DIGITALUSING AN AUTOMATED SPACED REPETITION ALGORITHM TO ENHANCE LEARNING IN CARIBBEAN MEDICAL STUDENTS: A PILOT STUDY
1 American University of Antigua College of Graduate Studies (ANTIGUA AND BARBUDA)
2 Yale School of Medicine (UNITED STATES)
2 Yale School of Medicine (UNITED STATES)
About this paper:
Appears in: EDULEARN23 Proceedings
Publication year: 2023
Pages: 6380-6383
ISBN: 978-84-09-52151-7
ISSN: 2340-1117
doi: 10.21125/edulearn.2023.1688
Publication year: 2023
Pages: 6380-6383
ISBN: 978-84-09-52151-7
ISSN: 2340-1117
doi: 10.21125/edulearn.2023.1688
Conference name: 15th International Conference on Education and New Learning Technologies
Dates: 3-5 July, 2023
Location: Palma, Spain
Dates: 3-5 July, 2023
Location: Palma, Spain
Abstract:
The United States is facing a critical shortage of physicians, particularly in primary care, and the lack of diversity in the medical profession is a major concern. To address these issues, increasing the number and diversity of international medical graduates, such as those from Caribbean medical schools who have higher percentage of underrepresented minority students, could be a potential solution. However, minority students face several academic challenges that hinder their progress, including lower standardized exam scores, higher rates of delayed progression, attrition, and dissatisfaction with the learning environment.This pilot study evaluated the effectiveness of an automated spaced retrieval formative quiz algorithm in improving the academic achievement of first-semester preclinical medical students in a Caribbean medical school. Logistic regression analysis was used to assess the data, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to determine the odds of achieving a passing score overall, as well as for students in the top 25% quartile of quiz takers compared to those in the lower 75%.
The study found that students in the experimental group (n=22) using the spaced retrieval algorithm had a higher likelihood of passing the final exam, although this was not statistically significant. The unadjusted odds ratio for passing the semester was 1.78 (p = 0.181; CI: 0.76-4.25) compared to those who did not use the quiz algorithm. However, when stratified by quartile of quizzes completed, the top 25% of quiz takers using the algorithm had a 152% increased likelihood (OR 2.52; p = 0.043) of passing the semester compared to those in the lower 75% of quiz takers.
The findings suggest that innovative learning practices, such as the use of assistive intelligence (AI) algorithms, such as an automated spaced retrieval formative quiz algorithm, may help promote learning and improve academic achievement among Caribbean medical students. This approach could potentially help address the physician shortage in the U.S. by increasing the number of diverse and well-prepared medical graduates who can provide care to underserved populations.