Xiao Chen

Gender bias in artificial intelligence (AI) applications has recently gained increasing attention in academia. While some studies have explored gender disparities in specific contexts, there is a lack of comprehensive analysis on how AI-driven gender biases impact female learners across different educational settings worldwide. This systematic review examines research on gender bias in AI applications used in education across various global regions, following PRISMA guidelines. It synthesizes findings from 23 empirical and conceptual papers published between 2019 and 2024—a period marked by the rapid integration of AI technologies in education. The review reveals that research on AI gender bias in educational contexts remains limited, with most studies originating from North America and Western regions. At the same time, South Asia, South America, and Africa receive comparatively little attention. Second, the focus of existing studies is on higher education, neglecting other educational levels. Third, the review found several methodological gaps in the reviewed literature that need improvement. Lastly, the results highlight persistent gender biases in AI tools, particularly in content generation, assessments, and feedback systems. The presence of these biases in the educational context discourages female participation and poses a significant challenge to achieving gender equality in education. The review emphasizes the need for more research in the neglected regions and educational levels to highlight the female issues with AI usage in general. The review also recommends inclusive AI development to foster equitable educational practices and mitigate gender bias in AI-driven learning environments.

This chapter advances understanding of person–environment misfit by framing it through self-regulation theory and goal hierarchies. The authors argue that misfit reflects a discrepancy between internal standards and external conditions, and that people are motivated to reduce such discrepancies through cognitive, affective, and behavioural regulation. Integrating self-regulation and person–environment fit research, the chapter develops a hierarchical model that distinguishes misfit at three levels: top (value or ideological incongruence), middle (interpersonal and relational dissimilarity), and bottom (skill or task mismatch). Each level elicits distinct forms of self-regulatory response, from sensemaking and identity negotiation to interpersonal adjustment and task adaptation. The authors demonstrate that misfit is not inherently negative but may generate constructive outcomes, such as innovation or learning, depending on its level and content. By mapping misfit within a goal hierarchy, the chapter provides a unifying framework linking individual motivation, emotion, and behaviour to environmental correspondence. This approach explains why some employees endure, reinterpret, or even embrace misfit while others disengage or exit. Overall, it contributes a theoretically integrative perspective that connects multilevel experiences of misfit with fundamental self-regulatory processes shaping work attitudes and outcomes.

Wir leben in einer Welt des massiven Wandels, und jedes Jahrzehnt scheint schneller und schneller zu vergehen. Es sind nicht nur die Erfindungen, die an Geschwindigkeit zunehmen, sondern auch die Übernahme von Technologien durch Unternehmen und Verbraucher nimmt zu. Die frühen Anpasser wechseln in einem zunehmenden Tempo zum allgemeinen Konsum. Ein Teil der Zunahme der Übernahme ist auf Herausforderungen wie eine Pandemie zurückzuführen. Dennoch werden im Allgemeinen die Konzepte einer VUCA (volatil, unsicher, komplex und mehrdeutig) Jahr für Jahr durch das exponentielle Wachstum des Wissens und daher der Technologie (Jari & Lauraeus, 2019) zum Standard. Wie dieses Kapitel erklären wird, wäre dieses exponentielle Wachstum der Technologie ohne den kreativen Aufschwung, der uns bevorsteht, nicht möglich. Organisationen fördern das Denken außerhalb der Box und Kreativität. Historisch gesehen war Kreativität nur für die Künste und philosophischen Denker notwendig. Kreativität hat ihren rechtmäßigen Platz als Teil unserer Problemlösung eingenommen. Keine Diskussion über Störungen ist vollständig, ohne die Arbeit des Harvard-Professors Dr. Christensen zu behandeln, der sich über 20 Jahre lang im Detail mit dem Phänomen der Störung auf technologischer und Geschäftsmodellebene beschäftigt hat. Christensen war sich nicht nur der disruptiven Natur einiger neuer Technologien bewusst und gab Richtlinien, wie Organisationen verschiedene disruptive Technologien betrachten sollten (Christensen, 1997; Christensen, 2015; Christensen et al., 2018). Akademische Einrichtungen und Wirtschaftsschulen müssen Kreativität und Technologie als Teil der Kernkompetenzen anerkennen, die für erfolgreiche Organisationen erforderlich sind.

Self-serving leadership is a form of unethical leadership behavior that has destructive effect on its targets and the overall organization. Adopting a social cognition perspective, this study expands our knowledge of its adverse effect and the way to mitigate the effect. Integrating two sub-theories of social cognition, we propose a theoretical model wherein self-serving leadership hinders team creativity through psychological safety as well as knowledge hiding, with task interdependence acting as a contextual condition. Results from a sample of 107 R&D teams revealed that self-serving leadership not only reduced team psychological safety, but also induced team knowledge hiding, both of which ultimately affected team creativity. The presence of high task interdependence buffered the destructive effect of self-serving leadership on team creativity via team psychological safety as well as the indirect effect via knowledge hiding.

We live in a world of massive change, and each decade appears to move faster and faster. It is not just the inventions that are picking up speed, but the adoption of technologies is increasing by businesses and consumers. The early adaptors switch to general consumption at an increasing pace. Part of the increase in adoption is attributed to challenges such as a pandemic. Nevertheless, in general, the concepts of a VUCA (volatile, uncertain, complex, and ambiguous) are becoming a standard year-on-year driven by the exponential growth of knowledge and, therefore, technology (Jari & Lauraeus, 2019). As this chapter will explain, this exponential growth in technology would not be possible without the creative surge upon us. Organizations are promoting out-of-the-box thinking and creativity. Historically, creativity was only necessary for the arts and philosophical thinkers. Creativity has moved to its rightful place as part of our problem solving. No discussion of disruption is complete without addressing the work of Harvard professor Dr. Christensen, who for over 20 years has looked in detail at the phenomenon of disruption at the technology and business model levels. Christensen was not just aware of some new technologies’ disruptive nature and provided guidelines on how organizations should view different disruptive technologies (Christensen, 1997; Christensen, 2015; Christensen et al., 2018). Academic institutions and business schools need to embrace creativity and technology as part of the core skill sets required for successful organizations.