Role of Communication Style, E learning Environment, and Student Satisfaction on Academic Performance: Moderating Role of Institutional Support

Several factors such as excessive usage of social media, quality of academic activities, family and social association, and a rapidly changing and challenging environment can negatively impact the academic performance of students. The present study aims to determine students’ academic performance in higher education institutions in China, considering the role of communication styles, e-learning environment, student satisfaction, and a moderating effect of institutional support in predicting students’ academic performance. Adopting a quantitative research design with sample random sampling technique, this study collected data through a validated questionnaire from a sample of 385 students from Chinese universities. Smart-PLS-4 was used for data analysis. The relationships between communication style and academic performance, e-learning and academic performance, and student satisfaction and academic performance were found to be significant. However, institutional support moderated the relationship between student satisfaction and academic performance, but no moderation effect was reported between communication style, e-learning, and academic performance. The implications of the study and future research avenues are given at the end of the paper

Authors

Institutions

Publication Details

Journal
El Profesional de la Informacion
Published
2024-11-10
DOI
https://doi.org/10.3145/epi.2024.ene.0402
Citations
2
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
1.56
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Role of Communication Style, E learning Environment, and Student Satisfaction on Academic Performance: Moderating Role of Institutional Support

Hongbo Zhang
2 citations
El Profesional de la Informacion
Education and Learning Interventions
1.56
article

Role of Communication Style, E learning Environment, and Student Satisfaction on Academic Performance: Moderating Role of Institutional Support

Hongbo Zhang
article en
2 citations

Abstract

Several factors such as excessive usage of social media, quality of academic activities, family and social association, and a rapidly changing and challenging environment can negatively impact the academic performance of students. The present study aims to determine students’ academic performance in higher education institutions in China, considering the role of communication styles, e-learning environment, student satisfaction, and a moderating effect of institutional support in predicting students’ academic performance. Adopting a quantitative research design with sample random sampling technique, this study collected data through a validated questionnaire from a sample of 385 students from Chinese universities. Smart-PLS-4 was used for data analysis. The relationships between communication style and academic performance, e-learning and academic performance, and student satisfaction and academic performance were found to be significant. However, institutional support moderated the relationship between student satisfaction and academic performance, but no moderation effect was reported between communication style, e-learning, and academic performance. The implications of the study and future research avenues are given at the end of the paper

El Profesional de la InformacionVol. 33(4)
Tianjin Medical University Eye Hospital (CN), Tianjin Medical University (CN)
Quality Education
Openalex Percentile: Top 12%
Education and Learning Interventions
1.56
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.