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The popularity of massive open online courses (MOOCs) has attracted worldwide research interest. This study aims to identify and summarize the research foci (e.g. themes, methods, contexts, etc.) and discuss the new directions and trends of MOOC research in the context of Mainland China.

A systematic review of the published MOOC research papers in Mainland China was conducted with the following inclusion criteria: (1) papers written in English; (2) context focused on Mainland China; and (3) empirical studies. Three main issues were explored with the selected 70 papers: (1) research methods (data collection and analysis); (2) the research foci; and (3) research objects.

The results found that the major MOOC research in China was quantitative, mostly using one method to collect data. Most studies collected data through the databases of MOOC platforms and survey techniques, which was consistent with the widely used descriptive statistics for data analysis. Learner-focused themes were investigated the most, aligning with the result that learners were the most popular research objects.

The findings suggest that using new technology tools, such as the Big Data approach for learning analytics, may transform traditional MOOC research into new practices. Transdisciplinary research concepts may also provide an alternative evolving model for constructing collaboratively dynamic research frameworks under the changing technologies and paradigms. Meanwhile, educational research traditions, such as qualitative methods, contribute to scaffolding MOOC research for more pragmatic applications.

Most systematic reviews on MOOCs focus on general or regional contexts other than Mainland China, and scant MOOC review is based on published English papers about Mainland China.

When it comes to special education, teachers are the cornerstone of children's development. A special education teacher (SET) who possesses correct perceptions to teach students with special education needs (SENs) in inclusive education and ability to maintain balance that works best for children with physical and emotional disabilities are expected to thrive. This requires several skills that are entirely different from traditional teaching, often depicted as ‘chalk and talk’ – keeping control and making decisions about what is the right thing to do for students. This trait is just an illustration of many myopic characteristics that will no longer work well for both SENs and regular students. An effective SET in the twenty-first century must be able to adapt and respond rapidly to the changing society and is more likely to be open to learning. These character qualities are typical among millennials and Generation Z or Alpha, who are more prone to be digital native, that will future-proof them in the upcoming era of ubiquitous technology. As such, new generation SETs are significant precursor to create a new special education system that responds well to the challenges encountered by the pervasive future ahead.

This study compared different types of full-time caregiver (e.g., children, older adults, COVID-19 patients) and subgroups (e.g., disability, race/ethnicity, sexual orientation) in the United States during the COVID-19 pandemic for potentially meaningful distinctions.

Data from the 9,854 full-time caregivers identified in Phase 3.2 (July 21–October 11, 2021) of the US Census Household Pulse Survey (HPS) were analyzed in this study using multinomial logistic regression to examine relationships between caregiver types, marginalized subgroups, generation, and vaccination status.

The prevalence of caregiving was low, but the type of full-time caregiving performed varied by demographic group (i.e., disability, race/ethnicity, sexual orientation, gender, generation, and vaccination status). The relative risk of being a COVID-19 caregiver remained significant for being a member of each of the marginalized groups examined after all adjustments.

To date, the HPS has not been analyzed to predict the type of full-time informal caregiving performed during the COVID-19 pandemic or their characteristics. Research limitations of this analysis include the cross-sectional, experimental dataset employed, as well as some variable measurement issues.

Prior informal caregiver research has often focused on the experiences of those caring for older adults or children with special healthcare needs. It may be instructive to learn whether and how informal caregivers excluded from paid employment during infectious disease outbreaks vary in meaningful ways from those engaged in other full-time caregiving. Because COVID-19 magnified equity concerns, examining demographic differences may also facilitate customization of pathways to post-caregiving workforce integration.

The purpose of this study is to examine the effect of perceived value of recommended product on consumer’s e-loyalty, based on the proposition of expectation confirmation theory. Vendors’ reputation is tested as the mediator in the perceived value of recommended product and e-loyalty relationship, whereas shopping enjoyment is predicted as the moderator that conditions the perceived value of recommended product and e-loyalty relationship through vendors reputation.

Data were collected via an online survey platform and through a QR code. Partial least squares analysis, confirmatory factor analysis and structural equation modeling were used to verify the research proposed model.

The findings revealed that the perceived value of recommended product had a significant positive effect on E-loyalty; in addition, the perceived value of the recommended product and e-loyalty link was partly explained by e-shopper’s confidence in vendor reputation. Therefore, the study established that the direct and indirect relationship between the perceived value of the recommended product and e-loyalty was sensitive and profound to shopping enjoyment.

This study has established that the perceived value of a recommended product can result in consumer loyalty. This has successively provided the e-shop manager and other stakeholders with novel perspectives about why it is necessary to understand consumers’ pre- and postacquisition behavior before recommending certain products to the consumer.

