Using Institutional data and messages on Social Media to Predict the Career decisions of University Students - A Data-Driven Approach

Tzu Chi Yang*, Chung Yuan Chang

*此作品的通信作者

研究成果: Article同行評審

摘要

Enabling college graduates to achieve career success is increasingly considered a major responsibility of universities. Many studies have developed models of predicting students’ career decisions and have sought to provide appropriate treatments or early support for students to achieve this goal. Most studies, however, have focused on using institutional data, which might not be entirely sufficient for the prediction because students’ career decisions might also be affected by the social context. This study proposes a data-driven approach that considers both institutional data and social media news for predicting students’ career decisions. The results of this study suggest that such an approach achieved a higher performance in the prediction task. This study also discusses the data-driven approach as a means of supporting students’ career development in the university setting, how the approach can be used to inform educators on how to use the data that are both internal and external to the university, and what the impact of this approach is on educational support decisions.

原文English
期刊Education and Information Technologies
DOIs
出版狀態Accepted/In press - 2022

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