Artificial Intelligence in Health Professions Education

In this study, we review 1830 research articles on artificial intelligence in education (AIED), with the aim of providing a holistic picture of the knowledge evolution in this interdisciplinary research field from 2010 to 2019. A novel three-step approach in the analysis of the keyword co-occurrence networks (KCN) is proposed to identify the knowledge structure, knowledge clusters and trending keywords within AIED over time. The results reveal considerable research diversity in the AIED field, centering around two sustained themes: intelligent tutoring systems (2010-19) and massive open online courses (since 2014). The focal educational concerns reflected in AIED research are: (1) online learning; (2) game-based learning; (3) collaborative learning; (4) assessment; (5) affect; (6) engagement; and (7) learning design. The highly connected keywords relevant to analytic techniques within this field include natural language processing, educational data mining, learning analytics and machine learning. Neural network, deep learning, eye tracking, and personalized learning are trending keywords in this field as they have emerged with key structural roles in the latest two-year period analyzed. This is the first article providing a systematic review of a large body of literature on artificial intelligence in education, and in it we uncover the underlying patterns of knowledge connectivity within the field, as well as provide insight into its future development. The three-step multi-scale (macro, meso, micro) framework proposed in this study can also be applied to map the knowledge development in other scientific research areas.

In recent years, the integration of Informatics and Didactics in education has been revolutionized by the advent of Artificial Intelligence (AI). AI has the potential to reshape how educational content is delivered, how students learn, and how teachers manage classrooms. In the context of Morocco, where educational reforms are underway, the integration of AI into teaching methodologies offers exciting possibilities for improving the quality of education, enhancing personalized learning experiences, and addressing the challenges of educational equity. This article explores the intersection of Informatics, Didactics, and AI, examining how AI-driven tools are transforming education in Morocco. By providing examples of AI applications such as adaptive learning systems, intelligent tutoring systems, and AI-driven content creation, this article highlights the ways in which AI can complement traditional didactic approaches and create more interactive, inclusive, and personalized learning environments. We also discuss the challenges of integrating AI into the Moroccan education system, including infrastructure limitations, teacher preparedness, and ethical considerations. Finally, the article offers recommendations for successfully adopting AI in education and fostering a future-ready generation of learners. Keywords: Informatics, didactics, artificial intelligence, personalized learning, adaptive learning, Morocco, education reform, digital tools, intelligent tutoring systems, AI-driven content creation, future of education. Received Date: August 21, 2025 Accepted Date: September 13, 2025 Published Date: October 01, 2025 Available Online at: https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/216

Artificial intelligence of large ensembles of intelligent agents in terms of computing power surpasses human intelligence. He is capable of artificial thinking and understanding. Giant ensembles of intellectual agents with artificial consciousness and intelligence are able, for the results set by the person necessary for him, to find solutions for their obtaining on the basis of professional competence and experience accumulation. The professional competence of artificial intelligence is the ability to use technologies, including computer vision, natural language processing, speech recognition and synthesis, intelligent decision support, as well as the use of synergistic methods, functional self-organizing methods and utility and preference criteria. For artificial intelligence, the functional organization of the system is important. The functionalism of artificial intelligence does not depend on its carrier, allows many methods of its functional implementation, as well as to form the completeness of its functions. Giant ensembles of intellectual agents with a full set of functions gradually and flexibly form events into solutions or rational behavior to obtain a given necessary result. Intelligent artificial intelligence has psychological, analytical, research, language, professional and behavioral hybrid competencies. Each competence is exercised by an intelligent agent with a competent functional professional manner. Intelligent agents form an ensemble with intelligent ethical artificial intelligence. Functional harmonious self-organization of the interaction of intellectual agents in different environments is carried out on the basis of data of a specific environment obtained by analytical competent intellectual agents. For each set of functions and smart hybrid competencies of an intelligent ensemble, there is a critical importance for the number of its intellectual agents capable of synergistic self-organization of interaction.

