Impact of artificial intelligence on academic performance in medical education: A systematic review

Abstract

Artificial intelligence (AI) plays a significant role in improving the quality of medical education. This study aimed to investigate the application of AI in medical education. A systematic review was conducted of all educational intervention studies in medical courses from January 1986 to 2023. Of the 16755 studies initially identified by our search, 7387 remained after removing duplicates. After that, 6205 studies were excluded for the title and abstract screening. Then, 15 full-text articles were included in our final review. The following keywords were used: artificial intelligence, machine intelligence, medical education, medical teaching, precision medical teaching, and precision medical education. A total of 16745 articles were identified from ISI, PubMed, Scopus, and Educational Resources and Information Center (ERIC) databases. Fourteen studies met the eligibility criteria. The quality of the included articles was appraised by the best evidence medical education (BEME) review of the education portfolio. PICO consists of <i>P</i> = medical student, I: use of AI, C = do not use AI, and I = enhance health professions students' knowledge, attitudes, and skills. The included studies were synthesized and categorized according to the Kirkpatrick model. Educational intervention outcomes were categorized into three parts^[1]: improvement in learners' knowledge (N = 6 studies)^[2]; enhancement of students' attitudes (N = 3 studies); and^[3] acquisition of learners' skills (N = 10 studies). The reviewed studies examined the impact of AI and virtual reality on enhancing health profession students' knowledge, attitudes, and skills. However, more research is still needed on integrating AI into diverse curriculum models and sustaining AI's role in real-world education systems.

Ähnliche Arbeiten