There is a troubling trend in science classrooms throughout Europe. School-aged students’ interest in science-related careers has been waning, achievement in science has been decreasing in many countries, and there is a widening gap between students based on migration background. These trends are especially alarming given that scientific and technological competencies are playing an increasingly critical role in economic growth and societies’ ability to address complex global challenges. Decades of research in science education have consistently established that inquiry-oriented (emphasizing questions, evidence, explanation, and communication), coherent (emphasizing a small set of key ideas over time through connected inquiry lessons) instruction aligns with current understanding of how students learn, creatively engages students in both the practice and content of science, and helps to engage diverse learners in the collaborative co-construction of scientific knowledge. Yet, despite widespread availability inquiry-oriented curricular resources, typical school science instruction often looks starkly different from the coherent, inquiry-oriented learning environments that the science education research literature has shown to be effective. Science teacher education experiences are critical for addressing this disparity by helping new teachers learn to teach science using pedagogy that is likely quite different from that which they experienced as science students. In this strategic partnership, we focused on sharing best practices for designing effective science teacher education that supports new teachers in implementing coherent, inquiry-oriented pedagogy. We assembled a group of six partners in the Baltic region and Turkey (which represents a substantial fraction of the migrant population in the Baltic region) to share and reflect upon promising approaches in science teacher education that can support preservice and new teachers in designing and implementing coherent, inquiry-oriented science instruction. Each project partner institution brought rich experience in providing science teacher education and in the development and support of coherent, inquiry-oriented science instruction; this project focused on bringing this expertise together to engage in much-needed knowledge sharing and to spur future innovation in science teacher education. We structured our partnership using the same design principles of coherent science instructional environments that we seek to promote, including contextualizing learning with meaningful questions, focusing on a small set of core ideas over time, and fostering reflective collaboration and communication. We organize project activities according to the overarching (driving) question: “How can teacher education experiences better prepare new science teachers to implement coherent science instruction?” To address this question, we have designed a series of workshops in partner countries across the Baltic region. In each workshop, host science teacher education institutions worked with local stakeholders (school-based educators, policy-makers, and teacher professional developers) to showcase promising practices for promoting coherent science instruction through teacher education, and host institutes received reflective feedback from other project partners. By using the principles of coherent instruction to structure our partnership, we both modeled best practices and ensured that activities build on each other over time. Our project resulted in the identification of key elements of science teacher education programs that support the enactment of coherent science instruction in schools. We have developed a model that identifies these elements and maps them relative to each other, and our hope is that this model might guide others in designing and refining science teacher education programs. This model is described in detail in the PICoSTE Project Final Report. Additionally, we make two key recommendations as a result of this project. First, science teacher education programs must themselves be coherent by focusing on a small set of ideas over time and across contexts. Second, science teacher education programs must actively work to build shared understanding and substantive collaboration between faculties across school and university contexts.

The XPM project aims to integrate explanations into Artificial Intelligence (AI) solutions within the area of Predictive Maintenance (PM). Real-world applications of PM are increasingly complex, with intricate interactions of many components. AI solutions are a very popular technique in this domain, and especially the black-box models based on deep learning approaches are showing very promising results in terms of predictive accuracy and capability of modelling complex systems. However, the decisions made by these black-box models are often difficult for human experts to understand – and therefore to act upon. The complete repair plan and maintenance actions that must be performed based on the detected symptoms of damage and wear often require complex reasoning and planning process, involving many actors and balancing different priorities. It is not realistic to expect this complete solution to be created automatically – there is too much context that needs to be taken into account. Therefore, operators, technicians and managers require insights to understand what is happening, why it is happening, and how to react. Today’s mostly black-box AI does not provide these insights, nor does it support experts in making maintenance decisions based on the deviations it detects. The effectiveness of the PM system depends much less on the accuracy of the alarms the AI raises than on the relevancy of the actions operators perform based on these alarms. In the XPM project, we will develop several different types of explanations (anything from visual analytics through prototypical examples to deductive argumentative systems) and demonstrate their usefulness in four selected case studies: electric vehicles, metro trains, steel plant and wind farms. In each of them, we will demonstrate how the right explanations of decisions made by AI systems lead to better results across several dimensions, including identifying the component or part of the process where the problem has occurred; understanding the severity and future consequences of detected deviations; choosing the optimal repair and maintenance plan from several alternatives created based on different priorities; and understanding the reasons why the problem has occurred in the first place as a way to improve system design for the future.

There is enough waste energy produced in the EU to heat the EU’s entire building stock; however despite of this huge potential, only a restricted number of small scale examples of urban waste heat recovery are present across the EU. The objective of REUSEHEAT is to demonstrate, at TRL8 first of their kind advanced, modular and replicable systems enabling the recovery and reuse of waste heat available at the urban level. REUSEHEAT explicitly builds on previous knowledge and EU funded projects (notably CELSIUS, Stratego and HRE4) and intends to overcome both technical and non technical barriers towards the unlocking of urban waste heat recovery investments across Europe. Four large scale demonstrators will be deployed, monitored and evaluated during the project, showing the technical feasibility and economic viability of waste heat recovery and reuse from data centres (Brunswick), sewage collectors (Nice), cooling system of a hospital (Madrid) and underground station (Berlin). The knowledge generated from the demonstrators and from other examples across the EU will be consolidated into a handbook which will provide future investors with new insight in terms of urban waste heat recovery potential across the EU. Innovative and efficient technologies and solutions, suitable business models and contractual arrangements, estimation of investment risk, bankability and impact of urban waste heat recovery investments, authorization procedures are examples of handbook content. The handbook will be promoted through a powerful dissemination and training strategy in order to encourage a rapid and widespread replication of the demonstrated solutions across the EU.

The purpose of B-SHAPES is to refocus on the role of borders in shaping perceptions of European societies in the 21st century, confronted with the challenge of re-borderings in Europe. Borders play a key role in shaping our perceptions of societies, culture, heritage and be-longing. B-SHAPES results will open for a reconfiguration of heritage policies, replacing national approaches with cross-border, European approaches to heritage, empowering citizens and economic sectors to contribute to the creation of a more inclusive vision of cultures and values. Scrutinizing the idea of a socially and culturally coherent Europe addressed in the call B-SHAPES will use a people’s perspective to focus on re-bordering as a European crisis with a negative impact on the quality of life in border regions. Border regions are living labs of European integration. The border closures of March 2020, induced by the pandemic, have severely disrupted previous attempts to develop more cross-border, inclusive, European perceptions of heritage and culture. Borders have continued to be a decisive factor shaping perceptions of ‘us’ and ‘them’, of culture, identity and belonging. Therefore, it is necessary to refocus on the central role of borders for the European integration project, for how they influence people’s perceptions of Europe’s historical and cultural past, of heritage, culture, identity and belonging. B-SHAPES will apply different participatory and ethnographic methods of Citizen Science, focusing especially on youth and minorities, to collect data in different European border regions to scrutinize this challenge with the aim to develop strategies and innovative policies using more inclusive approaches to cultivate joint natural, cultural, and historic heritage.