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Technological progress is a determining factor in the factors leading to economic and social well-being. Simultaneously, the development of a sustainable economy is based on the conservation of resources. In the energy sector, this fact can be corroborated with the reduction of energy consumption, thus increasing economic efficiency. On the one hand, improving energy efficiency contributes to increasing the quality of life, productivity, and, implicitly, the economy, but on the other hand, it leads to excess energy use – this behavioral change is known as rebound. The research estimates the rebound effect at the macroeconomic level for European countries in the period 2000–2019, referring the analysis to each country's gross domestic product (GDP) and energy consumption, as well as comparing the preaccession and postaccession periods of Romania in the EU space. The rebound effect is determined using multidimensional analysis methods, depending on the GDP of each country as well as the behavior of each in the use of energy resources in industry, agriculture, and services. Although the study results confirm the strong link between energy consumption and GDP at the level of each state, they did not show considerable changes between countries at the level of the two periods.

In this chapter, I propose a model for how school-level leaders manage their emotions. This model consists of six components. School-level leaders typically have little direct influence over the first component of the model, which are the socio-contextual factors in the schools, school communities and jurisdictions in which they work. A school-level leader's identity, sense of self and their personal characteristics comprise the second component of the model. The third component of the model is a multi-directional arrow demonstrating connections and interactions between the socio-contextual factors and a school-level leader's sense of self. Factors that heighten school-level leaders' emotional experiences in schools are considered as part of the fourth component of this model for school-level leaders' emotional regulation. The fifth component are the emotional regulation strategies school-level leaders use to manage emotions that emerge as part of their workday, while influence of supports and professional learning are considered as part of the sixth component, Finally, the model also accounts for the chain reactions and feedback loops that can occur when an individual utilizes an emotional regulation strategy that is unsuccessful. Those processes produce new emotions that must be regulated using similar, or different, emotional regulation strategy(ies).

L. Dee Fink proposes that different and more significant kinds of learning should be created in higher education to transition student outcomes from simply “learning” to “significant learning,” and these new types of learning should be situated within significant learning experiences (Fink, 2003). Fink also identified a taxonomy of significant learning that included six components: integration, foundational knowledge, application, human dimension, caring, and learning how to learn. Using Fink’s Taxonomy of Significant Learning as a framework, the authors will share the development of a course on navigating the US Healthcare System that resulted in significant learning outcomes for students completing the first semester of a four-year Doctor of Pharmacy curriculum. Each learning experience will link to a component of the taxonomy and will serve as the mechanism for the authors to share the development and implementation associated with each aspect of the semester-long course. The assessment structure of the course is described in detail. The authors present one or more learning experiences to illustrate each component of Fink’s Taxonomy. Finally, lessons learned from the development and implementation of the course are presented to guide programs considering implementation of a similar significant learning experience.

This study analyzes the digital competencies and the attitude toward the use of information and communication technologies (ICT) in secondary school teachers of the Javier Heraud Public Educational Institution, Lima, Peru, according to the technology, pedagogy, and content knowledge (TPACK) model, which focuses on knowledge about technology knowledge (TK), pedagogical content (PK) and content knowledge (CK). This implies that it is important to take these components into account in the development of teaching work, in order to contribute to the quality of student learning, within the framework of the restrictions established due to the global health emergency. The study is based on the quantitative approach, type of correlational research and cross-sectional design, the sample consisted of 106 secondary education teachers, questionnaire was applied which were validated by five experts and its reliability was analyzed by the values obtained for Cronbach's alpha, for the digital competencies variable α = 0.861 and for the variable attitude toward the use of ICT α = 0.854. It has been shown that there is a relationship between digital competencies and the attitude toward the use of information and communication technologies in teachers of a Peruvian Public Educational Institution.

Active and transformative learning (ATL) challenges the new era of teaching and learning in higher education. In this chapter a systematic approach to ATL theories and methodologies is provided. Authors provide a unique methodological framework for the integration of active learning practices in modern higher education curricula. This chapter also provides an integrated context for the overall discussion of the phenomenon in the volume. The recent arrivals of new disruptive artificial intelligence-enabled technologies such as OpenAI, ChatGPT, DeepAI and others are only few aspects of a new challenging era for the teaching, learning, innovation and sustainability in the higher education.

Building industrial clusters is getting much more political attention and strategic orientation in all developing countries. This study started by revising the conceptual and theoretical frameworks for industrial clusters, followed by some insights and contributions about empirical bases for clusters' dynamics and processes. The study focused on the case of Agadir Agreement between four Arab countries (Egypt, Jordon, Morocco, and Tunisia), which was initiated after the Euro-Mediterranean partnerships, and the rationale of the agreement was based on the concept of cumulative value-added origin. The study based its methodology on analyzing the international and bilateral trade flows of six industrial goods from the automotive sector among the four countries and with the EU countries to detect the degree of industrial collaboration and the achieved success of each country in this sector. The study indicated that the four countries used the concept of industrial clusters for economic development, but the results of the analysis showed that till now Agadir Agreement only achieved a shallow integration, while failed to deeply integrate as one big collaborative industrial cluster.