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Record W2994377727 · doi:10.5114/hm.2020.88154

Can multimedia enhance tactical teaching-learning-training in soccer? The case of Sphero™

2019· article· en· W2994377727 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHuman Movement · 2019
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversité du Québec à MontréalUniversité Laval
Fundersnot available
KeywordsLecture hallMovement (music)Training (meteorology)MultimediaMedicineComputer scienceGeographyArt

Abstract

fetched live from OpenAlex

Purpose The study aimed to compare the players’ and coach’s individual perception of tactical competence before and after an intervention based on imagery techniques and a multimedia resource (Sphero<sup>TM</sup>). Methods Sphero<sup>TM</sup>, a teleguided miniature ball rolling in any direction, was applied to teach tactics before and during training sessions and games over a 5-week specific training program. The ball was used to represent a game ball, and cones were placed on a miniature soccer pitch to simulate the play and explain the coach’s directives. The execution and the understanding of pre-game directives were respectively evaluated by the coach and the players themselves, before and after the training program. An empirical pre-post treatment was used to compare 245 rates provided by 14 players of an under-14 amateur soccer team in Canada. Descriptive analysis was performed and the t-test or Wilcoxon test (<i>z</i>) were used for pairedcomparison (pre- vs. post-training). The statistical significance of the results was set at <i>p</i> < 0.05. Results After 5 weeks of training with the use of Sphero<sup>TM</sup>, results showed that the players appreciated their ability to play in accordance with directives, and that the coach was able to observe his directives through how they played, although the assessment scores of understanding remained the same. Conclusions A teaching setup involving Sphero<sup>TM</sup> allowed a good understanding but training was necessary to reach better assessment scores for the actual application of the directives.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score0.999

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)0.0020.000

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 head0.016
GPT teacher head0.325
Teacher spread0.309 · 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