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Record W3082927348 · doi:10.5430/jct.v9n3p141

Curriculum Development Based on Online and Face-to-Face Learning in a Saudi Arabian University

2020· article· en· W3082927348 on OpenAlexvenueno aff
May Alashwal

Bibliographic record

VenueJournal of Curriculum and Teaching · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumFace-to-faceFlexibility (engineering)Medical educationPsychologyClass (philosophy)Mathematics educationQualitative researchPedagogyComputer scienceSociologyMedicine

Abstract

fetched live from OpenAlex

This research examined curriculum development in an academic program with respect to graduate education-level methods of teaching. Numerous studies have suggested that educational curricula should be redeveloped based on Web 2.0 technologies. The purpose of this research is to analyze student perspectives regarding curriculum development based on their online and face-to-face learning experiences in a Saudi Arabian university. This research surveyed 95 graduate students in a Saudi university to examine their perceptions of curriculum development based on online and face-to-face learning. The research objective was to determine students’ opinions regarding the performance and challenges of the developed curriculum. The research design in this study was based on a qualitative analysis study of an online survey. The survey data were analyzed and showed a consensus in favor of online learning courses. The results show that online students highlighted the flexibility, accessibility, and balance of time management in their personal and professional life during the course yet the face-to-face students emphasized that their main reason for enrolling in face-to-face classes involved having better class interaction with peers and faculties.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.016
GPT teacher head0.280
Teacher spread0.264 · 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

Citations9
Published2020
Admission routes1
Has abstractyes

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