Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds

读写能力 数学教育 人工智能 心理学 多样性(控制论) 计算机科学 教育学
作者
Siu Cheung Kong,William Man-Yin Cheung,Guo Zhang
出处
期刊:Computers & Education: Artificial Intelligence [Elsevier BV]
卷期号:2: 100026-100026 被引量:301
标识
DOI:10.1016/j.caeai.2021.100026
摘要

A few limited efforts have been made to promote artificial intelligence (AI) literacy for citizens. The objective of this study was to design, implement and evaluate an AI literacy course for university students. One of the study's research questions was whether university students from a variety of disciplines could develop a conceptual understanding of AI through a literacy course. We promoted this course to 4000 students and recruited 120 volunteer participants to attend and complete the 7-h course. The results of our pre-course and post-course surveys indicated that the participants made significant progress in understanding AI concepts, felt empowered to work with AI. These findings indicated that the participants of diverse study backgrounds, and of both genders, could understand the concepts of machine learning, supervised learning, regression, classification, unsupervised learning, and clustering. Prior knowledge of programming was not necessary for AI concepts development, and the flipped classroom learning approach enabled more flexible learning by the participants. In the future, this AI literacy course could be extended to include AI application projects and discussions of related ethical issues regarding the wider use of AI in society. We are planning to introduce this literacy course to senior secondary school students.
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