程序设计导论学生自我效能感与态度之性别与课程语言研究

Ezgi Deveci, D. Aydin, Kristin S. Benli, F. Tek
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引用次数: 0

摘要

本研究旨在探讨Işık大学工程学院编程入门课程(CSE101)学生在性别和课程语言(土耳其语-英语)方面的自我效能感和态度。共有114名大学生参与了这项研究,其中女性40人,男性74人。为了测量学生的自我效能感,使用一般自我效能感量表,并通过开放式问题评估课程结果(成功和失败),收集年龄和性别等基本人口统计信息。采用定性分析方法对开放性问题进行检验。定量分析显示,大学生自我效能感得分与平均成绩(GPA)显著相关;与CSE101期末平均成绩无显著相关。此外,我们看到学生的自我效能感得分在性别和语言(土耳其语-英语)方面没有显著差异。学生的动机分数不会因课程语言的不同而不同。在定性分析中,我们观察到学生给出的答案的频率百分比根据他们的性别而变化。通过揭示对编程课程态度的性别差异,期望本研究将有助于确定预测学生在工程编程教育中成功的变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Examining self-efficacy perception and attitudes of introduction to programming course students with respect to gender and course language
The purpose of this study is to examine generalized self-efficacy and attitudes of the F.M.V. Işık University Engineering Faculty students of Introduction to Programming Course (CSE101) with respect to student gender and course language (Turkish-English). A total of 114 university students, 40 female and 74 male, participated in the research. In order to measure students' self-efficacy perceptions, General Self-Efficacy scale was used and open-ended questions were asked for evaluation of course outcomes (success and failure) and basic demographic information such as age and gender were collected. The open-ended questions were examined by qualitative analysis method. The quantitative analysis revealed a significant relation between the self-efficacy scores of the students with the General Grade Point Average (GPA); and a non-significant relation with the CSE101 end of term grade average. In addition, it was seen that students' self-efficacy scores did not significantly differ with respect to the gender and language (Turkish-English). The motivation scores of the students do not differ according to the course language. In qualitative analysis, we observed that the frequency percentages of the answers given by the students changed according to their genders. By revealing the gender difference in attitudes towards programming course, it is expected that this study will contribute to the process of determining the variables that predict student success in engineering programming education.
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