Competencies of a Museum Guide as Predictors of Visitors’ Learning Outcomes: A Case from Canada
Bibliographic record
Abstract
The competencies and techniques used by employees, especially those who act as guides, are one of the most important vehicles for the transference of visitors’ cultural understanding and memorable experiences. The aim of the study was to identify which guides’ competencies can enhance generic learning outcomes of museum visitors. The data were collected from 594 people who visited art and history museums in Toronto (Canada). The results showed that learning outcomes depend on three groups of guide's competencies: handling the group within the museum environment, communication skills, and knowledge and pedagogy. Also, the findings revealed that the guide's competencies that encourage interaction and active participation of visitors were common predictors for all generic learning outcomes. The research findings can serve as guidelines for museums when recruiting or training guides. Also, it can direct museums how to develop their strategy if they want to improve visitors’ experiences when engaging with museums’ exhibitions, art, and objects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".