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- Emerging Trends in Higher Education: Technological Progress, Shifts in Student Populations, and Changing Workforce NeedsPublication . Peixoto, Cristina; Cecília Agostinho; Fialho, Joana; Márcio Nascimento; Antunes, Maria JoséThe higher education sector is undergoing significant changes driven by technological advancements, changing student demographics, and evolving workforce demands. Emerging trends shaping the future of higher education include personalized learning powered by adaptive technologies and artificial intelligence, the rise of short-term skill-specific certifications, virtual and augmented reality enhancing learning experiences, data- driven decision-making, interdisciplinary programs fostering critical thinking, global collaboration through online platforms, competency-based education prioritizing mastery, artificial intelligence and machine learning. This will enable personalized learning, lifelong learning initiatives supporting continuous education, increased focus on mental health and well- being, and alternative funding models like income share agreements and corporate partnerships. While these trends offer promising opportunities, they also present challenges related to equity, privacy, and balancing market demands with academic integrity. The aim of this study is to explore each of these trends, understand their implications, and evaluate the impact of the transformations they bring to the future of higher education.
- Using Process Mining to Analyze an Emergency ServicePublication . Gomes, André; Fialho, Joana; Wanzeller Guedes de Lacerda, Ana CristinaDigital solutions open up advances in institutions and in the services they provide. Many organizations collect large amounts of data (Big Data), but the value of these data is not readily available. Any possible solution to solve this problem is seen as an opportunity to obtain innovative indications for improving the functioning of the institutions. The health area is an important example in the context of the Big Data problem. Data collected in hospitals, combining log records from various sources, allow for a broader picture of medical processes. The scarcity and onerousness of resources and the growing need to provide health care to the population generate increasing pressures for good management of those processes. A possible solution to solve the mentioned problem is the usage of techniques of knowledge extraction from data, more precisely Process Mining. Thus, this work aims to show the benefits of using Process Mining to improve health processes, in this case in an emergency room. The results of this work are models that allow the analysis of the real functioning on care units, making it possible to draw conclusions about their management, as well as their resources’ use. With this type of information, professionals from each unit can act on existing inefficiencies, allowing them to improve a service that is of great importance to the population.