# Conceptualisation of Digital Wellbeing Associated with Generative Artificial Intelligence from the Perspective of University Students

## TL;DR

This study explores how university students view digital wellbeing in the context of generative AI, identifying key areas for future research and adaptive strategies.

## Contribution

The paper introduces a novel conceptualization of digital wellbeing specifically within the generative AI paradigm.

## Key findings

- Four key areas for research include societal expectations, interaction methods, risks, and adaptive strategies.
- Risks are integral to the environment where students seek balance through adaptive strategies.
- Key adaptive strategies include critical thinking, autonomy, and responsibility.

## Abstract

Digital wellbeing has been the subject of extensive research in educational contexts. Yet, there remains a paucity of studies conducted within the paradigm of generative AI, a field with the potential to significantly influence students’ sentiments and dispositions in this domain. This study analyses 474 student recommendations (information science and library science) for digital wellbeing in generative artificial intelligence. The research is based on the context of pragmatism, which rejects the differentiation between thinking and acting and ties both phenomena into one interpretive whole. The research method is thematic analysis; students proposed rules for digital wellbeing in the context of generative AI, which was followed by the established theory. The study has identified four specific areas that need to be the focus of research attention: societal expectations of the positive benefits of using generative AI, particular ways of interacting with generative AI, its risks, and students’ adaptive strategies. Research has shown that risks in this context must be considered part of the elements that make up the environment in which students seek to achieve balance through adaptive strategies. The key adaptive elements included the ability to think critically and creatively, autonomy, care for others, take responsibility, and the reflected ontological difference between humans and machines.