Personal Learning Research Articles

Pedagogical Interaction and Student Engagement at Selected University

This quantitative study examined pedagogical interaction and student engagement in a university in Guangdong, China, involving 364 students and 132 teachers. Surveys evaluated pedagogical strategies, including reflective, inquiry-based, and collaborative learning, alongside cognitive, emotional, and behavioral aspects of student engagement. Professional development was measured by the establishment of training systems aimed at enhancing students' capacity to engage in classroom interactions, ensuring that teachers progressively cultivate active participation.The findings show that teachers frequently facilitate teamwork, reflect on their teaching practices, and set clear expectations for group activities. They also promote inquiry-based learning by fostering interactive environments where students exchange ideas and engage in discussions. In problem-based learning settings, teachers guide students through research, data analysis, and presentations. However, Spearman’s rho correlation analysis found no significant relationship between teaching strategies and student engagement, suggesting that changes in one do not necessarily affect the other. This indicates that factors beyond pedagogy, such as student motivation or external influences, may impact engagement. The study highlights the need for more personalized learning approaches and enhanced support systems to encourage participation. And, continuous professional development remains crucial, ensuring educators can create environments that nurture meaningful student engagement, regardless of instructional strategies used.

Enhancing Higher Education in Portugal: Leveraging Generative Artificial Intelligence for Learning-Teaching Process

Recent advancements in Generative Artificial Intelligence (GAI) have revolutionized numerous fields, including higher education. This study focuses on the integration of GAI in Portuguese higher education institutions and explores its multifaceted implications and potential. Our research, conducted through a comprehensive survey between April and June 2023, engages with higher education faculty to understand their perceptions and utilization of GAI tools in teaching and learning processes. The potential of GAI to enhance personalized learning and interactive teaching methodologies is significant. It enables the creation of customized educational content, interactive simulations, and real-time feedback mechanisms, thus reducing the educators' workload and enhancing the learning experience. However, this integration is not without challenges. The study identifies critical ethical concerns around the use of GAI, including data privacy, intellectual property, and the potential for bias in AI-generated content. Additionally, our findings indicate varying acceptance and readiness among educators to adopt these technologies. While some express enthusiasm for the potential of GAI to transform educational practices, others remain cautious, highlighting the need for comprehensive training and support to leverage GAI capabilities fully. This paper captures the essence of the study's findings, illustrating both the promising opportunities and the complex challenges associated with using Generative AI in higher education. Higher education institutions can significantly enhance teaching and learning landscapes by addressing these challenges and fostering an informed and ethical approach to GAI integration.

Transforming higher education for the digital age

In this study, I explore the transformative potential of artificial intelligence (AI) and emerging technologies in higher education, focusing on case studies and pedagogical innovations that are reshaping the learning experience. Through an in-depth analysis of key initiatives—such as Stanford University's AI-driven personalized learning platform, the AI chatbot implemented at the University of Murcia, Knewton's adaptive learning system, and the intelligent tutoring platform developed by Pai et al.—the study highlights how AI enhances learner engagement, customizes educational experiences, and improves academic outcomes. The research also critically examines the ethical challenges and policy considerations associated with AI integration in educational settings. It emphasizes the need for clear guidelines to ensure responsible and equitable use of AI, particularly in addressing issues of fairness, student welfare, and access. The paper concludes by calling for further research into the long-term implications of AI on educational equity and ethical standards in higher education.

Research on the Innovation in College English Teaching under the Background of New Liberal Arts

This article provides a brief overview of the application and development of artificial intelligence (AI) in the field of education under the background of New Liberal Arts. It also highlights the importance and current status of innovative approaches in college English teaching. Furthermore, it presents the research objectives and methods. The application of artificial intelligence in education has witnessed significant growth and advancement in recent years. AI technologies, such as machine learning and natural language processing, have been utilized to enhance various aspects of education, including personalized learning, intelligent tutoring systems, and automated grading. These applications have shown promising results in improving students' learning outcomes and engagement. In the context of college English teaching, innovation is crucial to meet the evolving needs and expectations of students. Traditional teaching methods often fail to cater to individual learning styles and preferences, leading to limited effectiveness and student disengagement. Therefore, there is a pressing need to explore innovative approaches that leverage AI technologies to create more interactive and personalized learning experiences. The research aims to investigate the potential of integrating AI into college English teaching and its impact on students' learning outcomes and engagement. The study will employ a mixed-methods approach, combining quantitative analysis of students' performance data with qualitative interviews and surveys to gather comprehensive insights. By examining the effectiveness and challenges of AI integration in English teaching, this research seeks to provide valuable recommendations for educators and policymakers to enhance the quality of college English education. Above all , this study aims to explore the application of artificial intelligence in college English teaching, considering its potential to improve learning outcomes and engagement. By adopting a mixed-methods research approach, this study intends to provide valuable insights and recommendations for educators and policymakers to promote innovative and effective English teaching practices.

