Browsing by Author "Contreras-McKay, Ignacio"
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- ItemEmpowering human anatomy education through gamification and artificial intelligence: An innovative approach to knowledge appropriation(WILEY, 2023) Castellano, Monica Stambuk; Contreras-McKay, Ignacio; Neyem, Andres; Farfan, Emilio; Inzunza, Oscar; Ottone, Nicolas E.; del Sol, Mariano; Alario-Hoyo, Carlos; Alvarado, Macarena Soto; Tubbs, R. ShaneGamification has appeared as an alternative educational methodology to traditional tools. Specifically, in anatomy teaching, multiple technological applications have emerged in response to the difficulties of accessing cadaveric material; however, there is insufficient information about the effects of these applications on the performance achieved by students, or about to the best way to adapt learning to meet their educational needs. In this study, we investigated how teaching human anatomy through a mobile gamified technological tool containing recommendation systems can be combined with a virtual assistant to improve the learning and academic performance of medical students in the Anatomy Department at the Universidad de La Frontera in Temuco, Chile and the Anatomy Department at the Pontificia Universidad Catolica de Chile. In total, 131 students participated in the experiment, which was divided into two case studies. The main findings led to the conclusion that gamified components support students in learning anatomy. In addition, the predictions and recommendations provided by the virtual assistant enabled the academic aspects that the students needed to improve to be extracted adequately. Future work is expected to support adaptive learning by incorporating new artificial intelligence in education elements that can generate personalized scenarios for studying anatomy based on the application.
- ItemImproving learning experiences in software engineering capstone courses using artificial intelligence virtual assistants(2022) Gonzalez, Luis A.; Neyem, Andres; Contreras-McKay, Ignacio; Molina, DaniloStudents of Software Engineering Capstone Courses face situations and challenges that grant them valuable experiences. However, as this knowledge is acquired through real-life exposure, it is difficult to transmit it across different generations. To deal with this problem, it has been proposed that students record their learnings through a lesson learned model. But the question of how future students can best benefit from these records remains unanswered. This study addresses this problem through the use of Artificial Intelligence (AI) Virtual Assistant combined with a recommender system. Artificial Intelligence Virtual Assistants, as conversational chatbots, are a manifestation of AI via the simulation of conversation with human users. The technology has the potential to provide personalized service to a range of stakeholders. Thus, we seek to move this trend forward by now pushing these capabilities into the field of higher education. Consequently, we aim to assist software engineering students by leveraging collective knowledge to enhance learning experiences.