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Record W4387423029 · doi:10.5267/j.ijdns.2023.10.100

Examining the impact of YouTube vlogging on communication skills in teens with speech and language disorders

2023· article· en· W4387423029 on OpenAlexvenueno aff
Ali Alelaimat, Haitham Baibers, Mohamad Ahmad Saleem Khasawneh

Bibliographic record

VenueInternational Journal of Data and Network Science · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
FundersKing Khalid University
KeywordsPsychologyCompetence (human resources)FacilitationIntervention (counseling)Communication skillsCommunicative competenceDevelopmental psychologyApplied psychologyMedical educationPedagogySocial psychologyMedicine

Abstract

fetched live from OpenAlex

The major goal of this research is to examine how vlogging on YouTube affects the communication skills of Jordan teenagers with language and speech disorders. Fifty people, ranging in age from 13 to 18, participated in an eight-week vlogging intervention program designed to improve their communication skills. The results of the pre- and post-tests showed a statistically significant improvement in communicative competence, with the mean difference between the two measures being 10.5. Vlogging has a significant effect as an intervention because of its remarkable ability to actively engage participants in the creation of relevant content, the facilitation of authentic real-life communication experiences, the encouragement of creative and self-expressive expression, and the provision of individualized therapeutic approaches. Adolescents with speech and language disabilities have unique obstacles in communicating, and this study gives insight on the possible use of novel tools, such as vlogging, to address these issues.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.032
GPT teacher head0.362
Teacher spread0.330 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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