Blockchain in Education: Transforming Learning, Credentialing, and Academic Data Management

Background and Aims: Blockchain technology is critical in education for transforming learning, credentialing, and academic data management by ensuring secure, immutable, and transparent handling of academic records. This technology improves the integrity of credentials, streamlines administrative processes, and promotes personalized learning, resulting in a more dependable and efficient educational environment. This review is intended for educators, administrators, policymakers, and technologists who are interested in blockchain's potential to transform the education landscape. Methodology: The methodology for this review included a systematic approach to gathering and analyzing literature on blockchain in education. A rigorous protocol was used to screen, extract, and categorize relevant data from academic databases and supplementary sources. Thematic analysis, aided by tools such as NVivo, enabled a thorough understanding of blockchain's impact and prospects in educational settings. Results: Blockchain technology has the potential to transform the educational sector by addressing critical issues such as data security, credentialing, and administrative efficiency. Blockchain, which provides a decentralized, immutable system for managing educational records and credentials, can improve the integrity and accessibility of academic information, streamline processes, and support personalized learning experiences. Although challenges such as scalability, legal complexities, and institutional resistance persist, ongoing advancements and research are likely to pave the way for wider adoption. As educational institutions investigate and implement blockchain solutions, the technology's transformative impact on the global education system may result in a more transparent, equitable, and innovative learning environment for future generations. Conclusion: blockchain technology has the potential to revolutionize education by improving data security, credentialing, and administrative efficiency through its decentralized and immutable system. Despite current challenges, its continued development and implementation could result in a more transparent, equitable, and innovative educational environment.

A Systematic Review and Multifaceted Analysis of the Integration of Artificial Intelligence and Blockchain: Shaping the Future of Australian Higher Education

This study explores the applications and implications of blockchain technology in the Australian higher education system, focusing on its integration with artificial intelligence (AI). By addressing critical challenges in credential verification, administrative efficiency, and academic integrity, this integration aims to enhance the global competitiveness of Australian higher education institutions. A comprehensive review of 25 recent research papers quantifies the benefits, challenges, and prospects of blockchain adoption in educational settings. Our findings reveal that 52% of the reviewed papers focus on systematic reviews, 28% focus on application-based studies, and 20% combine both approaches. The keyword analysis identified 287 total words, with “blockchain” and “education” as the most prominent themes. This study highlights blockchain’s potential to improve credential management, academic integrity, administrative efficiency, and funding mechanisms in education. However, challenges such as technical implementation (24%), regulatory compliance (32%), environmental concerns (28%), and data security risks (40%) must be addressed to achieve widespread adoption. This study also discusses critical prerequisites for successful blockchain integration, including infrastructure development, staff training, regulatory harmonisation, and the incorporation of AI for personalised learning. Our research concludes that blockchain, when strategically implemented and combined with AI, has the potential to transform the Australian higher education system, significantly enhancing its integrity, efficiency, and global competitiveness.

The Impact of AI on Personalized Learning and Educational Analytics

The rapid advancement of artificial intelligence (AI) has revolutionized personalized learning and educational analytics, presenting new opportunities and challenges for adaptive education. This paper explores the impact of AI-driven technologies in creating personalized learning environments by examining how adaptive algorithms and data analytics shape educational experiences. The primary objective of this study is to assess the effectiveness of AI in enhancing learner engagement and outcomes through tailored instructional methods. Utilizing a mixed-method approach, this research gathers quantitative data from learning management systems to analyze engagement metrics, while qualitative insights are derived from interviews with educators and students. The findings indicate that AI-driven personalized learning significantly improves both student motivation and academic performance by adapting content to individual learning needs. Moreover, educational analytics enabled by AI offer educators critical insights into student progress, enabling proactive intervention and support. However, the study also highlights concerns regarding data privacy and the potential over-reliance on AI technologies in educational settings. These findings suggest that while AI holds transformative potential, a balanced approach is necessary to integrate technology with traditional teaching methods to ensure optimal educational outcomes. The study concludes that AI can serve as a powerful tool in enhancing personalized learning and educational analytics, provided that ethical considerations and data security are prioritized.

