确定人工智能(AI)基础素养的组成部分--德尔菲研究的初步结果

K. MacCallum, David Parsons, Mahsa Mohaghegh
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引用次数: 0

摘要

本文提供了德尔菲研究第一阶段的一些初步结果,该研究旨在确定人工智能(AI)扫盲课程的关键组成部分。本文探讨了针对四级能力模型的研究结果,但只是该模型的最低一级。德尔菲小组由 17 位人工智能领域的专家组成,第一轮研究采用调查的方式收集专家们在三个方面的回答,这三个方面是基于以前的文献--人工智能的知识(和概念)、与人工智能相关的技能以及在情境中理解人工智能。结构化主题分析显示了这些类别下的若干主题。在基础知识和概念方面,确定需要三个领域,即 1) 什么是人工智能?2) 人工智能的应用,以及 3) 人工智能技术。技能分为认知技能和技术技能,认知技能又分为 21 世纪技能和应用技能。理解包括社会问题、风险和辩论。形成这些主题的重复想法为如何构建人工智能扫盲课程提供了丰富的见解,并为后续研究奠定了坚实的基础,这些研究将涉及对这些想法的进一步迭代和整合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying the components of foundational Artificial Intelligence (AI) literacy - Early results from a Delphi study
This article provides some initial results from the first phase of a Delphi study to identify the critical components of an Artificial Intelligence (AI) literacy curriculum. This article explores the study results that address a four-level capability model, but only the lowest level of this model. The Delphi panel comprised 17 experts in AI, and the first round of the study used a survey to gather the experts' responses in three areas that were based on previous literature - knowledge (and concepts) of AI, skills related to AI, and understanding AI in context. A structured thematic analysis revealed several themes under these categories. For foundational knowledge and concepts, it was determined that three areas were needed, namely 1) what is AI? 2) applications of AI, and 3) AI technologies. Skills were divided into cognitive and technical skills, with cognitive skills further divided into 21st-century and applied skills. Understandings comprised social issues, risks, and debates. The repeated ideas that formed these themes gave rich insights into how an AI literacy curriculum might be structured and provided a firm foundation for subsequent rounds of the study, which will involve further iteration and consolidation of these ideas.
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