Vol.10, No.1, February 2021.                                                                                                                                                                           ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333

 

TEM Journal

 

TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS

Association for Information Communication Technology Education and Science


Guiding the Students in High School by Using Machine Learning

 

Mustafa Ababneh, Aayat Aljarrah, Damla Karagozlu, Fezile Ozdamli

 

© 2021 Mustafa Ababneh, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

 

Citation Information: TEM Journal. Volume 10, Issue 1, Pages 384-391, ISSN 2217-8309, DOI: 10.18421/TEM101-48, February 2021.

 

Received: 10 September 2020.

Revised:   25 December 2020.
Accepted: 30 December 2020.
Published: 27 February 2021.

 

Abstract:

 

Machine learning is considered the most significant technique that processes and analyses educational big data. In this research paper, many previous papers related to analysing the educational big data that uses a lot of artificial intelligence techniques were studied. The purpose of the study is to identify weaknesses and gaps in previous researches. The results showed that many researches highlighted early expectations for academic performance. Unfortunately, no one thought of finding an effective way to guide high schooled students to reach their appropriate majors that can be suitable to their abilities. Those students need to be guided to pass this sensitive phase with high efficiency and good results. Thus, this school level is considered as the starting point for students’ academic lives, professional, and future success.

 

Keywords: Big Data Analysis, education, machine learning, Student information system, student direction.

 

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