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Training Engineers for the Ambient Intelligence Challenge

机译:培训环境智能挑战的工程师

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The increasing complexity of the new breed of distributed intelligent systems, such as the Internet of Things, which require a diversity of languages and protocols, can only be tamed with design and programming best practices. Interest is also growing for including the human factor, as advocated by the ambient intelligence (AmI) research field, whose focus is on transparently and intelligently supporting people. These new design methodologies are increasingly needed in the toolbox of new electronic and computer engineers, and teaching strategies should be devised that allow students to acquire a systems-level view instead of getting lost in technology-oriented approaches. This paper describes a study carried out over two academic years, in a course in AmI at Politecnico di Torino, Italy. In the course, a project-based learning approach was adopted, in which students design and prototype an AmI system, and their progress is closely monitored throughout the semester. This paper presents the learning goals and teaching strategies, analyzes the learning outcomes from the qualitative and quantitative points of view, and highlights the lessons learned in the process.
机译:新一代的分布式智能系统(例如,物联网)的复杂性不断提高,这需要多种语言和协议,这只能通过设计和编程最佳实践来加以解决。正如环境情报(AmI)研究领域所倡导的那样,对于包括人为因素的兴趣也在增长,该领域的重点是透明和智能地支持人们。在新的电子和计算机工程师的工具箱中,越来越需要这些新的设计方法,并且应该设计教学策略,使学生能够获得系统级的视图,而不会迷失于面向技术的方法中。本文介绍了一项在意大利Politecnico di Torino的AmI课程中进行的为期两个学年的研究。在课程中,采用了基于项目的学习方法,学生可以设计和原型化AmI系统,并在整个学期中密切监视他们的进度。本文介绍了学习目标和教学策略,从定性和定量的角度分析了学习成果,并重点介绍了在此过程中吸取的教训。

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