用NLP技术理解教育-职业一致性的研究框架

Renzhe Yu, Suprotik Das, Sairam Gurajada, Kush R. Varshney, Hari Raghavan, Carlos X. Lastra‐Anadón
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引用次数: 3

摘要

了解工作要求和大学课程之间的差距对于提高学生的成功和高等教育机构的有效性至关重要。在这种情况下,可以利用自然语言处理(NLP)来生成关于差距在哪里以及它们如何变化的细粒度见解。本文提出了一个将NLP技术与经济和教育研究相结合的三维研究框架,以量化课程大纲和职位发布之间的一致性。我们详细阐述了该框架的关键技术细节,并进一步讨论了其对实践的潜在积极影响,包括揭示教育-职业一致的不平等和长期后果,为政策制定者提供信息,并促进信息系统的发展,以支持学生、机构和雇主从学校到工作的管道。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Research Framework for Understanding Education-Occupation Alignment with NLP Techniques
Understanding the gaps between job requirements and university curricula is crucial for improving student success and institutional effectiveness in higher education. In this context, natural language processing (NLP) can be leveraged to generate granular insights into where the gaps are and how they change. This paper proposes a three-dimensional research framework that combines NLP techniques with economic and educational research to quantify the alignment between course syllabi and job postings. We elaborate on key technical details of the framework and further discuss its potential positive impacts on practice, including unveiling the inequalities in and long-term consequences of education-occupation alignment to inform policymakers, and fostering information systems to support students, institutions and employers in the school-to-work pipeline.
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