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Record W3015313872 · doi:10.1177/1477971420913912

Using a multiliteracies approach to foster critical and creative pedagogies for adult learners

2020· article· en· W3015313872 on OpenAlexafffund
Susan M. Holloway, Patricia A. Gouthro

Bibliographic record

VenueJournal of Adult and Continuing Education · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsMount Saint Vincent UniversityUniversity of Windsor
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLifelong learningSociologyPedagogyAdult educationLiteracyDiversity (politics)

Abstract

fetched live from OpenAlex

Drawing upon a pilot study and a Social Sciences and Humanities Research Council (SSHRC) Insight research study to explore how a multiliteracies framework may inform more critical and creative pedagogical approaches for adolescents and adults, this article begins with a brief overview of the literature on multiliteracies and then overviews the methodology used in the two research studies. Although multiliteracies has not been used frequently as a theoretical framework to inform work in adult learning contexts, this article argues that there are many benefits to this approach for adult educators to consider, particularly given the increasing need to attend to learning issues pertaining to globalization, diversity, and the impact of new technologies. Data from the interviews are combined with an analysis of the literature to explore the benefits offered by a multiliteracies approach by considering four main areas: lifelong learning and multimodalities; opportunities for engagement for English as Additional Language learners; new digital technologies and multiliteracies; and multiliteracies’ emphasis on social justice. The article concludes with a consideration of the potential for multiliteracies to inform educators working in a range of adult learning contexts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.333

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)0.0000.000

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 head0.069
GPT teacher head0.338
Teacher spread0.269 · 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 designQualitative
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

Citations35
Published2020
Admission routes2
Has abstractyes

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