Influence of academic self-concept and achievement motivation on academic resilience of higher secondary students

The research sought to study the influence of Academic Self Concept and Achievement Motivation on Academic Resilience of Higher Secondary Students. A sample composed of 350 Higher Secondary Students from Pathanamthitta district of Kerala state was selected using random sampling technique. The collected data using Academic Self Concept Scale, Achievement Motivation Scale and Academic Resilience Scale were analysed using descriptive statistical techniques, percentage analysis and Regression analysis. The findings revealed that Academic Self Concept and Achievement Motivation are the significant predictors of Academic Resilience of Higher Secondary students. So, these variables can be considered as the explanatory variables of Academic Resilience. The findings of the study also revealed that 64% and 62% of the total sample possess moderate level of Academic Self Concept and Achievement Motivation respectively. The level of Academic Resilience of 82% of the total sample was also moderate.This leads to the conclusion that Higher Secondary Students have moderate level of Academic Self Concept, Achievement Motivation and Academic Resilience.The study recommends remedial measures such as personal and academic counseling in the purview of school settings for enabling the students to meet the challenges they face in academic setting.

Authors

Publication Details

Journal
International Journal of Science and Research Archive
Published
2025-05-15
DOI
https://doi.org/10.30574/ijsra.2025.15.2.1318
Primary Topic
Health and Well-being Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Influence of academic self-concept and achievement motivation on academic resilience of higher secondary students

Sethu S. Nath, R. Jayaprakash
International Journal of Science and Research Archive
Health and Well-being Studies
article

Influence of academic self-concept and achievement motivation on academic resilience of higher secondary students

Sethu S. Nath, R. Jayaprakash
article en

Abstract

The research sought to study the influence of Academic Self Concept and Achievement Motivation on Academic Resilience of Higher Secondary Students. A sample composed of 350 Higher Secondary Students from Pathanamthitta district of Kerala state was selected using random sampling technique. The collected data using Academic Self Concept Scale, Achievement Motivation Scale and Academic Resilience Scale were analysed using descriptive statistical techniques, percentage analysis and Regression analysis. The findings revealed that Academic Self Concept and Achievement Motivation are the significant predictors of Academic Resilience of Higher Secondary students. So, these variables can be considered as the explanatory variables of Academic Resilience. The findings of the study also revealed that 64% and 62% of the total sample possess moderate level of Academic Self Concept and Achievement Motivation respectively. The level of Academic Resilience of 82% of the total sample was also moderate.This leads to the conclusion that Higher Secondary Students have moderate level of Academic Self Concept, Achievement Motivation and Academic Resilience.The study recommends remedial measures such as personal and academic counseling in the purview of school settings for enabling the students to meet the challenges they face in academic setting.

International Journal of Science and Research ArchiveVol. 15(2)
Openalex Percentile: Top 85%
Health and Well-being Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.