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Record W4399541650 · doi:10.34257/gjhssgvol24is4pg1

Math Modules— A Theoretical Review and Cognitive Training Programme

2024· review· en· W4399541650 on OpenAlexaff
J. P. Das

Bibliographic record

VenueGlobal Journal of Human-Social Science · 2024
Typereview
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsRoyal Society of CanadaUniversity of Alberta
Fundersnot available
KeywordsFlexibility (engineering)CognitionCognitive flexibilityConstruct (python library)Focus (optics)Zone of proximal developmentWorking memoryMathematics educationComputer scienceCognitive developmentExecutive functionsPsychologyCognitive psychologyCognitive scienceMathematicsProgramming language

Abstract

fetched live from OpenAlex

The abstract outlines the content of a review on Math Modules, a program designed to facilitate the learning of foundational math skills through cognitive training techniques that are based on theory with a special focus on planning and executive functions, encompassing cognitive flexibility, attentional control, and working memory. The guiding educational principle is drawn from Vygotsky's concept of zones of proximal development, highlighting the belief that children can accomplish tasks with assistance that they may struggle with independently. In a way, the structure of cognitive training Modules can be viewed as an attempt at construct validity. A review of historical roots of Math modules is presented at some length. The program begins with the division of training the two key components of math proficiency: computing and solving word problems. Both rely on five essential skills.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.101
GPT teacher head0.430
Teacher spread0.329 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2024
Admission routes1
Has abstractyes

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