Selected article for: "accelerated development and machine learning"

Author: Eguchi, Amy; Okada, Hiroyuki; Muto, Yumiko
Title: Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches
  • Cord-id: j4us9v0h
  • Document date: 2021_8_6
  • ID: j4us9v0h
    Snippet: 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
    Document: 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.

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