To create more equitable engineering education, it is essential to understand the adversity faced by students due to their socio-economic status; the impact it has on their academic journey, and how to adapt to overcome it. An aim of the EUniWell "Maximising Academic and Social Outcomes in Engineering Education" (MASOEE) project is to understand student disadvantage and its effect on engineering skill and identity development across 3 European universities. This multiphase, mixed-method research explored the association between adversity through parental education and adaptability through academic self-concept, utilising data from a structured questionnaire and 1-to-1 interviews. We found that students who are first generation in their family to attend university is a common indicator of adversity, and that, on average, their self-concept specific academic skills – communication, networking, and entrepreneurial resourcefulness – is lower compared to other students. The thematic analysis of the 1-to-1 interviews reveals 5 recurrent themes when discussing academic resilience and success with students: social factors, networking, extra-curricular skills development, skill confidence and improvement, and engineering identity fluidity. The findings add to previous research, and the need to develop targeted interventions around these uncovered themes.

To create more equitable engineering education, it is essential to understand the adversity faced by students due to their socio-economic status; the impact it has on their academic journey, and how to adapt to overcome it. An aim of the EUniWell "Maximising Academic and Social Outcomes in Engineering Education" (MASOEE) project is to understand student disadvantage and its effect on engineering skill and identity development across 3 European universities. This multiphase, mixed-method research explored the association between adversity through parental education and adaptability through academic self-concept, utilising data from a structured questionnaire and 1-to-1 interviews. We found that students who are first generation in their family to attend university is a common indicator of adversity, and that, on average, their self-concept specific academic skills - communication, networking, and entrepreneurial resourcefulness - is lower compared to other students. The thematic analysis of the 1-to-1 interviews reveals 5 recurrent themes when discussing academic resilience and success with students: social factors, networking, extra-curricular skills development, skill confidence and improvement, and engineering identity fluidity. The findings add to previous research, and the need to develop targeted interventions around these uncovered themes.

In this extended abstract, we summarize our paper published in the ACM Transactions on Autonomous and Adaptive Systems [We23]. To gain insight into the application of self-adaptation in practice, we performed a large-scale survey and received 184 responses from practitioners spread over 21 countries. Based on the analysis, we provide an overview of state-of-the-practice in the application of self-adaptation. From that, we derive insights for researchers to check their current research with industrial needs, and for practitioners to compare their current practice in applying self-adaptation.

Architecting a self-adaptive system with decentralized control is challenging. Indeed, architects shall consider several different and interdependent design dimensions and devise multiple control loops to coordinate and timely perform the correct adaptations. To support this task, we propose Decor, a reasoning framework for architecting and evaluating decentralized control. Decor provides (i) multi-paradigm modeling support, (ii) a modeling environment for MAPE-K style decentralized control, and (iii) a co-simulation environment for simulating the decentralized control together with the managed system and estimating the quality attributes of interest. We apply the Decor in three case studies: an intelligent transportation system, a smart power grid, and a cloud computing application. The studies demonstrate the framework’s capabilities to support informed architectural decisions on decentralized control and adaptation strategies.

The ERASMUS+ European University for Well-Being (EUniWell) alliance’s mission aims to resolve the paradox of Europeans’ relative prosperity against the global security and sustainability challenge. “Maximising Academic and Social Outcomes in Engineering Education” is a project which interprets this contradiction for engineering educators; how to best teach non-technical skills to ensure engineers make the utmost contribution to societal wellbeing? Appreciably, the social outcome for the person who becomes an engineer is positive because the profession is relatively well-paid. Therefore, engineering education is good for social mobility providing the learning environment narrows attainment gaps between disadvantaged and mainstream cohorts. Accordingly, our strategy is to bring together the expertise of the British, French, Italian and Swedish faculties to transfer best practice for professional, business and sustainability skill teaching, while contrasting how their disadvantaged cohorts present. The project has two primary objectives: To understand how partners differ in terms of skill teaching, and how students from disadvantaged backgrounds are accommodated. The paper describes the background and rationale of the project, and its research design and methodology. Although the project is still in progress and data collection is still underway, this paper provides insights and perspectives for engineering educators looking to design similar collaborations to share best practice, while considering engineering identities and their underlying competencies. 

Engineering long-running computing systems that achieve their goals under ever-changing conditions pose significant challenges. Self-adaptation has shown to be a viable approach to dealing with changing conditions. Yet, the capabilities of a self-adaptive system are constrained by its operational design domain (ODD), i.e., the conditions for which the system was built (requirements, constraints, and context). Changes, such as adding new goals or dealing with new contexts, require system evolution. While the system evolution process has been automated substantially, it remains human-driven. Given the growing complexity of computing systems, human-driven evolution will eventually become unmanageable. In this paper, we provide a definition for ODD and apply it to a self-adaptive system. Next, we explain why conditions not covered by the ODD require system evolution. Then, we outline a new approach for self-evolution that leverages the concept of ODD, enabling a system to evolve autonomously to deal with conditions not anticipated by its initial ODD. We conclude with open challenges to realise self-evolution.

