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School leaders can significantly influence the conditions that affect teacher retention. Yet, leaders in rural and high-poverty schools often face limited opportunities to develop their abilities to enhance these conditions. In this case study, we examine how participating in a professional community supported school leaders' efforts to increase teacher retention and student learning outcomes.

We used case study methodology to study 14 leaders from rural, high-poverty or underperforming schools with greater-than-average levels of teacher turnover. The leaders were participating in a three-year research-practice partnership intended to assist them in using improvement science to address problems of practice related to teacher retention and student learning outcomes in their schools. We collected and analyzed data from interviews, exit surveys, artifacts and participant observations over a one-year period.

Participating in this professional community helped the leaders create the conditions for increased teacher retention and student learning outcomes by providing them with opportunities to collaborate with their peers, receive leadership coaching, exchange ideas and learn in a safe space.

These findings confirm and extend extant school leadership development research. A particularly interesting finding was the role of the professional community in reducing the leaders' feelings of isolation while providing them a safe space to learn. The findings also illustrate how universities and school districts can partner to provide professional learning opportunities that enhance school leaders' professional knowledge, leadership practices and well-being.

This study aims to explore interdisciplinary and transdisciplinary interactions around sustainability, focusing on the United Nations sustainable development goals (SDGs). By using the city as an informal learning space, it presents a case study to raise SDG awareness, promote interdisciplinarity, foster critical thinking and empower students.

Using qualitative content analysis, this study explores students' interdisciplinary engagements. The research centers on student-created Logbooks, combining field data for analysis via open coding.

The informal setting facilitates transdisciplinary interaction and enriches interdisciplinary skills while retaining individuals’ disciplinary tendencies.

Factors like local geographical conditions and participant numbers could lead to minor variations in future course applications. Although initial problem topics and discussions are confined to local urban geography, they might diversify during implementation.

The Logbook serves as a guide for local urban issues and embodies interdisciplinary outcomes. It can be enhanced with maps and problem zoning.

Demonstrates effective SDG integration into higher education.

This study spotlights interdisciplinary learning within an unconventional context – urbanism – bridging student gaps. Supported by a paradigm shift from sustainability to unsustainability, it underscores the significance of critical engagement with SDGs.

Traditional robot arm trajectory planning methods have problems such as insufficient generalization performance and low adaptability. This paper aims to propose a method to plan the robot arm’s trajectory using the trajectory learning and generalization characteristics of dynamic motion primitives (DMPs).

This study aligns multiple demonstration motion primitives using dynamic time warping; use the Gaussian mixture model and Gaussian mixture regression methods to obtain the ideal primitive trajectory actions. By establishing a system model that improves DMPs, the parameters of the nonlinear function are learned based on the ideal primitive trajectory actions of the robotic arm, and the robotic arm motion trajectory is reproduced and generalized.

Experiments have proven that the robot arm motion trajectory learned by the method proposed in this article can not only learn to generalize and demonstrate the movement trend of the primitive trajectory, but also can better generate ideal motion trajectories and avoid obstacles when there are obstacles. The maximum Euclidean distance between the generated trajectory and the demonstration primitive trajectory is reduced by 29.9%, and the average Euclidean distance is reduced by 54.2%. This illustrates the feasibility of this method for robot arm trajectory planning.

It provides a new method for the trajectory planning of robotic arms in unstructured environments while improving the adaptability and generalization performance of robotic arms in trajectory planning.

The purpose of this study is to explore how digital technologies at work serve as environments for informal workplace learning in knowledge work.

Digital ethnography was used to investigate the digital environments of one public sector workplace. The data included observations, interviews and participant diaries.

The digital work environment consisted of a complex network of technologies and people connected to them. The ethnographic accounts revealed both expansive and restrictive features of the digital environment. Digital technology extended learning opportunities by providing flexible possibilities for interaction, collaboration and access to a wealth of information. On the contrary, digitally mediated presence could restrict learning if the attendance and learning remained superficial. The complexity and constant change in digital workplace environments presented challenges that could potentially restrict learning. Information overload, constant interruptions and changes were burdens that required employees’ skills to manage these challenges.

The authors take a novel approach to view the workplace as a phygital environment in which social, physical and digital environments are combined. Because digital environments are becoming increasingly essential parts of the workplace, it is important to understand how they can support learning.

This paper aims to explore how digital capability incompatibility affects knowledge cooperation performance through the mediating effect of digital resilient agility and the moderating effect of project complexity in project network organizations (PNOs).

A cross-sectional questionnaire survey was conducted with 207 middle and senior managers in PNOs. Based on validated questionnaire items and construct definitions, a dynamic panel regression was performed using 292 project-focused firms’ annual reports.

The results show that digital capability incompatibility facilitates knowledge cooperation performance by enhancing digital resilient agility in PNOs. Increased project complexity strengthens this relationship, promoting better knowledge cooperation performance.

Managers can use partner firms’ diverse digital knowledge to quickly develop technologies and tackle digital transformation challenges, thereby improving knowledge cooperation. They can also evaluate the project environment to manage digitally-supported cooperation effectively.

