Investigation on association of self-esteem and students' performance in academics. (2018)

• Record Type: Journal Article
• Authors: Jayanthi, M. Amala; Kumar, R. Lakshmana; Swathi, S.
• Is Part Of: International journal of grid and utility computing. Volume 9:Number 3(2018)
• Page Start: 211
• Page End: 219
• Publication Date: 2018
• Subjects: Bloom's taxonomy -- educational data mining -- Rosenberg self-esteem scale -- educational data mining -- multilayer perceptron -- criterion reference model; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

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.