解决教师教育中的人工智能和数据素养:对现有教育框架的回顾

Viktoriya Olari, R. Romeike
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引用次数: 6

摘要

能够负责任地使用数据和人工智能技术被认为与所有学校科目越来越相关。尽管有这种趋势,用于设计教育活动的现有人工智能素养框架往往几乎没有涵盖数据素养。然而,如果没有数据素养,就无法适当地掌握人工智能,而处理数据需要多个层面的人工智能知识。然而,到目前为止,还没有创建一个全面考虑人工智能和数据素养的框架。为了解决这一差距,我们研究了现有教育框架中人工智能与数据素养能力之间的关系,并提出了一种利用数据生命周期来反映与人工智能相关的数据素养能力的初步方法。研究结果为制定对K-12所有科目教师进行人工智能和数据素养教育的综合方法提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Addressing AI and Data Literacy in Teacher Education: A Review of Existing Educational Frameworks
Being able to use data and AI technologies responsibly is considered increasingly relevant to all school subjects. Despite this trend, existing AI literacy frameworks used to design educational activities often barely cover data literacy. However, AI cannot be appropriately grasped without data literacy, and working with data requires knowledge of AI on multiple levels. To date, though, no framework has been created that considers AI and data literacy holistically. To address this gap, we examine the relationship between AI and data literacy competencies in existing educational frameworks and propose a preliminary approach that utilizes the data lifecycle to reflect on data literacy competencies relevant to AI. The findings provide a basis for developing a comprehensive approach to the education of K-12 teachers of all subjects in AI and data literacy.
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