Use of artificial intelligence in spaced repetition strategies for medical education and meaningful learning: a systematic review.

Authors

  • Jennifer Carolina Duque Espinel Maestrante de la Maestría en Docencia en Ciencias de la Salud Universidad San Gregorio de Portoviejo Manabí, Ecuador https://orcid.org/0009-0008-0063-7729
  • Andrés Leonardo García Casquete Universidad San Gregorio de Portoviejo, Ecuador
  • Yoiler Batista Garcet Universidad San Gregorio de Portoviejo, Medicina, Ecuador https://orcid.org/0000-0002-7851-5763
DOI: https://doi.org/10.6018/edumed.685191
Keywords: spaced repetition, learning, artificial inteligence

Abstract

Medical education faces the challenge of managing large amounts of information while preventing superficial learning. Spaced repetition, grounded in the forgetting curve, strengthens long-term retention and promotes meaningful learning. Its integration with artificial intelligence (AI) enables personalized review intervals, automated generation of learning materials, and immediate feedback, thereby expanding the pedagogical potential of this strategy. Objective: To evaluate the effectiveness and applicability of AI-assisted spaced repetition in Health Sciences education. Methods: A descriptive systematic review was conducted in accordance with PRISMA 2020. Searches were performed in Google Scholar and Web of Science (2020–2025) using the terms “spaced repetition,” “medical education,” “learning,” and “artificial intelligence.” Original studies, reviews, and applied reports addressing spaced repetition with or without AI were included. From 1870 initial records, 18 studies met the inclusion criteria and were analyzed qualitatively. Results: Direct evidence showed that AI enhances the personalization of review intervals, improves feedback quality, and supports knowledge consolidation. Indirect evidence confirmed the effectiveness of traditional spaced repetition, with sustained benefits in academic performance and memory in standardized examinations. Complementary evidence highlighted that AI strengthens other educational processes, such as automated tutoring, clinical simulation, and microlearning. Conclusions: AI-assisted spaced repetition represents an innovative pedagogical strategy aligned with competency-based medical education. It facilitates personalized learning, strengthens retention, and promotes student autonomy. However, methodological limitations in the available studies highlight the need for longitudinal and multicenter research to assess its educational and clinical impact, along with ethical strategies to ensure equity and human verification in the use of these technologies.

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Published
20-11-2025
How to Cite
Duque Espinel, J. C., García Casquete, A. L., & Batista Garcet, Y. (2025). Use of artificial intelligence in spaced repetition strategies for medical education and meaningful learning: a systematic review. Spanish Journal of Medical Education, 6(6). https://doi.org/10.6018/edumed.685191
Issue
Vol. 6 No. 6 (2025): Revista Española de Educación Médica
Section
Reviews

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