Abstract

© 2021 ACM.In Health Science Education (HSE), students must demonstrate technical skills in many procedures. However, traditional teaching methodologies limit the possibilities for personalized feedback from an instructor and generally do not allow students to achieve the required proficiency levels. Concerning this, technology has been installed as a learning resource with numerous benefits that allow new multidisciplinary lines of research, such as learning analytics (LA) and educational data mining (EDM). Both LA and EDM seek to improve educational practice based on the intensive use of educational data, such as analyzing online learning patterns, creating performance predictions, and incorporating artificial intelligence techniques. There is a range of possibilities in applying LA and EDM in teaching procedural skills that have not yet been explored. For this reason, this study aims to answer (1) How the educational data explain the development of procedural skills in virtual environments to support the teaching-learning process in Health Science Education?; and (2) How automatic feedback and adaptive personalization affect the performance and instructional design of the procedural skills learning process of health science students? We expect that this study contributes to the field of technical skills learning mediated by technology in higher education by using the data provided by the interaction of students with virtual resources to support educational decision-making and optimize the teaching and learning processes in HSE.