Formative Assessment Based Students’ Recruitment Estimation: Neural Network Approach

DOI

10.2991/978-94-6463-136-4_64How to use a DOI?

Keywords

Formative Assessment; Job Placement; eLearning; Machine Learning; Neural Network

Abstract

Even though there is a strong focus on achieving the objectives of the education system, it is undoubtedly dependent on the knowledge, skills, and, most notably, the methodology of how teachers use qualitative and quantitative assessment techniques to assist learners. Teachers use formative assessment to monitor students’ progress, their level of knowledge, and their ability to self-assess. One of the critical outcomes following completion of a degree program is the ability of the student to obtain employment. More specifically, it focuses on acquiring knowledge, skills, and capacities that are then applied to real-life contexts. This paper presents a neural network approach to predicting students’ job placement based on formative assessment. The approach aids Higher Education Institutions in determining the progress of individual students and areas for improvement during the graduation process, increasing the likelihood of students finding employment after graduation. The paper illustrates important parameters for campus placement selection, how embedding formative assessment and neural network modelling facilitate enhancing students’ knowledge, skills, and performance at the institute and fulfil its objectives of gaining meaningful employment.

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.

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TY  - CONF
AU  - Varsha P. Desai
AU  - Rajanish K. Kamat
AU  - Priyanka P. Shinde
AU  - Kavita S. Oza
PY  - 2023
DA  - 2023/05/01
TI  - Formative Assessment Based Students’ Recruitment Estimation: Neural Network Approach
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 742
EP  - 754
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_64
DO  - 10.2991/978-94-6463-136-4_64
ID  - Desai2023
ER  -