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Biometric and Intelligent Self-Assessment of Student Progress system

机译:学生进度系统的生物识别和智能自我评估

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摘要

All distance learning participants (students, professors, instructors, mentors, tutors and the rest) would like to know how well the students have assimilated the study materials being taught The analysis and assessment of the knowledge students have acquired over a semester are an integral part of the independent studies process at the most advanced universities worldwide. A formal test or exam during the semester would cause needless stress for students. To resolve this problem, the authors of this article have developed a Biometric and Intelligent Self-Assessment of Student Progress (BISASP) System. The obtained research results are comparable with the results from other similar studies. This article ends with two case studies to demonstrate practical operation of the BISASP System. The first case study analyses the interdependencies between microtremors, stress and student marks. The second case study compares the marks assigned to students during the e-self-assessment, prior to the e-test and during the e-test. The dependence, determined in the second case study, between the student marks scored for the real examination and the marks based on their self-evaluation is statistically significant (the significance >0.99%). The original contribution of this article, compared to the research results published earlier, is as follows: the BISASP System developed by the authors is superior to the traditional self-assessment systems due to the use of voice stress analysis and a special algorithm, which permits a more detailed analysis of the knowledge attained by a student.
机译:所有远程学习的参与者(学生,教授,讲师,导师,导师和其他人)都想知道学生对所学材料的吸收程度如何。对学生在一个学期中获得的知识的分析和评估是不可或缺的一部分全球最先进的大学开展的独立学习过程中。学期中的正式考试或考试会对学生造成不必要的压力。为了解决此问题,本文的作者开发了一种生物识别和学生进步的智能自我评估(BISASP)系统。获得的研究结果与其他类似研究的结果可比。本文以两个案例研究结尾,以演示BISASP系统的实际操作。第一个案例研究分析了微震,压力和学生成绩之间的相互依赖性。第二个案例研究比较了在电子自我评估,电子测试之前和电子测试期间分配给学生的分数。在第二个案例研究中确定,为真实考试评分的学生成绩与基于其自我评价的成绩之间的依存关系具有统计学意义(显着性> 0.99%)。与先前发表的研究结果相比,本文的原始贡献如下:作者开发的BISASP系统由于使用了语音压力分析和特殊算法而优于传统的自我评估系统,从而可以对学生所学知识的更详细分析。

著录项

  • 来源
    《Computers & education 》 |2010年第2期| P.821-833| 共13页
  • 作者单位

    Research Institute of Internet and Intelligent Technologies, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania;

    rnResearch Institute of Internet and Intelligent Technologies, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania;

    Department of Philosophy and Political Theory, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania;

    rnResearch Institute of Internet and Intelligent Technologies, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania;

    rnResearch Institute of Internet and Intelligent Technologies, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania;

    rnDepartment of Bridges and Special Structures, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania;

    rnResearch Institute of Internet and Intelligent Technologies, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania;

    rnDepartment of Bridges and Special Structures, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    e-learning; voice stress analysis; intelligent system; e-self-assessment; e-examination; historical information; reliability of results;

    机译:电子学习;语音压力分析;智能系统;电子自我评估;电子考试;历史信息;结果的可靠性;

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