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Record W2046191774 · doi:10.1037/0022-0663.98.1.44

An effective method for building meaning vocabulary in primary grades.

2006· article· en· W2046191774 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Educational Psychology · 2006
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyVocabularyMeaning (existential)Vocabulary developmentMathematics educationLinguisticsPrimary educationTeaching methodPsychotherapist

Abstract

fetched live from OpenAlex

Teaching vocabulary to primary grade children is essential. Previous studies of teaching vocabulary (word meanings) using story books in the primary grades reported gains of 20%-25% of word meanings taught. The present studies concern possible influences on word meaning acquisition during instruction (Study 1) and increasing the percentage and number of word meanings acquired (Study 2). Both studies were conducted in a working-class school with approximately 50% English-language learners. The regular classroom teachers worked with their whole classes in these studies. In Study 1, average gains of 12% of word meanings were obtained using repeated reading. Adding word explanations added a 10% gain for a total gain of 22%. Pretesting had no effect on gains. In Study 2, results showed learning of 41% of word meanings taught. At this rate of learning word meanings taught, it would be possible for children to learn 400 word meanings a year if 1,000 word meanings were taught. The feasibility of teaching vocabulary to primary grade children is 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.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.422
Teacher spread0.404 · 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