This research reveals how firms in PNOs transform digital capability incompatibility into knowledge cooperation performance through digital transformation efforts. This research extends the boundary of this relationship to project-level factors and proposes digital resilient agility as a digital transformation effort for knowledge cooperation in PNOs than previous research.

The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist in developing safety management strategies for improving safety performance in the context of the Chinese construction industry.

To achieve these objectives, 13 types and 48 causations were determined based on 274 construction safety accidents in China. Then, 204 cause-and-effect relationships among accidents and causations were identified based on data mining. Next, network theory was employed to develop and analyze the metro construction accident causation network (MCACN).

The topological characteristics of MCACN were obtained, it is both a small-world network and a scale-free network. Controlling critical causative factors can effectively control the occurrence of metro construction accidents. Degree centrality strategy is better than closeness centrality strategy and betweenness centrality strategy.

In practice, it is very difficult to quantitatively identify and determine the importance of different accidents and causative factors. The weights of nodes and edges are failed to be assigned when constructing MCACN.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to control construction risks and reduce safety accidents. More safety resources should be allocated to control critical risks. It is recommended that safety managers implement degree centrality strategy when making safety-related decisions.

This paper establishes the MCACN model based on data mining and network theory, identifies the properties and clarifies the mechanism of metro construction accidents and causations.

Reflective practice (RP) is a key skill for developing one’s professional practice. It has, however, not been unanimously prioritised in public health (PH) competency and education frameworks. Reflection activities are often unstructured in higher education. There is also a dearth of literature on the RPs of undergraduate PH students. This study aims to explore in greater depth how RP helps undergraduate PH students explore their own learning in internships.

Reflection prompts were designed using the DEAL model. 124 written reflection entries from 32 students were collected and analysed thematically using a deductive-inductive approach. The conceptual framework of internship learning goals by Ash and Clayton (2009) was used to guide the deductive analysis.

Three themes were identified: initial engagement with reflective learning; gradual integration of reflective learning, and a transformative phase involving professional development, personal growth, civic learning, growth through struggle, being confronted with differences in expectations, and skill acquisition.

This study extends the limited evidence regarding RP in undergraduate non-medical PH education, and contributes toward informing the revision of undergraduate PH programmes, for example, by integrating structured reflection earlier in the curricula, and establishing/supporting mentorship programmes between institutions. The findings call for PH educators to be more intentional in creating opportunities to nurture RP among budding PH professionals.

Social media is booming in the digital age, and its rich availability provides many opportunities for companies to innovate across borders. In reality, how enterprises use social media to achieve cross-border innovation also faces important challenges such as breaking path dependency.

This paper explores how social media can facilitate cross-border innovation from the perspective of strategic capability, combined with the path dependency theory and attention-based view. Hierarchical regression analysis and bootstrap method are adopted to test the hypotheses based on survey data provided by 173 firms in China.

The findings show a positive relationship between social media strategic capability and cross-border innovation, with path dependency playing a mediating role. In addition, two internal and external contextual factors, namely customer embeddedness and competitive pressure, play moderating roles, with customer embeddedness negatively moderating the negative relationship between social media strategic capability and path dependency and competitive pressure negatively moderating the negative relationship between path dependency and cross-border innovation.

These findings provide not only new insights into social media and cross-border innovation but also theoretical guidance on how companies can effectively use social media in practice.

Notwithstanding their potential benefits especially for individuals with low health literacy, users are still somewhat skeptical about the reliability of healthcare chatbots. The present study aims to address this challenge by investigating strategies to enhance users’ cognitive and emotional trust in healthcare chatbots. Particularly, this study aims to understand the effects of chatbot design cues in increasing trust and future chatbot use intention for low health literacy users.

We conducted two experimental studies with a final sample of 327 (Study 1) and 241 (Study 2). Three different chatbots were developed (Chatbot design: Bot vs Male-doctor vs Female-doctor). Participants were asked to have a medical consultation with the chatbot. Participants self-reported their health literacy scores. The PROCESS model 7 was used to analyze the hypotheses.

The results showed that the female-doctor cues elicited greater cognitive and emotional trust, whereas the male-doctor cues only led to greater cognitive trust (vs bot-like cues). Importantly, this study found that users’ health literacy is a significant moderating factor in shaping cognitive and emotional trust. The results indicated that both the female and male-doctor cues’ positive effects on cognitive trust were significant for those with lower levels of health literacy. Furthermore, the positive effect of the female-doctor cues on emotional trust was also significant only for those whose health literacy level was low. The increased cognitive and emotional trust led to greater future intention to use the chatbot, confirming significant moderated mediation effects.

Despite the strong economic and educational benefits of healthcare chatbots for low health literacy users, studies examining how healthcare chatbot design cues affect low health literate users surprisingly remained scarce. The results of this study suggest that healthcare chatbots can be a promising technological intervention to narrow the health literacy gap when aligned with appropriate design cues.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.