What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction
A bibliographic record and short editorial reading note for a paper included in the historical EDUCATE collection.
Original publication authors
Pei-Chen Sun; Ray J. Tsai; Glenn Finger; Yueh-Yang Chen; Dowming Yeh
What this paper examines
Sun and colleagues investigate learner satisfaction using a model spanning learners, instructors, courses, technology, design and the learning environment. The study identifies several relevant factors, including anxiety about computers, instructor attitudes, course quality and flexibility, perceived usefulness and ease of use, and assessment variety. Its findings provide a historical research framework; they do not establish one universal checklist that guarantees course success.
A question to take into course design
Which parts of the student experience are being measured separately, instead of being combined into a single satisfaction score?
The full paper remains a third-party publication. This page preserves its identity and provides a new editorial reading note; it does not attribute the note to the original researchers or change the paper’s publication date.
Why it belongs in the water programme archive
EDUCATE combined water resources and environmental management with distance delivery. The original reading collection included research about online teaching, course design and learner support.
Sun and colleagues studied learner satisfaction across several dimensions of e-learning. A satisfactory experience and an acquired technical skill are different outcomes.
New explanation and worked examples by the editorial team.
Original explanatory diagram · Water MSC editorial. Experience evidence → Performance evidence → A targeted next action.
The diagram in words: Experience evidence → Performance evidence → A targeted next action.
Write two outcome columns
For the learning column, define a task the learner should be able to perform, such as checking rainfall-volume units. For the experience column, ask about navigation, clarity or perceived usefulness. Keep these separate in both the instrument and the report.
A fictional disagreement that matters
A learner rates a lesson highly but multiplies millimetres by square kilometres without conversion. Another learner criticises navigation yet completes the dimensional check correctly. Neither result should be erased by averaging the two kinds of evidence into one unsupported “quality” score.
Use the mismatch to choose an action
An experience problem may call for a design repair; a task error may call for a clearer explanation, practice or feedback. Record the hypothesis and the evidence required for the next check. Do not treat a model from one research setting as a universal causal recipe.
Worked record
Field
Example or check
Learner A, invented
High satisfaction; unit-conversion error
Learner B, invented
Navigation concern; correct calculation
Response
Different evidence, different repair
Document evidence
What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction · 20 pages.
