可扩展的个性化学习

P. Reynolds, C. Milner, T. Highley
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引用次数: 1

摘要

我们描述了一种以高度个性化的方式教授中型计算机科学课程的方法。我们首先列举了一些基本原则,这些原则反映了普遍认可的家教的好处:学生负责、定制教学、明确的期望、强调讨论、定期评估和反馈。对于75人或75人以上的班级来说,如果没有一大批助教,其中一些目标似乎是无法实现的。但我们成功了,首先在一个23人的高级班进行了实验,当我们把它扩展到75到80人的离散数学班时,这个设计出人意料地保持了稳定。我们的教学方法包括新旧教学策略和技术的新组合,以创造一个以讨论为导向、高反馈、个性化、小组学习的环境。我们评估了与我们的方法相关的成本和收益,包括一个令人惊讶的结果:当评估所有成本和收益时,个别的、录像的离职面谈几乎没有增加教师和助教的负担。
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Scalable personalized learning
We describe an approach to teaching mid-sized computer science classes in a highly personalized manner. We began with an enumeration of fundamentals that reflect commonly recognized benefits of tutoring: student accountability, customized instruction, clear expectations, emphasis on discussion, and regular evaluation and feedback. For classes of 75 or more some of these appeared unattainable without an army of teaching assistants. But we succeeded, experimenting first in a senior level class of 23 with a design that has remained surprisingly stable as we have transitioned it into discrete math classes of 75 to 80. Our approach includes a novel mix of old and new teaching tactics and techniques combined to create a discussion oriented, high feedback, personalized, group learning environment. We evaluate the costs and benefits associated with our approach, including the surprising result that individual, video-taped exit interviews add little to the instructor's and TA's burden, when all costs and benefits are evaluated.
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