Proceedings of the International e-Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2023)

<Previous Article In Volume
Next Article In Volume>

Happiness Index Prediction of Students Using Machine Learning

Authors
N. Venkata Sailaja1, *, Kallam Lalithendar Reddy2, Gottipati Aditya3, Boppana Shashank4, Vattikuti Hareen Sai2
1Assistant Professor, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India
2Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India
3Department of Computer Science, George Mason University, Fairfax County, VA, USA
4Department of CS & EMSE, George Washington University, Washington D.C, USA
*Corresponding author. Email: sailaja_nv@vnrvjiet.in
Corresponding Author
N. Venkata Sailaja
Available Online 21 December 2023.
DOI
10.2991/978-94-6463-314-6_9How to use a DOI?
Keywords
Happiness Index; Activity-based learning; safe and secure school environment; Student Satisfaction
Abstract

The National Education Policy emphasizes the importance of providing joyful, holistic, and engaging education in schools. According to research, it is possible to teach children how to develop positive emotions, wellbeing, and engagement in their school experience. The goal is to promote happiness among students, teachers, and parents alike. There are various factors that can contribute to the happiness quotient, including the adoption of more activity-based learning methods rather than the traditional chalk and board approach, ensuring a safe and secure school environment, providing clean and hygienic toilets, creating cheerful and inviting classrooms and surroundings, allowing teachers to treat each other and students with respect and dignity, and promoting excellence in diverse areas, schools where parents are involved in some manner in the delivery of qualitative education, etc. By cultivating greater happiness, children can learn to discover and develop their strengths while boosting their sense of optimism. The development of a comprehensive framework for identifying and measuring the various factors that contribute to student happiness is a critical component in advancing the quality of education that schools provide. The identification of these critical indicators will allow for a predictive analysis that can identify outstanding schools and evaluate the different factors that make them better than others. In an effort to facilitate this process, we have undertaken the development of a website that provides a self-assessment tool for schools to use in optimizing their systems and improving overall student satisfaction.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International e-Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
21 December 2023
ISBN
10.2991/978-94-6463-314-6_9
ISSN
2589-4900
DOI
10.2991/978-94-6463-314-6_9How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - N. Venkata Sailaja
AU  - Kallam Lalithendar Reddy
AU  - Gottipati Aditya
AU  - Boppana Shashank
AU  - Vattikuti Hareen Sai
PY  - 2023
DA  - 2023/12/21
TI  - Happiness Index Prediction of Students Using Machine Learning
BT  - Proceedings of the International e-Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2023)
PB  - Atlantis Press
SP  - 85
EP  - 96
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-314-6_9
DO  - 10.2991/978-94-6463-314-6_9
ID  - Sailaja2023
ER  -