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A Retention Model for Community College STEM Students

机译:社区学院干药学生的保留模型

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摘要

The number of students attending community colleges that take advantage of transfer pathways to universities continues to rise. Therefore, there is a need to engage in academic research on these students and their attrition in order to identify areas to improve retention. Community colleges have a very diverse population and provide entry into science, technology, engineering, and math (STEM) programs, regardless of student high school preparedness. It is essential for these students to successfully transfer to universities and finish their STEM degrees to meet the global workforce demands. This research develops a predictive model for community college students for degree completion using the Mahalanobis Taguchi System and regression. Data collected from a Midwest community college over a five-year period in three specific associate degree programs will be used for the study. The study identified 92 students that completed a STEM degree within three years, while 730 students were not able to complete the degree within that period or at all. The research illuminates specific areas of concern related to community college students and better informs transfer institutions about this important sector of transfer students. Especially revealing is the important predictive factors traditionally found in research for STEM retention had very low correlation for this set of community college students. This research reinforces the need to investigate community college students more closely and through a different lens.
机译:参加社区院校的学生人数,即利用转移到大学的转移途径继续上升。因此,需要与这些学生和他们的磨损进行学术研究,以确定改善保留的领域。社区院校有一个非常多样化的人口,提供科学,技术,工程和数学(Stew)计划,无论学生高中准备如何。这些学生必须成功地转移到大学并完成他们的Step学位以满足全球劳动力需求。本研究开发了社区大学生的预测模型,使用Mahalanobis Taguchi系统和回归来完成学位的学位完成。在三个特定的副学士学位课程中,从中西部社区学院收集的数据将用于该研究。该研究确定了92名学生在三年内完成了茎的学生,而730名学生无法在该期间或根本上完成该程度。该研究阐明了与社区大学生有关的特定关注领域,更好地通知转派机构这一重要部门的转移学生。特别是揭示是传统上发现的重要预测因素在茎潴留研究中对这套社区大学生的相关性非常低。这项研究强化了需要更接近和通过不同镜头调查社区大学生的必要性。

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