Online learning
What do students rank as most important online?
Open access · cc by · source: Europe PMC
Students prioritize a hierarchy of online-course quality factors spanning basic modality, teaching presence, and richer interaction.
Study at a glance
- Design
- Cross-sectional — Large survey with EFA of student-rated online course quality factors
- N
- N=987 · 987 respondents (~40% of ~2,500 contacted); 397-student pilot
- Population
- University students rating online-course quality priorities
- Outcome
- Hierarchy of online-learning quality factors (modality, teaching presence, interaction)
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
Students treated some baseline online conditions as near-threshold requirements while weighting teaching presence and interactive features as higher-order quality drivers. Factor means showed clear differentiation among clusters of importance rather than a flat list of preferences.
Methodology
After piloting an instrument, instructors distributed a Qualtrics survey to roughly twenty-five hundred students; nearly a thousand responded. Exploratory factor analysis organised student priorities into a hierarchy of online-learning quality factors grounded in presence and modality literature.
Limitations
Self-report importance ratings are not measured learning gains. The sample skews young and comes from courses whose instructors opted into distribution, so priorities may differ elsewhere.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
Social presence is often the easiest CoI component for students to enact and feel in asynchronous role-play, even when critical thinking stalls before resolution.
Evidence for the claim as stated.
Student importance ratings for quality factors are not the same evidence as observed discourse quality or learning gains.
Evidence for the claim as stated.
Students often weight teaching presence and interactive features as higher-order online quality drivers above baseline modality conditions.
Evidence for the claim as stated.
Student importance ratings for quality factors are not the same evidence as observed discourse quality or learning gains.
Evidence for the claim as stated.
Groups may enact CoI components yet still fail to reach resolution-level critical thinking without stronger facilitation.
Evidence for the claim as stated.
Student importance ratings for quality factors are not the same evidence as observed discourse quality or learning gains.
Evidence for the claim as stated.
After a 397-student pilot, instructors distributed a Qualtrics survey to about 2,500 students; 987 responded (40%), 78% under age 30. Exploratory factor analysis organised priorities into a hierarchy of online-learning quality factors. Students treated some baseline conditions as near-threshold requirements while weighting teaching presence and interactive features as higher-order drivers; factor means differentiated clusters of importance rather than a flat list. Importance ratings are not measured learning gains, and instructors opted into distribution.
Evidence for the claim as stated.
Measurement models and change scores are different jobs. TIQS uses EFA/CFA then SEM paths, including an unexpected negative individualised-teaching path. The online-quality paper uses EFA to rank importance, not to predict engagement. The teacher-education paper uses SEM path coefficients among self-beliefs. The faculty paper reports pre/post attitude change for 695 trainees without a control. One software family (factors, SEM, scales) is not one empirical result.
Evidence for the claim as stated.
Theoretically positive quality dimensions do not all point the same way. TIQS finds support and classroom management positively linked to behavioural engagement, but individualised teaching negative in the reported model — a sign the authors flag as fragile. The hierarchy paper’s teaching-presence/interactive factors are importance ratings, not the same latent as TIQS’s integration-quality factors. Do not treat them as replications of one 'quality raises engagement' law.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Student importance ratings for quality factors are not the same evidence as observed discourse quality or learning gains.
Student importance ratings for quality factors are not the same evidence as observed discourse quality or learning gains.
Student importance ratings for quality factors are not the same evidence as observed discourse quality or learning gains.
Measurement models and change scores are different jobs. TIQS uses EFA/CFA then SEM paths, including an unexpected negative individualised-teaching path. The online-quality paper uses EFA to rank importance, not to predict engagement. The teacher-education paper uses SEM path coefficients among self-beliefs. The faculty paper reports pre/post attitude change for 695 trainees without a control. One software family (factors, SEM, scales) is not one empirical result.
Theoretically positive quality dimensions do not all point the same way. TIQS finds support and classroom management positively linked to behavioural engagement, but individualised teaching negative in the reported model — a sign the authors flag as fragile. The hierarchy paper’s teaching-presence/interactive factors are importance ratings, not the same latent as TIQS’s integration-quality factors. Do not treat them as replications of one 'quality raises engagement' law.
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Same topic cluster — not a recommendation engine.