A data analytics value chain for undergraduate engineering program under Thai University Central Admission System
3
Issued Date
2024
Copyright Date
2021
Resource Type
Language
eng
File Type
application/pdf
No. of Pages/File Size
x, 60 leaves: ill.
Access Rights
open access
Rights
ผลงานนี้เป็นลิขสิทธิ์ของมหาวิทยาลัยมหิดล ขอสงวนไว้สำหรับเพื่อการศึกษาเท่านั้น ต้องอ้างอิงแหล่งที่มา ห้ามดัดแปลงเนื้อหา และห้ามนำไปใช้เพื่อการค้า
Rights Holder(s)
Mahidol University
Bibliographic Citation
Thesis (M.Sc. (Information Technology Management))--Mahidol University, 2021
Suggested Citation
Sorawee Yanta A data analytics value chain for undergraduate engineering program under Thai University Central Admission System. Thesis (M.Sc. (Information Technology Management))--Mahidol University, 2021. Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/99486
Title
A data analytics value chain for undergraduate engineering program under Thai University Central Admission System
Alternative Title(s)
ห่วงโซ่คุณค่าการวิเคราะห์ข้อมูลสำหรับหลักสูตรวิศวกรรมศาสตร์บัณฑิตภายใต้ระบบการคัดเลือกกลางบุคคลเข้าศึกษาต่อในระดับอุดมศึกษา
Author(s)
Abstract
The University admission system in Thailand has been developing and transforming for decades. The current system, the Thai University Central Admission System (TCAS), is officially enforced since 2018 and causes some policy issues. This five-round admission system, which is the most frequent in Thailand's education history, results in the universities obtaining high-range performance students and affecting their educational process. To tackle this problem, data analytic is needed, either process improvement or strategic planning. Accordingly, this research proposes the full stream of data analytics value chain, which is sequentialized as descriptive, predictive, and prescriptive analytics. According to the education domain, those three data analytics levels are designed for two business requirements following by students' status life cycle: 1) freshman students' performance depending on TCAS, and 2) sophomore and junior students' performance depending on the background and recent scores. The research aims to extract insights from academic data, predict the performance, and derive action plans to support the decision-making of the Faculty of Engineering, Mahidol University, the top-ranked university in Thailand. The data were collected between 2018 and 2020. By evaluating the prediction model, Gradient Boosted Tree gave the highest accuracy on both domains which are 0-2.1% error rate and 93.8% accuracy rate respectively. The result is that the three analytics could support educational institutes for decision-making, give high accurate predictions, and suggest superior action plans. IMPLICATION OF THE THESIS. The thesis can help the educational institutes to improve educational outcome by supporting decision making in strategic planning for admission and student performance monitoring. The research applies the beauty of Data Science to Educational Data from the process of data collection to action plan creation. This is proved through three analytics model, which consists of Descriptive Analytics, Predictive Analytics and Prescriptive Analytics.
Description
Information Technology Management (Mahidol University 2021)
Degree Name
Master of Science
Degree Level
Master's degree
Degree Department
Faculty of Engineering
Degree Discipline
Information Technology Management
Degree Grantor(s)
Mahidol University