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Record W3089855673 · doi:10.1177/109258721201700104

The Effect of Tour Type on Visitors’ Perceived Cognitive Load and Learning

2012· article· en· W3089855673 on OpenAlexaffabout
Christine M. Van Winkle

Bibliographic record

VenueJournal of Interpretation Research · 2012
Typearticle
Languageen
FieldPsychology
TopicVisual and Cognitive Learning Processes
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsVisitor patternCognitive loadPsychologyAffect (linguistics)CognitionTransfer of learningTourismApplied psychologyCognitive psychologyComputer scienceGeographyDevelopmental psychologyCommunication

Abstract

fetched live from OpenAlex

This paper discusses the effect of audio versus guided tours on visitors’ cognitive load at a national historic site. As more sites employ digital media devices to engage visitors, a better understanding of the impact of these devices on visitors’ experiences at sites is needed. This research took place during the summer of 2008 at a Canadian national historic site and examined how tour type (audio or guided) impacted the visitor's learning process (cognitive load) and outcomes (learning transfer). The contextual model of learning, cognitive load theory, and learning transfer research were used as foundations to examine free-choice learning and the visitor's experience. The results show that the type of tour taken does affect the learning experience. Specifically, audio tour participants indicated greater cognitive load than guided tour participants. Participants’ ability to transfer learning was not affected by tour type. Theoretical and practical implications are discussed and directions for future research are identified.

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)0.001
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.046
GPT teacher head0.464
Teacher spread0.418 · 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 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

Citations7
Published2012
Admission routes2
Has abstractyes

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