Twelve tips on applying AI tools in HPE scholarship using Boyer's model.

AI has changed the landscape of health professions education. With the hype now behind us, we find ourselves in the phase of reckoning, considering what's next; where do we start and how can educators use these powerful tools for daily teaching and learning. We recognize the great need for training to use AI meaningfully for education.

Artificial Intelligence in Health Professions Education assessment: AMEE Guide No. 178.

Health Professions Education (HPE) assessment is being increasingly impacted by Artificial Intelligence (AI), and institutions, educators, and learners are grappling with AI's ever-evolving complexities, dangers, and potential. This AMEE Guide aims to assist all HPE stakeholders by helping them navigate the assessment uncertainty before them. Although the impetus is AI, the Guide grounds its path in pedagogical theory, considers the range of human responses, and then deals with assessment types, challenges, AI roles as tutor and learner, and required competencies.

Reflections From the Pandemic: Is Connectivism the Panacea for Clinicians?

The COVID-19 pandemic and the recent increased interest in generative artificial intelligence (GenAI) highlight the need for interprofessional communities' collaboration to find solutions to complex problems. A personal narrative experience of one of the authors compels us to reflect on current approaches to learning and knowledge acquisition and use solutions to the challenges posed by GenAI through social learning contexts using connectivism. We recognize the need for constructivism and experiential learning for knowledge acquisition to establish foundational understanding.

Preparing for Artificial General Intelligence (AGI) in Health Professions Education: AMEE Guide No. 172.

Generative Artificial Intelligence (GenAI) caught Health Professions Education (HPE) institutions off-guard, and they are currently adjusting to a changed educational environment. On the horizon, however, is Artificial Intelligence (AGI) which promises to be an even greater leap and challenge. This Guide begins by explaining the context and nature of AGI, including its characteristics of multi-modality, generality, adaptability, autonomy, and learning ability.

Submitting artificial intelligence in health professions education papers to Medical Teacher.

As any field evolves, so do journals' expectations from authors. As Artificial Intelligence (AI) usage in Health Professions Education (HPE) has evolved, 's expectations have changed, and previously-accepted paper types are now routinely rejected. This commentary gives some guidance for authors currently submitting AI in HPE papers to .

Regional variations in antimicrobial susceptibility of community-acquired uropathogenic in India: Findings of a multicentric study highlighting the importance of local antibiograms.

Objectives: Evidence-based prescribing is essential to optimize patient outcomes in cystitis. This requires knowledge of local antibiotic resistance rates. Diagnostic and Antimicrobial Stewardship (DASH) to Protect Antibiotics (https://dashuti.

Twelve tips on creating and using custom GPTs to enhance health professions education.

The custom GPT is the latest powerful feature added to ChatGPT. Non-programmers can create and share their own GPTs ("chat bots"), allowing Health Professions Educators to apply the capabilities of ChatGPT to create administrative assistants, online tutors, virtual patients, and more, to support their clinical and non-clinical teaching environments. To achieve this correctly, however, requires some skills, and this 12-Tips paper provides those: we explain how to construct data sources, build relevant GPTs, and apply some basic security.

Assessing ChatGPT's Mastery of Bloom's Taxonomy Using Psychosomatic Medicine Exam Questions: Mixed-Methods Study.

Background: Large language models such as GPT-4 (Generative Pre-trained Transformer 4) are being increasingly used in medicine and medical education. However, these models are prone to "hallucinations" (ie, outputs that seem convincing while being factually incorrect). It is currently unknown how these errors by large language models relate to the different cognitive levels defined in Bloom's taxonomy.

A checklist for reporting, reading and evaluating Artificial Intelligence Technology Enhanced Learning (AITEL) research in medical education.

Advances in Artificial Intelligence (AI) have led to AI systems' being used increasingly in medical education research. Current methods of reporting on the research, however, tend to follow patterns of describing an intervention and reporting on results, with little description of the AI in the system, or the many concerns about the use of AI. In essence, the readers do not actually know anything about the system itself.

Online learning in health professions education. Part 2: Tools and practical application: AMEE Guide No. 163.

Part 1 of the AMEE Guide focused on foundational concepts such as theory, methods, and instructional design in online learning. Part 2 builds upon Part 1, introducing technology tools and applications of these foundational concepts by exploring the various levels (from beginner to advanced) of utilisation, while describing how their usage can transform Health Professions Education. This Part covers Learning Management Systems, infographics, podcasting, videos, websites, social media, online discussion forums, simulation, virtual patients, extended and virtual reality.

