2024 IJRSE – Volume 13 Issue 5
Available Online: 15 May 2024
Author/s:
Uden, Lorna*
https://orcid.org/0000-0002-8598-7355
School of Computing, Staffordshire University, Stoke-on-Trent, United Kingdom (L.uden@staffs.ac.uk)
Ching, Gregory S.
https://orcid.org/0000-0001-9148-0019
Graduate Institute of Educational Administration and Policy, National ChengChi University, Taipei, Taiwan (gching@nccu.edu.tw)
Abstract:
The integration of Artificial Intelligence in Education (AIED) stands as a pivotal trend in education, yet comprehensive design frameworks remain a subject of ongoing exploration. While many AIED studies are still in their early stages of development and implementation, the uncertainties and challenges surrounding the ethical and responsible use of AI in education persist. Anchoring on the Activity Theory, this paper proposes a conceptual framework, aiming to construct a sustainable ecosystem for AIED design within the dynamic landscape in all levels of education. Within the constructs of Activity Theory, this framework endeavors to scrutinize the intricate relationship between individuals (learners), their learning activities, and the broader socio-cultural context wherein these activities unfold. Moreover, the paper advocates for collaborative agreements among educators, learners, and educational institutions as essential pillars in the design and implementation of AIED systems tailored for education. In essence, this conceptual paper serves as a theoretical proposition, utilizing Activity Theory as a lens to envisage an adaptive and ethically responsible AIED ecosystem specifically crafted to address the nuanced dynamics inherent in all levels of education. It urges designers to meticulously consider the interplay between learners, educators, technology, and the socio-cultural fabric when devising strategies for fostering effective, inclusive, and engaging learning experiences.
Keywords: artificial intelligence in education, activity theory, learner and task relationship, ecosystem
DOI: https://doi.org/10.5861/ijrse.2024.24000
Cite this article:
Uden, L., & Ching, G. S. (2024). Activity Theory-based Ecosystem for Artificial Intelligence in Education (AIED). International Journal of Research Studies in Education, 13(5), 41-54. https://doi.org/10.5861/ijrse.2024.24000
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