Analysis of Matching between Student and Curricula via TOPSIS Algorithm for Admission Decision Support

Pooripat Thongdeelert, Pientham Khongwiwat, Dussadee Somjaiwang, W. Yukunthorn
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Abstract

Recently, world education has been disrupted by the era of change. The digital lifestyle is closed in our daily life. Many curricula are reconstructed and developed for fitting students’ 21st century skills. In this paper, we investigate the decision support system for matching students and curricula. By analyzing soft skills, hard skills and competitiveness of student evaluation and curricula expectations. Multi criteria decision making is applied in the analysis of matching. Optimal curricula for the student are ranked via TOPSIS algorithm. A prototype of the decision support illustrated on Google cloud platform. Thirty students from the Demonstration School of Kanchanaburi Rajabhat University were the volunteer use case. Mostly, they feel positive after having seen the dashboard results. The decision support should add the varieties of curricula and universities in the country and develop an admission guidance service. The 1st rank may help their decision if there are more information and contact in the dashboard.
基于TOPSIS算法的录取决策支持学生与课程匹配分析
最近,世界教育被时代的变化所打乱。数字生活方式在我们的日常生活中是封闭的。许多课程都是为了适应学生的21世纪技能而重建和发展的。本文主要研究学生与课程匹配的决策支持系统。通过分析软技能、硬技能和竞争力对学生的评价和课程期望。在匹配分析中采用多准则决策。通过TOPSIS算法对学生的最佳课程进行排名。决策支持的原型在谷歌云平台上展示。来自北碧拉贾哈特大学示范学校的30名学生是志愿者用例。大多数情况下,他们在看到仪表板结果后会感到积极。决策支持应增加国内课程和大学的多样性,并开发入学指导服务。如果仪表板上有更多的信息和联系方式,那么第一等级可能有助于他们做出决定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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