Digital revolution and the resultant emergence of Industry 4.0 has driven the incorporation of Artificial intelligence (AI) in Industrial education to enhance skills development in the industry. However, there is a lack of adequate empirical evidence on the integration of Artificial intelligence in industrial education. To fill this gap, this study reviewed previous studies on the adoption of AI in Industrial education and examined the frequency of occurrence of variables obtained in the studies reviewed. Relevant literature was screened and reviewed to find empirical evidence to support findings. A systematic review of 14 studies provided insights into the current applications, benefit and challenges of AI integration in industrial education. The study found that the most cited applications of AI is Adaptive and personalised learning systems, which customise workers/learners’ information based on their interaction with learning content. Other applications are augmented simulators for real-time feedback, virtual mentors, and intelligent tutoring systems which replicate real-life interaction with professionals among others. Majority of the studies found increased engagement and improved learning outcomes and skills development as benefit of AI integration in Industrial education. Other benefits are promotion of early identification of learning challenges and timely intervention and feedback, improvement in administrative efficiency and support, personalisation of learning. Notable challenges were skills and capacity gaps, lack of infrastructure and AI resources, curriculum issues and difficulty in integrating AI into current curriculum, ethical and privacy concerns among others. Based on the findings of the study, it was recommended that the skill gap should be filled with training in AI applications and use, investment in AI infrastructural development should be explored, industry collaboration and partnership in the area of needs should be considered, AI marketing and literacy should be adopted in industries, all AI intervention should be a continuing and lifelong process to ensure sustainability.

Artificial Intelligence (AI) is a transformative field at the intersection of computer science, mathematics, and cognitive psychology.It involves the development of systems capable of performing tasks that typically require human intelligence, such as learning, problem-solving, perception, and decision-making.AI technologies, including machine learning, natural language processing, and robotics, are revolutionizing industries ranging from healthcare to finance, and reshaping the way we live, work, and interact with technology."In the 21st century, Artificial Intelligence (AI) has emerged as a transformative force reshaping various aspects of society and industry.With advancements in computing power, data availability, and algorithmic techniques, AI has made significant strides in enabling machines to perform tasks traditionally requiring human intelligence.One of the key drivers of AI progress in the 21st century has been machine learning, a subfield of AI that focuses on algorithms capable of learning from data and making predictions or decisions.Deep learning, a subset of machine learning that uses artificial neural networks with many layers, has particularly fuelled breakthroughs in areas such as image and speech recognition, natural language processing, and autonomous vehicles.AI applications have become pervasive across industries, revolutionizing sectors such as healthcare, finance, transportation, manufacturing, and entertainment.In healthcare, AI is being used for disease diagnosis, drug discovery, personalized medicine, and medical image analysis.In finance, it's employed for fraud detection, algorithmic trading, and customer service.Autonomous vehicles and smart transportation systems leverage AI for navigation, route optimization, and traffic management.Moreover, AI-driven virtual assistants like Siri, Alexa, and Google Assistant have become ubiquitous, enhancing user experience and productivity.AIpowered recommendation systems personalize content delivery on platforms like Netflix, Spotify, and Amazon, improving user engagement and satisfaction.However, alongside its transformative potential, AI raises ethical, social, and economic concerns.Issues such as job displacement due to automation, algorithmic biases, data privacy, and the potential misuse of AI for surveillance or military purposes require careful consideration and regulation.Overall, the 21st century has witnessed AI evolve from a theoretical concept to a practical technology with profound implications for society, promising both opportunities and challenges as it continues to advance. Artificial Intelligence and Human Society:Artificial Intelligence (AI) is deeply intertwined with human society, impacting various aspects of our daily lives, work, and culture.Here's how AI influences human society:1. Workforce Automation: AI technologies automate routine and repetitive tasks across industries, leading to increased efficiency and productivity.However, concerns about job displacement and the need for reskilling and upskilling arise as AI replaces certain human roles.2. Healthcare: AI applications in healthcare facilitate disease diagnosis, personalized treatment plans, drug discovery, and medical imaging analysis.AI-driven predictive analytics also help in identifying health risks and optimizing patient outcomes.3. Education: AI enhances education through personalized learning platforms, intelligent tutoring systems, and adaptive assessments tailored to individual student needs.It also enables the development of educational content and resources based on learner preferences and performance.4. Communication and Interaction: AI-driven virtual assistants, chatbots, and language translation services improve communication and accessibility.Natural language processing enables human-like interactions with AI systems, enhancing user experience and accessibility for people with disabilities.

In the recent years, the use of artificial intelligence in the education domain has experienced a significant growth. The main reasons for this are the numerous innovative solutions, products and services, which are used not only in the educational processes, but also in the corresponding to them administrative activities. Based on this, the present publication aims to present the latest trends and the applications of the artificial intelligence in the education sector. This research has led to the identification of several key areas, in which the artificial intelligence has a significant contribution to the educational processes, including the adaptive assessment, the intelligent tutoring systems, the educational data mining, the personalized learning, the virtual reality, etc. This publication also presents some of the potential benefits, challenges and ethical considerations, which are associated with the use of the artificial intelligence technologies in the education.

