Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches
Abstract
AI has become ubiquitous in our society, accelerated by the speed of the development of machine learning algorithms and voice and facial recognition technologies used in our everyday lives. Furthermore, AI-enhanced technologies and tools are no strangers in the field of education. It is more evident that it is important to prepare K-12 population of students for their future professions as well as citizens capable of understanding and utilizing AI-enhanced technologies in the future. In response to such needs, the authors started a collaborative project aiming to provide a K-12 AI curriculum for Japanese students. However, the authors soon realized that it is important to contextualize the learning experience for the targeted K-12 students. The paper aims at introducing the idea of contextualizing AI education and learning experience of K-12 students with examples and tips using the work-in-progress version of the contextualized curriculum using culturally responsive approaches to promote the awareness and understanding of AI ethics among middle school students.
- Citation
- BibTeX
Eguchi, A., Okada, H. & Muto, Y.,
(2021).
Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches.
KI - Künstliche Intelligenz: Vol. 35, No. 2.
Springer.
(S. 153-161).
DOI: 10.1007/s13218-021-00737-3
@article{mci/Eguchi2021,
author = {Eguchi, Amy AND Okada, Hiroyuki AND Muto, Yumiko},
title = {Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches},
journal = {KI - Künstliche Intelligenz},
volume = {35},
number = {2},
year = {2021},
,
pages = { 153-161 } ,
doi = { 10.1007/s13218-021-00737-3 }
}
author = {Eguchi, Amy AND Okada, Hiroyuki AND Muto, Yumiko},
title = {Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches},
journal = {KI - Künstliche Intelligenz},
volume = {35},
number = {2},
year = {2021},
,
pages = { 153-161 } ,
doi = { 10.1007/s13218-021-00737-3 }
}
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More Info
ISSN: 1610-1987
xmlui.MetaDataDisplay.field.date: 2021
Content Type: Text/Journal Article