AI as a constructive partner in academic career development, or a shortcut to promotion?

Abstract

In this essay, we discuss our experiences exploring the use of generative AI (GenAI) to develop teaching portfolios. Our motivation for this project stemmed from a curiosity about how well GenAI could meet the formal criteria for educational competence in promotion applications. Almost everyone in higher education is affected by generative language models in the way we work, learn, and think. When it comes to teaching and assessment, numerous measures have already been introduced at both institutional and national levels. Students and teachers have expressed concerns in public debates about how GenAI challenges teaching in academia, particularly in the assessment of student learning. However, little attention has been given to how generative AI may influence staff careers and how universities assess competencies in applications for positions and promotions. In this thinking piece, we explore whether GenAI could develop a teaching portfolio for the status as a merited teacher, based on the digital footprint of two teachers and the assessment criteria for promotion at UiT The Arctic University of Norway. Our experiment showed that GenAI tools can produce sections of a teaching portfolio that convincingly weave together educational theory, critical reflection, and practical examples to document teaching competence. Furthermore, GenAI also suggested innovative, ambitious, and visionary directions for future development. The result created unease and sparked a lively debate about whether teaching portfolios remain the suitable format for documenting and assessing educational competence.