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The Potential of AI in Health Higher Education to Increase the Students’ Learning Outcomes

Maria José Sousa, Francesca Dal Mas, António Pesqueira, Carlos M. Lemos, Juan M. Verde, Lorenzo Cobianchi

2021TEM Journal52 citationsDOIOpen Access PDF

Abstract

The main goal of this article is to understand the potential learning applications based on AI technologies for health higher education students. We employed a Systematic Literature Review, contributing to explore to what extent AI technologies are currently influencing the Health learning processes in higher education and the skills developed during the learning path. The intent is to contribute to a more profound understanding of learning contexts, methodologies, technologies, and pedagogical processes with the application of AI technologies. The literature emphasizes that AI can be used to potentiate the learning process and the learning outcomes, especially in laboratory classes, and such contexts are still largely unstudied. To fulfil this gap, some practical applications based on AI technologies applied to health higher education studies were identified, highlighting AI's innovations and possible opportunities for health higher education.

Topics & Concepts

Higher educationProcess (computing)Emerging technologiesKnowledge managementComputer sciencePsychologyData scienceArtificial intelligencePolitical scienceLawOperating systemArtificial Intelligence in Healthcare and EducationBiomedical and Engineering EducationClinical Reasoning and Diagnostic Skills
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