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Abstract
This article analyzes learning in the EU's Common Security and Defence Policy (CSDP) by way of drawing on recent theoretical advancements on the concept of communities of practice (CoP) in international relations (IR). The article presents an analytical framework that distinguishes between reproductive and transformative learning in relation to levels of contestation in CoPs. To illustrate the framework's analytical usefulness, the article analyzes the case of CSDP lessons learning during the COVID-19 pandemic. The analysis draws on data from a survey as well as interviews with EU officials, and it suggests that the combination of an external crisis and an institutional momentum to facilitate collective learning produced a context where CSDP practitioners demonstrated more willingness to engage in the formal process of recording lessons. A shared sense of urgency in collecting lessons from the pandemic and the unprecedented absence of informal sites for learning practices due to restrictions of physical meetings, meant that semi-formal learning practices could fill the void of informal interactions. This provided for a unique context for transformative learning in the CSDP that is highly relevant for IR scholars interested in the political effects of learning and contestation in international organizations and in CoPs more generally.

Purpose
This paper aims to explore whether formal, non-formal, and informal learning experiences contribute to developing sustainable development competencies (SDCs) among students in a Principles of Responsible Management Education (PRME) signatory business school.


Design/methodology/approach
An online survey based on the students' learning experiences and a questionnaire on sustainability competencies already validated in the literature were given to a sample of 274 bachelor students at a PRME signatory business school. Nominal variables representing students' categories were created to test a set of hypotheses developed according to the literature. Because the data was not normally distributed, non-parametric independent-samples Mann–Whitney U test was conducted, and descriptive statistics was used to help the analysis.


Findings
The results suggest that a hybrid format with a combination of formal, non-formal and informal learning experiences is essential to maximising the development of SDCs and raising students' sustainability literacy.


Research limitations/implications
This study is one of the first attempts to understand the importance of a hybrid approach in developing sustainable competencies (SDCs). Future studies could adopt longitudinal analysis to check the development of these competencies over time, assess students from different PRME signatory schools or comparing students to those in non-signatory business schools.


Practical implications
This study provides insight into how business schools could address challenges in developing sustainable competencies through redirecting their educational systems by balancing formal, informal and non-formal learning approaches to educate future responsible leaders.


Originality/value
This research provides evidence on how a hybrid learning approach could maximise the development of sustainable development competencies and, therefore, generating insights for educational policies.

Purpose
Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.


Design/methodology/approach
In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach's functions.


Findings
The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.


Research limitations/implications
The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.


Originality/value
The proposed approach explores the possibility of using machine learning for SDG classifications in scale.

In recent years the issue of youth unemployment has been identified as one of the most pressing for young people, who are affected particularly hard by the economic crisis in the European Union. In response, the EU institutions have designed and introduced a complex mix of political instruments, agencies, programmes and studies that are supposed to establish a complementary and systemic approach to education and youth policies. Youth policy, as a socioeconomic field of EU political intervention began in 2014 to be subject to a paradigm of employability and "the economy of fighting the crisis", including issues such as non-formal and informal learning and youth work outside of schooling systems. Thus the EU policy in question has significantly shifted from "personal and cultural development, and inspiring a sense of active citizenship among young people," as it was formulated in the Youth in Action Programme 2006-2013, towards "the acquisition of professional skills of youth workers, validation systems of non-formal learning, and greater complementarities with formal education and training", as it is formulated in the Youth Sector of the EU programme for Education - Erasmus+ 2014-2020. The objective of this article is to provide a comparative insight into the context that frames the design of EU policies aimed at mitigating the phenomenon of unemployment among young people, and to show how this has changed in light of the new EU programming period.

Becoming an entrepreneur is a way for someone who does have creative ideas and does have the intention to make ends meet. It is hoped that with an embedded entrepreneurial spirit, young people can create jobs for themselves and others. This research is using a qualitative approach by case study design. The case is entrepreneur activity as non-formal learning for higher education students in Universitas Negeri Padang. The results of this research are that entrepreneurial welfare increasing, Indonesia's economy will also be more advanced, and able to catch up. The government is very supportive if the entrepreneurial spirit can be applied to students. It also refers to students who have graduated from college not to concentrate too much on looking for work and start creating jobs. Not only the government, but several also support. The government has conducted training for entrepreneurship interest in youth to introduce to business, then create creative ideas and change the mindset of youth to be able to create a business. In creating a business, of course, several strategies are needed to produce a thriving business. Some of the proposed strategies for a startup consist of determining a business idea, knowing people's needs, and knowing market conditions.

AbstractAs debates continue over the effectiveness of after‐school programs, we need to create stronger links between schools and out‐of‐school activities. Where do such connections begin? How can we integrate skill‐building and academic competence into the out‐of‐school‐time context?

This dissertation focuses on how entrepreneurs learn to acquire entrepreneurial knowledge and competence, which ultimately can open doors to business success. Contemporary critics suggest that programs designed to develop general competence are not sufficiently relevant to these entrepreneurs. On the other hand, scholars and practitioners have recently noticed that external relations in formal learning networks can be a notable opportunity for learning in entrepreneurs. The aim of this dissertation is to elaborate on the processes and outcomes of government supported learning networks among entrepreneurs who work in small and medium sized enterprises. It draws on reports of four separate but interrelated research studies that author conducted. The research described in the dissertation is based on multiple theoretical perspectives, methodologies, and data sources. To gain a full understanding of the experiences of the different network participants, as well as the interactive processes within the learning network, data were collected from multiple sources: interviews, participant observation, and videotaping. The conclusions stated in appended paper 1 and 2 are primarily based on the interviews, but they are also supported by the observations and written material. Paper three focuses on the videos in combination with the interviews. Finally, to complement the qualitative research with insights regarding the relationships among trust, learning, and self-efficacy, the last paper reports the results of a quantitative survey study. The dissertation makes several major contributions to knowledge. First and foremost, by combining entrepreneurship theory and learning theory, it describes the outcomes that can emerge from formal learning networks and shows how these outcomes can have entrepreneurial consequences. Second, it suggests how the learning situation can be characterized and describes an appropriate learning environment for entrepreneurs from small and medium sized enterprises. The research also contributes to theory on how trust in formal learning networks is built and how this trust contributes to entrepreneurial learning. At the same time, it shows that the potential benefits derived from trust cannot be realized without incorporating the entrepreneur's level of self-efficacy in the analysis. The dissertation concludes by offering suggestions for exploiting learning and business opportunities through the construction and utilization of learning networks.

This article offers insights into the practices of a non-formal education programme for youth provided by the European Union (EU). It takes a qualitative approach and is based on a case study of the European Voluntary Service (EVS). Data were collected during individual and focus group interviews with learners (the EVS volunteers), decision takers and trainers, with the aim of deriving an understanding of learning in non-formal education. The research questions concerned learning, the recognition of learning and perspectives of usefulness. The study also examined the Youthpass documentation tool as a key to understanding the recognition of learning and to determine whether the learning was useful for learners (the volunteers). The findings and analysis offer several interpretations of learning, and the recognition of learning, which take place in non-formal education. The findings also revealed that it is complicated to divide learning into formal and non-formal categories; instead, non-formal education is useful for individual learners when both formal and non-formal educational contexts are integrated. As a consequence, the division of formal and non-formal (and possibly even informal) learning creates a gap which works against the development of flexible and interconnected education with ubiquitous learning and mobility within and across formal and non-formal education. This development is not in the best interests of learners, especially when seeking useful learning and education for youth (what the authors term "youthful" for youth in action). ; Originally published in thesis in manuscript form with title: "Non-formal learning: 'youthful' or 'youthless' for youths in action?"