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Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

Considering the potential of Collaborative International Online Learning (COIL) for cross-boundaries interacting and collaborating effectively, this study aims to explore the intercultural awareness of pre-service language teachers after participating in a COIL project.

Following a quantitative research approach and an exploratory cross-sectional method, the authors administered a 13-item questionnaire to unveil the perceptions of 64 future language teachers from Spain after their online experience with counterparts from the USA.

Participants consider that COIL may have enhanced their intercultural and global awareness and equipped them with valuable skills and knowledge for the future, being women more positive than men. Moreover, the results also suggest that those participants who have not traveled abroad consider COIL to be a good opportunity to compensate for the lack of knowledge or experience with other cultures resulting from not having had the opportunity to visit other countries.

COIL needs to be seen as a powerful tool to promote global learning, intercultural understanding and the development of skills among students that will be vital for success in today’s interconnected world. Nevertheless, universities and teacher training centers need to rethink the preparation of future teachers for the increasing demands to prepare students for the requirements of the global world, and to do so, they need to consider that COIL may offer them significant benefits.

This work offers an interesting exploration of teachers’ attitudes toward COIL, providing insights into the potential of online collaboration for developing intercultural awareness.