生成语法
计算机科学
科学教育
化学
集合(抽象数据类型)
工程伦理学
纳米技术
人工智能
数学教育
工程类
心理学
材料科学
程序设计语言
作者
Elizabeth Yuriev,Donald J. Wink,Thomas A. Holme
标识
DOI:10.1021/acs.jchemed.4c00836
摘要
The emergence of generative artificial intelligence has precipitated a wide range of predictions for its impact on science and the teaching and learning of science. Chemists and chemistry educators have been exploring the possibilities of this new technology, essentially as soon as it was broadly released for use. Because this technology is rapidly developing, the insights that can be gained from the work of early adopters and investigators can play a particularly important role in shaping the future of how chemistry education adapts to, and perhaps embraces, this new technology. This Special Issue provides a snapshot at this relatively early moment in the evolution of this technology for use in teaching and learning chemistry. The interplay between technology development and implementation in the classroom will always be important, but seldom more so than in the early stages of work. The set of articles presented in this Special Issue (https://pubs.acs.org/page/jceda8/vi/genai2024) shows a robust range of options for use, and potentially for misuse, and can help guide those interested in finding ways to enhance the emerging learning opportunities afforded by this new tool.
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