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Record W2282621310 · doi:10.4137/jmecd.s36646

Engagement Patterns of High and Low Academic Performers on Facebook Anatomy Pages

2016· article· en· W2282621310 on OpenAlexaff
Akram Abood Jaffar, Mohamed Ahmed Eladl

Bibliographic record

VenueJournal of Medical Education and Curricular Development · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsSaint John Regional Hospital
Fundersnot available
KeywordsConsistency (knowledge bases)Context (archaeology)PreferenceCyberpsychologyPsychologySocial mediaElement (criminal law)World Wide WebComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Only a few studies have investigated how students use and respond to social networks in the educational context as opposed to social use. In this study, the engagement of medical students on anatomy Facebook pages was evaluated in view of their academic performance. High performers contributed to most of the engagements. They also had a particular preference for higher levels of engagement. Although the students were deeply involved in the educational element of the pages, they continued to appreciate the inherent social element. The profound engagement of the high performers indicated a consistency between Facebook use in the educational context and better student performance. At the same time, the deeper engagement of high performers refutes the opinion that Facebook use is a distractor. Instead, it supports the notion that Facebook could be a suitable platform to engage students in an educational context.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.443

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 studies0.0000.000
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 head0.017
GPT teacher head0.340
Teacher spread0.323 · 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 designOther design
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

Citations25
Published2016
Admission routes1
Has abstractyes

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