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While most language departments of the university offer service-learning (SL) subjects based on language teaching, such as “Teaching Chinese as a Second Language in Local Schools” and “Serving the Community through Teaching English,” this paper aims to argue that teaching students to teach language(s) is yet to be the best strategy to serve the service recipients.

SL is widely understood as an experiential learning pedagogy that integrates academic focus, reflection and community service and is shown to be impactful. In Hong Kong, the first university that has made SL a graduation requirement is the Hong Kong Polytechnic University (the University). Considering this, new SL courses have proliferated over the past decade. Adopting a narrative inquiry approach, this paper examines personal narratives from a new SL subject aiming to raise awareness of refugees in Hong Kong. The data includes students’ reflective journals, co-created personal narratives and podcasts and semi-structured interviews.

This paper finds that crafting and recording narratives of shared experiences deepens cultural understanding, cultivates empathy and facilitates language learning in a genuine setting.

Ultimately, this paper advocates a well-designed SL that combines language, content and technology as a powerful, transformational experience for both college students and service recipients.

This paper focuses on a brand new SL course, “Storytelling for Understanding: Refugee Children in Hong Kong,” offered in Semester 1, 2022–2023. The subject was developed by the two authors from a language division affiliated to the University. The deliverables were podcast recordings, co-authored and co-edited by the students and the children.

Automatic modulation recognition (AMR) is a challenging problem in intelligent communication systems and has wide application prospects. At present, although many AMR methods based on deep learning have been proposed, the methods proposed by these works cannot be directly applied to the actual wireless communication scenario, because there are usually two kinds of dilemmas when recognizing the real modulated signal, namely, long sequence and noise. This paper aims to effectively process in-phase quadrature (IQ) sequences of very long signals interfered by noise.

This paper proposes a general model for a modulation classifier based on a two-layer nested structure of long short-term memory (LSTM) networks, called a two-layer nested structure (TLN)-LSTM, which exploits the time sensitivity of LSTM and the ability of the nested network structure to extract more features, and can achieve effective processing of ultra-long signal IQ sequences collected from real wireless communication scenarios that are interfered by noise.

Experimental results show that our proposed model has higher recognition accuracy for five types of modulation signals, including amplitude modulation, frequency modulation, gaussian minimum shift keying, quadrature phase shift keying and differential quadrature phase shift keying, collected from real wireless communication scenarios. The overall classification accuracy of the proposed model for these signals can reach 73.11%, compared with 40.84% for the baseline model. Moreover, this model can also achieve high classification performance for analog signals with the same modulation method in the public data set HKDD_AMC36.

At present, although many AMR methods based on deep learning have been proposed, these works are based on the model’s classification results of various modulated signals in the AMR public data set to evaluate the signal recognition performance of the proposed method rather than collecting real modulated signals for identification in actual wireless communication scenarios. The methods proposed in these works cannot be directly applied to actual wireless communication scenarios. Therefore, this paper proposes a new AMR method, dedicated to the effective processing of the collected ultra-long signal IQ sequences that are interfered by noise.

The purpose of this study is to examine relevant demographic and socio-economic factors as they relate to progress towards intercultural communicative competence (ICC) and intercultural sensitivity for ethnic-minority Latinx middle school English learners (ELs) using a mobile-assisted funds-of-knowledge-featured writing practice.

Through the theoretical lens of funds of knowledge, this three-year study implemented a survey-based quasi-experimental design centered on the Latinx ELs’ ICC development with the implementation of an intercultural sensitivity questionnaire (Chen and Starosta, 2000). The authors first investigated the relationship between ELs’ intercultural sensitivity and associated demographic and socio-economic factors. The authors then examined the changes of ELs’ intercultural sensitivity. Over ten weeks, the intervention group completed five funds-of-knowledge-featured narrative essays using pen and paper and mobile-based writing tools alternatively.

Findings indicated that ELs’ intercultural sensitivity increased as they advanced to a higher-level grade from sixth to eighth. The embedded mobile-assisted funds-of-knowledge writing practice as intervention promoted ELs’ intercultural sensitivity in interaction engagement, respect of cultural differences, interaction enjoyment and interaction attentiveness. Among the variables, interaction enjoyment was portrayed the most. ELs who reported not speaking English at home were statistically significant in this experiment.

This study acknowledges the robust and variance of funds of knowledge as a niche to address the interculturality and hybridity of ELs’ cultural practices accumulated through Latinx ELs’ family socialization and social development using mobile-assisted writing practice. This study could provide implications for optimizing inclusive experience to promote computer-assisted language learning in a contemporary, postcolonial global world.

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

The professional experiences of teachers of languages and cultures, along with the learning experiences of their students, are embedded in educational contexts, which themselves are informed, and constrained, by national language policies. This study aims to explore 51 English-as-a-foreign-language (EFL) secondary teachers’ perceptions of Web-based technology use to enhance students’ cultural awareness in Chile. Specifically, the study investigated teachers’ use of Web-based resources for cultural awareness, culture content and technology-based tasks, as well as perceived challenges in implementing technology-enhanced language and culture learning.

The study adopted a mixed-method research design combining online questionnaires and interviews as data collection tools. Results were analyzed through the use of descriptive statistics and content analysis.

The teachers in this study emphasized reflection in their classrooms but did not take a critical approach. Their approach to culture was limited to a “country-specific” view, and technology-enhanced activities accentuated differences rather than promoting meaningful intercultural exchange. Challenges to the successful implementation of technology-enhanced language and culture learning included a somewhat out-of-date theoretical approach to intercultural learning in the national curriculum, a nationwide approach to professional development that lacks a focus on critical reflection and inadequate support for effective use of technologies in schools.