The study explored the impact of Artificial Intelligence (AI) on pedagogical style and instructional design of teachers in higher education institutions in Adamawa State, Nigeria. As AI is revolutionizing educational domains globally, this is an important area to unpack in terms of pedagogy and curriculum development in higher learning contexts within the region. The study investigates the integration of AI tools into the pedagogy, including personalized learning platforms, intelligent tutoring systems and learning analytics. Moreover, it examines the degree to which these technologies inform pedagogy, create sense of engagement, and direct the design of instruction in both traditional and virtual classrooms. Data is gathered based on surveys, interviews, and classroom observations with academic staff, administrators, and students in selected institutions. It is hoped that the findings will shed light on the challenges and opportunities posed by AI in education, as well as provide recommendations for enhancing AI adoption in teaching and learning practices in higher institutions in Adamawa State, Nigeria. This study adds to the wider conversation around digitalization in education, shedding light on practical different ways of integrating AI into teaching and instructional design.

The integration of Artificial Intelligence (AI) into teacher education has been transformative, offering personalized learning experiences, enhanced professional development, and improved teaching methodologies. AI technologies such as Intelligent Tutoring Systems (ITS), AI-driven analytics, and automated assessment tools have become central to modern educational practices, significantly improving engagement, adaptability, and effectiveness. This study employs a qualitative thematic analysis of current literature on AI in teacher education, examining peer-reviewed articles and reports using thematic coding to identify key patterns, opportunities, and challenges. The findings reveal that AI enhances teacher education by providing personalized learning pathways, fostering critical thinking, and supporting ongoing professional growth. Technologies like ITS, Virtual Reality (VR), and AI-driven analytics have proven effective in promoting motivation and engagement among teachers. However, ethical challenges such as biases in AI systems and concerns regarding data privacy require continuous attention. Furthermore, a gap in teacher preparedness, particularly in developing AI literacy and integrating AI tools into classroom practices, is evident. Despite these challenges, AI offers substantial benefits, transforming teaching practices and enabling personalized, adaptive instruction that supports both teachers and students. The study emphasizes the need for comprehensive teacher training programs focusing on digital literacy and ethical AI use, ensuring educators can navigate an AI-enhanced educational environment effectively. This research contributes to the ongoing discourse by highlighting the need for ethical guidelines and robust teacher training programs, offering actionable insights for educators, policymakers, and institutions aiming to integrate AI into teacher education

Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence

Health professions’ education (HPE) research has evolved within an academic ecosystem. This paper works to put forth that generative artificial intelligence (AI) and autonomous AI agents are exposing the underbelly of HPE. Two responses have emerged: disclosure frameworks that report AI use, and formation frameworks that assess researchers’ readiness to critically examine evolving knowledge systems being reshaped by AI. The field has emphasized the former while neglecting the latter. We argue that HPE necessitates more than disclosure policies. Training should assess researcher formation, including the ability to question evidence hierarchies, peer review, technology disruptions, and publication systems, rather than relying on research outputs alone for scholarly development.

The rapid advancement of artificial intelligence (AI) technologies has significantly reshaped educational systems and learning environments worldwide. In particular, the integration of AI into language education has created new opportunities for improving learning efficiency, enhancing personalized instruction, and facilitating interactive communication environments. In the context of globalization and international talent development, the ability to communicate effectively in English has become an essential competence for participating in global economic, cultural, and technological exchanges. However, traditional language education models often rely on teacher-centered instruction and standardized assessments, which may not fully address the diverse learning needs of students or provide sufficient opportunities for authentic communication practice. This study explores the role of artificial intelligence in empowering the development of English competence for international talents. Drawing upon theories of technology-enhanced learning, intelligent tutoring systems, and global competence development, the paper proposes a conceptual framework that illustrates how AI technologies can support language learning through multiple application scenarios. These scenarios include intelligent language tutoring systems, AI-mediated communication environments, automated language assessment systems, and data-driven learning analytics. Based on these application scenarios, the study further proposes an AI-empowered educational model that integrates artificial intelligence technologies with innovative pedagogical approaches to support the cultivation of international talents. The model emphasizes personalized learning pathways, adaptive instruction, and global communication platforms supported by AI systems. The study contributes to theoretical discussions on AI-supported language education and provides practical insights for cultivating internationally competitive talents in the era of digital transformation.

