Artificial Intelligence-based Model for Predicting Student Performance in Higher Education

Clc Number:

TP391.48; TP311

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments

    Education is an important enabler for achieving sustainable development goals (SDGs). Artificial intelligence (AI) is a booming technology, and people are showing increasing interests in understanding students’ behavior and evaluating their performance. For the SDGs, AI has great potential to improve education as it has started to be developed in the education field with innovative teaching methods to create better learning. This study presents an artificial intelligence-based analytic tool for predicting the performance of students in a first-year information technology course at a university. A random forest-based classification model is built to predict students’ performance in Week 6, and the model reports the accuracy of 97.03%, sensitivity of 95.26%, specificity of 98.8%, precision of 98.86%, and the Mathews correlation coefficient of 94%. The result demonstrates that this method is useful in predicting the early performance of students in courses. During the COVID-19 pandemic, experimental results showed that the proposed prediction model met the accuracy, precision, and recall required to predict elements of students’ learning behavior in a virtual education system.

    Cited by
Get Citation


Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
  • Received:July 04,2022
  • Revised:July 29,2022
  • Adopted:
  • Online: April 17,2023
  • Published:
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a)
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063