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Record W3139309421 · doi:10.3389/fpsyg.2021.637085

Contrasting Learning Psychology Theories Applied to the Teaching-Learning-Training Process of Tactics in Soccer

2021· review· en· W3139309421 on OpenAlexaff
Grégory Hallé Petiot, Rodrigo Aquino, Davi Correia da Silva, Daniel Barreira, Markus Raab

Bibliographic record

VenueFrontiers in Psychology · 2021
Typereview
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBehaviorismPsychologyProcess (computing)Learning theoryContext (archaeology)AutonomyMathematics educationComputer science

Abstract

fetched live from OpenAlex

Research in sport pedagogy and its applied recommendations are still characterized by a contrast between the different learning theories from psychology. Traditional theories and their corresponding approaches to the specific case of teaching and learning “how to play [team sports like soccer]” are subject to compatibilities and incompatibilities. We discuss how behaviorism as an approach to teaching the game shows more incompatibilities with the nature of tactical actions when compared to constructivism. As coaches strive to teach the game and make their players and team perform, we argue that teaching the game requires teaching approaches that will help develop their way to play (i.e., tactical behavior) without taking away their autonomy and adaptiveness. The teaching-learning-training process for playing the game should then be conducted to harmonize the characteristics of the contents, the context, and the individual(s) at hand. We provide two illustrated examples and portray how the recommended approaches fit key contents of the game that are observed in the tactical behavior. We finally argue that the coherent design of games provides minimal conditions to teaching approaches, and that such a design should be a priority when elaborating the learning activities along the player development process. As a conclusion, the interactionist theory is the one that best serves the teaching of the game and the development of tactical behavior. We therefore defend that its principles can help coaches tailor their own strategy to teach the game with the many tools.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.008
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.429
Teacher spread0.380 · 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 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

Citations32
Published2021
Admission routes1
Has abstractyes

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