Children & education

While the extant research has provided a recipe for researchers to undertake thematic analysis (TA) in a theoretically and methodologically sound way, there has not yet been sufficient research to map out TA in the age of generative artificial intelligence (Gen AI). Building on and refining my 2020 article Applying thematic analysis to education: A hybrid approach to interpreting data in practitioner research published in International Journal of Qualitative Methods , which provides an example o

The integration of generative AI tools, such as ChatGPT, Gemini, and DeepSeek, into higher education offers transformative opportunities for personalised learning and academic productivity. However, their unregulated use raises concerns about academic integrity, critical thinking, and educational equity. This systematic review synthesises insights from 96 peer-reviewed articles, identifying six key intervention themes, namely, curriculum integration, policy and governance, faculty development, s

This study aims to deconstruct the complex relationship between artificial intelligence anxiety and generative AI adoption intention in the context of higher education. An extended analytical framework is constructed by integrating the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). Taking faculty and students from three universities in Sichuan Province as the research objects, data are collected through a questionnaire survey, and empirical

Introduction: Physical literacy is crucial for promoting lifelong engagement in physical activity. In response to rising childhood inactivity, this study explores the impact of traditional children's games on physical literacy within a school context. Methods: A quasi-experimental design was applied involving 60 students (aged 11-12) from two schools in Trabzon, Turkey. The experimental group participated in an 8-week program of culturally-rooted traditional games. The control group followed sta

The rise of artificial intelligence (AI) in education, particularly generative AI, challenges the sufficiency of the established Technological Pedagogical Content Knowledge (TPACK) framework. AI’s agentic autonomy, epistemic complexities, and ethical dimensions necessitate an evolved model. This study investigates the newly proposed Intelligent-TPACK (I-TPACK) framework, designed to address these gaps by integrating five knowledge domains: AI-Technological, AI-Content, AI-Pedagogical, Human-AI C

Artificial intelligence (AI) is reshaping how learning environments are designed and experienced, offering new possibilities for personalization, creativity, and immersive engagement. This systematic review synthesizes 43 empirical studies (Scopus, Web of Science) to examine the training needs and practices of primary and secondary education teachers for effective AI integration and overall professional development (PD). Following PRISMA guidelines, the review gathers teachers’ needs and practic

With the rapid advancement of educational digitalization, pre-service teachers' digital competence has become a critical prerequisite for adapting to modern teaching practices and promoting high-quality education. This systematic review provides a comprehensive analysis of research on the digital competence of pre-service teachers over the past decade (2014-2024). Drawing on 38 studies retrieved from the Web of Science and Scopus databases, it examines several key aspects, including publication

Introduction The aim of this systematic review is to examine the scientific literature published on digital reading and writing in higher education within the field of social sciences, assisted by generative artificial intelligence. Methods The PRISMA methodology and the SALSA Framework were applied, based on a bibliographic search conducted in the Scopus and Web of Science databases. Journal articles that explicitly addressed the established topic, published between 1 January 2023 and 7 March 2

Background Grit, defined as perseverance and passion for long-term goals, is a vital psychological trait that contributes to academic success and overall wellbeing. At the same time, regular PA supports physical and mental health, yet its engagement often declines among university students. Although grit has been linked to health-promoting behaviors, the mechanisms underlying this association remain unclear. This study investigated the mediating role of self-efficacy from a variable-centered per

This review examines the role of artificial intelligence (AI) agents in programming education, focusing on how these tools are being integrated into educational practice and their impact on student learning outcomes. An analysis of 58 peer-reviewed studies published between 2022 and 2025 identified three primary categories of AI agents: chatbots, generative AI (GenAI), and intelligent tutoring systems (ITS), with GenAI being the most frequently studied. The studies report that the primary instru

ABSTRACT Background Despite growing attention to English education in Bangladesh, conventional classroom instruction often fails to meet learners' diverse needs or ensure effective language development. Informal digital learning of English (IDLE) has emerged as a promising avenue for fostering learners' affective experience and enhancing proficiency beyond formal classroom settings. Nevertheless, empirical evidence on how Bangladeshi learners participate in and experience self‐directed language

Artificial intelligence (AI) is increasingly embedded in education through adaptive platforms, intelligent tutoring systems, and generative tools. While these technologies promise efficiency and personalization, they also raise concerns about pedagogical deskilling, reduced teacher autonomy, and ethical risks. This paper conceptualizes the potential impacts of AI on teaching expertise and instructional design through the lens of Cognitive Load Theory (CLT). The aim is to conceptualize how AI may

As an important development in CALL, artificial intelligence (AI)-assisted foreign language teaching not only offers unique advantages in leveled reading, vocabulary, pronunciation, self-assessment, personalized testing, and information retrieval but also effectively enhances learner interaction and emotional regulation in reading. Despite these advancements, research on learner emotional engagement in AI-augmented EFL reading instruction remains limited, and there is a lack of sufficient empiri

