技术增强评估中的人工智能:机器学习综述

Sima Caspari-Sadeghi
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引用次数: 0

摘要

智能评估是任何基于人工智能的教育技术的核心,它被定义为嵌入式、隐形和无处不在的评估,它使用智能技术来诊断当前的认知水平,监控动态进展,预测成功,并不断更新学生的概况。它还使用了各种技术,如学习分析、教育数据挖掘、智能传感器、可穿戴设备和机器学习。这可能是精准教育(PE)的关键:适应性、量身定制、个性化的教学和学习。本文探讨了(a)机器学习(ML)在智能评估中的应用,以及(b)在“知识跟踪和学生建模”中使用深度学习模型。本文最后讨论了使用最先进的机器学习方法所涉及的障碍,并提出了一些建议,以释放数据和机器学习的力量,以改善教育决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence in Technology-Enhanced Assessment: A Survey of Machine Learning
Intelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students’ profiling continuously. It also uses various technologies, such as learning analytics, educational data mining, intelligent sensors, wearables and machine learning. This can be the key to Precision Education (PE): adaptive, tailored, individualized instruction and learning. This paper explores (a) the applications of Machine Learning (ML) in intelligent assessment, and (b) the use of deep learning models in ‘knowledge tracing and student modeling’. The paper concludes by discussing barriers involved in using state-of-the-art ML methods and some suggestions to unleash the power of data and ML to improve educational decision-making.
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