Abstract
Motivation is the key to academic success. In the case of engineering, autonomous project teamwork guided by ethics and sustainability concerns acts as a major student motivator. Moreover, it empowers students to become lifelong learners and agents of sustainable development. Engineering schools can thus address simultaneously these two essential education goals – learning and academic success – by challenging students to find innovative, sustainable solutions in a learner-centred set-up.This paper describes how the European Project Semester (EPS), a capstone engineering programme offered by the Instituto Superior de Engenharia do Porto (ISEP), combines challenge-based learning, ethics and sustainability-driven problem-solving, and international multidisciplinary teamwork to achieve both goals.

Abstract
The introduction of IoT technologies in industrial settings is changing the way manufacturing companies perceive their production processes, allowing for more accurate monitoring of production-related parameters. Due to the introduction of IoT technologies and associated enhancements in terms of data acquisition, processing, and availability, it becomes possible for manufacturing companies to tackle complex issues, such as the efficiency of production. In this paper, the development of an Industrial IoT solution targeting the fish canning industrial sector is described, as an approach to identify and monitor raw input material losses as well as water and energy waste, an endemic issue of the sector, promoting an increased efficiency in the production processes. This paper mainly focuses on the description of the implementation of the proposed IoT technologies for monitoring waste and loss, and its deployment in three distinct environments, including at a fish canning manufacturing company.

Abstract
In Portugal, the dropout rate of university courses is around 29%. Understanding the reasons behind such a high desertion rate can drastically improve the success of students and universities. This work applies existing data mining techniques to predict the academic dropout mainly using the academic grades. Four different machine learning techniques are presented and analyzed. The dataset consists of 331 students who were previously enrolled in the Computer Engineering degree at the Universidade de Tras-os-Montes e Alto Douro (UTAD). The study aims to detect students who may prematurely drop out using existing methods. The most relevant data features were identified using the Permutation Feature Importance technique. In the second phase, several methods to predict the dropouts were applied. Then, each machine learning technique's results were displayed and compared to select the best approach to predict academic dropout. The methods used achieved good results, reaching an Fl-Score of 81% in the final test set, concluding that students' marks somehow incorporate their living conditions.

Abstract
New pocket-sized laboratories are proving to be an excellent tool as complementary equipment that students and lecturers can deploy to test control engineering design techniques. Here, the description and outcome results of an IFAC activity funded project entitled as Pocket-Sized Portable Labs: Control Engineering Practice Made Easy are presented. The project was executed in Portugal, from January 2021 to the end of June 2021, during the SARS-CoV2 pandemic. The global aim of this project was to motivate preuniversity students to enroll in control engineering courses by showing and demonstrating that simple practical experiments may be easily accomplished using portable pocket-size laboratories. Copyright (C) 2022 The Authors.

Abstract
This paper aims to analyze some different solutions that were adopted in control education activities during the pandemic. The authors of this paper are educators in the control education field from different countries on all the continents, who have developed a questionnaire with the idea of collecting data about the COVID-19 pandemic impact on the control education activities. The main objective is to study the diverse alternatives that were used worldwide to perform the online educational activities during that period, such as methodologies, tools, learning management systems (LMS), theoretical exercises, laboratory experiments, types of exams, simulators, software for online lecturing, etc. As a result, comparisons between preand during-pandemic educational resources and methods are performed, where useful ideas and discussions are given for the control education community. Copyright (C) 2022 The Authors.

Abstract
Scientific advances in recent decades have provided universal access to a variety of new digital technologies. These technologies are used by the vast majority of today's university students. Therefore, the incorporation of innovative methods and technologies is a must in order to actively engage students in the learning process. In this paper, a selection of techniques that can be considered 'outside of the box' are examined in the context of the application of teaching/learning methods in control engineering and industrial automation education. © 2022 IEEE.