论文标题
使用数据分析来预测学生得分
Using Data Analytics to predict students score
论文作者
论文摘要
教育对于新加坡非常重要，政府一直在我们的教育体系上进行大量投资，成为当今世界一流的系统之一。在过去的50年中，基础新加坡发展的基础是科学，技术，工程和数学（STEM）的坚实基础。 PISA是一项三年展的国际调查，它通过测试接近强制性教育结束的15岁学生的技能和知识来评估全球教育系统。在本文中，作者使用了2012年和2015年的PISA数据，并开发了机器学习技术来预测学生的分数并了解社会，经济和教育因素之间的关系。获得的见解对于对教育有了新的看法，对政策制定有用。
Education is very important to Singapore, and the government has continued to invest heavily in our education system to become one of the world-class systems today. A strong foundation of Science, Technology, Engineering, and Mathematics (STEM) was what underpinned Singapore's development over the past 50 years. PISA is a triennial international survey that evaluates education systems worldwide by testing the skills and knowledge of 15-year-old students who are nearing the end of compulsory education. In this paper, the authors used the PISA data from 2012 and 2015 and developed machine learning techniques to predictive the students' scores and understand the inter-relationships among social, economic, and education factors. The insights gained would be useful to have fresh perspectives on education, useful for policy formulation.
