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Drawing from emotional geography framework promoted by Hargreaves (2000), our research sought to depict the emotional geography of two faculty members who engaged in a virtual teacher professional development (VTPD) sessions during the COVID-19 pandemic. This study aimed to focus on capturing participants’ emotional closeness or distance while they were engaging in VTPD.

This study employed narrative inquiry by exploring three-dimensional narrative inquiry space: temporality, personal-social interaction and place (Clandinin and Connelly, 2000). Following this step, the participants were interviewed online through Zoom meetings and WhatsApp to capture critical incidents of their emotional experience. All collected data were transcribed, and some data from Bahasa Indonesia were translated into English. Member checking was also done several times to ensure the accuracy of the data as well as to avoid misinterpretation. The data were analysed inductively to generate coding categories using systemic functional linguistics (SFL) language appraisal (Martin and White, 2007) and emotional geography parameter (Hargreaves, 2001b).

The findings of the study revealed that both participants experienced greater positive feeling than negative ones. The participants experienced positive feelings such as seriousness, happiness, successfulness and satisfaction. They also experienced negative feelings such as insecurity, unhappiness, dissatisfaction and impatience. Such positive and negative feelings create closeness and distance among participants, mentor and workshop organiser. This study indicates that maintaining positive feelings is a passport to succeed in VTPD.

The study has two limitations. First, its findings cannot be overgeneralised since the analysis was restricted to data gathered from a small number of participants. Second, the scope of investigation was limited in virtual situations.

The present study empirically showed that faculty members need to engage in constructing or maintaining positive emotional bond with the mentor and other participants and create conducive situations to understand their own and others’ emotions (Mayer, 2011). Practically, a mentor in VTPD may ask faculty members to voice and share their emotional experience as an evaluation tool to make VTPD programmes more successful. Future participants can benefit from these findings by engaging in emotional understanding and building a conducive situation during VTPD to develop their academic competence, agency and identity.

While previous research into VTPD in the context of higher education mainly focused on designs, attention to pedagogy of online teacher learning environments, trends toward innovation in teacher collaboration and communities of practice in online settings, the present study specifically looked into how participants emotionally engaged in VTPD, which is inevitably linked to physical, moral, sociocultural, professional and political geographies.

With the advancement of technology, microlearning has emerged as a promising method to improve the efficacy of teaching and learning. This study aims to investigate the document types, volume, growth trajectory, geographic contribution, coauthor relationships, prominent authors, research groups, influential documents and publication outlets in the microlearning literature.

We adapt the PRISMA guidelines to assess the eligibility of 297 Scopus-indexed documents from 2002 to 2021. Each was manually labeled by educational level. Descriptive statistics and science mapping were conducted to highlight relevant objects and their patterns in the knowledge base.

This study confirms the increasing trend of microlearning publications over the last two decades, with conference papers dominating the microlearning literature (178 documents, 59.86%). Despite global contributions, a concentrated effort from scholars in 15 countries (22.39%) yielded 68.8% of all documents, while the remaining papers were dispersed across 52 other nations (77.61%). Another significant finding is that most documents pertain to three educational level categories: lifelong learning, higher education and all educational levels. In addition, this research highlights six key themes in the microlearning domain, encompassing (1) Design and evaluation of mobile learning, (2) Microlearning adaptation in MOOCs, (3) Language teaching and learning, (4) Workflow of a microlearning system, (5) Microlearning content design, (6) Health competence and health behaviors. Other aspects analyzed in this study include the most prominent authors, research groups, documents and references.

The finding represents all topics at various educational levels to offer a comprehensive view of the knowledge base.

Using sentiment analysis (SA), this study aims to examine the impact of COVID-19 on mental health and virtual learning experiences among 1,125 students at a public Argentinean faculty.

A study was conducted during the COVID-19 pandemic, surveying 1,125 students to gather their opinions. The survey data was analysed using text mining tools and SA. SA was used to extract the students’ emotions, views and feelings computationally and identify co-occurrences and patterns in related words. The study also examines educational policies implemented after the pandemic.

The prevalent emotions expressed in the comments were trust, sadness, anticipation and fear. A combination of trust and fear resulted in submission. Negative comments often included the words “virtual”, “virtual classroom”, “virtual classes” and “professor”. Two significant issues were identified: teachers’ inexperience with virtual classes and inadequate server infrastructure, leading to frequent crashes. The most effective educational policies addressed vital issues related to the “virtual classroom”.

