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This study aims to provide an overview of the past two decades of lifelong learning (LLL) policies for enhancing employability and reduce social exclusion in young people of European countries through the development of the so-called LLL key-competences.

Built on a quasi-systematic review, this contribution explores traditional and new methods for promoting the LLL transition, and then employability, in young adults (e.g. apprenticeship, vocational training, e-learning, etc.).

It argues the need to identify all the possible approaches able to support policymakers, as they can differently impact key-competence development.

Finally, based on the consolidated EU policy experience, we propose a strategy of implementation of the LLL programmes that facilitates the institutions’ decision processes for policy-making through the use of decisional support system.

This study aims to acknowledge that most Indonesian small and medium enterprises (SMEs) experience slow growth. It highlighted that this sluggishness is because of some falsification of Indonesia’s ecological psychology. It focuses on investigating the situated cognition that probably supports this falsification, such as affordance, a community of practice, embodiment and the legitimacy of peripheral participation situated cognition and social intelligence theories.

This study obtained data from published newspapers between October 2016 and February 2019. The authors used the Waikato Environment for Knowledge Analysis and the J48 C.45 algorithm. The authors analyzed the data using the emergence of news probability for both the Government of Indonesia (GoI) and Indonesian society and the situated cognition concerning the improvement of the SMEs. The authors inferred ecological psychology from these published newspapers in Indonesia that the engaged actions were still suppressed, in comparison with being and doing.

This study contributes to the innovation and leadership policies of the SMEs’ managerial systems and the GoI. After this study identified the backward-looking practices, which the GoI and the people of Indonesia held, this study recommended some policies to help create a forward-looking orientation. The second one is also a policy for the GoI, which needs to reduce the discrepancy between the signified and the signifier, as recommended by the structuralist theory. The last one is suggested by the social learning theory; policies are needed that relate to developing the SMEs’ beliefs, attitudes and behavior. It means that the GoI should prepare the required social contexts, which are in motoric production and reinforcement. Explicitly, the authors argue that the GoI facilitates SMEs by emphasizing the internal learning process.

The authors present some possibilities for the limitations of this research. The authors took into account that this study assumes the SMEs are all the same, without industrial clustering. It considers that the need for social learning and social cognition by the unclustered industries is equal. Second, the authors acknowledge that Indonesia is an emerging country, and its economic structure has three levels of contributors; the companies listed on the Indonesian Stock Exchange, then the SMEs and the lowest level is the underground economy. Third, the authors did not distinguish the levels of success for the empowerment programs that are conducted by either the GoI or the local governments. This study recognizes that the authors did not measure success levels. It means that the authors only focused on the knowledge content.

From these pieces of evidence, this study constructed its strategies. The authors offer three kinds of policies. The first is the submission of special allocation funds from which the GoI and local governments develop their budgets for the SMEs’ social learning and social cognition. The second is the development of social learning and social cognition’s curricula for both the SMEs’ owners and executive officers. The third is the need for a national knowledge repository for all the Indonesian SMEs. This repository is used for the dissemination of knowledge.

This study raises argumental novelties with some of the critical reasoning. First, the authors argue that the sluggishness of the Indonesian SMEs is because of some fallacies in their social cognition. This social cognition is derived from the cultural knowledge that the GoI and people of Indonesia disclosed in the newspapers. This study shows the falsifications from the three main perspectives of the structuration, structuralist and social learning theories. Second, this study can elaborate on the causal factor for the sluggishness of Indonesia’s SMEs, which can be explained by philosophical science, especially its fallacies (Hundleby, 2010; Magnus and Callender, 2004). The authors expand the causal factors for each gap in every theory, which determined the SMEs’ sluggishness through the identification of inconsistencies in each dimension of their structuration, structuralism and social learning. This study focused on the fallacy of philosophical science that explains the misconceptions about the SMEs’ improvement because of faulty reasoning, which causes the wrong moves to be made in the future (Dorr, 2017; Pielke, 1999).

This study aims to discuss science governance in Europe and the network of associated nonprofit institutions. The authors posit that this network, which comprises both (partial) learning organizations and non-learning organizations, has been observed to postpone taking up “responsibility” as an issue in science governance and funding decisions.

This paper discusses the challenge of learning and policy implementation within the European science governance system. By exploring how learning on responsible innovation (RI) in this governance system can be provoked, it addresses the question how Senge’s insights in organizational learning can clarify discourses on and practices of RI and responsibility in research. This study explores the potential of a new organizational form, that of Social Labs, to support learning on Responsible Research and Innovation (RRI) in standing governance organizations.

This study concludes that Social Labs are a suitable format for enacting the five disciplines as identified by Senge, and a Social Lab may turn into a learning organization, be it a temporary one. Responsibility in research and innovation is conducive for learning in the setting of a Social Lab, and Social Labs act as intermediary organizations, which not merely pass on information among actors but also actively give substantive shape to what they convey from a practice-informed, normative orientation.

This empirical work on RRI-oriented Social Labs therefore suggests that Social Lab–oriented temporary, intermediary learning organizations present a promising form for implementing complex normative policies in a networked, nonhierarchical governance setting.

Based on this research funding and governance organizations in research, policy-makers in other domains may take up and create such intermediary organizations to aid learning in (science) governance.

This research suggests that RRI-oriented Social Labs present a promising form for implementing complex normative policies, thus integrate learning on and by responsible practices in various governance settings.