The integration of Artificial Intelligence (AI) into education is reshaping traditional teaching models by enabling unprecedented levels of personalized learning. In conventional classrooms, educators often face the challenge of addressing diverse student needs within uniform curricula. AI offers a transformative solution by tailoring content, pace, and instructional strategies to the unique cognitive profiles, preferences, and performance patterns of individual learners. Through adaptive learning algorithms, intelligent tutoring systems, natural language processing, and predictive analytics, AI facilitates a more responsive and learner-centric educational experience. This paper explores the multi-dimensional impact of AI on personalized education. It analyzes case studies and global implementations of AI-powered tools such as Squirrel AI in China, Mindspark in India, and adaptive platforms like DreamBox Learning in the United States. The findings highlight key benefits including improved academic performance, increased engagement, early identification of learning gaps, and enhanced teacher productivity. However, the deployment of AI in education also presents complex challenges—ranging from data privacy and algorithmic bias to digital inequity and the ethical implications of automation in pedagogy. Using a qualitative meta-analysis of over 90 peer-reviewed studies, policy documents, and EdTech deployments, this article critically evaluates the pedagogical, technological, and ethical dimensions of AI-driven personalization. The conclusion underscores the need for inclusive policy frameworks, teacher training, algorithmic transparency, and human-centered design to ensure that AI serves as a tool for equity rather than exclusion. With deliberate and responsible implementation, AI holds the potential to transform education into a truly personalized, inclusive, and empowering experience for all learners.

This study investigates the impact of artificial intelligence (AI) integration on student skills in educational environments. As AI-powered personalized learning platforms and intelligent tutoring systems become increasingly prevalent, they are reshaping skill development for learners. The research employs a descriptive and analytical design based on a comprehensive literature review of recent studies examining AI implementation across diverse educational contexts. Primary objectives focus on evaluating differential impacts on procedural versus conceptual understanding, analyzing relationships between AI usage frequency and independent problem-solving, examining metacognitive awareness development, and assessing the balance between efficiency gains and cognitive dependency patterns. Existing research indicates widespread adoption of AI tools among students and reports notable improvements in learning outcomes and academic performance in AI-enhanced environments. However, findings also reveal paradoxical effects on cognitive skills, where increased task accuracy may be accompanied by weaker conceptual understanding, raising concerns about over-reliance on AI and its potential impact on higher-order thinking development. The study concludes that AI serves as a powerful enabler for personalized learning but requires careful pedagogical integration to ensure balanced cognitive growth and prevent dependency. Recommendations include strategic AI literacy education, thoughtful curriculum design promoting critical engagement, and continuous assessment of long-term impacts.

Artificial Intelligence (AI) is rapidly reshaping the teaching–learning landscape across educational institutions worldwide. From intelligent tutoring systems and adaptive learning platforms to automated assessment and learning analytics, AI-driven technologies are redefining how knowledge is delivered, acquired, and evaluated. While AI offers unprecedented opportunities for personalized learning, enhanced instructional efficiency, and data-informed decision-making, it also introduces significant challenges related to equity, data privacy, algorithmic bias, and ethical governance. This research paper examines the transformative role of artificial intelligence in teaching–learning processes, focusing on pedagogical opportunities, implementation challenges, and ethical implications. Through a conceptual and analytical approach, the study explores how AI can enhance learning outcomes while emphasizing the need for responsible, inclusive, and ethical integration within educational systems. The findings suggest that AI, when thoughtfully implemented, can significantly improve teaching effectiveness and learner engagement, provided ethical safeguards and human-centered pedagogical values remain central.

Artificial Intelligence (AI) is not a new concept for Hospitality Industry and Recruitment functions. AI has displaced the human intervention in routine tasks. In few years, AI will take over several jobs (Kubler, 2018). Recently AI technologies support application screening, data analysis, and preliminary interviews, saving time of recruiters. Chatbots are now designated recruitment officers supporting candidates. Researchers have studied the influence of AI on Recruitment, but only a few focused on the AI displacing human in the recruitment function performed in UAE’s hospitality industry. This research aims to understand the transformation in the recruitment function of UAE’s hospitality industry due to AI intervention. Using concurrent mixed-methods, data was collected by interviewing 10 UAE HR leaders and surveying 135 HR professionals. The inductive-deductive thematic analysis was conducted for subjective measures and descriptive analysis was performed for scaled measures. This study found that UAE’s hospitality sector deployed AI technologies in recruitment areas such as job advertisements, collecting applications, maintaining profiles, and storing the applications. The routine, repetitive, and heavy-volume tasks in the recruitment are delegated to AI while strategic roles are retained for human professionals including development of strategies, and creation of job descriptions and specifications. While the literature review suggested a wider application of AI in recruitment function, UAE’s hospitality sector seems to be lagging. The recommendations will benefit industry leaders, HR professionals, recruitment consultants, and AI developers to rethink on the recruitment strategies, operations, and administration and to embrace the intervention of AI in recruiting the best talent proficiently.