The study highlights the importance of periodically revising a country’s EFL language policies, communication methods, support mechanisms and implementation factors to ensure classroom integration of language, culture and technology education.

This paper explores the tension between macro-level national policy and teachers’ perspectives on their classroom practice, including the contextualized limitations of implementing national policy at the micro level.

This paper aims to present a lesson that showcases how artificial intelligence (AI) tools may be chiefly used in L2 language classrooms to design culture-focussed telecollaboration tasks and aid their completion by students.

The paper begins by reviewing traditional approaches and guidance for developing telecollaboration tasks. It then models how tasks can be designed using the popular AI tool “Chat Generative Pre-training Transformer (ChatGPT)” and then simulates how tasks may be completed by learners using ChatGPT-generated information as a springboard for their own culturally appropriate outputs.

The simulated lesson illuminates the potential value of AI tools for teachers and students. However, it also highlights particular aspects of AI literacy that teachers and learners need to be aware of.

This paper has clear practical implications for teacher development by raising awareness of the importance of teachers upskilling in telecollaboration task design and in their understanding of how AI tools can collaborate with them in language classrooms.

The paper adds to the current body of literature on telecollaboration and more specifically adds weight to current discussions taking place around AI tools in language education. By the end of reading the paper, teachers will have a comprehensive grounding in how to use ChatGPT in their classrooms. In doing so, the author demystifies how teachers and students may start exploring these tools in ways that target developing intercultural communicative competence.

First-line leaders across the emergency services are instrumental in leading the development of a workforce fit to face current and future challenges. As such in addition to utilising their specific craft, leaders need to be equipped to understand and apply evidence-based practices. With a focus on first-line leadership in policing, this paper will have both national and international resonance for those organisations attempting to embed an evidence-based culture.

The paper utilises a review of literature to develop a viewpoint identifying challenges and benefits of the adoption of evidence-based policing (EBP) by first-line leaders.

First-line leaders, whether police officers, police staff or volunteers, require opportunities to develop their own knowledge, understanding and skills of applying EBP in the workplace. Acknowledging challenges exist in the widespread adoption of EBP, such learning, at the appropriate educational level, will enable leaders to effectively champion the adoption of EBP, informing both their own decision-making and professional practices as well as those across their teams.

The first-line leader role is highly influential, as such, it is essential that these leaders develop their knowledge, understanding and application of EBP in the workplace in order to lead the expected cultural change.

This paper provides a current framework for the understanding of the context and potential impact of educationally levelled formal leadership learning required to champion the broad adoption of EBP across policing.

This study provides a meta-review of global virtual team (GVT)–related reviews, creating a resource that highlights dominant themes, research trends and shifts in topics over time culminating in a summary of opportunities for future research. By analyzing and grouping the evidence presented in previous research, this meta-review provides key insights toward future research and managerial implications.

This meta-review identifies 35 existing GVT-related reviews across 32 publication outlets, providing a longitudinal and cross-disciplinary view of GVT research to date.

Results of the analysis reveal over time that there has been a largely adopted reconceptualization of the GVT paradigm toward a continuum of virtuality. There has been a shift in the view of the cross-cultural and global components of GVTs toward a recognition that a greater variance of dimensionality exists. Additionally, popular themes across the literature emerge, notably, virtuality, concepts of culture, trust, leadership and communication technology.

As a multidisciplinary GVT-focused meta-review, this study complements previous efforts by taking a tour across this wide topic and is dedicated to those who are researching, teaching, working and managing GVT-related strategies. The reviews selected represent work published across multiple literature streams, providing a comprehensive and forward thinking perspective.

In academics and industry, significant efforts have been made to lead planners and control teams in evaluating project performance and control. In this context, numerous control metrics have been devised and put into practice, often with little emphasis on analyzing their underlying concepts. To cover this gap, this research aims to identify and analyze a holistic list of control metrics and their functionalities in the construction industry.

A multi-step analytical approach was conducted to achieve the study’s objectives. First, a holistic list of control metrics and their functionalities in the construction industry was identified. Second, a quantitative analysis based on social network analysis (SNA) was implemented to discover the most important functionalities.

The results revealed that the most important control metrics' functionalities (CMF) could differ depending on the type of metrics (lagging and leading) and levels of control. However, in general, the most significant functionalities include managing project progress and performance, evaluating the look-ahead level’s performance, measuring the reliability and stability of workflow, measuring the make-ready process, constraint management and measuring the quality of construction flow.

This research will assist the project team in getting a comprehensive sensemaking of planning and control systems and their functionalities to plan and control different dynamic aspects of the project.

The purpose of this study is to examine how construction project managers’ conflict management styles (CMSs) affect project team resilience from the perspective of social identity theory.

This study adopted a cross-sectional survey design and collected paired data from 110 construction project managers and 474 employees in China. Based on the data collected, the authors tested the proposed hypotheses using hierarchical regression analysis.

The results show that a project manager’s cooperative CMS positively affects team resilience, and a project manager’s competitive and avoidant CMS negatively affects team resilience. Team followership plays a mediating role in this relationship. The team power distance moderates the effects of a project manager’s cooperative and avoidant CMSs on team followership.

This paper enriches the existing literature on conflict management in construction projects and have potential guiding significance and application value for team resilience management practices.