Artificial intelligence in educational assessment: 'Breakthrough? Or buncombe and ballyhoo?'

J. Comput. Assist. Learn. Pub Date : 2020-02-21 DOI:10.1111/jcal.12577/v2/review1

J. Gardner, M. O’Leary, Li Yuan

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引用次数: 34

Abstract

Correspondence Michael O'Leary, Centre for Assessment Research, Policy and Practice in Education (CARPE), Dublin City University, Dublin, Ireland. Email: michael.oleary@dcu.ie Abstract Artificial Intelligence is at the heart of modern society with computers now capable of making process decisions in many spheres of human activity. In education, there has been intensive growth in systems that make formal and informal learning an anytime, anywhere activity for billions of people through online open educational resources and massive online open courses. Moreover, new developments in Artificial Intelligencerelated educational assessment are attracting increasing interest as means of improving assessment efficacy and validity, with much attention focusing on the analysis of the large volumes of process data being captured from digital assessment contexts. In evaluating the state of play of Artificial Intelligence in formative and summative educational assessment, this paper offers a critical perspective on the two core applications: automated essay scoring systems and computerized adaptive tests, along with the Big Data analysis approaches to machine learning that underpin them.

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人工智能在教育评估中的应用:突破?还是buncomb和ballhoo ?”

Michael O'Leary，爱尔兰都柏林都柏林城市大学教育政策与实践评估研究中心(CARPE)。摘要人工智能是现代社会的核心，计算机现在能够在人类活动的许多领域做出决策。在教育方面，通过在线开放教育资源和大规模在线开放课程，使正式和非正式学习成为数十亿人随时随地的活动的系统得到了密集的发展。此外，与人工智能相关的教育评估的新发展作为提高评估效率和有效性的手段正在引起越来越多的兴趣，人们非常关注对从数字评估环境中捕获的大量过程数据的分析。在评估人工智能在形成性和总结性教育评估中的作用状态时，本文提供了两个核心应用的关键视角:自动作文评分系统和计算机化自适应测试，以及支撑它们的机器学习的大数据分析方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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J. Comput. Assist. Learn.

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