EVALUATING THE IMPACT OF AI–POWERED TUTORS MATHGPT AND FLEXI 2.0 IN ENHANCING CALCULUS LEARNING

This study evaluates the effectiveness of AI-driven technologies, Flexi 2.0 and MathGPT, in enhancing personalized learning and advanced cognitive abilities among pre-service mathematics educators participating in Calculus I. Participants were allocated to a control group receiving conventional training and an experimental group utilizing AI technology, applying a quantitative experimental design. Data were gathered utilizing validated evaluations, surveys, and interviews. The results indicated that students employing AI tutors showed significant improvements in problem-solving and personalized learning compared to the control group. Concerns arose regarding potential over-reliance on AI, underscoring the need for rigorous criteria to guarantee that students engage actively in learning rather than passively receiving AI-generated responses. The findings suggest that educators should create activities requiring students to critically evaluate AI-generated responses to promote independent thinking. The findings highlight the potential of AI in mathematics education while stressing the importance of ethical considerations and teacher oversight. It requires both students and staff training to adapt to improvements in AI inside education. The study reveals that while AI can improve learning outcomes, careful implementation is essential for its effective and responsible use in educational settings.

Students’ perceptions of an artificially intelligent chatbot as a support tool to develop their research skills

PurposeThis research aims to evaluate students’ perception of using a chatbot to develop their understanding of the various parts of a research article, and their ability to apply what they have learned to write a new research plan.Design/methodology/approachThis research is qualitative in approach. The sample contained 10 students on a research skills course as part of the master of educational technologies program. The research instruments consisted of (1) semi-structured interviews to gather the students’ perceptions of the effectiveness of using a chatbot, and (2) observation notes to triangulate the interview results, relating to the students’ application of what they had learned from the teacher and ChatGPT, in new contexts.FindingsThis study found that the use of ChatGPT contributed to developing students’ knowledge of writing a research plan. The students were satisfied with their personalized learning experience, and believed that ChatGPT had improved their autonomy, competence and relatedness. These three variables had played a role in developing their application skill. However, there were concerns about using ChatGPT in learning, like limiting the students’ creativity, human interaction and critical thinking skills. There were also concerns over accuracy, ethics and plagiarism.Originality/valueThe originality of this study lies in its examination of how ChatGPT can help satisfy students' need for autonomy (having more knowledge to communicate with the app and control their choices), competence (feeling more capable of using artificial intelligence [AI] and possessing the necessary knowledge and skills to succeed) and relatedness (being less disappointed when failing to obtain satisfactory responses from the AI application), while improving their skills in application. According to self-determination theory (SDT), these factors affect students’ skills in applying what they have learned to new tasks. Therefore, this study extends the examination of SDT and its effect to include application skill, using qualitative methods to study the relationships between variables in depth.

The Impact and Prospects of AI-Generated Content in Educational Environments

This paper examines the impact and emerging prospects of generative artificial intelligence (AI) content creation (AIGC) within the educational sector. As AI technology continues to evolve rapidly, the potential for AIGC to revolutionize educational practices has garnered significant interest and scholarly focus. AIGC is proving instrumental in developing customized educational content, facilitating personalized learning experiences, and enhancing assessment methods. These capabilities have the potential to significantly boost teaching efficiency and elevate student outcomes. Nonetheless, the integration of AIGC also poses several challenges, including concerns over academic integrity, shifts in the instructional roles of educators, and issues related to data privacy and ethical considerations. This analysis delves into the current applications of AIGC in education, discussing technological trends, innovations in educational models, and strategic policy recommendations. It underscores the necessity for future research to concentrate on evaluating the practical effects of AIGC, addressing potential drawbacks, and ensuring its responsible growth in educational settings.

Students’ Perceptions and Use of AI in MLIS Courses

Artificial intelligence (AI) has been a buzzword on the Internet due to the development of ChatGPT. AI, especially generative AI, can create original text, audio, and images in response to users’ questions and needs. These programs have the potential to enhance students’ learning and creativity if used ethically. Especially for graduate students in the library and information science (LIS), AI can be used to help students outline essays or produce creative content (e.g., videos, slides, visual presentations) that mimic human intelligence and creativity. However, considering this is yet new technology, research needs to be done to understand how students perceive and use AI ethically in their coursework and research in higher education settings. Specifically, this study aims to explore students’ views on the ethical implications of AI in LIS research and class assignments in a course in the Master of Library and Information Studies (MLIS) program at a university and gather students’ perspectives on its responsible or irresponsible utilization. Content analysis of students’ online discussions revealed that students perceived that AI could enhance educational efficiency, foster creativity, and provide technical support. Students found AI helpful in personalized learning experiences, resource access, streamlining tasks, and critical thinking and problem-solving. However, they had concerns about incorrect citation, copyright, plagiarism, bias, misinformation, privacy, and the risk of diminished creativity. This inquiry will contribute to gaining insights into how to help MLIS students prepare with ethical understanding and use of AI for their professional activities.