Integrating artificial intelligence (AI) into higher education can revolutionise traditional learning paradigms by enhancing self-directed learning and fostering student autonomy. This systematic research paper examines the role of AI in supporting these educational shifts, analysing its impact on student engagement, personalised learning experiences and academic performance. Through a comprehensive review of existing literature, this study explores various AI-driven tools and applications that

Artificial intelligence (AI) is changing how we teach and learn, generating excitement and concern about its potential to transform education. To contribute to the debate, this systematic literature review examines current research trends (publication year, country of study, publication journal, education level, education field, and AI type), as well as the benefits and challenges of integrating AI into education. This review analyzed 155 peer-reviewed empirical studies published between 2015 an

In an age when machine learning and artificial intelligence are broadly employed, traditional statistics can still provide insightful information and results quickly and at a low computational cost. Statistics, in fact, offers many useful tools to researchers, including a series of univariate statistical tests that can identify relationships between pairs of numeric samples: Student's t-test, Mann-Whitney U test, Chi-squared test, and Kruskal-Wallis test. These tests generate several outcomes, i

Abstract Artificial intelligence (AI)-based learning tools are increasingly integrated in higher education, offering benefits such as personalized learning experiences, real-time feedback, and increased flexibility. However, effective design and implementation strategies for these tools are not well established. This study addresses this gap through a systematic literature review with two main objectives: (1) to summarize the design features of AI-based learning tools currently employed in highe

Introduction Generative Artificial Intelligence (GenAI) is transforming education by enabling personalized learning and more efficient teaching practices. However, it raises critical ethical concerns, including data privacy, algorithmic bias, and educational inequality, requiring comprehensive regulatory frameworks and pedagogical strategies. Methods A Systematic Literature Review (SLR) was conducted, analyzing 53 peer-reviewed articles published between 2020 and 2024. The search was performed i

This paper provides a systematic and in-depth examination of large language models (LLMs) in the healthcare domain, addressing their significant potential to transform medical practice through advanced natural language processing capabilities. Current implementations demonstrate LLMs' promising applications across clinical decision support, medical education, diagnostics, and patient care, while highlighting critical challenges in privacy, ethical deployment, and factual accuracy that require re

Abstract The release of ChatGPT in late 2022 marked the beginning of a rapid transformation in higher education, soon followed by the development of multimodal generative AI programs. As this technology becomes increasingly integrated into teaching and learning, it is crucial to evaluate its current use and impact. This systematic literature review captures the initial academic response to generative AI, providing insights into how higher education has adopted this transformative technology in i

BACKGROUND/OBJECTIVES: Artificial intelligence (AI)-enabled digital interventions are increasingly used to expand access to mental health care. This PRISMA-ScR scoping review maps how AI technologies support mental health care across five phases: pre-treatment (screening), treatment (therapeutic support), post-treatment (monitoring), clinical education, and population-level prevention. METHODS: We synthesized findings from 36 empirical studies published through January 2024 that implemented AI-d

The use of artificial intelligence in education (AIEd) has grown exponentially in the last decade, particularly intelligent tutoring systems (ITSs). Despite the increased use of ITSs and their promise to improve learning, their real educational value remains unclear. This systematic review aims to identify the effects of ITSs on K-12 students' learning and performance and which experimental designs are currently used to evaluate them. The 28 studies analyzed in this systematic review included a

The rapid integration of Generative Artificial Intelligence (GenAI) into educational contexts has presented both opportunities and challenges for students seeking and using feedback. While AI-generated feedback can offer increased access, timely responses and personalised insights, concerns about the quality of AI-generated feedback still persist, including issues of bias, factual inaccuracies, and homogenisation. This study investigates how students use, value and trust AI-generated feedback co

In the rapidly evolving landscape of healthcare technology, Co-Intelligence: Living and Working with AI, by Ethan Mollick, Ph.D. (an associate professor of management and academic director of Wharton Interactive, Wharton School, University of Pennsylvania), is a timely and insightful exploration of the symbiotic relationship between humans and artificial intelligence (AI). While not specifically tailored for the medical field or anesthesiology, this book offers valuable perspectives that may res

BACKGROUND: The emergence of Artificial Intelligence (AI), particularly Chat Generative Pre-Trained Transformer (ChatGPT), a Large Language Model (LLM), in healthcare promises to reshape patient care, clinical decision-making, and medical education. This review aims to synthesise research findings to consolidate the implications of ChatGPT integration in healthcare and identify research gaps. MAIN BODY: The umbrella review was conducted following Preferred Reporting Items for Systematic Reviews

As a new type of artificial intelligence, ChatGPT is becoming widely used in learning. However, academic consensus regarding its efficacy remains elusive. This study aimed to assess the effectiveness of ChatGPT in improving students’ learning performance, learning perception, and higher-order thinking through a meta-analysis of 51 research studies published between November 2022 and February 2025. The results indicate that ChatGPT has a large positive impact on improving learning performance ( g

