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Record W1973654007 · doi:10.5539/hes.v2n2p125

Factors Influencing the Use of Learning Management System in Saudi Arabian Higher Education: A Theoretical Framework

2012· article· en· W1973654007 on OpenAlex
Mohammed J. Asiri, Rosnaini Mahmud, Kamariah Abu Bakar, Ahmad Fauzi Bin Mohd Ayub

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

VenueHigher Education Studies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsLearning ManagementCompetence (human resources)Higher educationExternal variableVariablesMathematics educationPsychologyMedical educationKnowledge managementComputer sciencePolitical scienceMedicine

Abstract

fetched live from OpenAlex

The purpose of this paper is to present the theoretical framework underlying a research on factors that influence utilization of the Jusur Learning Management System (Jusur LMS) in Saudi Arabian public universities. Development of the theoretical framework was done based on library research approach. Initially, the existing literature relevant to the subject was reviewed to determine the important variables related to factors influencing the use of LMS in higher education. The paper provides insights of the external and internal variables or factors that influence the use of Jusur LMS for teaching and learning purposes. The internal variables consist of the attitude of Saudi Arabian faculty members towards using LMS, their beliefs towards e-learning, and their competence level in using LMS. The external variables consist of barriers faced by the faculty members and demographic factors. This study was limited to the use of Jusur LMS, one of the e-learning management tools used in Saudi Arabian universities, and surveyed faculty members of Saudi Arabian public universities. This theoretical framework can be adapted to suit the requirements of other similar studies related to planning and implementation of various technology programs in higher education.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.086
GPT teacher head0.387
Teacher spread0.301 · 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