Abstract:Purpose: Project-Based Learning (PBL) is considered to be an active learning methodology which can be used to develop both technical and transversal competences in engineering programs. This methodology demands a great deal of work effort from the students and also from the teachers and it requires a meticulous plan and a well-managed project as well. These activities go far beyond the normal activities in traditional lectures, enabling to outpace the difficulties that spur along the way that may be both complex and demotivating. This The aim of this paper is to identify and discuss the main difficulties of the implementation of PBL, mainly from the teachers' perspectives. Additionally, some effective strategies will be recommended to overcome such difficulties. Findings: Integration of courses in the project; student assessment; growing number of students in each team and the need of physical spaces for them; and compartmentalized knowledge has emerged as the main difficulties. To overcome these difficulties some key strategies were recommended.Originality/value: A new perspective based on course teachers' views and experiences will deepen the understanding of the problems and provide inputs for the development of strategies that may improve the effectiveness of PBL and introduce changes for its successful implementation. These strategies are intended to be transferable to other contexts, as most of the problems and constraints are common to other active learning approaches.

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A PC-based simulator of non-linear multiple-input multiple-output dynamic systems was employed for studies concerning the on-line estimation of both 'non-measured' state variables and multiple specific growth rates of a virtual baker´s yeast fed-batch fermentation. The identification algorithms were implemented in an 'Observer Computer' which received, optionally in 'real-time', in 'scaled time' or in 'simulation time', the 'measured' state variables generated by the process simulator in the 'Process Computer'. The state observer showed a robust behaviour under different situations where process parameters, operating variables and measuring characteristics (noise and delays) were changed in the process computer. The simulation package was seen to be an efficient and cheap tool for the simulation of non-linear processes with time varying parameters, providing a realistic environment for tests of identification, estimation and control strategies.

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