial intelligence (AI) technologies in education. The authors highlight the relevance of this issue in light of the rapid spread of AI technologies in various spheres of life and the need to develop students’ digital competencies related to the use of artificial intelligence. The study aims to identify the essential competencies that future computer science teachers need to effectively use AI in education. It also analyzes the existing problems and challenges in this area, studies the prospects for the use of AI in education, develops recommendations for improving relevant training programs, and overcoming barriers to the implementation of AI technologies. The study identified three main groups of competencies for future computer science teachers in the field of AI: technical, pedagogical, ethical and legal. Technical competencies include knowledge of AI technology principles, algorithms, and software. Pedagogical competencies relate to the ability to adapt teaching materials and methods to the capabilities of AI and to develop appropriate tasks and projects. Ethical and legal competencies involve comprehending the risks and challenges associated with AI usage, as well as being aware of the ethical principles and legal norms in this field. The article analyzes technical, pedagogical, ethical, and legal problems related to introducing AI technologies into computer science teacher training and education. It also explores the potential benefits of AI in education, such as personalized and adaptive learning, improved teaching and assessment effectiveness, and the development of critical thinking and creativity in students. The authors suggest methods to enhance computer science teacher training programs, such as incorporating specialized AI courses, providing practical training, and involving industry experts. They also stress the significance of considering the most effective international practices in this field. To summarize, the article highlights the pressing need to modernize the computer science teacher training system in Ukraine. This is necessary to develop the competencies required for the effective use of AI technologies in the educational process. Such modernization will contribute to the development of students’ digital literacy and ensure the competitiveness of the Ukrainian educational system in the context of digital transformation.

Educational Approaches with AΙ in Primary School Settings: A Systematic Review of the Literature Available in Scopus

As artificial intelligence (AI) becomes increasingly prevalent, it has become a topic of interest in education. The use of AI in education poses complex issues, not only in terms of its impact on teaching and learning outcomes but also in terms of the ethical considerations regarding personal data and the individual needs of each student. Our study systematically analyzed empirical research on the use of AI in primary education, specifically for children aged 4–12 years old. We reviewed 35 articles indexed in SCOPUS, filtered them according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, analyzed them, and categorized the findings. The research focused on the studies’ objectives, learning content, learning outcomes, learning activities, and the pedagogy of activities or the AI tools. Our categorization resulted in three main categories of research objectives regarding the creation, implementation, and evaluation of AI tools and five categories for learning content: AI and ML (machine learning) concepts in STEM and STEAM, language learning, mathematics, arts, and various other subjects. The learning activities were split into four categories: apply, engage, interact, use; project-based learning with multiple activities; experience and practice; and students as tutors. The learning outcomes were split into three levels: cognitive, affective, and psychomotor. The pedagogy of AI tools falls into four categories: constructivism, experiential learning, AI-assisted learning, and project-based learning. The implications for teacher professional development are discussed.

STRATEGIES OF USING ARTIFICIAL INTELLIGENCE FOR WRITTEN CORRECTIVE FEEDBACK IN LANGUAGE EDUCATION

The article discusses the strategies for using artificial intelligence (AI) in the context of providing written corrective feedback in language education. It provides an overview of the latest research in this area, starting from the most significant publications in the field of Russian neurodidactics and international conferences dedicated to the use of AI in education, to practical examples of using chatbots for feedback in language teaching. The article emphasizes the transformation of the role of language educators through the application of artificial intelligence, highlighting the importance of focusing the teacher on the essential aspects of students’ communicative development while delegating the technical aspects of proofreading written assignments to artificial intelligence. The application of such technologies changes the ways feedback is provided, allowing for a more in-depth linguistic analysis and the creation of more extensive comments on written works. Examples of specific requests made to artificial intelligence when marking assignments and examples of their implementation are provided. In addition, the article summarizes the strengths and weaknesses of using AI technologies for assessment and draws conclusions about its role in providing written corrective feedback. The article also highlights the need for a thoughtful integration of AI into the educational process and calls for further research on the impact of artificial intelligence technologies on the development of students’ written productive language skills.

Artificial Intelligence (AI) Vs Academic Integrity (AI) in Law and Society

Artificial Intelligence (AI) having its ever-evolving nature and far-reaching implications in law and society has become too great to be ignored by individuals, educators, businesses, and regulators globally. AI systems with specific sets of rules to conduct a particular task existed in our society for many decades in the form of voice assistants like Siri or Alexa, Google's search or Google map’s algorithm, and even the recommendation engines on Netflix or Amazon have been through the use of AI all these years. So why is this sudden need for thorough examination of this technology having remarkable capabilities and its unprecedented adoption facing the controversy of harming contemporary education’s integrity? For Bangladesh, to a large extent, it has been the rise of tech startups accelerating AI penetration where the abundance of collecting and mining educational data of the learners came with ethical implications. A survey conducted for this paper identified the impact of AI on college and university teachers which was critical for addressing the concerns about AI and its short and long-term impacts on education systems generally. This paper attempts to explore the intricate dual relationship between AI and academic integrity (ai), in law making it imperative to critically examine the unintended consequences by addressing some of the misconceptions regarding the use of AI in education, while acknowledging its potential benefits for society and educational institutions without compromising on academic integrity in law and society. By having a responsive approach to the changes brought about by AI in law & to uphold academic integrity in our society, rethinking and redeveloping the educational programs is the way to make an impact on our education and training systems which will only grow further and further in the future of Smart Bangladesh.

Factors influencing pre-service special education teachers’ intention toward AI in education: Digital literacy, teacher self-efficacy, perceived ease of use, and perceived usefulness

The use of artificial intelligence in education (AIEd) has become increasingly significant globally. In China, there is a lack of research examining the behavioral intention toward AIEd among pre-service special education (SPED) teachers in terms of digital literacy and teacher self-efficacy. Building on the technology acceptance model, our study evaluated the aspects influencing pre-service special education teachers’ intention toward AI in education. Data was gathered from 274 pre-service SPED teachers studying at a Chinese public normal university of special education and analyzed using structural equation modeling (SEM). The results show that digital literacy is associated with the perceived usefulness and ease of use of AIEd, which influences SPED teachers' intention to use AIEd. Additionally, digital literacy significantly impacts the self-efficacy of SPED teachers. Given these results, AI designers in special education should comprehend the effectiveness and usability of AIEd for fostering behavioral intention formation. Simultaneously, special educational programs that identify key content and activities for digital literacy training should be developed, and educators should attempt to execute the relevant pre-service training to enhance the intention of pre-service SPED teachers toward AIEd.

EDUCATION IN THE ERA OF ARTIFICIAL INTELLIGENCE: AXIOLOGICAL STUDY

Education in the era of Artificial Intelligence (AI) presents new challenges in the axiological aspect, namely the moral and ethical values related to the use of AI technology in the learning process. This article aims to conduct an axiological study of education in the era of artificial intelligence with a focus on understanding the values that emerge along with the development of AI technology and their implications in the educational context. The research approach used is literature analysis to explore understanding of the use of AI in education and its implications for moral and ethical values. The results of the study show that the use of AI technology can provide significant benefits in increasing the effectiveness and efficiency of learning, but also raises several axiological problems. This research is qualitative research involving literature analysis, the data obtained will be processed thematically. In its conclusion, this article emphasizes the need to develop axiological awareness in education in the era of artificial intelligence. By paying attention to moral and ethical values, education can be an effective forum for developing a generation that is technologically intelligent and has a strong axiological awareness. This effort needs to be supported by critical thinking, reflection, and collaboration between educators, stakeholders and related parties to ensure that the application of AI technology in education runs ethically and responsibly.