Exploring the Relationships of Learners and Instructors in Online Courses

This quantitative study explored the relationship between student-instructor connectedness and student anxiety in online higher education courses. Research shows the value of student-instructor connectedness for student satisfaction in online learning. Utilizing the Connectedness and Anxiety items of the Student-Instructor Relationship Scale (Creasey, et al., 2009) in a large-scale cross-sectional survey with a representative sample of students at a comprehensive research university in the southeastern United States of America, we found significant relationships between the dependent variables (connectedness, anxiety, and motivation). Students with higher connectedness with instructor(s) tended to have higher motivation with lower levels of anxiety. In addition, students with higher anxiety were likely to show lower levels of motivation. Students perceived male instructors to form lower connectedness and male students and transfer students had higher levels of anxiety. Findings contribute to the field of instructor connectedness in online learning and have implications for higher education institutions and faculty considering increasing online learning offerings. We provide recommendations for building rapport and enhancing connectedness in online learning to decrease anxiety and increase student motivation.

Authors

Institutions

Publication Details

Journal
Online Learning
Published
2024-12-01
DOI
https://doi.org/10.24059/olj.v28i4.4051
Citations
3
Primary Topic
Online and Blended Learning
Type
article
Field-Weighted Citation Impact
6.29
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the Relationships of Learners and Instructors in Online Courses

Sheri Conklin, Amy Garrett Dikkers, Beth Allred Oyarzun, Stella Yun Kim
3 citations
Online Learning
Online and Blended Learning
6.29
article

Exploring the Relationships of Learners and Instructors in Online Courses

Sheri Conklin, Amy Garrett Dikkers, Beth Allred Oyarzun, Stella Yun Kim
article en
3 citations

Abstract

This quantitative study explored the relationship between student-instructor connectedness and student anxiety in online higher education courses. Research shows the value of student-instructor connectedness for student satisfaction in online learning. Utilizing the Connectedness and Anxiety items of the Student-Instructor Relationship Scale (Creasey, et al., 2009) in a large-scale cross-sectional survey with a representative sample of students at a comprehensive research university in the southeastern United States of America, we found significant relationships between the dependent variables (connectedness, anxiety, and motivation). Students with higher connectedness with instructor(s) tended to have higher motivation with lower levels of anxiety. In addition, students with higher anxiety were likely to show lower levels of motivation. Students perceived male instructors to form lower connectedness and male students and transfer students had higher levels of anxiety. Findings contribute to the field of instructor connectedness in online learning and have implications for higher education institutions and faculty considering increasing online learning offerings. We provide recommendations for building rapport and enhancing connectedness in online learning to decrease anxiety and increase student motivation.

Online LearningVol. 28(4)
University of North Carolina at Charlotte (US), University of North Carolina Wilmington (US)
Quality Education
Openalex Percentile: Top 3%
Online and Blended Learning
6.29
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.