Bayesian Model Average for Student Learning Location

Authors

  • Nguyen Viet Lam Industrial University of Ho Chi Minh City, Vietnam
  • Bui Huy Khoi Industrial University of Ho Chi Minh City, Vietnam https://orcid.org/0000-0002-4976-7435

DOI:

https://doi.org/10.13052/jicts2245-800X.10211

Keywords:

Bayesian Model Selection, Students' perception, Price perception, perception of university, city, student, learning location

Abstract

The paper was conducted to understand the factors affecting the student’s learning location. The official study carried out an online survey through Google forms using a questionnaire with the participation of 125 samples. The Bayesian Model Selection shows that 03 factors are affecting student studying location (SSL), which are Students’ perception (PP), Price perception (PRI), Perception of universities in a big city (UNI). From the results, we have proposed many implications for improving student learning. This study uses the optimal choice of Bayesian Model Selection for the student learning location. Students’ perceptions (PP), price perceptions (PRI), and university perceptions in big cities (UNI) all have a 97.1 percent impact on student studying places (SSL). Model 1 is the best option by BIC, and four variables have a probability of 100%.

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Author Biographies

Nguyen Viet Lam, Industrial University of Ho Chi Minh City, Vietnam

Nguyen Viet Lam is a MBA student in Industrial University of Ho Chi Minh City. He is currently working as a Lecturer at Industrial University of Ho Chi Minh City, Vietnam. His research areas include economic analysis and management.

Bui Huy Khoi, Industrial University of Ho Chi Minh City, Vietnam

Bui Huy Khoi received the bachelor’s degree in economics from University of Economics HCM City in 2001, the master’s degree in economics from University of Economics and Law in HCM City in 2010, and the philosophy of doctorate degree in Management from University of Economics HCM City in 2021, respectively. He is currently working as a Lecturer at Industrial University of Ho Chi Minh City, Vietnam. His research areas include data analysis, data mining, and social network analysis.

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Published

2022-05-21

Issue

Section

Intelligent Systems for Smart Applications