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Record W3191041299

Exploring E-Learning Delivery in Saudi Arabian Universities.

2020· article· en· W3191041299 on OpenAlexvenueno aff
Eman Walabe, Rocci Luppicini

Bibliographic record

VenueInternational journal of e-learning & distance education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationPsychology
DOInot available

Abstract

fetched live from OpenAlex

Abstract: This qualitative research study explored E-Learning delivery in Saudi Arabian Universities from a holistic perspective to advance knowledge on the evolution of Saudi Arabia’s distance education system. Data collection consisted of 28 in-depth, one-on-one interviews with instructors and course designers to capture missing insider perspectives and was supplemented by a thematic analysis of core supporting documents related to the universities’ strategies for delivering online learning. Three core thematic areas were isolated and analyzed: (1) Distance education growing pains, (2) Learning theory integration challenges, and (3) Pedagogical and technical alignment. Stafford Beer’s Viable Systems Model (VSM) provided an interpretive lens to explain how Saudi Arabia’s distance education system remained viable while passing through periods of significant change. A blended learning model is proposed to address the complex interplay of factors influencing E-learning delivery within Saudi Arabia’s distance education system. Keywords: distance education, online learning, E-learning, blended learning, pedagogical and technical support Résumé: Cette étude fondée sur une recherche qualitative a exploré l'offre d'apprentissage en ligne dans les universités saoudiennes dans une perspective holistique afin de faire progresser les connaissances concernant l'évolution du système de formation à distance en Arabie saoudite. La collecte de données a consisté en 28 entretiens individuels approfondis avec des enseignants et des concepteurs de cours afin de recueillir les points de vue manquants venant des praticiens. Elle a été complétée par une analyse thématique des principaux documents d'appui liés aux stratégies des universités en matière de prestation d'apprentissage en ligne. Trois domaines thématiques fondamentaux ont été isolés et analysés : (1) Les difficultés de croissance de l'enseignement à distance, (2) Les défis de l'intégration de la théorie de l'apprentissage, et (3) L'alignement pédagogique et technique. Le modèle de systèmes viables (VSM) de Stafford Beer a fourni une grille d'interprétation pour expliquer comment le système de formation à distance de l'Arabie saoudite est resté viable tout en traversant des périodes de changements importants. Un modèle d'apprentissage mixte est proposé pour aborder l'interaction complexe des facteurs qui influencent la prestation de l'apprentissage en ligne au sein du système de formation à distance de l'Arabie saoudite. Mots-clés: formation à distance, formation en ligne, e-learning, formation mixte, soutien pédagogique et technique

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.048
GPT teacher head0.320
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2020
Admission routes1
Has abstractno

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