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Generative AI-Based Evaluation of Clinical Thinking and Decision-Making in Medical Students

30 de octubre de 2026 actualizado por: Danzhi Chen, Sir Run Run Shaw Hospital

Construction of an Intelligent Evaluation System for Clinical Thinking and Decision-making Ability of Medical Students Based on Generative Artificial Intelligence

The goal of this study is to develop and evaluate an intelligent system based on generative artificial intelligence (AI) for assessing clinical thinking and decision-making abilities in medical students.

The study will examine whether the AI-based evaluation system can provide reliable and valid assessments of medical students' performance in clinical scenarios. Participants will complete clinical case-based tasks designed to assess their clinical reasoning and decision-making abilities. Their responses will be evaluated using the AI-based system and compared with assessments made using established evaluation methods and/or expert ratings.

The findings of this study may help determine whether generative AI can be used as a practical tool for assessing clinical thinking and decision-making skills in medical education.

Descripción general del estudio

Descripción detallada

This study aims to develop and evaluate a generative artificial intelligence-based system for assessing clinical thinking and decision-making abilities in medical students. Clinical reasoning and decision-making are core competencies in medical education, but conventional assessment methods often require substantial faculty time and may be influenced by differences among evaluators.

The study will develop an intelligent evaluation framework using generative artificial intelligence to analyze medical students' responses to clinical case-based tasks. The system will assess key aspects of clinical thinking and decision-making, such as information interpretation, diagnostic reasoning, selection of appropriate management strategies, and overall decision-making logic.

Medical students participating in the study will complete standardized clinical scenarios or case-based assessment tasks. Their performance will be evaluated using the artificial intelligence-based system and compared with evaluations made by qualified clinical experts and/or established assessment methods. The study will examine the reliability, validity, consistency, and feasibility of the artificial intelligence-based evaluation approach.

The purpose of this study is to determine whether generative artificial intelligence can serve as a reliable and practical tool for evaluating clinical thinking and decision-making abilities in medical education. The system is intended for educational assessment and is not designed to replace clinical diagnosis or treatment decisions.

Tipo de estudio

Intervencionista

Inscripción (Actual)

90

Fase

  • No aplica

Contactos y Ubicaciones

Esta sección proporciona los datos de contacto de quienes realizan el estudio e información sobre dónde se lleva a cabo este estudio.

Ubicaciones de estudio

    • Zhejiang
      • Hangzhou, Zhejiang, Porcelana, 310000
        • Sir Run Run Shaw Hospital, Zhejiang University School of Medicine

Criterios de participación

Los investigadores buscan personas que se ajusten a una determinada descripción, denominada criterio de elegibilidad. Algunos ejemplos de estos criterios son el estado de salud general de una persona o tratamientos previos.

Criterio de elegibilidad

Edades elegibles para estudiar

18 años a 30 años (Adulto)

Acepta Voluntarios Saludables

No

Géneros elegibles para el estudio

Todos

Descripción

Inclusion Criteria:

  • Aged 18 to 30 years.
  • Fourth- or fifth-year undergraduate students majoring in Clinical Medicine at Zhejiang University School of Medicine, or trainees who have completed at least one year of standardized residency training at Sir Run Run Shaw Hospital, Zhejiang University School of Medicine.
  • Have completed basic surgery courses and theoretical learning related to breast diseases.
  • Voluntarily agree to participate in the study and provide written informed consent.
  • Have adequate communication and comprehension abilities.

Exclusion Criteria:

  • Have previously participated in similar generative artificial intelligence (GAI)-based teaching intervention studies.
  • Are unable to complete the entire study because of rotation schedules or other conflicts.
  • Belong to vulnerable populations other than employees of the study institution or subordinates of the investigators, including individuals with mental illness, cognitive impairment, critical illness, pregnancy, or illiteracy.
  • Refuse or are unwilling to provide informed consent.

Plan de estudios

Esta sección proporciona detalles del plan de estudio, incluido cómo está diseñado el estudio y qué mide el estudio.

¿Cómo está diseñado el estudio?

Detalles de diseño

  • Propósito principal: Otro
  • Asignación: Aleatorizado
  • Modelo Intervencionista: Asignación paralela
  • Enmascaramiento: Único

Armas e Intervenciones

Grupo de participantes/brazo
Intervención / Tratamiento
Comparador activo: Control Group: Traditional Teaching

the standardized surgical oncology teaching curriculum, utilizing standardized breast cancer teaching PowerPoint courseware.