Text mining and SA are valuable tools for decision-making during uncertain times, such as the COVID-19 pandemic. They can also provide insights to recover quality assurance processes at universities impacted by health concerns or external shocks.

The paper makes two main contributions: it conducts a SA to gain insights from comments and analyses the relationship between emotions and sentiments to identify optimal educational policies. The study pioneers exploring the link between emotions, policies and the pandemic at a public university in Argentina. This area of research still needs to be explored.

The purpose of this study is to investigate students’ attitudes, self-efficacy and emotional behaviour associated with online learning and the effectiveness of online learning.

A research model was formulated and analysed with the structural equation modelling technique. The respondents consist of 843 students pursuing their studies at a private university’s foundation, undergraduate and postgraduate levels. A two-step systematic approach was used using the SmartPLS version 3 software to conduct statistical analysis and draw meaningful insights.

The study’s findings have demonstrated that students’ attitudes and self-efficacy exhibit a positive relationship with online learning behaviour (OLB). It is observed that the students’ emotions are related to online learning effectiveness (OLE) and mediate the relationship between OLB and OLE. Furthermore, OLB partially mediates the relationship between attitude and OLE and between self-efficacy and OLE.

The operational instructions and digital resources have proven to be highly effective in providing valuable learning experiences to the students. As a result, the students are now expanding and applying their new encounters to a broader range of learning opportunities. This study has provided valuable insights for stakeholders, including scholars, higher education institutions and the Ministry of Higher Education, in providing the ideas of online learning or Web-based education.

The originality of this study sheds light on the role of OLB as a mediator. It was underlined that emotion is critical in improving students’ OLE. Thus, students’ attitudes and self-efficacy have been essential in reassuring OLB and enhancing OLE.

Emotional labour (EL) is a complex phenomenon that has received increasing attention in recent years due to its impact on employee’s well-being and job satisfaction. For a comprehensive understanding of the evolving field of EL, it is important to extract different research trends, new developments and research directions in this domain. The study aims to reveal 13 prominent research topics based on the topic modelling analysis.

Using latent Dirichlet allocation (LDA) method, topic modelling is done on 1,462 journal research papers published between 1999 and 2023, extracted from the Scopus database using the keyword “EL”.

The analysis identifies several emerging trends in EL research, including emotional regulation training and job redesign. Similarly, the topics like EL strategies, cultural differences and EL, EL in hospitality, organizational support and EL, EL and gender and psychological well-being of nursing workers are popular research topics in this domain.

The findings provide valuable insights into the current state of EL research and can provide a direction for future research as well as assist organizations to design practices aimed at improving working conditions for employees in various industries.

Topic modelling on emotional labor is done. The paper identifies specific topics or clusters related to emotional labor, quantifies these topics using topic modeling, adds empirical rigor, and allows for comparisons across different contexts.

The applications of Artificial Intelligence (AI) in various areas of professional and knowledge work are growing. Emotions play an important role in how users incorporate a technology into their work practices. The current study draws on work in the areas of AI-powered technologies adaptation, emotions, and the future of work, to investigate how knowledge workers feel about adopting AI in their work.

We gathered 107,111 tweets about the new AI programmer, GitHub Copilot, launched by GitHub and analysed the data in three stages. First, after cleaning and filtering the data, we applied the topic modelling method to analyse 16,130 tweets posted by 10,301 software programmers to identify the emotions they expressed. Then, we analysed the outcome topics qualitatively to understand the stimulus characteristics driving those emotions. Finally, we analysed a sample of tweets to explore how emotional responses changed over time.

We found six categories of emotions among software programmers: challenge, achievement, loss, deterrence, scepticism, and apathy. In addition, we found these emotions were driven by four stimulus characteristics: AI development, AI functionality, identity work, and AI engagement. We also examined the change in emotions over time. The results indicate that negative emotions changed to more positive emotions once software programmers redirected their attention to the AI programmer's capabilities and functionalities, and related that to their identity work.

Overall, as organisations start adopting AI-powered technologies in their software development practices, our research offers practical guidance to managers by identifying factors that can change negative emotions to positive emotions.

Our study makes a timely contribution to the discussions on AI and the future of work through the lens of emotions. In contrast to nascent discussions on the role of AI in high-skilled jobs that show knowledge workers' general ambivalence towards AI, we find knowledge workers show more positive emotions over time and as they engage more with AI. In addition, this study unveils the role of professional identity in leading to more positive emotions towards AI, as knowledge workers view such technology as a means of expanding their identity rather than as a threat to it.

