International Journal of Internet, Broadcasting and Communication

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Applying Machine Learning approaches to predict High-school Student Assessment scores based on high school transcript records

  • Nguyen Ba Tien (Center for Educational Testing Vietnam National University Hanoi) ;
  • Hoai-Nam Nguyen (VNU University of Education, Vietnam National University in Hanoi) ;
  • Hoang-Ha Le (VNU University of Education, Vietnam National University in Hanoi) ;
  • Tran Thu Trang (Faculty of Information Technology, Dainam university) ;
  • Chau Van Dinh (Faculty of Information Technology, Electric Power University) ;
  • Ha-Nam Nguyen (Faculty of Information Technology, Electric Power University) ;
  • Gyoo Seok Choi (Department of Computer Science, Chungwoon University)
  • Received : 2023.04.21
  • Accepted : 2023.04.27
  • Published : 2023.05.31
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Abstract

A common approach to the problem of predicting student test scores is based on the student's previous educational history. In this study, high school transcripts of about two thousand candidates, who took the High-school Student Assessment (HSA) were collected. The data were estimated through building a regression model - Random Forest and optimizing the model's parameters based on Genetic Algorithm (GA) to predict the HSA scores. The RMSE (Root Mean Square Error) measure of the predictive models was used to evaluate the model's performance.

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References

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