Research Article
Adaptive Deep Learning Technique to Predict Student’s Graduation Results
@INPROCEEDINGS{10.1007/978-3-030-92942-8_6, author={Nguyen Quoc Viet and Vo Pham Tri Thien and Nguyen Thanh Binh}, title={Adaptive Deep Learning Technique to Predict Student’s Graduation Results}, proceedings={Nature of Computation and Communication. 7th EAI International Conference, ICTCC 2021, Virtual Event, October 28--29, 2021, Proceedings}, proceedings_a={ICTCC}, year={2022}, month={1}, keywords={Data analysis Student’s graduation result Deep learning Data mining}, doi={10.1007/978-3-030-92942-8_6} }- Nguyen Quoc Viet
Vo Pham Tri Thien
Nguyen Thanh Binh
Year: 2022
Adaptive Deep Learning Technique to Predict Student’s Graduation Results
ICTCC
Springer
DOI: 10.1007/978-3-030-92942-8_6
Abstract
Analyzing educational data techniques helps educational institutions predict the final graduation results of students based on the average score in the first semesters of the course. To predict student’s graduation results, this research proposed the method to predict includes five steps: data collection, data preprocessing, predict student’s graduation results model, evaluating model and deployment model. The proposed method is based on the average academic points data of the six main semesters out of a total of eight main semesters of students to predict their graduation result with the accuracy of about 90.53%. To objectively evaluate the effectiveness of the proposed method, the results of the proposed method, which compared with the other methods, are better than the other methods.