Abstract Artificial intelligence (AI) technologies are advancing swiftly, both in terms of quantity and quality. Students must possess a solid understanding, abilities, and skills to successfully employ them. Therefore, the purpose of this quantitative study is to examine students’ AI literacy, including AI technological understanding, its practical application, critical appraisal, and its effects on students’ AI output quality, self-efficacy, and academic performance. Moreover, this research ex

Abstract Artificial intelligence (AI) holds significant potential for enhancing student learning. This reflection critically examines the promises and limitations of AI for cognitive learning processes and outcomes, drawing on empirical evidence and theoretical insights from research on AI-enhanced education and digital learning technologies. We critically discuss current publication trends in research on AI-enhanced learning and rather than assuming inherent benefits, we emphasize the role of i

BACKGROUND: To analyze medical students' perceptions, trust, and attitudes toward artificial intelligence (AI) in medical education, and explore their willingness to integrate AI in learning and teaching practices. METHODS: This cross-sectional study was performed with undergraduate and postgraduate medical students from two medical universities in Beijing. Data were collected between October and early November 2024 via a self-designed questionnaire that covered seven main domains: Awareness of

problems in student retention and critical thinking in 206 vocational education students in the Akwa Ibom State, Nigeria. The results showed that AI posed significant threats to the male students showing more concern than their female peers. While AI aids vocational education, it has the potential to reduce cognitive engagement because the students may accept passively the information provided by AI without critical scrutiny (Ododo et al., 2024). The study emphasizes the need for AI-powered lear

INTRODUCTION: The integration of artificial intelligence (AI) in healthcare has transformed clinical practices and medical education, with technologies like diagnostic algorithms and clinical decision support increasingly incorporated into curricula. However, there is still a gap in preparing future physicians to use these technologies effectively and ethically. OBJECTIVE: This scoping review maps the integration of artificial intelligence (AI) in undergraduate medical education (UME), focusing

This systematic literature review rigorously evaluates the impact of Generative AI (GenAI) on academic integrity within higher education settings. The primary objective is to synthesize how GenAI technologies influence student behavior and academic honesty, assessing the benefits and risks associated with their integration. We defined clear inclusion and exclusion criteria, focusing on studies explicitly discussing GenAI’s role in higher education from January 2021 to December 2024. Databases in

Generative AI (hereinafter GenAI) technology, such as ChatGPT, is already influencing the higher education sector. In this work, we focused on the impact of GenAI on the academic integrity of assessments within higher education institutions, as GenAI can be used to circumvent assessment approaches within the sector, compromising their quality. The purpose of our research was threefold: first, to determine the extent to which the use of GenAI can be detected via the marking and moderation process

BACKGROUND: Artificial intelligence (AI) is rapidly transforming health care, offering substantial advancements in patient care, clinical workflows, and nursing education. OBJECTIVE: This umbrella review aims to evaluate the integration of AI into nursing practice and education, with a focus on ethical and social implications, and to propose evidence-based recommendations to support the responsible and effective adoption of AI technologies in nursing. METHODS: We included systematic reviews, sco

Abstract This study investigates the evolving landscape of Artificial Intelligence (AI) literacy, acknowledging AI's transformative impact across various sectors in the twenty-first century. Starting from AI's inception to its current pervasive role in education, everyday life, and beyond, this paper explores the relevance and complexity of AI literacy in the modern world. To evaluate the current state of the literature on AI literacy, a systematic literature review was conducted with the object

Artificial intelligence (AI) holds immense promise in revolutionising dentistry, spanning, diagnostics, treatment planning and educational realms. This narrative review, in two parts, explores the fundamentals and the multifaceted potential of AI in dentistry. The current article explores the profound impact of AI in dentistry, encompassing diagnostic tools, treatment planning, and patient care. The Part 2 of the article delves into the potential of AI in patient education, ethics and the FDI co

Abstract This study examined the guidelines issued by the top 50 U.S. universities regarding the use of Generative AI (GenAI) in academic and administrative activities. Employing a mixed methods approach, the research combined topic modeling, sentiment analysis, and qualitative thematic analysis to provide a comprehensive understanding of institutional responses to GenAI. Topic modeling identified four core topics: Integration of GenAI in Learning and Assessment, GenAI in Visual and Multimodal M

This study investigates the challenges hindering the implementation of Digital Transformation (DT) in Higher Education Institutions (HEIs) by thoroughly reviewing the literature. It identifies multiple dimensions and subdimensions of these barriers to offer valuable insights to help HEIs navigate their transformation processes successfully. By doing so, they can effectively address the changing requirements of students, faculty, administration, and other stakeholders in an increasingly digital e

Background/Objectives: This systematic review integrates Cognitive Load Theory (CLT), Educational Neuroscience (EdNeuro), Artificial Intelligence (AI), and Machine Learning (ML) to examine their combined impact on optimizing learning environments. It explores how AI-driven adaptive learning systems, informed by neurophysiological insights, enhance personalized education for K-12 students and adult learners. This study emphasizes the role of Electroencephalography (EEG), Functional Near-Infrared