首页> 外文会议>IEEE EDUCON Conference >Analyzing self-reflection by Computer Science students to identify bad study habits: Self-reflection performed by students of programming courses on the study habits and skills acquired through b-learning supported by an automatic judge
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Analyzing self-reflection by Computer Science students to identify bad study habits: Self-reflection performed by students of programming courses on the study habits and skills acquired through b-learning supported by an automatic judge

机译:通过计算机科学学生识别不良学习习惯的自我反思:通过自动判断支持的学习课程学生进行编程课程的学生进行自我反思

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We present some preliminary results and the main conclusions of a study that we conducted at the University of Algarve, for one of the programming courses in the first year of the Computer Science degree at the University of Algarve. We analyzed the self-reflections made by the students about their study habits and about the skills they acquired in the course. This particular course uses a methodology of blended-learning supported by an automatic judge. The research data were obtained through questionnaires that were distributed and collected during the period of study between the end of classes and the exam. We took into account data from other instruments related to previous work carried out by students, in this course and in previous courses, as well as the performance of the students. We intended to ascertain to what extent the planning, motivation, previous study or knowledge about the type of examination influenced final results. The results suggest measures to be implemented in future editions of the course.
机译:我们展示了一些初步结果,以及在阿尔加维大学在阿尔加维大学计算机科学学位的第一年进行的一项编程课程中进行的研究的主要结论。我们分析了学生对学习习惯和他们在课程中获得的技能所作的自我反思。此特殊课程使用自动判决支持的混合学习方法。通过在课程结束和考试之间的研究期间分配和收集的调查问卷获得了研究数据。我们考虑到与学生在本课程和以前的课程中进行的以前的工作相关的其他文书的数据,以及学生的表现。我们打算确定关于考试类型的规划,动机,先前的研究或知识的程度,影响了最终结果。结果表明在课程的未来版本中实施措施。

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