Beware False Growth Mindset: Building Growth Mindset in Medical Education Is Essential but Complicated

Can Artificial Intelligence Coach Faculty to Utilize Growth Mindset Language? A Qualitative Analysis of Feedback Statements

INTRODUCTION

Feedback is at the core of competency-based medical education. Learner perceptions of the evaluation process influence how feedback is utilized. Systems emphasize a fixed mindset, prioritizing evaluation over growth. Embracing growth mindset culture, the belief that ability is acquired through effort and human capabilities can be developed over time, will allow learners to gain greater benefits from feedback. Transitioning from fixed mindset language (FML) to growth mindset language (GML) will require faculty training. Artificial intelligence (AI) can assist faculty with incorporating GML concepts in written feedback. The aim of this study was to assess the ability of AI to assist in changing FML feedback statements into statements with GML.

METHODS

A qualitative study was performed utilizing a sample of 83 summative and formative feedback statements provided to students (37) and residents (46) from surgery clerkship and national SIMPL-inguinal hernia evaluations. Of these 83 statements, a reviewer coded 41 statements as using GML and 42 using FML. Original statements identified as using FML were entered into the Google Chrome "Help me write" tool, a writing aid using Generative AI. The AI tool was prompted with the statement "rewrite using growth mindset language:," followed by an original FML statement. A dataset containing a combination of AI-altered and original statements, 99 statements in all, was provided to two additional blinded reviewers trained in GML concepts. Reviewers evaluated statements as predominantly GML or FML and commented on their perception of AI use in statements. Reviewer agreement was adjudicated by the original coder.

RESULTS

Of the 41 original GML statements, coders correctly identified 37 (90.2%) as using GML. Of the 26 original FML statements, coders correctly identified all 26 (100%) as using FML. Of the AI-modified FML to GML statements, coders correctly identified 17 of 18 (94.4%) as using GML. They correctly identified 56.3% as AI-modified and 44.8% as not AI-modified statements. They disagreed on AI use in 39.4% of statements. AI-assistance was unrecognized in 16 (8.1%) statements and mistaken for use in 47 (23.7%) statements.

CONCLUSIONS

AI was successful at modifying FML statements into feedback containing GML, and in a way that was not obviously AI-generated. This proof-of-concept study demonstrates that AI can be a helpful tool for faculty to increase the use of GML in written feedback. While AI cannot perfectly create GML feedback without initial input and understanding from faculty, it does serve as a promising educational aid. As the body of work on using GML in surgical education grows, the better AI can assist in the generation of quality feedback.

Strategic tips to successfully undertake research: a comprehensive roadmap for medical trainees

Engaging in research during medical training is crucial for fostering critical thinking, enhancing clinical skills, and deepening understanding of medical science. Despite its importance, the shortage of physician-scientists lingers with many trainees and junior doctors encountering challenges navigating the research process. Drawing on current literature, this article provides a comprehensive roadmap, categorising 12 actionable strategies into five themes, to help medical trainees overcome common obstacles and optimise their research experience. The strategies include early planning, research conduct and integrity, productivity and time management, collaboration and dissemination, and personal growth and development. By implementing these evidence-based recommendations, derived from current literature and expert insights, medical trainees can refine their research skills, produce high-quality outputs, and contribute meaningfully to the scientific community, ultimately enriching their medical training and future careers.

Lifelong Learning Indicators in Medical Students After a Novel Communication Skills Session

CONTEXT

A growth mindset and mastery approach have gained attention as useful learning orientations in medical education, however few studies of interventions to foster these orientations exist.

OBJECTIVES

We sought to discover whether a communication skills session on delivering serious news could foster a communication growth mindset and/or a mastery approach in medical students.

METHODS

This was an interventional survey study of third-year medical students before and after a session on delivering serious news. Students were administered a communication mindset survey before and after the session; achievement goal and learning environment surveys were administered after the session. Chi-square tests were used to assess the difference in pre and post mindsets. Logistic regression was used to determine the odds of achieving a mastery approach with pre- and post-communication growth mindset as the independent variables.

RESULTS

Students' communication growth mindset increased from 79% (n = 186) before the intervention to 92% (n = 142) after the intervention. Achievement goal analysis demonstrated that 64% (n = 91) of students had a mastery approach, 14% (n = 20) had a performance approach and 22% (n = 32) had an avoidant approach. Ninety-nine percent (n = 151) felt the session provided a safe learning environment. The odds of having a mastery approach correlated with both pre and post-intervention growth mindset, with post-session growth mindset having the strongest correlation.

CONCLUSIONS

A novel communication skills session on delivering serious news fostered a communication growth mindset in third year medical students. Most students exhibited a mastery approach to learning; this approach was more likely when they had a growth mindset.