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This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

In today’s workplace, employees are taking responsibility for their own learning and development. The learning paths they take are often strategically motivated and directed, as opposed to simply provided and planned by human resource professionals. Some learning-path types can be found specific to certain occupations, while learning-path strategies and motives can be found in employees regardless of occupation. For successful learning, individual learning paths must be recognized and it is also necessary to consider a specific occupational context.

The paper provides strategic insights and practical thinking that have influenced some of the world’s leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

This paper aims to explore the possible relationships between the dominant actor and levels of reflection within learning paths. Learning-network theory, the framework of individual learning paths (Poell and Van der Krogt, 2013), suggests that organizational actors create different learning processes through their interactions. The second theoretical perspective emphasizes the influence of interactions on the depth of the reflective process of an individual (Kemper et al., 2000).

This paper examines a thesis that dominant actors within four ideal learning paths may influence one of four anticipated levels of reflection for individuals. Two prior qualitative, interview-based data sets were reanalyzed and coded for pattern matching.

Reflection levels were higher than anticipated for several ideal learning paths and lower in others. Findings indicate that contextual variables impact the level of reflection, importantly the role of coaches, mentors, feedback and reflective learning programs.

Data sets were reanalyzed from prior studies with relatively small numbers of participants. Further research is necessary to draw conclusions about the relationships between the two constructs.

This research shows the impact of incorporating reflective practices in workplace learning programs to increase levels of reflection. This study did not find fixed relationships, but rather discovered more fluid, dynamic relationships. Those responsible for creating learning programs might consider the potential of including reflective practices even in highly structured learning arrangements.

In the complex, rapidly changing organizational environment, where employees need to adapt and change, reflective practices seem to influence desired behavioral change and learning.

This study sheds new light on the potential impact of reflective practices in workplace learning arrangements.

The purpose of this paper is to identify the different sequence generation techniques for learning, which are applied to a broad category of personalized learning experiences. The papers have been classified using different attributes, such as the techniques used for sequence generation, attributes used for sequence generation; whether the learner is profiled automatically or manually; and whether the path generated is dynamic or static.

The search for terms learning sequence generation and E-learning produced thousands of results. The results were filtered, and a few questions were answered before including them in the review. Papers published only after 2005 were included in the review.

The findings of the paper were: most of the systems generated non-adaptive paths. Systems asked the learners to manually enter their attributes. The systems used one or a maximum of two learner attributes for path generation.

The review pointed out the importance and benefits of learning sequence generation systems. The problems in existing systems and future areas of research were identified which will help future researchers to pursue research in this area.

This paper aims to focus on professional development in the education sector. Its goal is to understand team leaders’ roles in teachers’ professional learning. Second, this paper seeks to understand the influence that team leaders have on teachers’ learning path strategies.

Following from van der Krogt’s (2007a) Learning Network Theory (LNT), this paper presents a qualitative study of teachers’ preferences for specific learning path strategies. Interview data were collected from teachers (N = 24) and team leaders (N = 5) at an intermediate vocational school in the Netherlands. Research questions ask to what extent teachers learning path strategies align with the learning path strategies that their team leaders think they should use, and about the influence team leaders have on teachers’ professional development.

Findings suggest that teachers and team leaders’ beliefs about learning path strategies differ greatly, and that team leaders have limited influence on the learning path strategies that teachers adopt. On the other hand, team leaders appear able to create conditions in which teachers can pursue professional learning because they do have influence on learning facilities.

These findings add to the scarce empirical evidence regarding LNT, learning path strategies and team leaders beliefs about teachers professional development. They also imply practical changes for team leaders who want to influence teacher professional development.

Employees are increasingly expected to organize their own human resource development activities. To what extent and how exactly employees in various organizational contexts manage to shape their individual learning paths however remains largely unclear. The purpose of this present study is to explore, leaning on the empirical Learning-Network Theory (LNT) research and its findings, how employees in different occupations create learning paths that are attuned to their specific work context.

The paper reviews 23 MSc theses based on 14 distinct data sets collected between 2005 and 2015, containing approximately 1,484 employees from some 45 organizations and across various professions. The teachers, nurses, postal, software, telecom, railway and logistics company employees were mostly based in the Netherlands. The analysis focuses on learning-path types and learning-path strategies found in the 23 studies.

Motives, themes, activities, social contexts and facilities were found to be instrumental in explaining differences among individual learning paths. A total of 34 original learning-path types and strategies were found to cluster under 12 higher-order labels. Some of these were based on learning motive, some on learning theme, some on core learning activities, some on social learning context and a few on a combination of these elements. Overall, the socially oriented learning-path strategy was the most prevalent, as it was found among nurses, employees of software/postal/telecom, railway and logistics company employees, as well as teachers in two schools.

