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首页> 外文期刊>BRAIN. Broad Research in Artificial Intelligence and Neurosciences >Personality Questionnaires as a Basis for Improvement of University Courses in Applied Computer Science and Informatics
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Personality Questionnaires as a Basis for Improvement of University Courses in Applied Computer Science and Informatics

机译:人格问卷调查作为改进应用计算机科学和信息学大学课程的基础

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摘要

In this paper, we lay the foundation for an adaptation of the teaching process to the personality traits and academic performance of the university students enrolled in applied computer science and informatics (ACSI). We discuss how such an adaptation could be supported by an analytical software solution and present the initial version of this solution. In the form of a case study, we discuss the scores from a personality questionnaire that was administered to a group of university students enrolled in an introductory programming course at the Faculty of Technical Sciences, University of Novi Sad, Serbia. During a non-mandatory workshop on programming, the participants completed the 48-item short-scale Eysenck Personality Questionnaire–Revised (EPQ– R). By using various exploratory and analytical techniques, we inspect the student EPQ–R scores and elaborate on the specificities of the participating student group. As part of our efforts to understand the broader relevance of different student personality traits in an academic environment, we also discuss how the EPQ–R scores of students could provide information valuable to the process of improving student learning and performance in university courses in ACSI.
机译:在本文中,我们为适应计算机科学与信息学(ACSI)应用的大学生的人格特质和学习成绩的教学过程奠定了基础。我们讨论了分析软件解决方案如何支持这种改编,并介绍了该解决方案的初始版本。以案例研究的形式,我们讨论了一份个性调查表的分数,该调查表是针对一组在塞尔维亚诺维萨德大学技术学院攻读编程入门课程的大学生而设计的。在关于编程的非强制性研讨会上,参与者完成了48项艾森克人格问卷(修订版)。通过使用各种探索性和分析性技术,我们检查了学生的EPQ–R分数,并详细说明了参与的学生群体的特殊性。为了理解学术环境中不同学生个性特征的广泛相关性,我们还讨论了学生的EPQ-R分数如何为ACSI大学课程中提高学生学习和表现的过程提供有价值的信息。

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