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Record W4408846985 · doi:10.1080/09588221.2025.2482151

Digital literacy practices outside language classrooms: insights of adult migrants’ language education

2025· article· en· W4408846985 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer Assisted Language Learning · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsLiteracyComputer scienceLinguisticsMathematics educationPedagogySociologyPsychology

Abstract

fetched live from OpenAlex

To explore the role of digital tools in adult migrants’ literacy practices and the strategies they develop in real-life situations, we conducted filmed observations of three migrants who were engaged in digital literacy events outside the language classroom. Digital literacy events are defined as empirical and observable configurations of action, technology, text and discourse that offer insights into individuals’ digital literacy. To capture the data comprehensively, we employed a multifocal approach using a 360° camera and screen captures. This method documented three distinct events: managing routine interactions, navigating geographic and administrative tasks, and job hunting. The inductive analysis revealed key elements, including interface navigation, transmediation, the extensive use of the Google suite in digital practices, and the crucial role of machine translation in migrants’ literacy development. In conclusion, the findings highlight the importance of acknowledging and fostering migrants’ existing digital practice repertoires while establishing links between these practices and structured learning opportunities.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.276
Teacher spread0.267 · 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