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Record W4321522483 · doi:10.5539/ies.v16n2p35

Students’ Evaluating of Online Learning Quality at Al Baha University and Their Satisfaction with Online Courses

2023· article· en· W4321522483 on OpenAlexvenueno aff
Abdulmajid Alsaadoun

Bibliographic record

VenueInternational Education Studies · 2023
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMedical educationBlended learningHigher educationEducational technologyQuality (philosophy)Likert scaleDistance educationMathematics educationMedicine

Abstract

fetched live from OpenAlex

The study aims to explore students’ perceptions of the quality of online courses offered for them at Al-Baha University. The current study mainly explores the quality of online learning courses, students’ satisfaction with online learning courses, and the effect of students’ perceived quality of online learning on their satisfaction with these courses. The quality of online courses was measured based on the following factors: learning outcomes, assessment and measurement, learning resources material, learner interaction, and online course technology. An online survey was used to collect data. Seventy-nine graduate students participated in the study. Findings showed that the overall quality of online education was high, and students were predominantly satisfied with their online courses. Additionally, the study found that gender, learning outcome, learning resources, learner interaction, and online technology were significant predictors of students’ satisfaction. The study includes recommendations for implementing online courses as well as suggestions for future studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.083
GPT teacher head0.415
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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