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Record W4292959179 · doi:10.5267/j.ijdns.2022.6.012

The role of digital leadership, system of information, and service quality on e-learning satisfaction

2022· article· en· W4292959179 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Data and Network Science · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSimple random sampleKnowledge managementService qualityInformation qualityQuality (philosophy)Information systemPerspective (graphical)Computer scienceService (business)Sampling (signal processing)MarketingBusinessEngineeringSociologyArtificial intelligence

Abstract

fetched live from OpenAlex

This study aims to determine and analyze the influence of private university digital leadership and information system success models (system quality, information quality, service quality) on the satisfaction of e-learning users of agricultural students. This research method is a quantitative survey, and the number of research samples is 323 agricultural students who were selected by a random sampling system. The sampling technique used is simple random sampling. The analytical method used is SEM with the help of SmartPLS 3.0 software. The results show that the role of digital leadership had a significant positive effect on the three variables of the information system success model. Likewise, system quality, information quality, and service quality have a significant positive and significant effect on user satisfaction of e-learning systems. This finding can increase the exploration ability of agricultural students as users to obtain various agricultural information. This finding confirms previous studies which state that usage has a significant effect on user satisfaction. Suggestions for further research, in this study only involves a single student perspective. Future research is recommended to use the perspective of the organization/institution (e-learning system management unit), lecturers, and university employees and agricultural stakeholders.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.055
GPT teacher head0.358
Teacher spread0.303 · 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