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Record W2104952684 · doi:10.5539/cis.v6n1p15

Conceptual and Methodical Procedures of Psychomotor Learning

2012· article· en· W2104952684 on OpenAlexvenueno aff
Jarmila Honzíková, Jan Janovec

Bibliographic record

VenueComputer and Information Science · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsPsychomotor learningCreativityAgency (philosophy)Mathematics educationFormal educationPsychologyPedagogyComputer scienceSociologyCognition

Abstract

fetched live from OpenAlex

Author article stakes part in several projects focused just on development of technical creativity and imagination in students of faculties of education, teachers and primary school pupils. The article deals with the teacher’s approach to the teaching of psychomotor skills, while specifically seeking to answer whether among teachers of technical education and practical activities, there are groups with significantly different approaches to teaching in terms of chosen objectives, methods and forms of teaching. This claim was first examined using a questionnaire survey focused on the objectives of education and further using Q-methodology concerning methods and forms. These examinations were performed as part of the “Nonverbal Creativity in Technical Education” project - GACR 406/07/0109 and as part of the “The Development of School-age Pupils’ Competencies in the Area of Psychomotor Skills” project by the Internal agency of the Faculty of Education at Jan Evangelista Purkyne University.

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)0.036
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.003
Science and technology studies0.0030.028
Scholarly communication0.0070.005
Open science0.0030.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.063
GPT teacher head0.320
Teacher spread0.257 · 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 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
Published2012
Admission routes1
Has abstractyes

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