CENTRE FOR INFORMATICS AND SYSTEMS OF THE UNIVERSITY OF COIMBRA

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Mathematics classes for tourism undergraduate students and pre-service teachers with active methodologies using technologies

Publication . Santos, Vanda; Pais, Sónia; Hall, Andreia

In the last few decades, technology has advanced in multiple fields, including Education. Some of its benefits include improving student performance and motivation, fostering active learning and tracking student progress. Game-based learning platforms, like Kahoot!, can be used for reviewing content and motivating students for learning. The participants in the study are undergraduate and postgraduate students from two Portuguese public higher education institutions. The aim of the study is to investigate students’ perceptions of how Kahoot! can be used as a tool for reviewing class content or designing warm-up activities. A quantitative survey is being conducted to gather information about students’ insights on the use of Kahoot!. Other studies have also shown that higher education students are usually receptive to the use of this tool, finding it useful to increase their motivation and considering that technology can positively impact learning.

2021Journal article

Restricted access

Burnout protective patterns among oncology nurses: a cross-sectional study using machine learning analysis

Publication . Rocha, Ana; Costeira, Cristina; Barbosa, Raul; Gonçalves, Florbela; Castelo-Branco, Miguel; Viana, Joaquim; Gaudêncio, Margarida; Ventura, Filipa

Background Oncology nurses face unique and intense demands due to the nature of their work, caring for patients with life-threatening illnesses. The emergence of professional burnout among these nurses is influenced by several factors, highlighting the importance of identifying protective and risk factors to mitigate its impact. This study aims to identify burnout profiles and protective socio-demographic and work-related patterns associated with reduced burnout among oncology nurses. Methods A cross-sectional study was conducted with 150 oncology nurses at a specialized hospital exclusively dedicated to adult oncology treatment in Portugal. Data collection included a self-administered questionnaire incorporating the validated Portuguese version of Maslach Burnout Inventory (MBI). Statistical analyses were performed using SPSS and machine learning tools, specifically KMeans clustering and Random Forest algorithms. Results Six protective patterns against burnout were identified, characterized by conditions of permanent contracts, work-life balance, and supportive work environments. Moreover, factors such as holding management roles and being a parent of two or more children might even be protective in some circumstances, suggesting a nuanced relation between personal and professional factors. Machine learning analyses made apparent the unpredictability of burnout and highlighted the critical role of protective factors in mitigating its impact. Conclusions This study underscores the importance of resilience-building strategies and promoting protective factors, such as job stability, learned experience, and adequate rest, to reduce burnout risk among oncology nurses. Future research should validate these findings through hypothesis-driven analyses to inform targeted and context-specific burnout prevention programs.

2025-07-01Journal article

Open access