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Table 2. Open field and structures clustering analysis position
variable results.
Table 3. Open field and structures clustering analysis experience
variable results.
carefully. The personnel survey was conducted
on the Internet using the Surveymonkey
platform system. The obtained
data tables were uploaded to the statistical
package program in Excel-file format
and necessary statistical analyses were
performed.
Seven demographic variables were
identified and analysed according to
these variables. These variables were position
(student-staff), experience (1–4
years, 4+ years), faculty (Faculties of Science,
Literature, Electrical Electronics,
Construction, Chemistry Metallurgy,
Education, Economics and Art Design),
gender (male-female) , disability status
(exist-none), disability type (orthopaedic,
vision, hearing, neurological and
other disability types), graduation (high
school, associate, university, graduate).
The questionnaire was applied to 384
students and 75 staff. Although a questionnaire
was sent to all personnel via
the Internet, only 75 of them were returned.
The questionnaire was applied
to 459 people in total; there were 23 disabled
people. Four of the participants are
in orthopaedic disabilities, seven were
visually impaired, one was hearing impaired,
one had a neurological disability,
and 10 of them are in the other disability
group.
3.1. Clustering analysis in the
context of open spaces – physical
arrangements
Questions about open areas were included
in the cluster analysis. As a result
of clustering analysis, it was determined
that three clusters had good decomposition;
the participants were divided into
three groups. In clustering analysis, the
distinction of clusters was made according
to the scores given in the questionnaire.
The answers to the survey questions
were coded as follows: 1 (Very
low), 2 (Low), 3 (Medium), 4 (More), 5
(Too much). Of the clusters formed as
a result of clustering analysis, the questions
included in the first cluster analysis
were between 1.00 and 2.50 points
(dissatisfied), 2. Cluster 2.50 and 3.50
points (moderately satisfied) consisted
of those whose responses derived a
score between 3.50 and 5.00 (satisfied).
The following cluster distribution table
shows the cluster profiles.
Clustering analysis was performed
using questions about open spaces and
structures/physical arrangements. Cluster
profiles obtained as a result of the
research were determined according
to position, experience, faculty, gender,
disability status, disability type, and
graduation variables.
When the answers given to the physical
competence questions in open spaces
were evaluated according to the po-
A model proposal for university campuses in the context of inclusive design