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Record W4414876282 · doi:10.18806/tesl.v42i2/1430

Exploring Language Teachers’ Perspectives on Hybrid Delivery with Adult Literacy Learners

2025· article· en· W4414876282 on OpenAlexvenueaboutno aff
Marianne Barker, Paula Jireh Sampang, Geneca Henry, Fatemeh Kazemi, Kateřina Palová, Odessa González Benson

Bibliographic record

VenueTESL Canada Journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyInformation literacyDigital literacyParticipatory action researchCitizen journalismAdult literacyTheme (computing)

Abstract

fetched live from OpenAlex

Canada’s federally-funded English language programming has historically overlooked the holistic learning needs of adult literacy learners, who have limited prior education and low English proficiency. Literacy learners’ educational and language needs are further compounded by limited digital literacy, as they face barriers accessing and navigating digital interfaces, which are increasingly integrated into educational spaces. The challenge falls on literacy instructors to address these challenges. Yet instructors lack sufficient support, training, and resources to do so effectively. This study addresses this gap using a participatory approach to develop a teacher toolkit to support literacy educators in integrating technology and transitioning to hybrid modes of instruction. The research team collaborated with an advisory group (n=7) made up of literacy educators to co-design a teacher toolkit. The toolkit was pilot-tested by literacy educators (n=24) on a local and national scale and was iteratively revised according to their feedback. Three themes emerged that shaped the toolkit: adapting a multifaceted, dynamic, flexible role as an instructor, addressing the diverse needs of literacy learners, and adapting to digital pedagogies. We explain how the toolkit addresses each theme and reflect on the methodological implications of using a participatory approach for toolkit development. Les programmes d’apprentissage de l’anglais financés par le gouvernement fédéral canadien ont historiquement négligé les besoins holistiques d’apprentissage des apprenants adultes en apprentissage de la littératie et qui ont un niveau d’éducation préalable limité et une faible maîtrise de l’anglais. Les besoins éducatifs et linguistiques des apprenants en apprentissage de la littératie sont davantage complexifiés par une littératie numérique limitée. En effet, ces apprenants se heurtent à des obstacles pour accéder et naviguer les interfaces numériques, qui sont de plus en plus intégrées dans les espaces éducatifs. C’est aux enseignants en alphabétisation qu’il incombe de relever ces défis. Or, ces derniers ne disposent pas d’un soutien, d’une formation et de ressources suffisants pour y parvenir efficacement. Cette étude comble cette lacune en utilisant une approche participative pour développer une boîte à outils afin d’aider les enseignants en alphabétisation à intégrer la technologie et à passer à des modes d’enseignement hybrides. L’équipe de recherche a collaboré avec un groupe consultatif (n = 7) d’enseignants en alphabétisation pour concevoir conjointement une boîte à outils pour les enseignants. La boîte à outils a été testée par des enseignants en alphabétisation (n = 24) à l’échelle locale et nationale et a été révisée de manière itérative en fonction de leurs commentaires. Trois thèmes ont émergé et ont façonné la boîte à outils : s’adapter à un rôle multidimensionnel, dynamique et flexible en tant qu’enseignant, répondre aux besoins variés des apprenants en alphabétisation et s’adapter aux pédagogies numériques. Nous expliquons comment la boîte à outils aborde chaque thème et réfléchissons aux implications méthodologiques de l’utilisation d’une approche participative pour le développement de boîtes à outils.

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)0.000
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 score0.249
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.283
Teacher spread0.264 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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