Whose problem is it anyway? Confronting myths of ‘problems’ in health professions education

Abstract

Introduction:The growing interest in knowledge translation and implementation science, both in clinical practice and in health professions education (HPE), is reflected in the number of studies that have sought to address what are believed to be evidence-practice gaps. Though this effort may be intended to ensure practice improvements are better aligned with research evidence, there is a common assumption that the problems researchers explore and the answers they generate are meaningful and applicable to practitioner needs.Methods: This Mythology paper considers the nature of problems from HPE as the focus of HPE research and the ways in which they may or may not be aligned. The authors argue that, in an applied field such as HPE, it is vital that researchers better understand how their research problems relate to practitioner needs and what the limitations on evidence uptake might be. Not only can this establish clearer paths

A Case Study on the Generative AI Project Life Cycle Using Large Language Models

“…To perform this prompt engineer-ing, fine-tuning parameters, and human reinforcement learning from human feedback (RLHF) techniques are used to meet specific needs [4]. Prompt Engineering is the process of designing effective prompts or inputs for language models to generate desired outputs, particularly for those based on the Transformer architecture like GPT (Generative Pre-trained Transformer) models [19]. Language models like GPT are trained to generate text based on the input they receive, making the quality and specificity of the input.…”