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Record W24752552 · doi:10.1007/s11682-014-9296-x

Studying the effects of increased volume of on-level, self -selected reading on ninth graders' fluency, comprehension, and motivation

2008· article· en· W24752552 on OpenAlexfundno aff
Katherine Norris

Bibliographic record

VenueBrain Imaging and Behavior · 2008
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsnot available
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute of Mental HealthCanadian Institutes of Health Research
KeywordsNinthFluencyComprehensionReading comprehensionPsychologyReading (process)Reading motivationCognitive psychologyMathematics educationDevelopmental psychologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

In response to the literacy achievement gap that exists between high-poverty, high-minority school districts and their counterparts, a quasi-experimental multi-measure study was designed to increase the reading skills and attitudes of ninth grade students. The goal of this study was to increase the volume of on-level, self-selected reading with the expectations of positively impacting the students' fluency, comprehension, and motivation. Two teachers participated in the study, each teacher taught both a control and a treatment group. The treatment consisted of twenty minutes of daily increased volume of on-level, self-selected reading. The students also kept daily response logs. The results did not support the expectations. At the end of the sixteen-week study, the data showed that the treatment was not effective in increasing the fluency, comprehension, and motivation of ninth grade students. Other studies should be done that address the time factor in this study.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.278
Teacher spread0.245 · 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 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

Citations1
Published2008
Admission routes1
Has abstractyes

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