Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 225

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Examining student satisfaction with wholly online learning

Open access
Palmer, S.R., Holt, D.M.·2009·Journal of Computer Assisted Learning

Abstract

Learner satisfaction has been shown to be positively correlated with quality of learning outcomes. An understanding of the factors that influence student satisfaction with online learning in a particular context can be used as an input to the appropriate design of learning environments, and for the provision of targeted support to students, with an aim to positively influence the student online learning experience. Following the mandatory inclusion of at least one wholly online unit of study in all undergraduate programs at Deakin University, a large ‘experiences of learning online’ (ELO) survey was undertaken to gauge students’ perceptions of studying in the wholly online mode. A multivariate linear regression of all the questionnaire items was performed against an overall satisfaction item. Five items were found to significantly contribute to a model that explained approximately 70% of reported student satisfaction. Factors that were found to positively influence student satisfaction with studying a wholly online unit primarily related to how confident they felt about their ability to communicate and learn online, having a clear understanding of what was required to succeed in the unit and how well they thought they were performing in the unit. Other results are also reported.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/j.1365-2729.2008.00294.x

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 225

Metadata

Authors
Palmer, S. R., & Holt, D. M.
Venue
Journal of Computer Assisted Learning
Publisher
Wiley
Published
2009-03-09
Volume
25
Issue
2
Pages
101-113
ISSN
  • 0266-4909 (ISSN-L)
  • 1365-2729
OpenAlex
W1962253820
Cited by
225
References
1
FWCI
30.05
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Examining student satisfaction with wholly online learning. https://app.cochat.ai/papers/10.1111/j.1365-2729.2008.00294.x
The paper
Palmer, S. R., & Holt, D. M. (2009). Examining student satisfaction with wholly online learning. Journal of Computer Assisted Learning. https://doi.org/10.1111/j.1365-2729.2008.00294.x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.