JMIR Medical Education

Opportunities to practice low-frequency skills for high-acuity pediatric emergency procedures in clinical settings are limited. The Basic Emergency Skills Techniques 3N1 (BEST 3N1) workshop was designed as a structured, hands-on training program to support procedural skill development among pediatric emergency care practitioners.

The term “experience” is widely used in health education literature. However, it has not been explicitly defined in this field, which could lead to multiple interpretations by researchers, teachers, and health students. Philosophical works offer clear definitions of “experience,” which can provide useful theoretical insights for its appropriation in research, practice, and teaching. Notably, pragmatist, rationalist, and phenomenological philosophers John Dewey, Georges Canguilhem, and Maurice Merleau-Ponty define experience as the significance that emerges during the interaction between a subject and its environment. They distinguish between episodic (making an experience) and cumulative (acquiring experience) dimensions. The article further explores the implications of this definition in health education, particularly in relation to experiential learning, simulation-based education, and assessment. This conceptualization has also paved the way for a method of exploring experience designed to facilitate awareness, known as the “explicitation interview.” Studies using this method have yielded interesting results in understanding the activities of students, health care professionals, and patients in real-life situations, particularly regarding the influence of context on reasoning and decision-making. The explicitation interview can also be used as a training tool through the supervision of past situations. Practical guidance for its implementation in educational settings is provided. Overall, highlighting individuals’ meaning-making processes opens new perspectives for research, teaching, and assessment in health professions education.

Effective communication, therapeutic relationships, and interprofessional collaboration are essential to high-quality occupational therapy (OT) practice. However, communication education across prelicensure and postlicensure OT training has not been comprehensively mapped.

Medical school curricula are managed through fragmented, static tools that prevent faculty and curriculum committees from seeing a unified view of content scope, sequence, and licensing examination alignment. Governance relies on manual reporting that is neither timely nor consistent, and no widely adopted platform incorporates a generative AI agent that queries a relational curriculum database to produce tailored, on-demand reports.

The fundamental goal of medical education is to develop physicians who can independently provide safe and effective patient care. This requires learners to acquire not only knowledge but also meaningful experience to progress along the continuum from novice to expert. In the last several decades, however, medical education has undergone numerous transformations that have resulted in decreased clinical experience for medical students and residents alike. These transformations include the increasing complexity of health care delivery in the inpatient and outpatient settings; duty hour restrictions; and the explosion of digital technologies, including the electronic health record and AI. Additionally, the introduction and broad acceptance of competency-based medical education, which is focused on demonstrable behaviors rather than the time spent in training, risks exacerbating this loss of meaningful clinical experience if implemented without attention to trainees’ need for clinical volume, variation, and redundancy. While these changes in the number and intensity of patient encounters in educational programs are multifactorial in origin, when combined, they jeopardize the acquisition of experience, the development of expertise, and the resulting quality of patient care. In this Viewpoint, our aim is to discuss the importance of meaningful experience in the development of expertise; highlight threats to its achievement resulting from the intersection of 3 transformations affecting medical training (the increased complexity of 21st-century health care systems, expansion of the electronic medical record and AI, and flawed understanding of the full implications of competency-based medical education as presently implemented); and present solutions for medical educators, academic institutions, and accrediting bodies. Our views are based on our perspectives and observations, as well as insights from the literature.

Despite the increasing use of liver contrast-enhanced ultrasound (CEUS), no standardized, organ-specific tool exists for assessing trainees’ cognitive competency. Existing instruments lack multidimensional evaluation and external validation, which limit training quality and patient safety.

AI is reshaping the landscape of medical education, yet the widespread adoption of general-purpose AI tools in student learning raises substantial concerns about curricular alignment, information accuracy, and the absence of pedagogical scaffolding.

Generative AI (GenAI) expands possibilities for content generation, feedback, personalization, and instructional support in higher education. Its growing use also challenges established assumptions about teaching, assessment, professional expertise, academic integrity, and educational responsibility. Although research has examined technology adoption and AI competencies, less is known about how educators experience and interpret the pedagogical transformation associated with GenAI in everyday teaching.

Large language models (LLMs) are increasingly used to generate case-based materials for health professions education (HPE). Previous reviews have examined broad applications in HPE or focused on clinical cases, but none have comprehensively synthesized the generation and evaluation of diverse case-based materials.

Large language model–based virtual-patient systems score history-taking practice, but whether scores correspond to independently scored examination performance remains untested. Existing evaluations emphasize internal platform metrics or simulated-patient fidelity, leaving criterion-related evidence limited.

Mobile learning apps are increasingly used in medical education, but cross-national evidence on their longitudinal development and rating-based satisfaction patterns remains limited.

Short-answer questions (SAQs) effectively assess higher-order reasoning skills in medical education but face challenges in scalability due to time-intensive manual grading and concerns about interrater reliability. Recent advances in large language models (LLMs) may offer a solution through automated assessment.