European science governance is characterized by a network of partial Learning Organization (LOs) and Non-Learning Organization (nLOs) who postpone decision-making on topics around “responsibility” and “solving societal challenges” or delegate authority to reviewers and individual actors, filtering possibilities for collaborative transformation toward RRI. social lab (SLs) are spaces that can address social problems or social challenges in an open, action-oriented and creative manner. As such, they may function as temporary, intermediary LOs bringing together diverse actors from a specific context to work on and learn about issues of science and society where standing organizations avoid doing so. Taken together, SLs may offer temporary organizational structures and spaces to move beyond top-down exercise of power or lack of real change to more open, deliberative and creative forms of sociopolitical coordination between multiple actors cutting across realms of state, practitioners of research and innovation and civil society. By taking the role of temporary LOs, they may support existing research and innovation organizations and research governance to become more flexible and adaptive.

This study was conducted to understand students' achievements in learning and to improve the overall curriculum of the first-year experience course.

In this study, a series of questionnaire-based surveys were conducted on students enrolled in the Introductory Seminar for Policy Science, a mandatory first-year experience course offered in the first semester (from April to July) at a university in Japan. The studies were conducted in 2015 (n = 29), 2016 (n = 29) and 2017 (n = 31).

Results revealed that, regardless of the year, students deepened their understanding of policy science and gained increased confidence to explain what group works and reports are throughout the semester. In addition, students' level of worry about life at the university decreased throughout the course in all three years. A stepwise multiple regression analysis (n = 84) revealed that those students who knew what policy science was (B = 0.271) and had the confidence to write their opinions in reports (B = 0.264) more likely answered that they knew what they wanted to study over four years at the university.

This study revealed that the mandatory first-year experience course taught by the same instructor generated similar educational effects for different students in different years. The results elucidated the progressive effects of different components of the course, eliminating possibilities of any bias or specific characteristics of a single group of students.

This article explores to what extent the long debate in England over the funding of long-term care (LTC) has involved learning from abroad.

It draws on Mossberger and Wolman’s (2003) framework which proposes criteria for assessing policy transfer as a form of prospective policy evaluation: awareness; assessment and application. The documents examined are the sources cited by the reports that examined funding LTC in England since 1999. The study uses interpretive content analysis in a deductive approach (applying the framework) that focuses on both manifest and latent content.

It finds that both the reports and the cited studies tend to focus on a fairly narrow range of nations, with most attention on Germany, Japan and Scotland. Most studies broadly do not provide much in the way of a clear rationale, and the level of details provided varies. There is relatively little focus on problems. Aims, objectives and goals are little mentioned in some studies, but they tend to be fairly abstract or “high level.” Similarly, there is limited detail on settings. Finally, only a few studies provide a clear recommendation.

It focuses on the neglected topic of the evidence behind reports which are intended to provide recommendations for policy change. The Mossberger and Wolman’s (2003) framework has been used in a small-scale but appears to be well-suited for this purpose.

In this research, the authors demonstrate the advantage of reinforcement learning (RL) based intrusion detection systems (IDS) to solve very complex problems (e.g. selecting input features, considering scarce resources and constrains) that cannot be solved by classical machine learning. The authors include a comparative study to build intrusion detection based on statistical machine learning and representational learning, using knowledge discovery in databases (KDD) Cup99 and Installation Support Center of Expertise (ISCX) 2012.

The methodology applies a data analytics approach, consisting of data exploration and machine learning model training and evaluation. To build a network-based intrusion detection system, the authors apply dueling double deep Q-networks architecture enabled with costly features, k-nearest neighbors (K-NN), support-vector machines (SVM) and convolution neural networks (CNN).

Machine learning-based intrusion detection are trained on historical datasets which lead to model drift and lack of generalization whereas RL is trained with data collected through interactions. RL is bound to learn from its interactions with a stochastic environment in the absence of a training dataset whereas supervised learning simply learns from collected data and require less computational resources.

All machine learning models have achieved high accuracy values and performance. One potential reason is that both datasets are simulated, and not realistic. It was not clear whether a validation was ever performed to show that data were collected from real network traffics.

The study provides guidelines to implement IDS with classical supervised learning, deep learning and RL.

The research applied the dueling double deep Q-networks architecture enabled with costly features to build network-based intrusion detection from network traffics. This research presents a comparative study of reinforcement-based instruction detection with counterparts built with statistical and representational machine learning.

The aim of this policy brief is to summarize the key priorities and recommendations made by ARC delegates and thought leaders who came together virtually between March 2020 and November 2021 to find ways to support students, parents, teachers, and school leaders in their respective educational communities during the COVID-19 pandemic.

This paper aims to examine how academics enact trust in e-learning through an inductive identification of perceived risks and enablers involved in e-learning adoption, in the context of higher education institutions (HEIs).

Grounded Theory was the methodology used to systematically analyse data collected in semi-structured interviews with 62 academics. Data analysis followed the constant comparative method and its three-staged coding approach: open, axial and selective coding.

The resulting trajectory of trust factors is presented in a Grounded Theory narrative where individual change and integration through shared collective understanding and institutionalisation are discussed as stages leading to the overcoming of e-learning adoption barriers.

The paper proposes that the interplay between institutionalism and individualism has implications in the success or failure of strategies for the adoption of e-learning in HEIs, as perceived by academics. In practical terms, this points to the need for close attention to contextually sensitive trust-building mechanisms that promote the balance between academics’ commitments, values and sense of self-worth and centrally planned policy, rules, resources and exhortations that enable action.