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Work-in-Progress: Closing the Gaps: Diversity in Programming Education

机译：工作进展：关闭空白：编程教育的多样性

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In programming education for non-computer science students, high diversity exists among our students, including gender, culture, age, educational background, and work experience. Introductory programming courses traditionally face high drop-out rates and poor performance, and students often perceive learning to program as difficult. Current research on diversity in programming education has primarily focused on gender differences, thus neglecting the influence of other diversity dimensions on students’ performance. The project Diversity in Programming Education (DIPE) aims to fill this gap by identifying how heterogeneous groups of students can be best supported. Based on our findings, we develop a didactic concept with accompanying teaching and learning material to support different diversity dimensions actively in programming education. The concept includes competence models for measuring competences and individual learning paths. To support a flat learning curve further in university programming courses in the future, we closely work with schools and educational centres for teachers to integrate algorithmic thinking into school curricula. We empirically evaluate our concept using a mixed methods approach. In particular, we will explore the effects of our concept in our programming course and will investigate the value of these effects as perceived by lecturers and students.
机译：在非计算机科学生的编程教育中，我们的学生中存在高多样性，包括性别，文化，年龄，教育背景和工作经验。介绍性编程课程传统上面对高辍学率和糟糕的表现，学生往往认为难以学习困难。目前的编程教育多样性研究主要集中在性别差异，从而忽略了其他多样性维度对学生绩效的影响。编程教育（DIPE）的项目多样性旨在通过识别最佳支持异构群体，填补这种差距。基于我们的调查结果，我们开发了一个教学和学习材料的教学理念，以积极地支持不同的多样性维度。该概念包括测量能力和个人学习路径的能力模型。为了在未来进一步支持大学编程课程的平面学习曲线，我们与学校和教育中心密切合作，为教师融入学校课程中的算法思考。我们使用混合方法方法凭经验评估我们的概念。特别是，我们将探讨我们概念在我们的编程过程中的影响，并将调查讲师和学生所感知这些效应的价值。

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