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Artificial intelligence literacy in sustainable development: A learning experiment in higher 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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“This is a necessity since harnessing the potential of AI in higher education depends on learners' AI literacy (Alamäki et al., 2024).”
From Development and validation of the Generative AI Literacy for Learning Scale (GenAI-LLs) (2025) · cites this paper as Alamäki et al., 2024
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Cited by
Sorted by citations
Cai, L., Msafiri, M. M., & Kangwa, D. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13112-0 · Cited by 104
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Development and validation of the Generative AI Literacy for Learning Scale (GenAI-LLs)
Gümüş, M. M., & KARA, M. (2025) · Australasian Journal of Educational Technology · doi:10.14742/ajet.10236 · Cited by 31
Kim, J., Yang, G., Chan, W. S., Lin, X., Song, Y., & Li, N. (2026) · European Journal of Education · doi:10.1111/ejed.70658 · Cited by 1
Metadata
- Authors
- Alamäki, A., Nyberg, C., Kimberley, A., & Salonen, A. O.
- Venue
- Frontiers in Education
- Publisher
- Frontiers Media SA
- Published
- 2024-03-06
- Volume
- 9
- ISSN
- 2504-284X
- Cited by
- 80
- References
- 9
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