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Record W4416366205 · doi:10.22329/jtl.v19i5.8666

The Role of Engaged Scholarly Relationships in Enhancing the Pedagogy of Reading Proficiency

2025· article· en· W4416366205 on OpenAlexvenueno aff
Debbie A. Sanders, Shirley S. Mukhari

Bibliographic record

VenueJournal of Teaching and Learning · 2025
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipReading (process)Scholarship of Teaching and LearningQualitative researchTeaching method

Abstract

fetched live from OpenAlex

In recent years there has been a growing trend of academics and teachers collaborating in complementary associations. This is often achieved through engaged scholarship projects such as those which aim to enhance learners’ reading skills. A comprehensive review of the literature underscores the importance of pedagogical support in cultivating effective reading skills, with numerous engaged scholarship relationships focusing on reading-related support, in an effort to meet this need. This study investigated the essential role of engaged scholarly relationships in advancing pedagogical approaches to the teaching of reading. A qualitative participatory-action research approach was adopted, which enabled the researchers to interview thirteen (13) primary school language teachers who were purposively selected for their experience and expertise in this field. Through interviews, the researchers investigated the pivotal role of engaged scholarship projects in supporting the teaching and learning of reading. The findings are relevant in that they bear testimony to the success of implementing engaged scholarship projects for improving the teaching and learning of reading. The researchers conclude that engaged scholarship projects enhance the teaching and learning of such skills, provided that certain challenges are addressed, and strategies are implemented to support their progress.

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)0.021
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.007
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 integrity0.0000.005
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 head0.021
GPT teacher head0.336
Teacher spread0.315 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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