4 research outputs found

    Aprendizaje basado en proyectos como metodología alternativa en la educación tecnológica

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    This article presents an analysis of current university teaching practices, and Project-Based Learning is introduced as an alternative methodology to improve said practices. In addition, this document includes examples of how this methodology was applied in four Electronics-related courses from different universities, to guide those willing to apply it.En el presente artículo se hace un diagnóstico de la práctica docente universitaria y se presenta el Aprendizaje Basado en Proyectos como una metodología alternativa con el fin de mejorar dicha práctica, además se muestra cómo se aplicó esta metodología en cuatro cursos relacionados con la Electrónica en diferentes universidades, con el fin de orientar a quienes estén dispuestos a aplicarla

    The Use of Scilab-Cloud for Teaching Digital Signal Processing Concepts in Electrical Engineering Curricula

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    The digital signal processing (DSP) is a relevant area in the electrical/computer engineering field, since several applications have been observed during the past decades. On the other hand, students have demonstrated difficulties to understand not only the eventual applications, but also its mathematical concepts and theory. Actually, open source packages are available and increasing, but the use of these tools are not very widespread in electrical engineering curriculum. This paper presents the use of Scilab-Cloud software platform for teaching some fundamentals of digital signal processing in undergraduate level, particularly for electrical engineering curriculum. Therefore, some experiments have carried out with undergraduate electrical engineering students and a questionnaire answered by them evidenced the potential of Scilab-Cloud as an interesting alternative tool to foster and motivate students for learning DSP skills

    Educating Sub-Saharan Africa:Assessing Mobile Application Use in a Higher Learning Engineering Programme

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    In the institution where I teach, insufficient laboratory equipment for engineering education pushed students to learn via mobile phones or devices. Using mobile technologies to learn and practice is not the issue, but the more important question lies in finding out where and how they use mobile tools for learning. Through the lens of Kearney et al.’s (2012) pedagogical model, using authenticity, personalisation, and collaboration as constructs, this case study adopts a mixed-method approach to investigate the mobile learning activities of students and find out their experiences of what works and what does not work. Four questions are borne out of the over-arching research question, ‘How do students studying at a University in Nigeria perceive mobile learning in electrical and electronic engineering education?’ The first three questions are answered from qualitative, interview data analysed using thematic analysis. The fourth question investigates their collaborations on two mobile social networks using social network and message analysis. The study found how students’ mobile learning relates to the real-world practice of engineering and explained ways of adapting and overcoming the mobile tools’ limitations, and the nature of the collaborations that the students adopted, naturally, when they learn in mobile social networks. It found that mobile engineering learning can be possibly located in an offline mobile zone. It also demonstrates that investigating the effectiveness of mobile learning in the mobile social environment is possible by examining users’ interactions. The study shows how mobile learning personalisation that leads to impactful engineering learning can be achieved. The study shows how to manage most interface and technical challenges associated with mobile engineering learning and provides a new guide for educators on where and how mobile learning can be harnessed. And it revealed how engineering education can be successfully implemented through mobile tools

    Project based learning to enhance teaching digital signal processing

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