在电子评估中使用脑电图数据的潜力

Q3 Engineering

Serbian Journal of Electrical Engineering Pub Date : 2018-01-01 DOI:10.2298/SJEE1803339A

Milos Antonijevic, G. Shimic, A. Jevremović, M. Veinovic, Sladjana Arsic

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引用次数: 2

摘要

电子评估最重要的目标之一是通过尽可能简单和简短的测试实现最小的测量误差。考生的心理状态通常被忽视，无论是在设计考试的过程中还是在考试过程中。使用开发的框架，我们在一个实验中测试了35名参与者，以获得尽可能多的关于学生情绪状态的数据，这取决于所提出的不同类型的问题。在本文中，我们从使用脑电图数据对应用人工智能改进电子评估的潜力的检查以及为此目的的技术平台中展示了我们目前的结果。

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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The potential for the use of EEG data in electronic assessments

: One of the most important goals of electronic assessments is to achieve the smallest measurement error with tests that are as simple and short as possible. The psychological state of an examinee is typically ignored, both in the process of designing the tests and during the exam itself. Using the developed framework, we tested 35 participants in an experiment to obtain as much data as possible about the emotional states of the students depending on the different types of question posed. In this paper, we present our current results from an examination of the potential of using EEG data towards applying artificial intelligence for improvement of electronic assessments, as well as a technical platform for this purpose.

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来源期刊

Serbian Journal of Electrical Engineering Energy-Energy Engineering and Power Technology

CiteScore

1.30

自引率

0.00%

发文量

审稿时长

25 weeks

期刊介绍： The main aims of the Journal are to publish peer review papers giving results of the fundamental and applied research in the field of electrical engineering. The Journal covers a wide scope of problems in the following scientific fields: Applied and Theoretical Electromagnetics, Instrumentation and Measurement, Power Engineering, Power Systems, Electrical Machines, Electrical Drives, Electronics, Telecommunications, Computer Engineering, Automatic Control and Systems, Mechatronics, Electrical Materials, Information Technologies, Engineering Mathematics, etc.