Medical EducationNCT07915622
Generative AI-Based Evaluation of Clinical Thinking and Decision-Making in Medical Students
A study testing AI-Assisted Teaching and Traditional Teaching in people with Medical Education and Generative AI, run by Sir Run Run Shaw Hospital at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 to 30 years
- Conditions the study is for
- Medical Education, Generative AI
- What is being tested?
- AI-Assisted Teaching and Traditional Teaching
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 90 participants
- Where
- 1 siteChina
- Study dates
- 26 Sep 2025to 25 Dec 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 30 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country.
China1 site
Sir Run Run Shaw Hospital, Zhejiang University School of Medicine
Hangzhou, Zhejiang, 310000
About this study
Official title: 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.
Read the detailed description
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.
- Conditions
- Medical Education, Generative AI
- Being tested
- AI-Assisted Teaching, Traditional Teaching
- Keywords
- Medical Students, Clinical Reasoning, Clinical Decision-Making;, Generative Artificial Intelligence, Medical Education, Educational Assessment
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Assisted TeachingBehavioural
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.
Traditional TeachingBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| Control Group: Traditional Teaching | Active comparator | the standardized surgical oncology teaching curriculum, utilizing standardized breast cancer teaching PowerPoint courseware. Receives: Behavioral: Traditional Teaching |
| Intervention Group: Traditional Teaching Plus AI Assistance | Experimental | the independently developed "Clinical Reasoning and Decision-Making Dialogue Evaluation System" on the basis of the same traditional teaching. Receives: Behavioral: AI-Assisted Teaching; Behavioral: Traditional Teaching |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in Clinical Reasoning Score on Objective Structured Clinical Examination (OSCE)
The total score ranges from 0 to 100. A higher score indicates better clinical thinking and decision-making ability
Measured: Baseline to Week 4
Secondary outcomes (3)
Intraclass Correlation Coefficient (ICC) Between GAI-Based and Expert Assessment Scores
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.
Measured: Baseline to Week 4
Time to Complete the Assessment
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.
Measured: 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
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.
Measured: Week 4
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Nov 2026
- Study start26 Sep 2025
- Primary completion25 Dec 2025
- Study completion25 Dec 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Medical EducationStudies of the same condition, open and under way.
- More trials run by Sir Run Run Shaw HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 90 participants (actual)
Sponsor and investigators
- Lead sponsor
- Sir Run Run Shaw Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Danzhi Chen, Sir Run Run Shaw Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07915622
- Sponsor's protocol ID
- Research 2025734
- Status last verified
- Oct 2026
- First submitted
- 9 Oct 2026
- Last updated
- 4 Nov 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 4 Nov 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Construction of an Intelligent Evaluation System for Clinical Thinking and Decision-making Ability of Medical Students Based on Generative Artificial Intelligence
- ClinicalTrials.gov ID
- NCT07915622
- Acronym / sponsor ID
- Research 2025734
- Conditions
- Medical Education, Generative AI
- Keywords
- Medical Students, Clinical Reasoning, Clinical Decision-Making;, Generative Artificial Intelligence, Medical Education, Educational Assessment
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 90 participants (actual)
- Lead sponsor
- Sir Run Run Shaw HospitalUniversity, hospital or other
- Study start
- 26 Sep 2025 (actual)
- Primary completion
- 25 Dec 2025 (actual)
- Study completion
- 25 Dec 2025 (actual)
- First posted
- 4 Nov 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Control Group: Traditional Teaching | Active comparator | Behavioral: Traditional Teachingthe standardized surgical oncology teaching curriculum, utilizing standardized breast cancer teaching PowerPoint courseware. |
| Intervention Group: Traditional Teaching Plus AI Assistance | Experimental | Behavioral: AI-Assisted Teaching, Behavioral: Traditional Teachingthe independently developed "Clinical Reasoning and Decision-Making Dialogue Evaluation System" on the basis of the same traditional teaching. |
Who may qualify
- Ages
- 18 to 30 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (5 listed)
- 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.
Key exclusion criteria (4 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Assisted TeachingThe 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. | Behavioural | Intervention Group: Traditional Teaching Plus AI Assistance |
| Traditional TeachingParticipants 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. | Behavioural | Control Group: Traditional Teaching, Intervention Group: Traditional Teaching Plus AI Assistance |
Primary outcome
Change in Clinical Reasoning Score on Objective Structured Clinical Examination (OSCE)
Time frame: Baseline to Week 4
The total score ranges from 0 to 100. A higher score indicates better clinical thinking and decision-making ability
3 secondary outcomes
Intraclass Correlation Coefficient (ICC) Between GAI-Based and Expert Assessment Scores
Time frame: Baseline to Week 4
Time to Complete the Assessment
Time frame: 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
Time frame: Week 4
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Nov 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Assisted Teaching and Traditional Teaching in people with Medical Education and Generative AI, run by Sir Run Run Shaw Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 4 Nov 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in Clinical Reasoning Score on Objective Structured Clinical Examination (OSCE) (time frame: Baseline to Week 4). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 4 Nov 2026.