Artificial intelligence–powered virtual standardized patients in teaching history-taking skills to medical students: a randomized controlled trial

Read full text
Authors: Hai Nguyen Ngoc Dang, Thang Viet Luong, Hoa Thi Ha Vo, Linh Thi Khanh Nguyen, Trung Nguyen Tran, Hong Thi Anh Pham, Huong Thanh Truong, Hoa Tran, Toan Thanh Tran, Tien Anh Hoang, Thang Chi Doan, Quan Long Huynh
+1 more Thomas Hugh Marwick
Cited by: 1
References: 36

Abstract

BACKGROUND: Artificial intelligence (AI) has emerged as a promising tool in medical education. It offers opportunities to enhance learning experiences, particularly through the development of virtual standardized patients (SP) integrated with AI for training purposes. These virtual patients are especially useful for teaching history-taking skills (HTS). However, evidence comparing AI-powered virtual standardized patients (AI-VSP) with traditional SP in teaching HTS remains unclear. This study aimed to evaluate the effectiveness of AI-VSP and compare it with conventional SP in teaching HTS to undergraduate medical students. METHODS: A randomized controlled trial (TCTR20251202012) was conducted among third-year medical students at Duy Tan University, Vietnam. This study included participants in the pre-clinical skills curriculum without prior formal HTS training. Students were randomized at the class level to intervention or control groups via a computer-generated sequence. The intervention group practiced with AI-VSP, while the control group learned with conventional SP. Primary outcomes included pre-test, post-test, and objective structured clinical examination (OSCE) scores. Examiners were blinded to group allocation. Student satisfaction was assessed as a secondary outcome using a 5-point Likert scale. RESULTS: A total of 67 medical students were included, comprising 34 in the AI-VSP group and 33 in the SP group. Both groups demonstrated significant improvement in post-test scores compared with pre-test results (p < 0.001). In the AI-VSP group, the mean score increased from 3.41 ± 2.56 to 8.56 ± 1.85, while in the SP group, it rose from 3.24 ± 1.64 to 7.97 ± 1.85. The magnitude of improvement was 5.15 ± 2.88 in the AI-VSP group and 4.73 ± 1.75 in the SP group (p = 0.503). The mean OSCE scores were 6.5 ± 1.5 for the AI-VSP group and 6.3 ± 1.7 for the SP group (p = 0.543). Mixed-effects modeling adjusting for age and class-level clustering confirmed that neither pre-test, post-test, OSCE scores, nor score improvement differed significantly between instructional methods. Regarding student satisfaction, there was no statistically significant difference in perceived learning experience between the two groups (all p > 0.05). CONCLUSIONS: Learning outcomes and student satisfaction did not differ significantly between the AI-VSP and SP instructional methods. TRIAL REGISTRATION: TCTR20251202012 (registered on 20/11/2025); retrospectively registered; https://www.thaiclinicaltrials.org/show/TCTR20251202012.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Clinical Reasoning and Diagnostic Skills Simulation-Based Education in Healthcare

Publication details

Journal / source
BMC Medical Education
Publisher
Springer Science and Business Media LLC
Volume
26
Issue
1
Publication date
30 April 2026
Language
EN