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Record W2910467823 · doi:10.5430/jnep.v9n5p64

Faculty members’ perceptions towards utilizing blackboard in teaching system at Hafr Al-Batin University, Saudi Arabia

2019· article· en· W2910467823 on OpenAlexvenueno aff
Lobna Khamis Ibrahim, Faten Mane Aldhafeeri, Malik Alqdah

Bibliographic record

VenueJournal of Nursing Education and Practice · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsBlackboard (design pattern)PerceptionMedical educationPsychologyProcess (computing)University facultyBlackboard systemComputer scienceMedicine

Abstract

fetched live from OpenAlex

Background and objective: The faculty members’ perceptions regarding Blackboard as the pedagogical management tool plays a vital role in learning and teaching process. Aim: To survey the perceptions of faculty members towards utilizing Blackboard in the teaching system at Hafr Al-Batin University.Methods: Design: Quantitative descriptive design was utilized depending on online surveys. Setting: The study was conducted in all Colleges of Hafr Al-Batin University. Participants: 174 faculty members from different colleges at the University of Hafr Al-Batin. Tools: Questionnaire consisted of two parts; the first includes the faculty demographic information and the second describes faculty perception in four sections; usefulness, enjoyment, satisfaction, and challenges.Results: The study demonstrated that perceived “usefulness” and “enjoyment” were the most highly mean scores.Conclusions: The faculty members have a positive attitude towards the implementation of the Blackboard system. Recommendations: A great need for training of both faculty members and students in the Blackboard system regularly.

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)0.002
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 score0.481
Threshold uncertainty score0.472

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 science0.0000.000
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 head0.070
GPT teacher head0.429
Teacher spread0.359 · 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 designQualitative
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

Citations23
Published2019
Admission routes1
Has abstractyes

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