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Record W3071594838 · doi:10.5539/jel.v9n5p59

Availability of ISTE Digital Citizenship Standards Among Middle and High School Students and Its Relation to Internet Self-Efficacy

2020· article· en· W3071594838 on OpenAlexvenueno aff
Fouad F. Aldosari, Mohammad A. Al-Daihan, Riyadh Alhassan

Bibliographic record

VenueJournal of Education and Learning · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipThe InternetIdentity (music)Intellectual propertyPsychologySample (material)SociologyMathematics educationPolitical scienceComputer scienceWorld Wide WebLawPolitics

Abstract

fetched live from OpenAlex

The purpose of this study was to gauge the level of availability of ISTE Digital Citizenship standards among middle and high school students in Riyadh, Saudi Arabia. The research employed a quantitative survey approach to measuring the availability of elements of digital citizenship. The survey was administered to a sample of 394 students from several middle and high schools. The survey items were built based on the four domains of digital citizenship by ISTE (Digital identity, Ethical behavior, Intellectual property, and Digital privacy and security). Findings revealed that students showing a high level of availability of digital citizenship in the first and second domains, as well as showing a high level of Internet self-efficacy. Based on the findings, it was recommended to put more emphasis on promoting digital citizenship among middle and high school students, especially raising awareness about intellectual property rights, cybersecurity, online bullying, digital identity, and good interaction with others over the Internet.

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)0.003
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 score0.029
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.030
GPT teacher head0.318
Teacher spread0.288 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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