Analyzing students academic performance using multilayer perceptron model

Title

Analyzing students academic performance using multilayer perceptron model

Creator

Sinthia G.; Balamurugan M.

Description

Identification of the students behavior in the class room environment is very important. It helps the lecturer to identify the needs of the students. It also aids in identifying the strength and weakness of the individual and guide them to improve on their performance. Observing and supervising the students regularly can improve their performance. The data has been collected from 120 students who took the common the course taught by two different lectures. The students were observed based on the internal assignments and quizzes and the model exam given by the respective lecturers. In this paper the students are categorized into different groups based on their performance using Multilayer Perceptron (MLP) and also different factors which are influencing the performance of the students are identified. BEIESP.

Source

International Journal of Recent Technology and Engineering, Vol-7, No. 5, pp. 156-160.

Date

2019-01-01

Publisher

Blue Eyes Intelligence Engineering and Sciences Publication

Subject

K-means; K-Nearest Neighbor (KNN); Machine Learning; Multilayer Perceptron; Students Performance

Coverage

Sinthia G., Dept. of Computer Science and Engineering CHRIST (Deemed to be University), Faculty of Engineering, Bangalore, Karnataka, India; Balamurugan M., Dept. of Computer Science and Engineering CHRIST (Deemed to be University), Faculty of Engineering, Bangalore, Karnataka, India

Rights

Restricted Access

Relation

ISSN: 22773878

Format

Online

Language

English

Type

Article

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068001944&partnerID=40&md5=86e0dc54ef165ac1c593cc4522645ec0