跨国界的计算机科学联合教学:大规模的以人为中心的学习

C. Piech, Lisa Yan, Lisa Einstein, Ana Saavedra, B. Bozkurt, Eliška Šestáková, Ondřej Guth, N. McKeown
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引用次数: 5

摘要

编程正迅速成为每个国家学生的必备技能。我们提出了CS1的跨界合作教学模型CS Bridge,以及相应的易于本地化的开源盒中课程。在CS Bridge模式中,来自不同国家的教师和学生教师聚集在一起,为数百名当地高中生教授一门简短的、独立的CS1课程。相应的开源课程是专门设计的,可以很容易地适应各种各样的当地教学实践、语言和文化。在过去的六年中,该课程已被用于向哥伦比亚、捷克共和国、土耳其和几内亚的1000多名高中生教授CS1材料。我们的大部分学生在大学继续学习计算机科学或计算机科学相关领域。更重要的是,我们的许多本科生兼教师在课程之外仍然参与教学。联合教学为世界各地的学生创造了积极的、高质量的学习体验,也为教学团队——教师和师生——创造了强大的、高影响力的专业发展体验。
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Co-Teaching Computer Science Across Borders: Human-Centric Learning at Scale
Programming is fast becoming a required skill set for students in every country. We present CS Bridge, a model for cross-border co-teaching of CS1, along with a corresponding open-source course-in-a-box curriculum made for easy localization. In the CS Bridge model, instructors and student-teachers from different countries come together to teach a short, stand-alone CS1 course to hundreds of local high school students. The corresponding open-source curriculum has been specifically designed to be easily adapted to a wide variety of local teaching practices, languages, and cultures. Over the past six years, the curriculum has been used to teach CS1 material to over 1,000 high school students in Colombia, the Czech Republic, Turkey, and Guinea. A large majority of our students continue on to study CS or CS-related fields in university. More importantly, many of our undergraduate student-teachers stay involved with teaching beyond the program. Joint teaching creates a positive, high-quality learning experience for students around the world and a powerful, high-impact professional development experience for the teaching team---instructors and student-teachers alike.
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Trust, Sustainability and [email protected] L@S'22: Ninth ACM Conference on Learning @ Scale, New York City, NY, USA, June 1 - 3, 2022 L@S'21: Eighth ACM Conference on Learning @ Scale, Virtual Event, Germany, June 22-25, 2021 Leveraging Book Indexes for Automatic Extraction of Concepts in MOOCs Evaluating Bayesian Knowledge Tracing for Estimating Learner Proficiency and Guiding Learner Behavior
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