The Design and Implementation of Personalized Learning Platform Based on Android

Through an investigation and analysis of learning platforms, the author designed and implemented the personalized learning platform based on Android, adhering to the design principles. The platform is customized to learners’ learning styles and ubiquitous learning. Learners may receive personalized recommendations from the platform and get optimized user experience, which in turn enhances learners’ motive and efficiency in learning and supports teachers’ teaching.

The AI-empowered Researcher: Using AI-based Tools for Success in Ph.D. Programs

Generative artificial intelligence (AI) changes the picture of graduate education by providing personalized learning, automated feedback, intelligent research assistants, and automated content creation (George, 2023). AI tools will support doctoral students in text generation, language translation, responding to academic queries, and data collection and analysis and encourage self-learning and thinking development (Rasul et al., 2023; Zou & Huang, 2023). They also would be helpful for doctoral students working as teaching assistants and aiding in daily problems (Can et al., 2023; Parker et al., 2024). However, the rise of AI tools also leads to considerations of academic integrity, over-reliance on AI, misinformation, and the potential biases embedded in algorithms (George, 2023; Rasul et al., 2023). Echoing the opportunities and challenges of AI applications in research and learning, the ALISE Doctoral Students SIG wants to encourage a discussion on how doctoral students can use AI tools to empower us in the Ph.D. journey. The panel invites a diverse group of doctoral students/candidates to share how AI tools can facilitate data collection and analysis and their critical understanding of AI systems. Manar Alsaid will talk about using AI and machine learning to detect complex misinformation on social media. The talk aims to enhance our understanding of misinformation and reduce its negative impacts. This presentation will provide valuable insights for research on misinformation and information literacy. Adam Eric Berkowitz will introduce the black-box tinkering method that experimentally discerns how AI systems operate. The method enhances the transparency of AI systems, challenging the technocratic paradigm. With three examples, Berkowitz encourages attendees to learn what black-box tinkering is, how to identify cases using it, and potential opportunities to incorporate it in research. Anisah Herdiyanti will share insights from a study comparing transcripts generated by Otter.ai and Zoom Meetings. The presentation will highlight both the benefits and challenges of AI-based notes and transcription software, including technical concerns and the convenience of automated result delivery. The audience will enhance their understanding of AI tools in qualitative data transcribing and the ethical considerations in the process. Rebecca Bryant Penrose will showcase the use of HeyGen, an AI-based video generator and translation tool, in an international interview project between students at California State University Bakersfield and a Ukrainian artist/author. The presentation will increase awareness of the potential use of AI-based video and help researchers overcome language barriers in data collection. The panel will last 90 minutes, including a 5-minute introduction and a 5-minute wrap-up. Each panelist will have 10 minutes to present their topics, followed by 5-minute Q&As. A 25-minute moderated roundtable discussion will follow the panelists’ presentations to explore the potential use of different AI tools in research, including ChatGPT and AI-powered article summarizers. The panel’s learning outcomes include (1) Identifying challenges and opportunities to incorporate AI tools in research and study and (2) Explaining how to interact with AI tools to improve efficiency in research. It also provides a platform for doctoral students to share their knowledge of how AI changes research approaches and networks with each other.

System differential learning for detecting learning styles in science education for students with learning disabilities

The research aims to develop a Differential System Learning (SIDILAN) effective for students to learn Disabilities (LD) in science learning. SIDILAN is designed to detect students' learning styles that suit their unique needs, especially those with difficulty understanding science concepts. The research method used is the ADDIE Model, an abbreviation for the five stages of the development process: Analysis, Design, Development, Implementation, and Evaluation. The implementation stage of ADDIE SIDILAN was implemented on 68 prospective teacher students in Indonesia aged 20-22 years, and they were then given a questionnaire to respond. The study results showed that the development of the SIDILAN online URL https://s.id/SIDILAN can be used to detect students' learning styles in science learning. Based on the student response questionnaire to SIDILAN for Learning Disability (LD), information was obtained that LD A for the Indicator of Understanding and Engagement was 84.31%, LD B for the Indicator of Effectiveness 87.25%, LD C for the Indicator of Skills and Self -Development of 92.65% and LD D for Indicator of Satisfaction and Recommendation of 95.59%. The findings indicate that SIDILAN effectively improves the quality of learning by offering personalized learning styles according to their needs, creating a more inclusive and supportive educational environment for students with learning disabilities. The study suggests that SIDILAN should be integrated into special education programs as an innovative solution to support the science learning process for students with special needs.