The paper presents the first overview of empirical studies on employee learning path(s) (strategies). In addition, it strengthens the empirical basis of the LNT.

The purpose of this study was to explore how customer-facing professionals (CFPs) created learning paths to adapt to changing customer needs in a digital environment.

Two groups of CFPs were created from a previous single-case study to examine the learning paths of the two groups. Both groups were digitally competent yet differed in their ability to adapt to the increased usage of digital technologies by their customers: adaptive or conservative CFPs. Research questions addressed perceived learning needs, learning strategies to meet needs and factors that helped or hindered success. Transcripts were coded based on the five elements of a learning path, described within the learning network theory (i.e. motives, learning themes, learning activities, social context and facilities), using the Dedoose coding software. Group findings were compared to identify similarities and differences in their learning path elements.

CFPs learning path elements varied individually and between adaptive and conservative CFPs. Individually, they varied in learning themes: digital or traditional customer-facing competencies and learning activities such as learning from experience, self-directed learning and learning from others. Drive and ambition emerged as a learning motive for several CFPs in both groups. Although small samples, adaptive CFPs saw a need for digital competencies and engaged in self-directed learning (e.g. solving problems and using digital technologies), more so than conservative CFPs. A positive work environment (e.g. healthy relationships and support from others) was perceived as necessary for success for both groups.

This study sheds light on how one’s approach toward technology influences the creation of one’s learning path. It shows the increased importance of digital competencies for CFPs in a digital world and how CFPs who embrace technology develop technological savviness, solve problems using online resources and experiment with technology and systems, strive for self-sufficiency and rely on self-directed learning.

The purpose of the paper is to propose and demonstrate a novel approach for addressing the challenges of path planning and obstacle avoidance in the context of mobile robots (MR). The specific objectives and purposes outlined in the paper include: introducing a new methodology that combines Q-learning with dynamic reward to improve the efficiency of path planning and obstacle avoidance. Enhancing the navigation of MR through unfamiliar environments by reducing blind exploration and accelerating the convergence to optimal solutions and demonstrating through simulation results that the proposed method, dynamic reward-enhanced Q-learning (DRQL), outperforms existing approaches in terms of achieving convergence to an optimal action strategy more efficiently, requiring less time and improving path exploration with fewer steps and higher average rewards.

The design adopted in this paper to achieve its purposes involves the following key components: (1) Combination of Q-learning and dynamic reward: the paper’s design integrates Q-learning, a popular reinforcement learning technique, with dynamic reward mechanisms. This combination forms the foundation of the approach. Q-learning is used to learn and update the robot’s action-value function, while dynamic rewards are introduced to guide the robot’s actions effectively. (2) Data accumulation during navigation: when a MR navigates through an unfamiliar environment, it accumulates experience data. This data collection is a crucial part of the design, as it enables the robot to learn from its interactions with the environment. (3) Dynamic reward integration: dynamic reward mechanisms are integrated into the Q-learning process. These mechanisms provide feedback to the robot based on its actions, guiding it to make decisions that lead to better outcomes. Dynamic rewards help reduce blind exploration, which can be time-consuming and inefficient and promote faster convergence to optimal solutions. (4) Simulation-based evaluation: to assess the effectiveness of the proposed approach, the design includes a simulation-based evaluation. This evaluation uses simulated environments and scenarios to test the performance of the DRQL method. (5) Performance metrics: the design incorporates performance metrics to measure the success of the approach. These metrics likely include measures of convergence speed, exploration efficiency, the number of steps taken and the average rewards obtained during the robot’s navigation.

The findings of the paper can be summarized as follows: (1) Efficient path planning and obstacle avoidance: the paper’s proposed approach, DRQL, leads to more efficient path planning and obstacle avoidance for MR. This is achieved through the combination of Q-learning and dynamic reward mechanisms, which guide the robot’s actions effectively. (2) Faster convergence to optimal solutions: DRQL accelerates the convergence of the MR to optimal action strategies. Dynamic rewards help reduce the need for blind exploration, which typically consumes time and this results in a quicker attainment of optimal solutions. (3) Reduced exploration time: the integration of dynamic reward mechanisms significantly reduces the time required for exploration during navigation. This reduction in exploration time contributes to more efficient and quicker path planning. (4) Improved path exploration: the results from the simulations indicate that the DRQL method leads to improved path exploration in unknown environments. The robot takes fewer steps to reach its destination, which is a crucial indicator of efficiency. (5) Higher average rewards: the paper’s findings reveal that MR using DRQL receive higher average rewards during their navigation. This suggests that the proposed approach results in better decision-making and more successful navigation.

