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Record W3124173859 · doi:10.1080/10494820.2020.1870503

Technology-enhanced multiliteracies teaching towards a culturally responsive curriculum: a multiliteracies approach to ECE

2021· article· en· W3124173859 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInteractive Learning Environments · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of CanadaWestern University
KeywordsCurriculumLiteracyPedagogyTechnology integrationTeaching methodSociologyEarly childhood educationMathematics educationPsychology

Abstract

fetched live from OpenAlex

Much attention has been paid to the introduction of a culturally responsive curriculum in early childhood education in our increasingly globalized society to support young children of diverse cultural and linguistic (CLD) backgrounds. With the rise of twenty-first century concepts of what literacy means in the digital age, traditional literacy practices that have relied primarily on print-based texts have been also challenged. To response to these imperatives, this qualitative case study presents a lived story of a grade one teacher who implemented multiliteracies pedagogy in her classroom for young culturally and linguistically diverse (CLD) children. Our findings show that applying multiliteracies pedagogy not only motivated the teacher to value her CLD students’ diverse semiotic resources as available designs but also transformed the way the teacher integrated technology in literacy teaching. We end this paper with the discussion of implications of integration of multiliteracies pedagogy to technology-enhanced literacy teaching and learning.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.267
Teacher spread0.253 · 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