초등학생의 학습 동기와 학습 의지의 관계

Objectives The purpose of this study is to explore the relationship between elementary school students' learning motivation and learning volition. Specifically, by analyzing the impact of learning motivation on learning volition, we identified the role of learning motivation as a strategy to enhance elementary students' learning volition. Additionally, we provided concrete recommendations divided into teacher, school, and parent levels. Methods To investigate the relationship between learning motivation and learning volition, 216 elementary school students were surveyed to measure these variables. Correlation analysis and regression analysis were conducted to analyze the impact of learning motivation on learning volition. Results The results of the regression analysis indicated that learning motivation has a significant effect on learning volition. In particular, among the sub-dimensions of learning motivation, achievement motivation and self-efficacy positively influenced the sub-dimensions of learning volition, which include behavioral control, learning effort, and learning perseverance. It was confirmed that the higher the learning motivation, the higher the learning volition. Conclusions This study suggests that enhancing learning motivation is important for improving elementary school students' learning volition. Specifically, teachers should provide personalized learning and emotional support to boost students' learning motivation and self-efficacy, and schools should establish support systems for customized educational programs and teacher capacity building to back this up. Parents should create an environment that enhances their children's learning motivation and supports self-directed learning. Through these efforts, concrete strategies to enhance students' learning volition should be sought.

Unveiling the Potential: Experts' Perspectives on Artificial Intelligence Integration in Higher Education

<p style="text-align:justify">This article investigates artificial intelligence (AI) implementation in higher education (HE) from experts' perspectives. It emphasises the view of AI's involvement in administrative activities in higher education, experts' opinions concerning the influence of the incorporation of AI on learning and teaching, and experts' views on applying AI specifically to assessment, academic integrity, and ethical considerations. The study used a qualitative method based on an unstructured qualitative interview with open-ended questions. The participants were thirteen individuals currently involved with higher education institutions and had various talents related to AI and education. Findings stress that implementing AI technology in administrative roles within higher education institutions is essential since it cuts costs, addresses problems efficiently and effectively, and saves time. The findings also revealed that AI plays a vital role in learning and teaching by speeding up the learning process, engaging learners and tutors, and personalising learning depending on the learner's needs within an entirely intelligent environment. AI can produce an accurate, objective, and suitable level of assessment. AI aids students in developing a stronger sense of integrity in their academic work by guiding them through AI-powered applications. AI must adhere to ethical laws and policies, ensuring its potential negative aspects are not overlooked or left unchecked.</p>

Large language models for whole-learner support: opportunities and challenges.

In recent years, large language models (LLMs) have seen rapid advancement and adoption, and are increasingly being used in educational contexts. In this perspective article, we explore the open challenge of leveraging LLMs to create personalized learning environments that support the "whole learner" by modeling and adapting to both cognitive and non-cognitive characteristics. We identify three key challenges toward this vision: (1) improving the interpretability of LLMs' representations of whole learners, (2) implementing adaptive technologies that can leverage such representations to provide tailored pedagogical support, and (3) authoring and evaluating LLM-based educational agents. For interpretability, we discuss approaches for explaining LLM behaviors in terms of their internal representations of learners; for adaptation, we examine how LLMs can be used to provide context-aware feedback and scaffold non-cognitive skills through natural language interactions; and for authoring, we highlight the opportunities and challenges involved in using natural language instructions to specify behaviors of educational agents. Addressing these challenges will enable personalized AI tutors that can enhance learning by accounting for each student's unique background, abilities, motivations, and socioemotional needs.

