Search results

Introduction: Numerous decision-making situations are faced in education where Artificial Intelligence may be prevalent as a decision-making support tool to capture streams of learners’ behaviours.

Purpose: The purpose of the present study is to understand the role of AI in student performance assessment and explore the future role of AI in educational performance assessment.

Scope: The study tries to understand the adaptability of AI in the education sector for supporting the educator in automating assessment. It supports the educator to concentrate on core teaching-learning activities.

Objectives: To understand the AI adaption for educational assessment, the positives and negatives of confidential data collections, and challenges for implementation from the view of various stakeholders.

Methodology: The study is conceptual, and information has been collected from sources comprised of expert interactions, research publications, survey and Industry reports.

Findings: The use of AI in student performance assessment has helped in early predictions for the activities to be adopted by educators. Results of AI evaluations give the data that may be combined and understood to create visuals.

Research Implications: AI-based analytics helps in fast decision-making and adapting the teaching curriculum’s fast-changing industry needs. Students’ abilities, such as participation and resilience, and qualities, such as confidence and drive, may be appraised using AI assessment systems.

Theoretical Implication: Artificial intelligence-based evaluation gives instructors, students, and parents a continuous opinion on how students learn, the help they require, and their progress towards their learning objectives.

The current challenges experienced by all nations promote the trade-off between the increase in economic performance and the protected environment. The investigation based on the energy economy has become an irreplaceable topic to determine the correct path for minimizing the trade-off cost. Within this scope, this study has been performed to investigate the causality nexus between the exports indicators (aggregated exports and the ICT exports) and the energy consumption (renewable and nonrenewable energy consumption of the selected five emerging countries. The Dumitrescu–Hurlin panel causality analysis is performed on the annual data between 2000 and 2014. As a consequence of the evidence, it is documented that there are various causality relationships between the exports and the energy consumption indicators in the light of the performed analysis at different lags. However, the role of nonrenewable energy consumption is more active in the economies of the considered countries. According to the evidence, it is recommended for the emerging countries to invest and allocate more funds to renewable energy resources to diminish the role of nonrenewable energy resources in the economy.

Doxing refers to the intentional public release by a third party of personal data without consent, often with the intent to humiliate, intimidate, harass, or punish the individual concerned. Intuitively, it is tempting to condemn doxing as a crude form of cyber violence that weaponizes personal data. When it is used as a strategy of resistance by the powerless to hold the powerful accountable, however, a more nuanced understanding is called for. This chapter focuses on the doxing phenomenon in Hong Kong, where doxing incidents against police officers and their family members have skyrocketed since 2019 (a 75-fold increase over 2018). It contends that doxing for political purposes is closely related to digital vigilantism, signifying a loss of confidence in the ruling authority and a yearning for an alternative form of justice. The chapter therefore argues that public interest should be recognized as a legal defense in doxing cases when those discharging or entrusted with public duty are the targets. Equally, it is important to confine the categories of personal data disclosed to information necessary to reveal the alleged wrongdoer or wrongdoing. Only in this way can a fair balance be struck between privacy, freedom of expression, and public interest.

Professional touching behavior (PTB), defined as intentional touching behavior that occurs between organizational members and that falls within the boundaries of appropriateness and professionalism in the workplace, is prevalent in organizations. Scholars from multiple disciplines, including human resources researchers, have acknowledged the importance of physical contact for facilitating interpersonal communication and relationship-building. However, PTB may not only elicit positive reactions from those who receive it but also negative reactions as well, with implications for social dynamics in organizations. PTB can, on the one hand, fulfill employees’ desires for interpersonal connection; at the same time, such physical contact at work can represent a threat to employees’ health. To explain the nature and implications of these divergent effects of receiving PTB, the authors draw upon sociometer theory and behavioral immune system (BIS) theory to model the emotional, cognitive, and physiological processes via which, and the conditions under which, receiving such behavior will result in socially functional responses and prompt subsequent prosocial behavior, and when PTB will be perceived as a health risk and prompt withdrawal behavior. The theoretical framework of this chapter expands our conceptual understanding of the consequences of interpersonal physical contact at work and has important human resources management (HRM) implications for organizational managers.