Research on The Impact of Childhood Coping Strategies in Academics and Adolescence Lives of Students using Data Mining
S. Vallikala1, V. Geetha2, V. Jalaja Jayalakshmi3

1S. Vallikala, Student Counsellor, Kumaraguru College of Technology,  Coimbatore,  India.

2V. Geetha, Professor, Deptmnt of Computer Applications, Kumaraguru  College  of  Technology, Coimbatore,  India.

3V. Jalaja Jayalakshmi, Assistant Professor, Deptmant of Computer Applications, Kumaraguru College of Technology, Coimbatore,  India.

Manuscript received on 20 August 2019 | Revised Manuscript received on 27 August 2019 | Manuscript Published on 31 August 2019 | PP: 404-408 | Volume-8 Issue-9S2 August 2019 | Retrieval Number: I10860789S219/19©BEIESP DOI: 10.35940/ijitee.I1086.0789S219

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The role of a counsellor in educational institutions revolves mostly around academic and behavioural issues. The aim of this study is to identify common sources of stress among adolescence students and to determine the impact of coping strategies practised by the students in academics and life in general. The association between adolescent life, geographical location, stress sources, and coping strategies is explored in this work. Diverse factors contribute to stress, agitation and academic performanceamong students. The major factors that were considered for this study are regional and familial backgrounds of the students, their gender, residential status, communication skills, the five childhood coping strategies and their influence in the campus life. Counselling sessions were conducted for the students and the empirical data is classified using data mining techniques to analyze the factors that contribute to the behavioural aspects of the students.

Keywords: Academic, Behavioural, Adolescent, Coping strategies, Counselling, Data Mining
Scope of the Article: Data Mining Methods, Techniques, and Tools