Yavuz Selim Kıyak

Biographic Data

ID7390737
NAMEYavuz Selim Kıyak
GIVEN NAMESYavuz Selim
FAMILY NAMEKıyak
SIGNATUREKIYAK Y S
AFFILIATIONSGazi University
ORCID0000-0002-5026-3234
VERIFIEDYes
TOTAL WORKS9
TOTAL CITATIONS0
WORKS AS AUTHOR9
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2023
LATEST PUBLICATION YEAR2026
H-INDEX0

  • Virtual reality enhances ophthalmic anatomy learning

    Open AccessAyşe Soylu, Ahmet Yücel Üçgül et al.ARTICLEBMC Medical Education2026

    BACKGROUND: The aim of this study is to evaluate the effectiveness of virtual reality (VR) for learning ophthalmic anatomy and to determine whether peer-assisted facilitation produces learning outcomes comparable to expert-assisted facilitation among preclinical medical students. A secondary objective was to contextualize learning outcomes by comparing performance of preclinical students with that of senior medical students receiving expert-assis…

  • ‘ChatGPT can make mistakes’ warnings fail

    Open AccessYavuz Selim Kıyak, Özlem Coşkun et al.ARTICLEMedical Education2026

  • ChatGPT versus human authors

    Open AccessRenata Szydlak, Yavuz Selim Kıyak et al.ARTICLEMedical Teacher2026

    Purpose This study investigates whether ChatGPT can generate clinically accurate and pedagogically valuable maps for clinical reasoning (CR) training. The aim is to assess its potential as a tool for supporting the creation of high-quality educational resources for CR training.Materials and methods We selected 10 diverse virtual patients (VPs) from the European iCoViP project. For each case, CR concept maps were generated by a custom ChatGPT mode…

  • Large language models for generating script concordance test in obstetrics and gynecology

    Zuhal Yapıcı Coşkun, Yavuz Selim Kıyak et al.ARTICLEMedical Teacher2025

    OBJECTIVE: To evaluate the performance of large language models (ChatGPT-4o and Claude 3.5 Sonnet) to generate script concordance test (SCT) items for assessing clinical reasoning in obstetrics and gynecology. METHODS: This cross-sectional study involved the generation of SCT items for five common diagnostic topics in obstetrics and gynecology in primary care settings. A total of 16 panelists evaluated the AI-generated SCT items against 11 predef…

  • ChatGPT to generate clinical vignettes for teaching and multiple-choice questions for assessment

    Özlem Coşkun, Yavuz Selim Kıyak et al.ARTICLEMedical Teacher2025

    AIM: This study aimed to evaluate the real-life performance of clinical vignettes and multiple-choice questions generated by using ChatGPT. METHODS: This was a randomized controlled study in an evidence-based medicine training program. We randomly assigned seventy-four medical students to two groups. The ChatGPT group received ill-defined cases generated by ChatGPT, while the control group received human-written cases. At the end of the training,…

  • Keeping humans in the loop efficiently by generating question templates instead of questions using AI

    Yavuz Selim Kıyak, Emre Emekli et al.ARTICLEMedical Teacher2025

    BACKGROUND: Manually creating multiple-choice questions (MCQ) is inefficient. Automatic item generation (AIG) offers a scalable solution, with two main approaches: template-based and non-template-based (AI-driven). Template-based AIG ensures accuracy but requires significant expert input to develop templates. In contrast, AI-driven AIG can generate questions quickly but with inaccuracies. The Hybrid AIG combines the strengths of both methods. How…

  • Large language models for generating key-feature questions in medical education

    Open AccessYavuz Selim Kıyak, Stanisław Górski et al.ARTICLEMedical Education Online2025

    In this study, we conducted a descriptive study to evaluate the quality of KFQs generated by OpenAI's o3 model. We developed a reusable generic prompt for KFQ generation, designed in alignment with the Medical Council of Canada's KFQ development guidelines. We also created an evaluation metric to systematically assess the quality of the KFQs based on the KFQ development guideline. Twenty unique cardiology-focused KFQs were created using recent Eu…

  • Case-based MCQ generator

    Yavuz Selim Kıyak, Andrzej A KononowiczARTICLEMedical Teacher2024

    WHAT IS THE EDUCATIONAL CHALLENGE?: A fundamental challenge in medical education is creating high-quality, clinically relevant multiple-choice questions (MCQs). ChatGPT-based automatic item generation (AIG) methods need well-designed prompts. However, the use of these prompts is hindered by the time-consuming process of copying and pasting, a lack of know-how among medical teachers, and the generalist nature of standard ChatGPT, which often lacks…

  • The effect of watching lecture videos at 2× speed on memory retention performance of medical students

    Yavuz Selim Kıyak, Işıl İrem Budakoğlu et al.ARTICLEMedical Teacher2023

    Aim This study aimed to determine how watching lecture videos at 1× and 2× speeds affects memory retention in medical students.Methods A posttest-only experimental design was utilized. The participants were 60 Year-1 and Year-2 medical students. The participants were assigned to one of two groups through stratified randomization: Group 1 would watch the video at 1× speed, and Group 2 at 2× speed. Their performance was assessed using a test compri…