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Record W2049138741 · doi:10.1504/ijsmile.2013.057464

Using Facebook to explore adolescent identities

2013· article· en· W2049138741 on OpenAlexaff
Janette Hughes, Laura Morrison

Bibliographic record

VenueInternational Journal of Social Media and Interactive Learning Environments · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsSocial mediaIdentity (music)Digital literacyDeconstruction (building)Qualitative researchLiteracyPsychologyCyberpsychologyMobile devicePedagogyMedia literacySociologyMathematics educationComputer scienceWorld Wide WebEngineeringSocial science

Abstract

fetched live from OpenAlex

This study examines the construction, deconstruction and reconstruction of adolescent identities through an exploration of their social practices within a digital landscape using mobile devices and Facebook for learning in the classroom and in their lives. Using a mixed methods research approach of qualitative case study analysis and quantitative surveying, the research investigates the relationship between a multiliteracies pedagogy and the development of adolescent digital literacies and identity. More specifically, it answers the following research questions: 1) How are adolescents’ identities shaped and performed, as they use new media tools and social media in the classroom? 2) How does the use of mobile devices and Facebook in the classroom potentially transform teaching and learning literacy practices? The researchers found that using social networking sites such as Facebook can motivate students to engage with the content and explore how they perform their identities to others, but privacy issues are still a concern to some students.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.351
Teacher spread0.301 · 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.

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

Citations6
Published2013
Admission routes1
Has abstractyes

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