提高学生成功的数据驱动策略

Sashidhar Chintalapati, G. Garcia, Ángel García, L. Reddi
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引用次数: 0

摘要

本文展示了数据驱动的干预措施及其对学生成功的影响。特别是,讲师变化与相关课程交付变化的相对贡献,以及学习社区中的辅导/指导帮助,都进行了评估。结果表明,教师的变化是一个主要参数,辅导计划的贡献在很大程度上取决于教师是否以一种战略性的方式使用这些计划来帮助最需要帮助的学生。此外,课程顺序的变化也演示使用课程分析软件程序。增加一门工程数学课程以减少与两门微积分课程相关的复杂性就是一个例子。即使课程复杂性分数上的微小变化也可能导致学生在课程流程图中导航能力的显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Driven Strategies for Enhancing Student Success
This paper demonstrates data-driven interventions and their impacts on student success. In particular, the relative contributions of instructor changes with associated course delivery changes, and tutoring/mentoring help in learning communities, are assessed. The results suggest that instructor change is a major parameter, and the contributions of tutoring programs are largely governed by the instructor's use of these programs in a strategic manner to help students where help is most needed. Additionally, course sequencing changes are also demonstrated using the Curricular Analytics software program. The addition of an engineering mathematics course to reduce the complexity associated with two Calculus courses is provided as an example. Even slight changes in the curricular complexity scores might result in significant improvements in students' ability to navigate through their curricular flow charts.
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