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Record W97642637 · doi:10.5206/eei.v24i2.7711

WWW.com: A Brief Intervention to Bolster a 5th Grader's Regrouping Skills in Math

2014· article· en· W97642637 on OpenAlexaffvenue
Matthew Waugh, Gina L. Harrison

Bibliographic record

VenueExceptionality Education International · 2014
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsSubtractionIntervention (counseling)MnemonicFluencyResponse to interventionSession (web analytics)MetacognitionMathematics educationPsychologyCurriculumCognitionMedical educationComputer scienceMathematicsPedagogyMedicineSpecial educationCognitive psychologyArithmetic

Abstract

fetched live from OpenAlex

This study examined the efficacy of a brief math intervention using cognitive behaviour instruction (CBI) supplemented by a mnemonic cue system for a 5th grade student with math computation and fluency difficulties. Regrouping operations in addition and subtraction were the targeted skills. Curriculum-based measurements were conducted at the end of each session to monitor the student’s response to the intervention. Pre- and post-assessment with alternate forms of Key Math-Revised were also conducted. As compared to baseline performance, there was a 48% improvement in computing regrouping problems. There was a greater effect on accuracy in computing addition than on subtraction problems requiring regrouping, based on the post-intervention assessment. The results are discussed in relation to previous intervention research incorporating CBI approaches aimed at promoting students’ cognitive, metacognitive, and self-regulatory skills for proficient computation.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.365
Teacher spread0.335 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations3
Published2014
Admission routes2
Has abstractyes

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