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The purpose of this paper, intended primarily for practitioners, is to demonstrate how features of psychological capital (PsyCap) may be combined with manager efforts to collaborate with an employee on an action learning project. In reciprocal action learning, manager and employee create a partnership to learn, achieve work-focused goals and advance their relationship. Initiatives aimed at positively stimulating employee assets and psychological or behavioral attributes can overlay the action learning process.

A narrative synthesis was used to examine three sources of empirical research from organizational psychology and human resource management: reciprocity, action learning and PsyCap. Information was integrated to create a guide, a model for managers for use in considering options about how to structure employee and self-learning, as well as options for use in stimulating employee assets and PsyCap.

The approach presented may serve as a practical guide for manager consideration. Research identifies several types of behaviors and activities intended to positively stimulate and reinforce the learning of both participants. The literature on PsyCap offers many initiatives for a manager to consider in assisting an employee to develop talent and positive attitudes. Such efforts have to be carefully tailored to the individual employee, the tasks at hand and the manager’s own learning needs.

The value of action learning is supported by a relatively large research base. The significance of PsyCap also has substantial support. Innovatively, this paper offers guidance to a manager in consideration of combining the attributes of both concepts to maximize positive effects on learning, personal growth, skill development and work achievement.

This paper aims to introduce the concept of Entrepreneurial Collective Intelligence (ECI) as a means of understanding how communities of entrepreneurial actors learn to act both collectively and knowingly. It explores how connections between processes of CI, agency and action can explain and enable the development entrepreneurial community organisations.

There is a selective literature review of prior works on the related fields of community and collective entrepreneurship; collectives and intelligence; agency and action. The review is used to propose a framework of collective entrepreneurial intelligence, agency and action. An interpretive approach is used to research four case studies of community organisations which use CI to generate entrepreneurial outcomes.

The cases are compared with themes from prior literature to develop a conceptual model of four ECI processes which enable intelligence, agency and action: collaborative processes; distributed working; intelligence representations and organisation of infrastructures. These are theorised to discuss ideas, challenges, methods and questions to enhance entrepreneurial actions, based on sharing knowledge and learning, in the context of collective agency, action and intelligence.

The four processes, both together and separately, represent a coherent framework useful for further studies on the role of collectives in enterprising communities.

The four processes each represent a central area of attention, not only for development, learning, decision-making and leadership within enterprising communities but also for entrepreneurship education in terms of alternative didactics, pedagogies and learning forms.

The improved knowledge on the role of collective agency and CI within entrepreneurial processes is useful for strengthening civil activism and other fruitful forms of entrepreneurial collective processes. This may help solve complicated societal problems where traditional conceptions of entrepreneurship fail.

The conceptual contribution is to explain the dynamic relationships between ECI and action, mediated by collective agency. The role of CI in informing entrepreneurial communities is explored and four enabling processes are proposed. This coherent framework is useful for further studies on the role of collectives in enterprising communities, whilst informing their learning, decision-making and leadership.

Prior research suggests that collaboration is key to sustainable community development and environmental management, and peer-to-peer learning (P2PL) may facilitate community building and collaborative learning skills. This study aims to examine the effect of P2PL on the enhancement of environmental management and sustainable development skills, community building and social capital (i.e. connectedness) and understanding of course learning objectives.

Quantitative and qualitative longitudinal survey data was collected in a sustainable development focused course offered at a large American public university that uses P2PL to explicitly facilitate community building and collaborative skills. Safety precautions and changing locational course offerings due to the COVID-19 pandemic in years 2020, 2021 and 2022 provided an opportunity to evaluate the impact of P2PL on these skills during both virtual and in-person formats. Additionally, this study compared in-course student evaluations with students taking other sustainable development-related courses with collaborative learning aspects to understand the wider effectiveness of this course structure.

This study finds that course format (virtual vs in-person) overall made no difference in either connectedness or conceptual understandings, and that students in both formats felt more connected to others than students taking other courses with P2PL. Scaffolding P2PL and supplemental peer support can yield improved connectedness and learning among students taking environmental coursework.

Sustainable development requires group collaboration and partnership building skills. Issues are consistently raised about the challenges to teaching these skills in higher education. The students and instructors in this research study identify P2PL strategies to address these challenges for in-person and virtual classroom settings.

The purpose of this paper is to argue that human resource development (HRD) needs to embrace and include futures and foresight learning (FFL) as a new addition to its field of theorising and practice. The question to consider is: How can FFL become a new feature of HRD? A key part of the authors’ argument is that the inclusion of FFL will enable HRD to add to the success of any organisation and make a vital contribution to the management of people at work.

