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Record W2778776314 · doi:10.51657/ric.v4i1.41001

“Chess for overall development” software in the frame of Reflection and Activity

2017· article· en· W2778776314 on OpenAlexvenueno aff
Aleksei A. Chernysh

Bibliographic record

VenueRevue internationale du CRIRES innover dans la tradition de Vygotsky · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPsycheComputer scienceAction (physics)SoftwarePsychologyMathematics educationCognitive science

Abstract

fetched live from OpenAlex

The paper discusses “Chess for overall development” project, which is based on Reflection and Activity Approach in helping overcome learning diÿculties. The project has been running for over 12 years now, putting theory of the approach into practice in several cities throughout the Russian Federation. One of the key elements in this project is developing the ability to think in mind using chess problems and sequential progress through material where solving of problems becoming more idea-based and less action-based using the notion of the stage-by-stage formation of mental actions. Unlike other methods teachers use to teach chess, the Chess for Overall Development project views chess primarily as a psychological instrument for helping develop the ability to think in mind. The basis for the ideas of the project is L. S. Vygotsky’s cultural-historical psychology. Vygotsky’s notions on the development of the human psyche are implemented and partially expanded as part of the project. In recent years the software “Chess for overall development” was made designed with full compatibility with the principles of the reflection and activity approach and implementing the notion of the ability to think in mind development and sequential transition from material to ideal plane of mental actions. We present detailed description of the software features as well as its approbation results collected in schools, universities and hospitals.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.070
GPT teacher head0.358
Teacher spread0.288 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

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