Quantum Artificial intelligence in Predicting University Students’ Performance


Quantum Artificial intelligence is a new scientific field that combines quantum mechanics and artificial intelligence. Quantum artificial intelligence – based educational applications are at a very early stage. In this research, a quantum machine learning approach is proposed in predicting university students’ performance. A quantum circuit was developed by combining several qubits to achieve better results. The circuit was implemented by using python programming language, and parallel computation/GPU for the TensorFlow-based models. The results have shown very good forecasting accuracy. The proposed Quantum Artificial intelligence approach can be incorporated into several sectors of education in the future.


Technologies in Learnning, Quantum Mechanics, Quantum Artificial Intelligence


Technologies in Learning


Paper Presentation in a Themed Session


  • Georgios N. Kouziokas
    • University Teaching Assistant, Polytechnic School, University of Thessaly, Greece Greece
    • Ph.D. Researcher. University Teaching Assistant. Holds 4 Masters of Science.. Lead Guest Editor in the journal S.I. "Artificial Intelligence in Education" (Indexed in Scopus, Web of Science) and associate editor in several international journals. Reviewer in 38 international scientific journals. He holds 4 Masters of Science:a MSc in Information Systems, MSc in Contemporary Learning Environments and Production of Instructive Material, from the School of Humanities, a MSc in Spatial Analysis (GIS) and Environmental Management and in Applied Mathematics. His main research interests are: Artificial Intelligence, Applied Mathematics, Neural Networks, management information systems, educational informatics, project based learning, environmental informatics and geographical information systems. He has developed several information systems and he has published more than 40 scientific articles in peer-reviewed international journals and international conferences.