This paper firstly considers some of the debates surrounding the meaning of HRD. The authors suggest that instability of the time serves to disturb any comforts that have been created in HRD and that there is a need to consider how there might be different futures for what we still call HRD in research, practice and praxis. This paper then considers how FFL might become one possibility for expanding the existing boundaries of HRD. The authors characterise futures and foresight as a learning process, which provides new but complementary features to what is already considered as HRD. This paper will show how FFL can lead to organisation's success and the way this can be achieved.

There is a wide variety of meanings of the term HRD; however, HRD is still cast as a “weakened profession” which has to play a subservient role to others in the workplace. Over the last 15 years, the expansion of the meaning of HRD has been seen as evidence of its evolving and emerging nature and development based on a co-creation with other disciplines. This creates a space for FFL, defined as an ongoing learning process to find predictable, probable, possible and/or a variety of long-term futures. FFL embraces three key processes of scanning, futuring and reconfiguring, all of which contain a high potential for participants and others to learn as they proceed, providing outcomes at each stage. FFL has been shown to enhance organisation performance and success and HRD interventions can play a key part in implementation. This represents a significant opportunity for the HRD profession to move from weakness towards strength.

For HRD researchers, while FFL is not yet on its radar, the authors would argue that the uncertainties of the future require that more attention be given to what might lie ahead. Indeed, HRD researchers need to ask the question: What is the future of HRD research? In addition, if the authors’ call for FFL to be included in the practice of HRD, such practice will itself provide new pathways for HRD research. Further research questions might include: To what extent is FFL practiced in organisations and what role do HRD practitioners play in delivery? How does FFL impact on organisation behaviour and outcomes? What new products and services emerge from FFL? What new skills are required to deliver FFL? Can FFL enhance the status of HRD practitioners in the work place and its role in decision-making? and How can the HRD profession develop as a hybrid profession with respect to machine learning (ML)/artificial intelligence (AI)?

FFL produces outcomes that have importance for strategy, HRD practitioner can learn to facilitate FFL by action learning and in leadership development programmes. FFL offers a significant opportunity to enhance the importance of HRD in organisations and beyond. FFL offers those involved in HRD a significant opportunity to transfer ideas into practice that have an impact on organisation sustainability. HRD can play a significant role in the design and delivery of ML and AI projects.

This paper concludes with a call for embracing FFL as a challenging but important addition to how we talk about learning at work. The authors argue that FFL offers a significant opportunity to enhance the importance of HRD in organisations and beyond. At its centre, FFL involves learning by people, groups, organisations and machines and this has to be of concern to HRD.

Large class sizes are becoming the norm in higher education against concerns of dropping learning qualities. To maintain the standard of learning and add value, one of the common strategies is for the course convenor to proactively monitor student engagement with learning activities against their assessment outcomes and intervene timely. Learning analytics has been increasingly adopted to provide these insights into student engagement and their performance. This case study explores how learning analytics can be used to meet the convenor’s requirements and help reduce administrative workload in a large health science class at the University of New South Wales.

This case-based study adopts an “action learning research approach” in assessing ways of using learning analytics for reducing workload in the educator’s own context and critically reflecting on experiences for improvements. This approach emphasises reflexive methodology, where the educator constantly assesses the context, implements an intervention and reflects on the process for in-time adjustments, improvements and future development.

The results highlighted ease for the teacher towards the early “flagging” of students who may not be active within the learning management system or who have performed poorly on assessment tasks. Coupled with the ability to send emails to the “flagged” students, this has led to a more personal approach while reducing the number of steps normally required. An unanticipated outcome was the potential for additional time saving through improving the scaffolding mechanisms if the learning analytics were customisable for individual courses.

The results provide further benefits for learning analytics to assist the educator in a growing blended learning environment. They also reveal the potential for learning analytics to be an effective adjunct towards promoting personal learning design.

With the growing need for employees to be innovative, public-sector organizations are investing in employee training. This study aims to examine the effects of a combined Lean Six Sigma and innovation training, using action learning, on public-sector employees’ creative role identity and innovative work behavior.

The authors studied a public service agency in Singapore in which a five-day Lean Innovation Training was implemented, using a combination of Lean Six Sigma and Creative Problem-Solving tools, with a simulation on day one and subsequent team-based project coaching, spread over six months. The authors administered pre- and postintervention surveys among all the employees, and initiated group interviews and observations before, during and after the intervention.

