Prediction of students’ performance in education system based on artificial intelligence
| Autor: | Pooja Pathak, Nazia Farheen, Avinash Dubey |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | IOP Conference Series: Materials Science and Engineering. 1116:012132 |
| ISSN: | 1757-899X 1757-8981 |
| DOI: | 10.1088/1757-899x/1116/1/012132 |
| Popis: | The main objective of any educational system is to provide the best knowledge to students. To achieve this goal this is important to identify the weak students who need more support and take correct decisions to improve their performance. In this research for predicting the students’ performance, four techniques of machine learning are used. For this technique, we take the data from computer science students of GLA University, Mathura, U.P. INDIA. These machine learning techniques include various processes such as Artificial Neural Networks (ANN), Naive Bayes (NB), Logistic Regression, and Decision Tree. In this model, we put more efforts to know the time attended by the students on the internet for learning and social media. Also, various measurements have been done such as precision, F measure, recall, and classification errors. We used the dataset for building a model depending upon the survey that given to the all-computer science students and grade copy of students. The decision tree identified four main attributes that influence the performance of students a lot. This helps us to achieve an accurate prediction of around 98%. |
| Databáze: | OpenAIRE |
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