The MASOEE project brings together engineering faculties in the EUniWell alliance to share best practices for teaching transversal skills so that engineers contribute to societal well-being. The study combines the expertise of several engineering faculties at European universities. It focuses on sharing and developing expertise to improve the social outcomes of engineering students. Namely, researchers examine the similarities and differences between partners regarding their student bodies, teaching, programme structures, and institutions’ culture. Moreover, the work also explores how transversal skills are taught, what student attitudes are in terms of learning these skills, and how educators can better teach them.

The research design includes several activities across four work packages (WPs). To ensure that partners use the same skill descriptions, we use well-established organizations' existing definitions. WP1 strives to identify best practices within EUniWell based on the 15 entrepreneurial competencies defined in EU EntreComp Framework. WP2 targets engineering students' ability to solve complex challenges, communication, and networking skills defined in the "21st century skills" by the World Economic Forum. WP3 investigates the engineering schools’ capacity to train engineering students in sustainable competence, forming responsible engineers capable of developing sustainable solutions using the skills defined by the EU GreenComp. WP4 supports the other packages with engineering education research, specifically data collection and analysis, knowledge forming, and evaluation. The project runs from August 2022 until September 2023.  

The MASOEE project partners gather knowledge within their organisations through joint surveys and focus groups and collectively identify and share best practices. The engineering identity, taught as transversal skills by participating partners, can evolve from a traditional technologist identity along three paths: the self-made engineer, the progressive technologist, and the responsible engineer. By sharing best practices for teaching these skills, we believe we will better understand what the future engineer - who integrates all three identities – will be.

Computing systems form the backbone of many areas in our society, from manufacturing to traffic control, healthcare, and financial systems. When software plays a vital role in the design, construction, and operation, these systems are referred to as software-intensive systems. Self-adaptation equips a software-intensive system with a feedback loop that either automates tasks that otherwise need to be performed by human operators or deals with uncertain conditions. Such feedback loops have found their way to a variety of practical applications; typical examples are an elastic cloud to adapt computing resources and automated server management to respond quickly to business needs. To gain insight into the motivations for applying self-adaptation in practice, the problems solved using self-adaptation and how these problems are solved, and the difficulties and risks that industry faces in adopting self-adaptation, we performed a large-scale survey. We received 184 valid responses from practitioners spread over 21 countries. Based on the analysis of the survey data, we provide an empirically grounded overview the of state of the practice in the application of self-adaptation. From that, we derive insights for researchers to check their current research with industrial needs, and for practitioners to compare their current practice in applying self-adaptation. These insights also provide opportunities for applying self-adaptation in practice and pave the way for future industry-research collaborations.

There is a notable discrepancy between the relative prosperity of Europeans and the global security and sustainability challenge. The mission of the ERASMUS+ 2020 European University for Well-Being (EUniWell) alliance is to address this. Our project, “Maximizing Academic and Social Outcomes in Engineering Education” (MASOEE) interprets this contradiction for engineering educators, exploring how to ensure graduates make the utmost contribution to societal wellbeing by narrowing attainment gaps. We are combining the expertise of British, French, Italian, and Swedish faculties to identify, share, and ultimately transfer best practices for professional, business, and sustainability skill teaching that is aligned to the EU competency frameworks including EntreComp (Bacigalupo et al. 2016) and GreenComp (Bianchi, Pisiotis, and Cabrera Giraldez 2022). Furthermore, we are finding out how disadvantaged cohorts in each partner faculty are characterized and supported. The project is guided by the following research questions:

• What are the similarities and differences between our students, staff, teaching, and culture?
• How are skills taught and embedded in programmes? What are student attitudes to learning these? How do we currently define and measure social outcomes?
• Which new approaches can we employ improve social and academic outcomes?

Self-Adaptation equips a software system with a feedback loop that automates tasks that otherwise need to be performed by operators. Such feedback loops have found their way to a variety of practical applications, one typical example is an elastic cloud. Yet, the state of the practice in self-Adaptation is currently not clear. To get insights into the use of self-Adaptation in practice, we are running a largescale survey with industry. This paper reports preliminary results based on survey data that we obtained from 113 practitioners spread over 16 countries, 62 of them work with concrete self-Adaptive systems. We highlight the main insights obtained so far: motivations for self-Adaptation, concrete use cases, and difficulties encountered when applying self-Adaptation in practice. We conclude the paper with outlining our plans for the remainder of the study. © 2022 ACM.