Comparison of Students' Attitudes about the Effectiveness of Algorithm-based Education with Lecture-based Education.

Background: Training is a complex process, especially when the students are being prepared for patient's management. Therefore, the development of effective teaching methods is critical for to improvement of learning and communication between the content and concepts. In algorithm-based education, more focus is placed on more involvement of students in the subject, thereby providing a better understanding of the concept. In this study, we compared students' attitudes about the effectiveness of algorithm-based education (education based on the patient's complaints and symptoms) with lecture-based education in the learning ability of the medical students presented in the clinical course of the orthopedic group. Methods: This research is a single-group quasi-experimental study; we assessed the students' attitudes on a five-point Likert scale questionnaire with confirmed validity and reliability. The scores of two teaching methods were assessed after the training course, which was presented using the algorithmic method for selective titles and lectures for the other titles. Data were analyzed on SPSS software using a paired t-test. Results: A total of 220 internship medical students, including 58.7% of girls with a mean age of 22.9 ± 1.19 years, participated in the study. The mean score of the questions was 3.92±0.54 and 2.17±0.58 in the algorithmic and the lecture training, respectively. After comparing the results with a paired t-test, there was a significant difference between students' attitudes toward the two teaching methods (p ˂ 0.001), so the students' attitude was more positive toward the algorithm-based method. Conclusion: For the education of medical students, algorithm-based training is more efficacious compared to traditional methods such as lecture-based training.