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Leveraging Partnerships in Assessment as a Pillar of Leadership in VUCA Contexts

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This a conceptual chapter that seeks to create a new framework for the different forms of partnership for assessment. This chapter will explore the necessity and advantages of a collaborative approach to leadership of assessment in the context of rapid advancements in artificial intelligence (AI). As AI technology continues to evolve, the dynamics of organizational leadership are undergoing a fundamental transformation. Traditional hierarchical leadership models are becoming increasingly inadequate in addressing the complexities and ethical considerations associated with AI integration. This chapter will argue that a collaborative leadership framework, characterized by shared decision-making with students, inclusivity, and interdisciplinary cooperation, is essential for effectively navigating the opportunities and challenges posed by AI. The chapter contains detailed examples of organizations that have successfully adopted collaborative leadership models, lessons learned from these case studies, and an analysis of how collaborative leadership could contribute to the success of AI initiatives in higher education organizations. This chapter is valuable to a wide range of readers, including but not limited to organizational leaders seeking to understand how AI impacts leadership, scholars and students of leadership studies, AI ethics, and organizational behavior, as well as policymakers interested in the ethical implications of AI.

Original languageEnglish
Title of host publicationHigher Educational Leadership in VUCA Contexts
Subtitle of host publicationAccessing VUCA Prime and Wisdom for Effective Leadership
Pages231-242
Number of pages12
ISBN (Electronic)9781836086826
DOIs
Publication statusPublished - 5 Nov. 2025

Keywords

  • Alternative assessment
  • Artificial intelligence
  • Fit-for-purpose assessment
  • Higher education
  • Partnership in assessment

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