Participants will receive standard traditional teaching, including routine classroom instruction, case-based learning, and teacher-guided discussion, without the use of the generative artificial intelligence-assisted learning component.

Experimental: Intervention Group: Traditional Teaching Plus AI Assistance

the independently developed "Clinical Reasoning and Decision-Making Dialogue Evaluation System" on the basis of the same traditional teaching.

Participants will receive standard traditional teaching, including routine classroom instruction, case-based learning, and teacher-guided discussion, without the use of the generative artificial intelligence-assisted learning component.

The intervention consists of traditional medical education supplemented with a generative artificial intelligence-based learning tool. The tool will support students in clinical case analysis, reasoning, and decision-making exercises. The control group will receive the same traditional teaching without access to the AI-assisted learning component.

¿Qué mide el estudio?

Medidas de resultado primarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Change in Clinical Reasoning Score on Objective Structured Clinical Examination (OSCE)
Periodo de tiempo: Baseline to Week 4

The total score ranges from 0 to 100. A higher score indicates better clinical thinking and decision-making ability

Baseline to Week 4

Medidas de resultado secundarias

Medida de resultado
Medida Descripción
Periodo de tiempo
Intraclass Correlation Coefficient (ICC) Between GAI-Based and Expert Assessment Scores
Periodo de tiempo: Baseline to Week 4

Both Generative AI (GAI) and human experts will evaluate the participants using the clinical Reasoning Assessment Rubric. The agreement between the GAI-based scores and expert assessment scores will be evaluated using the Intraclass Correlation Coefficient (ICC) . The coefficient ranges from 0 to 1, where higher values indicate better agreement.

Baseline to Week 4
Time to Complete the Assessment
Periodo de tiempo: During the clinical thinking and decision-making assessment at Week 4 (completion time measured in minutes).

Assessment completion time is defined as the duration, measured in minutes, from the initiation of the clinical thinking and decision-making assessment to its final submission by the participant. The time will be automatically recorded by the evaluation platform. Each participant's assessment completion time will be measured during the assessment conducted at Week 4.

During the clinical thinking and decision-making assessment at Week 4 (completion time measured in minutes).
Participant Satisfaction Score on the GAI-Assisted Evaluation System
Periodo de tiempo: Week 4

Participant satisfaction will be measured using a 5-point Likert scale (ranging from 1 = Very Dissatisfied to 5 = Very Satisfied). A higher score indicates higher satisfaction with the GAI-assisted evaluation system.

Week 4

Colaboradores e Investigadores

Aquí es donde encontrará personas y organizaciones involucradas en este estudio.

Fechas de registro del estudio

Estas fechas rastrean el progreso del registro del estudio y los envíos de resultados resumidos a ClinicalTrials.gov. Los registros del estudio y los resultados informados son revisados ​​por la Biblioteca Nacional de Medicina (NLM) para asegurarse de que cumplan con los estándares de control de calidad específicos antes de publicarlos en el sitio web público.

Fechas importantes del estudio

Inicio del estudio (Actual)

26 de septiembre de 2025

Finalización primaria (Actual)

25 de diciembre de 2025

Finalización del estudio (Actual)

25 de diciembre de 2025

Fechas de registro del estudio

Enviado por primera vez

9 de octubre de 2026

Primero enviado que cumplió con los criterios de control de calidad

30 de octubre de 2026

Publicado por primera vez (Actual)

4 de noviembre de 2026

Actualizaciones de registros de estudio

Última actualización publicada (Actual)

4 de noviembre de 2026

Última actualización enviada que cumplió con los criterios de control de calidad

30 de octubre de 2026

Última verificación

1 de octubre de 2026

Más información

Términos relacionados con este estudio

Plan de datos de participantes individuales (IPD)

¿Planea compartir datos de participantes individuales (IPD)?

NO

Información sobre medicamentos y dispositivos, documentos del estudio

Estudia un producto farmacéutico regulado por la FDA de EE. UU.

No

Estudia un producto de dispositivo regulado por la FDA de EE. UU.

No

Esta información se obtuvo directamente del sitio web clinicaltrials.gov sin cambios. Si tiene alguna solicitud para cambiar, eliminar o actualizar los detalles de su estudio, comuníquese con register@clinicaltrials.gov. Tan pronto como se implemente un cambio en clinicaltrials.gov, también se actualizará automáticamente en nuestro sitio web. .

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