Education 4.0 using artificial intelligence for students performance analysis


  • Zhongshan Chen School of Mathematics and Information Science, Nanjing Normal University of Special Education, Shennong Road
  • Juxiao Zhang
  • Xiaoyan Jiang
  • Zuojin Hu
  • Xue Han
  • Mengyang Xu
  • Savitha V
  • G.N. Vivekananda



Education 4.0, Artificial Intelligence, Students Performance Analysis


Nowadays, predicting students' performance is one of the most specific topics for learning environments, such as universities and schools, since it leads to the development of effective mechanisms that can enhance academic outcomes and avoid destruction. In education 4.0, Artificial Intelligence (AI) can play a key role in identifying new factors in the performance of students and implementing personalized learning, answering routine student questions, using learning analytics, and predictive modeling. It is a new challenge to redefine education 4.0 to recognize the creative and innovative intelligent students, and it is difficult to determine students' outcomes. Hence, in this paper, Hybridized Deep Neural Network (HDNN) to predict student performance in Education 4.0. The proposed HDNN method is utilized to determine the dynamics that likely influence the student's performance. The deep neural network monitor,  predicts, and evaluates the student's performance in an education 4.0 environment. The findings show that the proposed HDNN method achieved better prediction accuracy when compared to other popular methods.


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How to Cite

Zhongshan Chen, Juxiao Zhang, Xiaoyan Jiang, Zuojin Hu, Xue Han, Mengyang Xu, Savitha V, & G.N. Vivekananda. (2020). Education 4.0 using artificial intelligence for students performance analysis. Inteligencia Artificial, 23(66), 124–137.