Artificial intelligence literacy in sustainable development: A learning experiment in higher education

Ari V. Alamäki · Crister Nyberg · Anna Kimberley · Arto O. Salonen

77 citations0/0 files storedFrontiers in Education

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Sustainability in Higher Education Artificial Intelligence in Education Digital literacy in education

Abstract

Introduction The purpose of this empirical research was to map the capabilities and perceptions of undergraduate business administration students about artificial intelligence (AI) and its potential to answer questions related to sustainable transition in society, and to obtain information about the suitable pedagogical solution to increase the knowledge and understanding related to these themes. Methods The data was gathered among higher education (HE) students in a workshop that consisted of introductory lecture, answering surveys, questionnaire, group discussions, and reflective narratives on the relationship and possibilities of AI and sustainable development. In data analysis an abductive qualitative research methodology was adopted. Results Through abduction new insights were obtained and new knowledge was created new knowledge regarding AI literacy in the context of sustainable development. This brought new knowledge in the context of HE studies. The taxonomy of AI literacy in sustainable development created a new reference framework for learning tasks, and course planning in HE. The findings showed that the students had difficulties solving the actual problem because they lacked knowledge and understanding of the basics of AI and sustainable development. However, in groups where one person had a deeper understanding of the concepts, the whole group began to understand the task and work on both meta-level ethical questions and practical examples. Discussion The assistance of AI potentially creates opportunities for developing solutions supporting sustainable development. However, utilizing this potential requires AI literacy. In this task HE plays a significant role. This study contributes to the pedagogical approach where AI and sustainable development are integrated in HE curricula.

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1998Basics of qualitative research : techniques and procedures for developing grounded theory 2008The qualitative content analysis process 2025The Coding Manual for Qualitative Researchers 2012Seeking Qualitative Rigor in Inductive Research 2002A Revision of Bloom's Taxonomy: An Overview 1997Interpreting Qualitative Data Methods for Analysing Talk, Text and Interaction 2002Systematic combining: an abductive approach to case research 2020The role of artificial intelligence in achieving the Sustainable Development Goals

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