Online Student Feedback System Using Machine Learning

Authors

  • Haider Abdula Haddad Department of Computer Science & Information Technology, Salahaddin University, Erbil, Kurdistan Region, Iraq

DOI:

https://doi.org/10.21271/ZJPAS.35.3.7

Keywords:

Feedback system, SVM algorithm, machine learning, university dataset, online system

Abstract

       In order to develop plans to enhance the teaching experience, student feedback data analysis is a very good tool to enhance the relationship between teachers and students.

This research is to present an analytical model for data from student feedback systems to improve the quality of teaching in academic institutions and universities. The developed system in this research uses the lexical analysis algorithm SVM, which has the best accuracy and is one of the machine learning algorithms that can provides textual feedback and useful insights into the overall quality of teaching to improve teaching methods.

In this research an online system for student feedback was created. The system is used to get feedback from students about teachers and their methods of teaching. The system uses a large database to collect a large dataset from all students at different colleges at the university level. The system administrators include staff on the college levels from all colleges. All students will be provided with unique usernames and passwords to log in to the system.

Among the main tasks for the system administrator is to create classes and to create feedback questions that are designed in two questionnaire forms. The first questionnaire form is about academic questions that are related to the quality of teaching the academic subject. The second questionnaire form is the questions that are related to general education for students. The textual analysis in this system is provided using the SVM lexical analysis algorithm, which has the best accuracy but it requires more training time for large data sets to classify the text.

The student feedback system developed and used in this research proved to be an excellent tool to improve the academic and educational status of the university. It also helps reduce manual labor in collecting, storing and analyzing feedback data. This system is an efficient way to provide qualitative feedback to teachers that improves student-learning performance.

References

Aggarwal, C. C., 2015. In: C. &. Hall/CRC, ed. Data Classification Algorithms and Applications. Yorktown Heights, New York, USA: CRC Press is an imprint of Taylor & Francis Group, an Informa business.

A. N. & T. M., 2023. CS229 Lecture Notes. [Online]

Available at: https://sgfin.github.io/files/notes/CS229_Lecture_Notes.pdf

Asmita, S., Anuja, D. & D., A., 2019. Analysis of Student Feedback Using Deep Learning. International Journal of Computer Applications Technology and Research, 8(5), pp. 161-164.

Bhanukiran, G. et al., 2018. Student Feedback System. IRE Journals, 1(10).

Bidve, V. S., Patwari, P., Raut, R. & Kadam, A., 2021. Student Feedback System Using Machine Learning. International Journal of Engineering Research in Computer Science and Engineering, 8(8).

Hatwar, N. et al., 2019. Online Student Feedback System. Journal of Innovation in Engineering and Science, 4(5).

Kandhro, I. A. et al., 2020. Performance Analysis of Hyperparameters on a Sentiment Analysis Model. Engineering, Technology & Applied Science Research, 10(4), pp. 6016-6020.

Kuo, J.-Y., Lin, H.-C., Wang, P.-F. & Nie, Z.-G., 2022. A Feedback System Supporting Students Approaching a High-Level Programming Course. Applied Sciences, 12(14).

L. S., 2022. Application Of Student Feedback Using Machine Learning Model. ijcrt, 10(7).

Lwin, H. et al., 2020. Feedback Analysis in Outcome Base Education Using Machine Learning. s.l., s.n.

Nasim, Z., Rajput, Q. & Haider, S., 2017. Sentiment Analysis of Student Feedback Using Machine Learning and Lexicon Based Approaches. IEEE, Volume 4.

Paulaa, F., Alexandera, B. & Georga, H., 2017. Feedback Based Learning Through Online Feedback Systems in Higher Education. s.l., Polytechnic University of Valencia Congress.

Published

2023-06-15

How to Cite

Haider Abdula Haddad. (2023). Online Student Feedback System Using Machine Learning. Zanco Journal of Pure and Applied Sciences, 35(3), 78–85. https://doi.org/10.21271/ZJPAS.35.3.7

Issue

Section

Mathematics, Physics and Geological Sciences