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Record W3148428639 · doi:10.22215/etd/2020-14097

Wayfinding Experience of Persons with Autism Spectrum Disorder within a Museum Context

2020· dissertation· en· W3148428639 on OpenAlexaff
Amina Balaa

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsCarleton University
Fundersnot available
KeywordsDiversity (politics)Context (archaeology)AutismAutism spectrum disorderUniversal designPsychologyObservational studyAutistic spectrum disorderSpace (punctuation)Applied psychologyDevelopmental psychologyGeographyComputer scienceMedicineWorld Wide WebSociology

Abstract

fetched live from OpenAlex

Designing for disabilities may present great challenges but the potential rewards that result may benefit a wider population. This study investigates whether the wayfinding available within a specific museum setting accommodates the needs of persons with Autism Spectrum Disorder (ASD). Identifying the 'wayfinding' needs and/or preferences of the group that was studied in this research is an important first step in developing a knowledge base to further this area of research and perhaps assist designers to facilitate more inclusive wayfinding experience within museum settings. To obtain some insight on the personal experience of people with ASD, three qualitative methods were used: an anonymous survey to gather basic insight about museum visit experience showing that most respondents do visit museums and the majority do not use any assistive devices during their visits; an observational study revealed how participants navigated this particular environment and that visual memory played a large role when traveling through the museum; and finally, a workshop revealed environmental preferences and aversions highlighting the differences between individuals, and how an understanding of diversity is an important consideration in design. The findings of this case study support the notion that it is challenging to design a space to support a diversity of needs and preferences, but that improving our knowledge of diversity as well as commonalities can better support the movement and aspiration toward universal design.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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 designQualitative
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

Citations2
Published2020
Admission routes1
Has abstractyes

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