The paper’s originality stems from its unique combination of Q-learning and dynamic rewards, its focus on efficiency and speed in MR navigation and its ability to enhance path exploration and average rewards. These original contributions have the potential to advance the field of mobile robotics by addressing critical challenges in path planning and obstacle avoidance.

An e‐portfolio is a useful tool to increase reflection and awareness in teachers and students. However, benefits of e‐portfolio use are weakened by difficulties due to the lack of motivation, the heavy weight of creation and revision of the e‐portfolios, the rigid tool structure. The paper aims to answer these emerging issues, showing how to cope with the above‐mentioned questions, by proposing a structure for an e‐portfolio able to fulfil the users' needs and to be perceived as an extremely usable and motivating tool.

In the paper three types of e‐portfolios are described. A brief survey of how the students used them with related data is provided. The research is based upon qualitative (students' posts) and quantitative (log tracement) data.

After five years of experimentation and over 200 e‐portfolios analysed, the paper describes lessons learned and suggests some guidelines that might be useful to plan the introduction and the implementation of an e‐portfolio in post degree courses and for adult and in‐service learning.

In the paper some guidelines for designing formative portfolios are shown. These guidelines might be used to design and build feasible e‐portfolios in different kinds of courses. The new perspective is about the use of formative e‐portfolios in different learning paths. The paper shows how, starting from the same structure, the model is able to fit various needs, proposing technological and pedagogical devices in order to foster reflection and to promote formal and informal recording of learning activities.

This paper focuses on the integration of the learning objects and knowledge map as the learning sequence suggestion in the mobile learning environment and explains the technologies involved, the applications and the issues of usability, accessibility, evaluation and effectiveness. Mobile learning has open up new path for learning support and opportunities to reach wider audience (learner) for education. This research focuses on using the knowledge map to store the characteristics of each learning object via concept schemas and represent the corresponding learning accessibility in the mobile learning environment. The proposed architecture provides a medium for the learning accessibility of learners through mobile applications and wireless portable devices such as smart phones, PDAs and tablet PCs. The approach using the combination of "touch" and "observe" spatial learning objects provides an intelligent solution to creating, sharing and improving the efficiency of mobile learning. The proposed mobile learning environment architecture consists of knowledge map components mainly, navigation, concept schemas and learning object path. By using these knowledge structures, this study may enhance and enrich the concept and activity of adaptive learning in different individuals and communities. The spatial knowledge map constructed was useful in identifying the characteristics of the learning objects (e.g., learning object 1: lesson with navigating sentences, learning object 2: lesson with navigating sentence and code explanation, etc) and automatically matches the most appropriate learning contentand path suitable for learners. The architecture of the platform discussed in this study using the learning objects approach and knowledge map would facilitate a more widespread use of mobile learning, including courses or modules delivery of individualised learning path and learning style analysis.

Extending the study of Chan et al. (2016), this paper aims to focus on specific aspects of performance (conceptual and factual knowledge) to provide insight into whether computer game attributes designed into Prrinciples Aren’t That Hard (PATH) improve performance.

A between-subjects experiment is conducted to test the hypotheses. The experimental and control groups are PATH and traditional paper medium, respectively.

The results reveal that PATH users perform better on the conceptual knowledge questions compared to the traditional paper medium users. No significant difference in performance on the factual knowledge (computational) questions is found between PATH and traditional paper medium users.

This study demonstrates that PATH creates an engaging learning environment, which facilitates the acquisition of conceptual knowledge and improved (conceptual) performance. Research can investigate whether technology may be used to facilitate automation of computational tasks which downplay the importance of computational skills (factual knowledge) and focus on the design of computer game attributes in educational or training programs to enhance conceptual knowledge and (conceptual) performance.

The findings of this study will assist educators and educational technology developers to identify and design motivation-enhancing computer game features to promote remember and understand cognitive processes which improve (conceptual) performance.

Game-based learning serves as the underlying theoretical framework for the design of PATH used in an experimental study to examine the positive effects of motivation-enhancing computer game attributes on remember and understand cognitive processes which facilitate (conceptual) performance. This study also uses separate measures of performance; that is, conceptual and factual knowledge, to provide additional insight into the findings of Chan et al. (2016).