's first ChatGPT's referencing hallucinations: Lessons for editors, reviewers, and teachers.

Students' inappropriate use of ChatGPT is a concern. There is also, however, the potential for academics to use ChatGPT inappropriately. After explaining ChatGPT's "hallucinations" regarding citing and referencing, this commentary illustrates the problem by describing the detection of the first known submission using ChatGPT inappropriately, the lessons that can be drawn from it for journal editors, reviewers, and teachers, and then the wider implications if this problem is left unchecked.

Online learning in Health Professions Education. Part 1: Teaching and learning in online environments: AMEE Guide No. 161.

Online learning in Health Professions Education (HPE) has been evolving over decades, but COVID-19 changed its use abruptly. Technology allowed necessary HPE during COVID-19, but also demonstrated that many HP educators and learners had little knowledge and experience of these complex sociotechnical environments. Due to the educational benefits and flexibility that technology can afford, many higher education experts agree that online learning will continue and evolve long after COVID-19.

The effect of watching lecture videos at 2× speed on memory retention performance of medical students: An experimental study.

Aim: This study aimed to determine how watching lecture videos at 1× and 2× speeds affects memory retention in medical students.

Methods: A posttest-only experimental design was utilized. The participants were 60 Year-1 and Year-2 medical students.

Ethical use of Artificial Intelligence in Health Professions Education: AMEE Guide No. 158.

Health Professions Education (HPE) has benefitted from the advances in Artificial Intelligence (AI) and is set to benefit more in the future. Just as any technological advance opens discussions about ethics, so the implications of AI for HPE ethics need to be identified, anticipated, and accommodated so that HPE can utilise AI without compromising crucial ethical principles. Rather than focussing on AI technology, this Guide focuses on the ethical issues likely to face HPE teachers and administrators as they encounter and use AI systems in their teaching environment.

Can Medical Students Evaluate Medical Websites?: A mixed-methods study from Oman.

Objectives: This study aimed to discover the extent to which medical students can evaluate medical websites, evaluation criteria used, factors affecting their abilities and whether a teaching intervention could rectify problems. Medical students and practitioners are required to evaluate medical information available on the Internet. Most current medical students are familiar with the Internet, but their ability to evaluate material may require improvement.

AMEE Guide to ethical teaching in online medical education: AMEE Guide No. 146.

The Covid-19 pandemic necessitated (ERT): the sudden move of educational materials online. While ERT served its purpose, medical teachers are now faced with the long-term and complex demands of formal online teaching. One of these demands is ethical online teaching.

Designing and developing an app to perform Hofstee cut-off calculations.

Determining a Hofstee cut-off point in medical education student assessment is problematic: traditional methods can be time-consuming, inaccurate, and inflexible.  To counter this, we developed a simple Android app that receives raw, unsorted student assessment data in .csv format, allows for multiple judges' inputs, mean or median inputs, calculates the Hofstee cut-off mathematically, and outputs the results with other guiding information.

How Have Researchers Acknowledged and Controlled for Academic Work Activity When Measuring Medical Students' Internet Addiction? A Systematic Literature Review.

Internationally, medical students' Internet Addiction (IA) is widely studied. As medical students use the Internet extensively for work, we asked how researchers control for work-related Internet activity, and the extent to which this influences interpretations of "addiction" rates. A search of PubMed, CINAHL, Web of Science, Scopus, and Google Scholar was conducted on the search phrase of "medical students" and "internet addiction" in March 2020.

They Shoot Horses, Don't They? A warning to medical schools about medical teacher burnout during COVID-19.

This article was migrated. The article was marked as recommended. The 1969 film, provides a contextual background for what appears to be happening to medical teachers as they attempt to cope with teaching during the COVID-19 pandemic, staving off the threat of exhaustion.

Medical student Internet usage: is the literature correct to call it addiction? An opinion piece.

Over the past few years, there has been a sharp rise in the number of academic articles examining "Internet addiction" among medical students. This opinion piece views the Internet as a communication environment and a medical information tool within medical education. Within this context, the paper investigates the Internet Addiction Test (IAT) and criteria used in those articles, and questions their assumptions and conclusions.

Artificial Intelligence developments in medical education: a conceptual and practical framework.

This article was migrated. The article was marked as recommended. As Artificial Intelligence (AI) develops in medicine, there is a greater awareness that medical education may also benefit from AI.