ECG Tutor: a gamified intelligent tutoring system for electrocardiogram teaching

Abstract

Abstract: Introduction: New methodological approaches have been suggested in an attempt to improve the acquisition of skills in electrocardiogram (ECG) interpretation, known to be complex and difficult to assimilate. Considering the expansion of active methodologies and the encouragement of technological innovations for medical education, the use of internet technologies (e-learning) has gained strength, highlighting the use of artificial intelligence platforms, such as intelligent tutoring systems (ITS), for their capacity to promote adaptive instruction. Researchers have used gamification (game design techniques) in conjunction with ITS, reporting greater engagement. Objective: Seeking to improve ECG learning performance among medical students through the development of new methodologies and considering the benefits of ITS and the use of gamification in medical education, the present study aimed to explore the interest and motivation of medical students in the use joint use of these technologies to study ECG. Method: This is an exploratory, quantitative study, in which graphic design prototypes of a gamified ECG instructor ITS were created by teachers of the medical course and evaluated by medical students from a public university and another private university after improvement into an interactive format, with the contribution of an interdisciplinary team. Result: At first, 53 undergraduate students from the 5th to the 11th semesters of the course participated in the study. That number was reduced to 14 in the second stage. The analysis showed approval of aspects related to perceived easy-to-use format, perceived usefulness, attitude towards use and intention to use. On the other hand, an urgent need to adapt to mobile devices and improve gamification and aesthetic elements was observed. Conclusion: The obtained results allowed us to conclude that medical students intend to use the ECG Tutor in the future, implying the need to develop a computational solution for the system and measure its impact on student learning.