Comparative Study

Open Access

|

Peer-reviewed

A Study of Self-Concept in Relation to Academic Streams, Gender, and Area of Residence among College Students

Mr. Sandeep Dhananjay Satonkar

DIP: 18.02.010/20200504

DOI: 10.25215/2455/0504010

Received: November 28, 2020; Revision Received: December 20, 2020; Accepted: December 27, 2020

Abstract

The present study aimed to examine the influence of academic stream, gender, and area of residence on self-concept among college students. The sample consisted of 120 students (40 Arts, 40 Commerce, and 40 Science) from the Aurangabad, district of Maharashtra, aged between 18 and 21 years (M = 18.93, SD = 2.83), with an equal male-to-female ratio. A purposive sampling technique was employed, and the Self-Concept Questionnaire (SCQ) by Dr. R.K. Saraswat (1984) was used for data collection. The study adopted a balanced 3 × 2 × 2 factorial design, and data were analyzed using Mean, Standard Deviation, and Analysis of Variance (ANOVA). Results revealed significant differences across all three independent variables. Science students reported significantly higher self-concept than Arts and Commerce students. Female students exhibited significantly higher self-concept compared to male students. Urban students demonstrated significantly higher self-concept than rural students.

The author(s) appreciates all those who participated in the study and helped to facilitate the research process.

The author declared no conflict of interest.

This is an Open Access Research distributed under the terms of the Creative Commons Attribution License (www.creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any Medium, provided the original work is properly cited.

Responding Author Information

Mr. Sandeep Dhananjay Satonkar @ sdsatonkar@gmail.com

Related Content
A Study of Self-Concept in Relation to Academic Streams, Gender, and Area of Residence among College Students

Total Download: 2 | Total View: 26

PlumX Matrix

Plum Analytics uses research metrics to help answer the questions and tell the stories about research. Research metrics that immediately measure awareness and interest give us new ways to uncover and tell the stories of research.

Dimensions Matrix

Dimensions is a next-generation linked research information system that makes it easier to find and access the most relevant information, analyze the academic and broader outcomes of research, and gather insights to inform future strategy. (digital science)

Article Overview

ISSN 2455-670X

DIP: 18.02.010/20200504

DOI: 10.25215/2455/0504010

Published in

Volume 05, Issue 4, October – December, 2020

  • 2Downloads
  • 0Citations
  • 26Views
  • 0Likes
How to Cite
Print
Share
Make a Submission