Short-Term Forecasting of Student Dropout Trends Using Minimal-Data Predictive Modeling

International Journal of Advanced Multidisciplinary Research and Studies; 5(3); pp:1237-1244

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Glavni autor: Nguyen, Ngoc Huyen Tran
Format: Bài viết
Jezik:English
Izdano: International Journal of Advanced Multidisciplinary Research and Studies 2025
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Online pristup:https://elib.vku.udn.vn/handle/123456789/5878
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spelling oai:elib.vku.udn.vn:123456789-58782025-11-17T22:55:13Z Short-Term Forecasting of Student Dropout Trends Using Minimal-Data Predictive Modeling Nguyen, Ngoc Huyen Tran Gray Level Accuracy MAPE GM (1,1) International Journal of Advanced Multidisciplinary Research and Studies; 5(3); pp:1237-1244 The important and sustainable factor for the reputation and development of universities is the student retention rate. Domestic educational institutions are facing an increasing dropout rate over time, which not only affects the psychology and learning outcomes of students but also leads to unpredictable consequences for the economy and reputation of educational institutions. This study will forecast the student dropout rate using widely accepted mathematical technology. The study has transformed the initial student dropout data through a univariate forecasting method for a small data set. Through the steps in the GM (1,1) model to forecast the number of students likely to drop out for the next period. The accuracy of the model is also evaluated through the Mean Absolute Percentage Error (MAPE), the correlation coefficient (R), Gray Level Accuracy, and the posterior error ratio. The forecast results show that the trend of student dropouts will gradually increase from 2025 to 2030, with relatively good model accuracy (MAPE ≈ 2.8%, R ≈ 0.92, Gray Level Accuracy ≈ 0.97, and Posterior Error Ratio ≈ 0.4). From these results, educational institutions have a tool to forecast the dropout rate, thereby developing appropriate and proactive policies. From there, the study also highlights the role of businesses in creating conditions for students to practice and orient their careers. However, the study also has certain limitations because it has not combined many other influencing factors to make more accurate predictions. 2025-11-17T22:55:01Z 2025-11-17T22:55:01Z 2025-06 Working Paper 2583-049X https://elib.vku.udn.vn/handle/123456789/5878 en application/pdf International Journal of Advanced Multidisciplinary Research and Studies
institution Trường Đại học Công nghệ Thông tin và Truyền thông Việt Hàn - Đại học Đà Nẵng
collection DSpace
language English
topic Gray Level Accuracy
MAPE
GM (1,1)
spellingShingle Gray Level Accuracy
MAPE
GM (1,1)
Nguyen, Ngoc Huyen Tran
Short-Term Forecasting of Student Dropout Trends Using Minimal-Data Predictive Modeling
description International Journal of Advanced Multidisciplinary Research and Studies; 5(3); pp:1237-1244
format Working Paper
author Nguyen, Ngoc Huyen Tran
author_facet Nguyen, Ngoc Huyen Tran
author_sort Nguyen, Ngoc Huyen Tran
title Short-Term Forecasting of Student Dropout Trends Using Minimal-Data Predictive Modeling
title_short Short-Term Forecasting of Student Dropout Trends Using Minimal-Data Predictive Modeling
title_full Short-Term Forecasting of Student Dropout Trends Using Minimal-Data Predictive Modeling
title_fullStr Short-Term Forecasting of Student Dropout Trends Using Minimal-Data Predictive Modeling
title_full_unstemmed Short-Term Forecasting of Student Dropout Trends Using Minimal-Data Predictive Modeling
title_sort short-term forecasting of student dropout trends using minimal-data predictive modeling
publisher International Journal of Advanced Multidisciplinary Research and Studies
publishDate 2025
url https://elib.vku.udn.vn/handle/123456789/5878
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