It’s all about the patients: a shift in medical students’ approach to learning during a novel distributed integrated clinical rotation

IntroductionTo ensure that pre-final year medical students at Stellenbosch University were able to resume clinical training during the COVID-19 pandemic, a 12-week integrated rotation was introduced, during which students were distributed across a widespread training platform in two provinces of South Africa, utilizing a range of health care facilities in both rural and urban areas, rather than the central academic hospital (CAH) in which they would have been doing clerkships. Called the Integrated Distributed Engagement to Advance Learning (IDEAL) rotation, this clerkship was based on supervised engagement in healthcare services, focusing on patient-based clinical training, self-regulated learning and student participation as integral members of clinical teams. The success of this emergency intervention has led to its formal incorporation into the medical curriculum. This study aimed to understand the factors that influenced learning among students undertaking the IDEAL rotation at multiple sites on a distributed training platform.MethodsUsing an interpretive paradigm, we sought to conduct focus group interviews with students who completed the first iteration of the IDEAL rotation in the year after they had undertaken it to understand their experiences. All 252 students who were eligible were invited to participate by email on several occasions. Ultimately three focus group discussions and two individual interviews were undertaken, based on volunteers. Using a semi-structured interview guide, these explored student perceptions of their learning and growth through the rotation. Inductive and deductive analysis was carried out to identify themes.FindingsStudent descriptions of their learning experiences coalesced in 6 themes. The rotation was an enabling learning experience, which was more practically focused and assisted students in developing confidence in their clinical skills. It was seen to be a humanizing learning experience with greater opportunities for the development of relationships with patients and families, as well as with health professionals, who made them feel part of the team, so it was also a more collegial learning experience. At the same time, it was a variable learning experience with a lack of standardization on a number of levels and challenges being experienced at particular sites regarding both logistics and the nature of the exposure. Students perceived it to be a very different learning experience from what they had encountered in the CAH in terms of relationships, the kinds of patients and problems they saw, and their active participation. Through this, they also learned more about themselves and their roles, making it a personal learning journey. The findings confirm the importance of the dimensions of person, participation and place for being and becoming a doctor in a clinical environment.ConclusionsStudent learning experiences in the IDEAL rotation emphasize the importance of context, reinforcing the value of a distributed training platform in developing health professionals who are responsive to their environment. They emphasize the vital role of active participation in learning and the centrality of relationships in medical training, helping to develop graduates who are human beings and not only human doings.

Determining the Influence of Digital Literacy on Learning Personal Competence: The Moderating Role of Fear of Missing Out

<p style="text-align:justify"><span style="font-size:9.0pt">One of the ways to enhance and improve the quality of learning delivery is through the use of technology, particularly the Internet, which facilitates faster and easier access to information. This research aims to explore the degree to which factors such as digital literacy, metacognitive awareness, meaningful learning, habits of using smartphones, and personal learning competence are related to one another. Both the relationship between metacognitive awareness and personal learning competence, as well as the relationship between smartphone habits and personal learning competence, are moderated by a moderating variable known as the fear of missing out. Fear of missing out is a moderating variable. Structural equation modeling, specifically partial least squares, was employed to analyze data from 597 engineering students. SmartPLS version 4 was the tool used for this analysis. The study found that the moderating variable, fear of missing out, significantly impacts metacognitive awareness, learning personal competence, and smartphone habits, making it a crucial factor to investigate. This result is significant because it is a variable that influences the learning that students go through for their education and because it is an extremely important thing to investigate.</span></p>

THE USE OF ARTIFICIAL INTELLIGENCE, VIRTUAL AND AUGMENTED REALITY IN TEACHING GEOGRAPHY IN SECONDARY SCHOOL

In today's innovative education, artificial intelligence (AI), virtual reality (VR) and augmented reality (AR) technologies are increasingly emerging as powerful tools to enhance the learning experience, especially in the teaching of geography in primary schools. This research explores how these technologies are being used to improve geography teaching and stimulate students' interest. AI brings personalised learning where content is adapted to individual learners' needs. Easier access to information, better visualisation of content, and help with analysis and interpretation make learning more accessible for students. At the same time, the ease of recreating content and the help in tracking individual learners' progress allows teachers to adapt learning strategies better and provide additional resources according to individual needs. VR and AR technologies help to create more interactive and realistic learning environments. Virtual reality allows learners to experience geographical phenomena more directly, while augmented reality complements the real world with digital information that can enrich the understanding of geographical concepts. These technologies focus on creating interactive content, virtual field trips, simulations of natural phenomena, and encouraging student participation and interest. The study also discusses challenges and solutions related to introducing AI in school geography, such as access to technology, teacher training and professional development, curriculum adaptation and ethical dilemmas. AI, VR and AR technology enable a new, at least in Slovenia, technologically sophisticated approach to teaching geography in primary schools. It encourages students to explore, interact and better understand complex geographic content. Keywords: geography education, artificial intelligence, virtual reality, augmented reality, interactive content