引入人工智能以提高下一代评估方法效率的挑战

Brian Moon, Farima Fatahi Bayat, Sneha C. Nair, Andrew Slaughter
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摘要

美国陆军寻求开发允许自动化或半自动化的能力,大大减少人工参与,创建测试和评估。在认识到一种超越多项选择的评估方法的潜力后,陆军选择了我们的团队来引入和评估自动化能力,以编写基于概念映射的评估。本文描述了我们将效率引入基于概念图的评估的创作过程的初步方法。我们正在开发和评估从知识领域自动生成概念图的方法,并将这些图转换为形成和总结目的的评估。我们最初的工作是试图克服在创作过程中引入人工智能的挑战。在本文中,我们描述了我们的紧急方法和我们在寻求文本到概念图转换的效率方面所面临的挑战。
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Challenges for introducing artificial intelligence to improve the efficiency of a next generation assessment approach
The U.S. Army sought to develop capabilities that allow for the automated or semi-automated, with greatly reduced human involvement, creation of tests and assessments. In recognizing the potential for an assessment approach that goes beyond multiple-choice, the Army chose our team to introduce and evaluate automated capabilities to author concept mapping-based assessments. This paper describes our initial approaches toward introducing efficiencies into the authoring process for concept map-based assessments. We are developing and evaluating methods to automatically generate concept maps from a knowledge domain and convert the maps into assessments for formative and summative purposes. Our initial work has sought to overcome challenges as we introduced artificial intelligence into the authoring process. In this paper, we describe our emergent approach and the challenges we have faced in seeking efficiencies in the conversion of text to concept maps.
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