教育学最新文献

Introduction: The use of large language models (LLMs) such as ChatGPT to generate multiple-choice questions (MCQs) for medical and dental education is rapidly increasing. However, the educational validity, cognitive depth, and practical usability of AI-generated questions remain underexplored in dental education. This study aimed to evaluate the performance of ChatGPT-4o in generating MCQs for pre-doctoral oral and maxillofacial radiology curricula.

Methods: ChatGPT-4o was prompted to generate 100 multiple-choice questions based on lecture materials from a pre-doctoral oral and maxillofacial radiology course. A panel of expert oral radiologists independently evaluated the quality of the questions, answers, and explanations. Additionally, a randomised subset of 64 MCQs was assessed by human experts and an AI-detection tool to determine the accuracy of source identification.

Results: Experts rated 43% of AI-generated questions and 65% of their corresponding answers as correct and usable with minor adjustments. Most questions focussed on knowledge recall, with few assessing higher order thinking skills. Both human experts and AI-detection tools struggled to accurately differentiate between AI-generated and human-created questions.

Conclusion: While ChatGPT-4o can generate MCQs, its output often requires refinement. Future research should explore ways to improve the quality and cognitive level of AI-generated questions for dental education.

Pedagogical content knowledge (PCK) refers to educators' understanding of subject matter integrated with teaching approaches that ensure teaching effectively supports learners' needs. Anatomy demonstrators are temporary or sessional early career educators responsible for facilitating the full spectrum of anatomical learning, yet their understanding and application of PCK are poorly understood. Given the educational value of PCK, this study sought to explore demonstrators' understanding of PCK and identify factors influencing their PCK development. The 11 study participants were current and former anatomy demonstrators at an Australian medical school. Data were collected through seven semi-structured group and individual interviews and analyzed through reflexive thematic analysis using PCK components as the conceptual framework. Three themes were developed: (1) PCK Familiarity, (2) PCK in practice, and (3) Factors influencing PCK development. While demonstrators had limited explicit familiarity with the PCK concept, multiple PCK elements were implicit within descriptions of their educational practice, such as how their knowledge of content, students and context influenced their specific approach. Factors influencing demonstrator PCK development included educational experience, peer collaboration, reflective practice, embodying feedback and development time. Despite anatomy demonstrators having limited teaching experience, this study highlights the application of several components of PCK within their teaching practices. However, there is a considerable opportunity to further develop this group's PCK and thereby the support of learners. Key implications for demonstrators' supervisors and mentors include supporting professional development opportunities such as educational fellowships, encouraging and facilitating reflective practice, and including PCK in role performance standards.

Introduction: Peripheral intravenous catheterisation is a complex procedure that is primarily performed by nurses in healthcare services. Peripheral intravenous catheterisation (PIVC) is also part of the updated 2024 Core Program in the National Dental Education catalogue. This study aimed to implement this practice and to evaluate the approach and compliance of students with IV catheterisation.

Method: This study included 122 final-year dentistry students with no previous experience of intravenous catheterisation. The volunteers were randomly divided into three groups: model arm group, game-based learning group and combined group. A questionnaire was completed by the students after the training sessions. In addition, the success of the model arm group and the combined group was compared.

Results: The training appeared beneficial across all groups. In particular, combined methods (game-based learning and model arm application) and hands-on teaching methods (model arm) were perceived by students to be more effective. The majority of students (77.5%) stated that both methods (game-based learning and model arm practice) contributed equally. After the training, all groups were most likely to say that they could do this practice again with a supervisor. Participants in all groups indicated that they had sufficient or partially sufficient knowledge after the training.

Conclusion: Most participants reported that training increased their confidence in performing intravenous cannulation. This finding highlights the success of the training programme in enhancing the practical skills of students.

Purpose: Given varying preference signal numbers and structures across residency specialties, this study investigates the impact of preference signaling on match outcomes in highly competitive medical specialties.

Method: Data were from University of Texas Southwestern Medical School's Texas Seeking Transparency in Application to Residency survey of applicants to the top 10 most competitive specialties using signaling between 2021 and 2024. Bivariate statistical testing compared groups across categorical and continuous variables. Multivariate logistic regression compared outcomes between 10 or fewer and 20 or more signals.

Results: The dataset contained 4,469 applications from 4,391 unique students. Number of signals used did not affect number of overall matches (2,458 of 2,908 [84.5%] for 3-5 signals, 94 of 112 [93.9%] for 6-10 signals, 178 of 203 [86.7%] for 21-25 signals, and 585 of 662 [88.4%] for 26-30 signals; P = .08). Higher signal numbers were associated with significantly higher matching rates at signaled institutions (916 of 2,098 [37.2%] vs 525 of 662 [89.6%], P < .001). Away rotations (odds ratio [OR], 9.25; 95% CI, 6.37-13.43; P < .001), signaling gold (OR, 7.74; 95% CI, 3.85-15.55; P < .001), geographic connections (OR, 4.12; 95% CI, 3.01-5.64; P < .001), and signaling programs (OR, 3.38; 95% CI, 2.43-4.68; P < .001) were significantly associated with matching. Away rotations were ranked as most important (β = 2.23) followed by gold signals (β = 2.05), geographic connection (β = 1.42), and program signals (β = 1.22). Program signals had a stronger impact for applicants with 10 signals or fewer vs 20 signals or more (OR, 5.99 [95% CI, 3.96-9.08] vs 3.00 [95% CI, 1.33-6.77]; P < .001).

Conclusions: Specialties with more signals favor successful matching to signaled programs, but signal effectiveness diminishes as quantity increases. Applicants should prioritize impactful strategies to improve their chances of matching.

Purpose: Clinician educators are essential to the academic medicine workforce, yet understanding how they assess their own teaching competencies is limited. The Clinical Educator Milestones (CEMs) guide growth across key educator domains, but their use and perceived relevance remain underexplored. This study aims to (1) evaluate clinician educators' self-reported performance on the CEMs; (2) examine differences by career level, specialty, and experience; and (3) inform faculty development efforts through a clearer understanding of educators' perceived strengths and gaps.

Method: Clinician educators from 9 US academic institutions completed a self-assessment rating their performance across 4 universal pillars and 11 educational theory and practice competencies on a 1- (novice) to 5- (expert) point scale in 0.5-point increments from August to November 2024. Descriptive statistics and mean difference tests were used to analyze variation across demographic and professional characteristics.

Results: A total of 484 responses to at least 1 CEM were received. Respondents rated themselves highest in commitment to professional responsibilities (mean [SD], 4.30 [0.68]), teaching and facilitating learning (mean [SD], 3.96 [0.74]), and professionalism (mean [SD], 3.93 [0.73]) and lowest in medical education scholarship (mean [SD], 3.11 [1.15]), program evaluation (mean [SD], 3.33 [1.03]), and the science of learning (mean [SD], 3.43 [1.10]). Statistically significant group differences were found by years of posttraining clinical experience (F2,413 = 16.87, P < .001, η2 = .076), years of teaching experience (F2,433 = 20.87, P < .001, η2 = .088), and academic rank (F2,403 = 13.96, P < .001, η2 = .065).

Conclusions: This study identifies key trends in self-perceived strengths and needs among clinician educators and highlights the limited awareness of the CEM framework. As institutions aim to build effective educator development systems, the CEMs can serve as a useful structure for tailoring support to individuals and identifying institutional needs.