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Record W2159140698 · doi:10.3916/c43-2014-12

Educating teens about the risks on social network sites. An intervention study in Secondary Education

2014· article· en· W2159140698 on OpenAlexaff
Ellen Vanderhoven, Tammy Schellens, Martín Valcke

Bibliographic record

VenueComunicar · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsImpact
Fundersnot available
KeywordsPopularityIntervention (counseling)Set (abstract data type)PsychologyPoint (geometry)Social psychologyComputer science

Abstract

fetched live from OpenAlex

The growing popularity of social network sites (SNS) is causing concerns about privacy and security, especially with teenagers since they show various forms of unsafe behavior on SNS. Media literacy emerges as a priority, and researchers, teachers, parents and teenagers all point towards the responsibility of the school to educate teens about risks on SNS and to teach youngsters how to use SNS safely. However, existing educational materials are not theoretically grounded, do not tackle all the specific risks that teens might encounter on SNS and lack rigorous outcome evaluations. Additionally, general media education research indicates that although changes in knowledge are often obtained, changes in attitudes and behavior are much more difficult to achieve. Therefore, new educational packages were developed –taking into account instructional guidelines- and a quasi-experimental intervention study was set up to find out whether these materials are effective in changing the awareness, attitudes or the behavior of teenagers on SNS. It was found that all three courses obtained their goal in raising the awareness about the risks tackled in this course. However, no impact was found on attitudes towards the risks, and only a limited impact was found on teenagers’ behavior concerning these risks. Implications are discussed. La creciente popularidad de las redes sociales (RS) está causando preocupación por la privacidad y la seguridad de los usuarios, particularmente de los adolescentes que muestran diversas formas de conductas de riesgo en las redes sociales. En este contexto, la alfabetización mediática emerge como una prioridad e investigadores, profesores, padres y adolescentes enfatizan la responsabilidad de la escuela de enseñar a los adolescentes acerca de los riesgos en RS y cómo utilizarlas sin peligro. Sin embargo, los materiales educativos existentes no están teóricamente fundamentados, no abordan todos los riesgos específicos que los adolescentes pueden encontrar en las redes y carecen de evaluaciones de resultados. Además, estudios acerca de la educación mediática indican que, mientras los cambios a nivel de conocimientos suelen obtenerse fácilmente cambios en las actitudes y el comportamiento son mucho más difíciles de lograr. Por este motivo, nuevos paquetes educativos han sido desarrollados teniendo en cuenta directrices educativas. Posteriormente se llevó a cabo un estudio de intervención cuasi-experimental a fin de verificar si estos materiales son eficaces para cambiar el conocimiento, las actitudes y el comportamiento de los adolescentes en las redes sociales. El estudio constató que los cursos obtienen su objetivo en la sensibilización de los riesgos tratados. Sin embargo, no se observó ningún impacto en las actitudes hacia el riesgo, y el impacto en el comportamiento de los adolescentes en relación con estos riesgos fue limitado. Las implicaciones de este estudio son discutidas.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.074
GPT teacher head0.395
Teacher spread0.321 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations62
Published2014
Admission routes1
Has abstractyes

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