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題名 Activity theory-based ecosystem for Artificial Intelligence in Education (AIED)
作者 莊俊儒
Ching, Gregory S.;Uden, Lorna
貢獻者 教育學院
關鍵詞 artificial intelligence in education; activity theory; learner and task relationship; ecosystem
日期 2024-05
上傳時間 10-Sep-2024 13:20:54 (UTC+8)
摘要 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.
關聯 International Journal of Research Studies in Education, Vol.13, No.5, pp.41-54
資料類型 article
DOI https://doi.org/10.5861/ijrse.2024.24000
dc.contributor 教育學院
dc.creator (作者) 莊俊儒
dc.creator (作者) Ching, Gregory S.;Uden, Lorna
dc.date (日期) 2024-05
dc.date.accessioned 10-Sep-2024 13:20:54 (UTC+8)-
dc.date.available 10-Sep-2024 13:20:54 (UTC+8)-
dc.date.issued (上傳時間) 10-Sep-2024 13:20:54 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/153693-
dc.description.abstract (摘要) 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.
dc.format.extent 104 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) International Journal of Research Studies in Education, Vol.13, No.5, pp.41-54
dc.subject (關鍵詞) artificial intelligence in education; activity theory; learner and task relationship; ecosystem
dc.title (題名) Activity theory-based ecosystem for Artificial Intelligence in Education (AIED)
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.5861/ijrse.2024.24000
dc.doi.uri (DOI) https://doi.org/10.5861/ijrse.2024.24000