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Record W3157964807 · doi:10.1177/00169862211009856

Gifted Adolescent Readers’ Perceptions of How Teachers Should (or Should Not) Listen During Dialogic Discourse

2021· article· en· W3157964807 on OpenAlexaff
Cindy M. Gilson, Adrienne E. Sauder

Bibliographic record

VenueGifted Child Quarterly · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsThe King's UniversityWestern University
Fundersnot available
KeywordsActive listeningPsychologyDialogicFeelingPedagogyPerceptionMathematics educationPhenomenonSocial connectednessSocial psychology

Abstract

fetched live from OpenAlex

Effective listening is essential when teachers facilitate instructional classroom discussions. While the intersection between teacher listening and how students engage in discussions has received a wealth of research attention from other fields, this important phenomenon continues to be underresearched in the gifted and literacy education fields. To deepen our understanding of the phenomenon of teacher listening from students’ perspectives, we conducted an in-depth focus group study with middle school gifted students from five schools in a Southeastern state in the United States. Findings of our data analysis revealed four key interrelated themes: (a) teachers as active listeners, (b) teacher character traits, (c) student feelings and behaviors, and (d) listening as a pedagogical tool. Of significance, this study revealed students’ perspectives of how gifted education teachers should listen and that their listening influences students’ sense of connectedness and motivation for learning. Implications for professional learning and recommendations for future research are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
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 head0.085
GPT teacher head0.353
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2021
Admission routes1
Has abstractyes

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