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The aim of this paper is to analyze the links between leaders' creation of knowledge in the setting of a leadership development program and the transfer of knowledge to their own organizations.

This is a case study of a leadership development program conducted during 2020–2022. The program was focused on how to lead and manage learning and knowledge processes in organizations, and offered a mix of theoretical perspectives and practical collaborative sessions. Data were collected through interviews and the participants' written reflections on their learning experiences. Total number of interviews was 13.

Overall the participants showed many examples of how they applied theories and practical tools that they had learned during the program in their own organizations. The participants experienced different types of challenges regarding knowledge transfer, but also potential meta-knowledge transfer through dialogue.

Pedagogical organizing of leadership development point to a need for supplementary dialogue between the leader of the development program and both the participating leader and manager.

This study shows that meta-knowledge transfer is not a simple matter of moving codified knowledge from the development program to new settings. Knowledge about others' knowledge requires and stimulates subject-to-subject relations between people through which new knowledge potential is created. These findings confirm and enhance previous studies that indicate the need for social support for soft-skill knowledge transfer.

The purpose of this paper is to examine the relationship among training design, trainee motivation and work environment on the transfer of learning for teachers enrolled in a continuing professional education (CPE) training program and the confirmation of potential positive, predictive relationships of trainee motivation, work environment and training design to transfer of learning. This study investigated the contribution of training efficiency and relevance as measured by the training design; work environment as measured by work autonomy, work complexity and work variability; and trainee’s motivation of training (learning- and job-oriented) to the transfer of knowledge and skills from the training program to their workplace. Both direct and indirect effects of mentioned components on the learning transfer were explored.

This study included 160 teachers working in high-needs schools with large numbers of English learners (ELs) Southwest USA. Teachers in this study primarily needed professional development to empower them and enhance their instructional capacity for ELs and economically challenged students. During the recruitment, participants completed a demographic information (e.g. gender, ethnicity, number of years teaching, age, educational background) survey.

A mediation model with training design as the mediating factor was developed and analyzed. The results revealed that training design fully mediated the relationship between trainees’ work environments and the transfer of knowledge, skills and attitude acquired from the training to their workplace. Furthermore, it partially mediated the relationship between learning-oriented motivation and the transfer of learning. These findings further amplify the significance of CPE program training design and foster important considerations for future research regarding the isolation of specific training design aspects that significantly contribute to the mediation of these relationships.

Considering the significance of learning transfer in developing professional knowledge and skills for target employees and trainees, confirming the mediating effects of training design on training transfer holds critical implications for future research. Specific and purposeful attention needs to be given to the design of CPE training. Investigations into the effects of training design and successful elements such as the training platform (online, hybrid or in-person), sample size, group structure, facilitation and participant demographics are warranted.

The finding of this research provides a preliminary guide for scholar-practitioners. Results of the study confirmed the role that learning-oriented motivation, job-oriented motivation, work variability or flexibility, work complexity and training design play in transfer of learning. In practice, training professionals will be more comfortable pinpointing the factors that lead to the transfer of learning or the lack of it.

Learning transfer has been found to be imperative for target employees and trainees to develop professional knowledge, skills and attitudes. Results of this study reveal variables that promote the positive transfer of learning to the workplace.

This study aims to investigate the impact of technologies on the knowledge transfer process. In particular, the authors aim to analyze the topic of knowledge brokers and the relationship between broker and digital tools in the knowledge transfer process in the sport context. The study developed, therefore, aims to investigate the creating of this environment for knowledge transfer and knowledge sharing between man and machine, looking to improve the planning of technical sports projects of the clubs.

This paper presents a qualitative approach aimed at analyzing how platforms and the players’ agents can be useful tools in the knowledge transfer process. The research was conducted through a survey with a structured questionnaire via e-mail to 64 managers at the head of clubs playing in the Italian Series B basketball in the 2021–2022 championship. The total number of questions administered is 21.

The results demonstrate how sports directors, for the construction of a technical sports project, in addition to learning off the pitch by interactions with media, fans, pressure management, leadership skills, positive attitude, tolerance, understanding of other opinions, background and cultures, see the athletes’ agents as the main stakeholder of the managers. The research resulted, by the clubs’ managers, in both formal learning and informal-type learning. Informal learning, by far the most frequently used and most important in the general learning process of executives, is identified in the use that executives make of information available on digital platforms and of the fiduciary relationships that management has with players’ agents.

