Title: Investigation on association of self-esteem and students' performance in academics

Authors: M. Amala Jayanthi; R. Lakshmana Kumar; S. Swathi

Addresses: Department of Computer Applications, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India ' Department of Computer Applications, Hindusthan College of Engineering and Technology, Coimbatore, Tamil Nadu, India ' Accenture Services Private Ltd, Chennai, Tamil Nadu, India

Abstract: Educationalists have formulated a taxonomy called Bloom's taxonomy. It states that during education a student progresses not only in knowledge (cognitive), but also in emotions (attitude/behaviour) and skill sets (psychomotor). In general only the knowledge of the students is assessed. This paper researches on the influence of students' self-esteem (attitude) on their performance in the academics. Self-esteem is emotional evaluation of self-worth positively or negatively. Rosenberg's self-esteem scale is used to evaluate the individual's self-esteem. The students are categorised based on their self-esteem scale and performance scale respectively using supervised and unsupervised learning. The relation between the self-esteem and the performance is proven using predictive and descriptive modelling. The study reveals the positive association between the self-esteem and the performance. This research helps the teaching community to realise the influence of student's self-esteem on their performance and helps them to grow positively in their knowledge, emotions and skills.

Keywords: Bloom's taxonomy; educational data mining; Rosenberg self-esteem scale; educational data mining; multilayer perceptron; criterion reference model.

DOI: 10.1504/IJGUC.2018.093976

International Journal of Grid and Utility Computing, 2018 Vol.9 No.3, pp.211 - 219

Received: 14 Nov 2017
Accepted: 02 Jan 2018

Published online: 10 Aug 2018 *

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