Creative role identity and innovative work behavior had significantly improved six months after the intervention, enabled through senior management’s transformational leadership. The training induced managers to role-model innovative work behaviors while cocreating, with their employees, a renewal of their agency’s core processes. The three completed improvement projects contributed to an innovative work culture and reduced service turnaround time.

Starting with a role-playing simulation on the first day, during which leaders and followers swapped roles, the action-learning type training taught all the organizational members to use various Lean Six Sigma and Creative Problem-Solving tools. This nimble Lean Innovation Training, and subsequent team-based project coaching, exemplifies how advancing the staff’s creative role identity can have a positive impact.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

To address the absence of Lean in transportation logistics in the digital era, this study aims to investigate the application of Lean transportation (LT) tools to reduce waste and facilitate the digital transformation of dedicated road transportation in the offshore industry.

The study adopts action research with a multimethod approach, including a scoping review, focus groups (FG) and participant observation. The research is conducted within the offshore supply chain of a major oil and gas company.

Implementing LT’s continuous improvement tools, particularly value stream mapping (VSM), reduces offshore transportation waste and provides empirical evidence about the intersection of Lean and digital technologies. Applying techniques drawn from organisational learning theory (OLT), stakeholders involved in VSM mapping and FGs engage in problem-solving and develop action plans, driving digital transformation. Waste reduction in loading and unloading stages leads to control actions, automation and process improvements, significantly reducing downtime. This results in an annual monetary gain of US$1.3m. The study also identifies waste related to human effort and underutilised digital resources.

This study contributes to theory and practice by using action research and LT techniques in a real intervention case. From the lens of OLT, it highlights the potential of LT tools for digital transformation and demonstrates the convergence of waste reduction through Lean and Industry 4.0 technologies in the offshore supply chain. Practical outputs, including a benchmarking questionnaire and a plan-do-check-act cycle, are provided for other companies in the same industry segment.

The purpose of this study is to investigate the driving factors for staff cohesiveness in the workplace and how they are related to workplace learning and development opportunities. Two research questions guided the inquiry: (1) What are the driving factors for staff cohesiveness in the workplace? and (2) How does staff cohesiveness influence workplace learning?

This study is based on a phenomenological research design. The data collection involved interviews and focus group discussions with 22 lecturers in two public universities. Thematic analysis was followed to analyse and interpret data.

The findings of this study indicate that staff cohesiveness is greatly influenced by several factors. Firstly, the presence of shared visions and goals plays a significant role in fostering staff cohesion. In addition, the similarity of age and gender among employees, as well as the presence of mutual support and a sense of belongingness, trust and solidarity, managerial support and the nature of the job that requires collective action, all contribute to staff cohesiveness. It is worth noting that previous studies have not reported the influence of age, gender and job characteristics as factors influencing staff cohesiveness.

Employers should not only focus on the knowledge and hard skills of applicants but also on the soft skills which support teamwork and cohesion in the workplace. Managers who want to enhance workplace learning should create opportunities for social gatherings and informal contacts in the workplace to facilitate informal learning in the workplace. Researchers focusing on workplace learning should include tacit learning practices that occur in the workplace as a result of the closeness between teammates.

This manuscript, which the authors hereby present, is the result of own original work. To the best of the authors’ knowledge, the authors wish to emphasise that it has not been submitted for publication in any other journals.

Climate change poses risks to society and the demand for carbon literacy within small and medium-sized enterprises is increasing. Skills and knowledge are required for organizational greenhouse gas accounting and science-based decisions to help businesses reduce transitional risks. At the University of Copenhagen and the University of Northern British Columbia, two carbon management courses have been developed to respond to this growing need. Using an action-based co-learning model, students and business are paired to quantify and report emissions and develop climate plans and communication strategies.

This paper draws on surveys of businesses that have partnered with the co-learning model, designed to provide insight on carbon reductions and the impacts of co-learning. Data collected from 12 respondents in Denmark and 19 respondents in Canada allow for cross-institutional and international comparison in a Global North context.

Results show that while co-learning for carbon literacy is welcomed, companies identify limitations: time and resources; solution feasibility; governance and reporting structures; and communication methods. Findings reveal a need for extension, both forwards and backwards in time, indicating that the collaborations need to be lengthened and/or intensified. Balancing academic requirements detracts from usability for businesses, and while municipal and national policy and emission targets help generate a general societal understanding of the issue, there is no concrete guidance on how businesses can implement operational changes based on inventory results.

The research brings new knowledge to the field of transitional climate risks and does so with a focus on both small businesses and universities as important co-learning actors in low-carbon transitions. The comparison across geographies and institutions contributes an international solution perspective to climate change mitigation and adaptation strategies.