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Tundra lists 2 Assessment Methods in Medical Training clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.
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NCT07672288
Assessment of Hysteroscopy Skills With a New Assessment Tool
Objective To investigate validity of the hysteroscopy assessment tool (HYSAT) for assessment of competence in a clinical environment. Methods Novices and experienced gynecologists are recruited from three hospitals and observed and assessed while performing hysteroscopy. Performances are assessed using the HYSAT tool by two independent raters. Validity evidence is gathered in accordance with Messick's framework: validity evidence for content was ensured in previously published Delphi study, response process is ensured by standardization of written rater instructions. Internal structure is explored using Cronbach's alpha for internal consistency reliability; inter-rater reliability and test-retest reliability are calculated as Pearson's r independently across all ratings. Relationship to other variables is investigated by comparing performances of the participants in each group. Consequences evidence is explored by calculating a pass/fail standard using the contrasting groups' standard setting method.
Gender: All
Updated: 2026-06-26
1 state
NCT07522658
Artificial Intelligence-Generated vs Academician-Developed Multiple True/False Questions in Anesthesiology Education
This prospective observational study aims to evaluate the effectiveness and educational value of artificial intelligence (AI)-generated multiple true/false questions compared to those developed by experienced academicians in anesthesiology training. A total of 27 anesthesiology residents will be included in the study. Question sets consisting of 200 multiple true/false items will be created, with half generated by academicians and the other half generated using an artificial intelligence model (ChatGPT-based system). The questions will be based on standardized educational materials from the anesthesiology training curriculum. Participants will complete the test in a single session. Each correct answer will be scored as one point, and total scores will be calculated. In addition to test performance, item difficulty, discrimination indices, and test reliability will be analyzed. Furthermore, participants' perceptions regarding question quality will be evaluated. The study aims to determine whether AI-generated questions can provide a reliable and effective alternative to traditional question development methods in medical education and contribute to more objective and standardized assessment processes.
Gender: All
Ages: 18 Years - Any
Updated: 2026-05-06