Based on self-determination theory (SDT), this study aims to investigate the motivational antecedents of faculty members’ continuance intention of using online teaching platforms. For this purpose, we introduced a model incorporating basic psychological needs satisfaction (BPNS) and different motivational mechanisms.

Using a survey study of 312 faculty members, we examined the model by structural equation modeling (SEM).

The SEM results revealed a positive correlation between BPNS and continuance intention. Additionally, we illustrate the importance of different types of extrinsic motivation. By presenting an alternative model, we demonstrate that the initial-use-identified regulation (one type of extrinsic motivation) has an association with continuance intention (CI). However, this association loses significance if BPNS is present within the model. Moreover, we determined that there is no significant relationship between initial-use external regulation (another type of extrinsic motivation) and faculty members' CI for online teaching. Lastly, the results revealed that pre-use amotivation and intrinsic motivation impact CI through initial-use BPNS.

The results suggest that decision-makers at educational institutions should consider that extrinsic motivation has different types with different impacts and that BPNS has a vital role in faculty members’ intention to continue using online teaching platforms.

This study is novel because it reveals some details of extrinsic motivation effects by offering a model that combines BPNS and different types of motivation in two stages. It is important and rare that we concentrate on the almost neglected issue of faculty members’ motivational perspectives in online teaching, while the literature mainly focuses on students’ perspectives.

This research aims to examine how consumer minimalism (CM), self-conscious feelings (such as consumer guilt (CG) and consumer pride (CP)) and the inclination to use rental services interact. It also looks at how attitudes toward pro-environmental advertisements affect these relationships as a moderator, recognizing the importance of pro-environmental advertising in influencing consumer behavior.

This study employed a quantitative methodology to investigate the aforementioned associations. Survey questionnaires are used to collect data, which is then analyzed using AMOS 25 and Process Macro to generate meaningful insights.

The findings indicate that the willingness to use rental services is directly associated with CM, while self-conscious emotions (SCEs) play the role of a mediator in this relationship.

It is essential to recognize the limitations of this study. There may be other variables at play, but the research focuses on SCEs (CG and CP) and their role as mediators. The findings must be interpreted based on the selected research methodology and sample size. Future research could investigate additional variables and enlarge the sample size to increase generalizability.

Targeted marketing can leverage CM, SCEs and willingness to use rental services. Recognizing the moderating effect of attitude toward pro-environmental advertisements can help create more effective campaigns promoting environmental behavior.

Underpinned by SCEs, the current study is one of the initial studies to explain how CM encourages responsible environmental behavior through access-based consumption models.

The purpose of this study is to analyze the potential mediating role of employee engagement in the relationship between gratitude and subjective well-being (SWB) of employees working in the information technology (IT) sector in India. The study investigated a moderated mediation model for gratitude and SWB, treating employee engagement as a mediator and gender as a moderator.

Data was collected from 162 professionals working IT sector in India. Process Macro, AMOS and IBM SPSS 22 were used to analyze the mediation and moderation effects.

The results depicted that employee engagement fully mediates the positive association between gratitude practice and the SWB of employees as well as the demographic variable; gender also demonstrated a full moderation effect between them.

This research may be one of the few studies from the Indian context that explore whether gratitude practiced by employees working in the IT sector can play a significant role in impacting their SWB. Past research models had not introduced employee engagement’s indirect impact on the examined variables.

This study examines the antecedents and dynamics of authoritarian leadership and extends the effects of managers' sleep quality to employee behavior.

On the basis of self-regulation theory, 513 unit day samples were analyzed using cross-level path analysis and a Monte Carlo simulation test.

Managers' sleep quality is positively related to authoritarian leadership and positive emotions play a mediating role. Authoritarian leadership is positively related to employees' counterproductive behavior. Managers' sleep quality affects employees' counterproductive behavior through managers' positive emotions and authoritarian leadership.

Individuals should learn to reduce stress and maintain a positive mood. Organizations should reduce employees' overtime work and work stress and find other ways to improve employees' sleep quality.

First, we considered authoritarian leadership to be dynamic and studied it on a daily basis. Second, we studied the antecedents of authoritarian leadership from the perspective of leaders' states (sleep quality and emotions). Third, we discussed the effect of managers' sleep quality on employee behavior.