Overall, the purpose of this paper is to define and delineate the meaning of the concept of Organizational Incivility (OI) by examining its features, scope and implications. Furthermore, it depicts a set of research propositions aiming to guide future research.

Toward this end, this paper draws upon the literature of workplace incivility, unethical behavior, organizational dark side behavior and corporate social irresponsibility, which have been examined through distinct theoretical streams and frames them under the lens of OI concept. The ensuing analysis focuses on some well-known business-cases and their tragic consequences. In doing so, it also argues that the OI concept provides a solid theoretically based framework about how uncivil mindset have been specifically shaped at the organizational level.

Overall, it is proposed that OI is a by-product of conscious (bad) decisions in which the organizational leaderships are allured, at some point and for distinct reasons, to embrace moral disengagement and unethical choices. In doing so, the organizations overlook or neglect their commitments to society’s well-being and environmental preservation. As a result, the organizations start to play a dirty game without any sense of respect for those that rely on them (i.e. consumers and citizens).

The implementation of strict ethical codes and governance measures have proved not to be enough to contain the OI practices. In this regard, organizational leaderships should question themselves if their companies are truly aligned with a civilized conduct. In turn, government agencies, federal laws and institutions dedicated to preserve people’s well-being should play a more incisive role by identifying and stifling the organizational dark side.

On the face of it, it is argued that a myriad of demonstrations of organizational dark side that are identified worldwide can be theoretically explored through the lens of OI and therein lies the major contribution of this work. More specifically, it demonstrates that incivility can go, in fact, beyond organization frontiers spilling over the stakeholders in a negative manner and damaging the interactions. Further, it also contributes to theory by suggesting that OI is a process carefully designed by the organizational leaderships to achieve obscure goals and/or darker purposes.

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.

Behavioral threat assessment and intervention is a violence prevention strategy that has become widely used in US schools. Instead of relying on a zero tolerance disciplinary approach that often leads to school exclusion of students with disabilities, schools can use a multidisciplinary threat assessment team to assess the seriousness and context of a student's behavior and identify appropriate interventions and supports. This process is especially valuable for students with disabilities who are identified as threatening violence. This chapter describes an evidence-based model of threat assessment, the Comprehensive School Threat Assessment Guidelines (CSTAG), ¹ reviews some common misunderstandings of threat assessment, and presents a case example illustrating the value of threat assessment in preventing school exclusion, and provides services for a student with a disability.

This research investigates the threshold effects of the interplay between finance, development and carbon emissions across 97 countries, including 50 low-income and 47 high-income countries, during the period from 1991 to 2019.

Employing various econometric modeling techniques such as dynamic linear regression, dynamic panel threshold regression and in/out of sample splitting, this study analyzes the data obtained from the World Bank's world development indicators.

The results indicate that low-income countries require a minimum financial development threshold of 0.354 to effectively reduce carbon emissions. Conversely, high-income countries require a higher financial development threshold of 0.662 to mitigate finance-induced carbon emissions. These findings validate the presence of a finance-led Environmental Kuznet Curve (EKC). Furthermore, the study highlights those high-income countries exhibit greater environmental concern compared to their low-income counterparts. Additionally, a minimum GDP per capita of US$ 10,067 is necessary to facilitate economic development and subsequently reduce carbon emissions. Once GDP per capita surpasses this threshold, a rise in economic development by a certain percentage could lead to a 0.96% reduction in carbon emissions across all income levels.

This study provides a novel contribution by estimating practical financial and economic thresholds essential for reducing carbon emissions within countries at varying levels of development.

Brief loving-kindness meditation (LKM) is introduced here as a valid social marketing intervention. LKM positively influences prosocial cognitions and affects. However, it remains unclear whether brief meditation interventions can influence prosocial behavior. This study aims to provide evidence of the effects of short LKM on prosocial behavior.

This study reports the results of three experiments examining the effects of brief LKM on donations to unknown others. The results are then integrated with the results of seven other studies testing the effects of brief LKM on prosocial behavior using a meta-analysis (n = 683).

LKM increased love more than the control group (focused breathing) in the three experiments; however, its effects on donations were mixed. The meta-analysis shows that LKM has a small-to-medium significant effect compared to active control groups (d = 0.303); moreover, age and type of prosocial measure used moderate the effects.

Results suggest that LKM can nurture prosocial emotions such as love and lead young individuals to donate. However, these emotions may not be sufficient to lead adult meditators to share their resources with unknown others. This study presents the first meta-analysis of brief LKM and provides insights into the use of meditation in social marketing programs.

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.