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Effect of Information Load and Time on Observational Learning

2009· article· en· W2027935092 on OpenAlexaff
Gavin Breslin, Nicola J. Hodges, Mark Williams

Bibliographic record

VenueResearch Quarterly for Exercise and Sport · 2009
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsObservational studyGazeObservational learningPsychologyPerceptionAction (physics)KinematicsCricketPhysical medicine and rehabilitationArtificial intelligenceComputer scienceSimulationCognitive psychologyMathematicsMedicineStatisticsMathematics education

Abstract

fetched live from OpenAlex

We examined whether altering the amount of and moment when visual information is presented affected observational learning for participants practicing a bowling skill. On Day 1, four groups practiced a cricket bowling action. Three groups viewed a full-body point-light model, the model's bowling arm, or between-limb coordination of the model's left and right wrists only. Following retention tests on Day 2, all participants practiced after viewing a full-body display. Retention was again tested on Day 3. Bowling accuracy improved in all four practice groups. Kinematics of the bowling arm became more like the model for the full-body and intralimb groups only. All groups improved on measures of interlimb coordination. Visual search data indicated that participants mainly focused their gaze on the model's bowling arm. These data lead to the suggestion that viewing "end-effector" information (i.e., information pertaining to the bowling arm) is an important perceptual constraint early in observational learning. Implicit manipulations designed to increase attention to other sources of information did not facilitate the learning process.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.957
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.038
GPT teacher head0.379
Teacher spread0.341 · 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 designOther design
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

Citations27
Published2009
Admission routes1
Has abstractyes

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