Conceiving modern engineers within the framework of the sustainability action plan (PASUS) of ISEP: sustainability matters!

Engineering education practices have evolved not only due to the natural changes in the contents of the curricula and skills but also, and more recently, due to the requirements imposed by the Bologna revision process. In addition, industry is becoming more demanding, as society is becoming more and more aware of the global needs and consequences of industrial practices. Under this scope, higher education needs not only to follow but also to lead these trends. Therefore, the School of Engineering of the Polytechnic Institute of Porto (ISEP), a Global Reporting Initiative (GRI) training partner in Portugal, prepared and presented its Sustainability Action Plan (PASUS), with the main objective of creating a new kind of engineers, with Sustainable Development at the core of their graduation and MsC degrees. In this paper, the main strategies and activities of the referred plan along with the strategic approach, which guided its development and implementation, will be presented in detail. Additionally, a reflection about the above mentioned bridge between concept and application will be established and justified, in the framework of the action plan. Although in most of the situations, there was no prior discussion or specific request, many of the graduation and post-graduation programmes offered by ISEP already include courses that attend to PASUS philosophy. As a consequence, the number of Master thesis, Graduation projects and R&D projects that address sustainability problems has grown substantially, a proof that for ISEP community, sustainability really matters!

Modelling an e-learning environment for learning programming languages

It is widely accepted that solving programming exercises is fundamental to learn how to program. Nevertheless, solving exercises is only effective if students receive an assessment on their work. An exercise solved wrong will consolidate a false belief, and without feedback many students will not be able to overcome their difficulties. However, creating, managing and accessing a large number of exercises, covering all the points in the curricula of a programming course, in classes with large number of students, can be a daunting task without the appropriated tools working in unison. This involves a diversity of tools, from the environments where programs are coded, to automatic program evaluators providing feedback on the attempts of students, passing through the authoring, management and sequencing of programming exercises as learning objects. We believe that the integration of these tools will have a great impact in acquiring programming skills. Our research objective is to manage and coordinate a network of eLearning systems where students can solve computer programming exercises. Networks of this kind include systems such as learning management systems (LMS), evaluation engines (EE), learning objects repositories (LOR) and exercise resolution environments (ERE). Our strategy to achieve the interoperability among these tools is based on a shared definition of programming exercise as a Learning Object (LO).

Power Law Behavior and Self-similarity in Modern Industrial Accidents

Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.