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Record W4298625155 · doi:10.1177/87568705221110464

Narrative Writing Progress of Rural Elementary Students in Mixed-Ability Online Pairings

2022· article· en· W4298625155 on OpenAlexaff
Sung Hee Lee, Malayna Bernstein

Bibliographic record

VenueRural Special Education Quarterly · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsUniversity of Toronto
FundersWest Virginia University
KeywordsNarrativeMathematics educationQuality (philosophy)Qualitative researchPsychologyPedagogyQualitative propertyQualitative analysisControl (management)SociologyComputer scienceLiteratureArt

Abstract

fetched live from OpenAlex

This article reports on a qualitative secondary data analysis of a study of upper elementary students’ narrative writing progress in U.S. rural schools. It compares students working online in pairs with those working alone. We explain why the intervention had some positive effects for struggling writers but few effects for skilled writers. The qualitative analysis of student online writing products, student peer feedback, and teacher interviews indicated that struggling writers in the experimental group wrote more ambitious but less coherent stories than struggling writers in the control group, and that skilled writers in the experimental group received poor-quality feedback and were less inclined to revise than skilled writers in the control group. We provide suggestions for writing instruction and technology support for skilled and struggling writers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.353
Teacher spread0.339 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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