The results demonstrate the valuable opportunities for executives, coaches, managers and clubs to strategically manage learning and knowledge sharing. Improving and managing knowledge-sharing strategies would help increase knowledge, not only of the sports directors but also of the entire club, thus improving the absolute quality of the game within the Italian basketball divisions. The authors have developed an innovative framework regarding the construction of a “typed sports technical project”, and the authors have identified a series of crucial phases capable of determining the creation of a new roster of athletes.

This study aims to understand how practitioners use their insights in software development models to share experiences within and between organizations.

This is a qualitative study of practitioners in software development projects, in large-, medium- or small-size businesses. It analyzes interview material in three-step iterations to understand reflexive practice when using software development models.

The study shows how work processes are based on team members’ experiences and common views. This study highlights the challenges of organizational learning in system development projects. Current practice is unreflective, habitual and lacks systematic ways to address recurring problems and share information within and between organizations. Learning is episodic and sporadic. Knowledge from previous experience is individual not organizational.

Software development teams and organizations tend to learn about, and adopt, software development models episodically. This research expands understanding of how organizational learning takes place within and between organizations with practitioners who participate in teams. Learnings show the potential for further research to determine how new curriculums might be formed for teaching software development model improvements.

The impact of the number of coworkers participating in training on transfer outcomes has largely been overlooked. This paper aims to examine whether the number of coworkers participating in training interacts with peer support (PS) to influence training motivation and transfer.

Data were collected using a cross-sectional survey from a sample of 688 employees working in 14 midsize and large companies. All participants were recent trainees in various open skill (e.g. leadership) training programs. Moderated mediation was used to test the hypotheses.

Motivation to transfer (MTT) mediated the relationship between PS and perceived training transfer. When more coworkers participated in the training, PS had a stronger influence on trainee MTT.

Organizations should consider training coworker cohorts at the same time to influence MTT and training transfer. Generally, whole-team training programs could be used to boost training transfer outcomes, although it could potentially have a negative impact on transfer if PS is low.

To the best of the authors’ knowledge, this was the first study to demonstrate that the number of coworkers participating in training can moderate the effect of PS on MTT and training transfer.

This study investigates the impact of large-scale teaching in higher education on students’ preparedness for the workforce within the context of evolving labour market demands, the expansion of higher education and the application of high-impact teaching strategies. It synthesizes perspectives on employer work readiness, the challenges and opportunities of large-scale teaching and strategies for fostering a dynamic academia-industry feedback loop. This multifaceted approach ensures the relevance of curricula and graduates’ preparedness while addressing the skills gap through practical recommendations for aligning teaching methodologies with employer expectations.

The research methodically examines the multifaceted challenges and opportunities inherent in large-scale teaching. It focuses on sustaining student engagement, maintaining educational quality, personalizing learning experiences and cultivating essential soft skills in extensive student cohorts.

This study highlights the critical role of transversal skills in work readiness. It also uncovers that despite its challenges, large-scale teaching presents unique opportunities. The diversity of large student groups mirrors modern workplace complexities, and technological tools aid in personalizing learning experiences. Approaches like peer networking, innovative teaching methods, real-world simulations and collaborative resource utilization enrich education. The importance of experiential learning for augmenting large-scale teaching in honing soft skills is emphasized.

This manuscript contributes to the discourse on large-scale teaching, aligning it with employer expectations and the dynamic requirements of the job market. It offers a nuanced perspective on the challenges and opportunities this educational approach presents, providing insights for crafting engaging and effective learning experiences in large cohorts. The study uniquely integrates experiential learning, co-creation in education and industry-academia feedback loops, underscoring their importance in enhancing student work readiness in large-scale teaching.

Rooting in the literature on training and laying on Kirkpatrick model, this paper aims to explore key drivers of corporate training to identify how they can be combined into an integrated framework of learning for human capital development.

By adopting the constructivist grounded theory, this contribution analyzes the experience carried out in the last ten years by Virvelle, an Italian corporate training firm.

Results show the rise of five core categories, g1iving rise to an integrated model of Kirkpatrick. Their dynamic interplay led to a new orientation of Kirkpatrick model giving rise to a metalearning ecosystem.

Managerial implications have identified key factors on which building and implementing appropriate corporate training programmes capable of triggering co-generative processes of value creation. Particularly, the essential role of learning quality culture, digital technology and personalization are detected in integrating not only hard but furthermore soft shades of learning. Concerning theoretical implications, the emergence of key structural and systems enabling dimensions for learning, and contextual mechanisms involved in reshaping training effectiveness and achieving integrated learning outcomes are detected. The main limitation of this study lies in the need to generalize results: the conceptualized framework needs to be empirically tested.

The value of this research is built along three main points. The first is the integration among the core categories that an integrated learning system can be built on, promoting learning quality culture through positive feedback loops. The second is represented by the chance to enhance an integrated mutual knowledge development among engaged actors, thereby shaping a more holistic and multidimensional learning model. The third is related to the transversal role that digital technology plays in all phases of the training process as it integrates and enriches them.

The debriefing is a procedure based on intra-team feedback, which has frequently been applied in university formation in health but has been less used in business. The aim of this research is to analyse best practices in the actual implementation of debriefing in organisations, based on criteria the guidelines for carrying out each stage established in the procedure.

To achieve these goals, working teams from different organisations carried out 19 group-debriefing sessions on an authentic work problem. These sessions were observed and analysed following a qualitative approach.

After observing a debriefing session in 19 organisations, four categories related to its implementation have been identified: Self-analysis, information, planning and orientation of the development of the team.

It is important to mention some limitations to this work. The major limitation was the lack of published literature related to the debriefing in the area of organisational management. The qualitative and exploratory nature of the study limits the generalisation of the results.

The research has practical implications as the characterisation and description of each phase favours the transfer to implement the debriefing technique adequately in different types of organisations.

It has been observed that all forms of debriefing have a common purpose in learning and, team and employee development, due to the powerful transferability and usefulness of debriefing in different contexts. Therefore, knowing the correct use of debriefing is a breakthrough in this area. In addition, including this type of practice will not just facilitate a better performance, it will also help teams to learn to work in a team from their own experiences.

It has been characterised by the process of debriefing from the correct implementation of each phase through the analysis of the narratives that arise in the debriefing sessions carried out.

匯報是一個基於團隊內部回饋的程序, 它常見於大學組建的醫療衛生方面, 在商業上則較少使用。本研究擬基於匯報程序中所建立的每個階段, 來分析在組織內實際進行匯報的典範實務。

為達至研究目標, 來自不同組織的工作團隊, 就一個真實的工作問題進行了19個匯報會議。研究人員觀察這些會議, 並以定性研究法進行探討和分析。

研究人員觀察於19個組織進行的匯報會議後, 找出了四個進行匯報會議的範疇, 自我分析、資料、計劃和團隊發展的取向。

本研究提供了實務方面的啟示, 因研究結果確認了匯報每個階段的特徵的描述, 以及每個階段的描述, 這會幫助在不同種類的組織內進行匯報會議時, 舉行匯報使用之技巧得以靈活調動, 以發揮各技巧的最佳效果。

研究人員分析有關的匯報會議內的敘述, 並從會議每個階段的正確執行, 找出了匯報程序的各個特徵。

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

This paper aims to examine employee-driven innovation (EDI) intertwined with learning, creating a new description combining these two concepts: employee-driven learning and innovation (EDLI). This paper provides insights into the nature of EDLI based on the existing theories and perspectives. It seeks to elaborate EDLI as an ongoing process in and through work.

The paper draws on Jaakkola’s (2020) guidance for structuring a conceptual article. The authors first describe the theoretical starting points related to EDI and then elaborate its relationship with learning at work, with the aim of structuring the key elements involved, drawing on and interpreting existing theory and knowledge.

In summary, advanced here are five premises for describing EDLI at work: (1) EDI and workplace learning are strongly intertwined phenomena, (2) learning in the EDI process occurs simultaneously at the intra-personal and inter-personal levels as a reciprocal process of adaptive and innovative learning, (3) innovations are only manifested in and are relevant to the specific cultural-historical and social context of particular enterprises, (4) the continuity of innovations and learning processes is enabled by participation and (5) triggers from outside the workplace, behind the innovation and the specific consequences (that transcend workplace boundaries) of the innovation anchor aspects of the process outside the workplace or work practice.

The paper advances a description and justification of EDLI. As such, it extends, connects and updates previously established theoretical models and explanations of this about EDIs. Based on the premises advanced here, the theoretical and practical contributions are discussed and the research gaps and needs for further research identified.