Objective: A descriptive design, using the methodological approach, is carried throughout the present
study from April 1st 2012 to May 20th 2013 to construct the school physical environment standardized
features tool.
Methodology: An instrument of (141) item is constructed for the purpose of the study. A purposive
sample of (44) school; (22) public and (22) private ones is selected. Content Validity of the instrument is
determined through the use of panel of (11) expert who are specialists in Community Health Nursing and
Community Medicine. Internal consistency reliability, using the split-half technique, is employed through
the computation of Cronbach alpha correlation coefficient of (0.93) for internal scale. Data were collected
through the use of the instrument and the schools' visits as means of data collection. Data are analyzed
through the application of the inferential statistical data analysis procedure of simple Pearson’s
correlation coefficient and factor analysis (principle component) method.
Results: Findings of the study reveal that the features are presented, post their rearrangement, under five
factors that include school services, emergency and school sanitation, food and protection services, safe
school environment, and school environment. So, the new tool can be structured, tested and used as
guide for new investigations. Such presentation of factors reflects the actual model by which the school's
physical environment features can be considered as essential elements for future evaluation through the
utilization of the constructed tool.
Recommendations: The study recommends that the new discovered tool can be used as measure for
future work, and further studies can be carried out on large sample size and nation-wide base.
Abstract
The study aims to know the degree of secondary school managers' practice of servant leadership in Gaza from their teachers’ perspective. It further aims to examine whether there are any statistically significant differences at (α 0.05≥) between the means of the study sample’s members attributed to variables such as (gender, educational qualification, and years of experience). To achieve the objectives of the study, the study adopted the descriptive survey method, using a questionnaire consisting of (30) items distributed to four domains: (workers service, ethical dealing, motivation & influence, and building an organized, integrated society). Then, the questionnaire was distributed to t
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The decision maker needs to understand the strategic environment to be addressed through different means and methods. It is obvious that there is a difference between the three strategic environments (conflict environment, peace environment, post- peace environment) in terms of inputs and strategies to deal with each one of them. There is an urgent need to understand each pattern separately, analyze its inputs, and identify the factors and variables that affect the continuity of this situation (conflict, peace, post-peace). It is not appropriate to identify treatment without diagnosis of the condition, so it is very important to understand the type of strategic environment to be dealt with it.
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To achieve this, the researcher adopted on an experimental design is located in women with partial seizure experimental designs field in order to achieve the goals of the research, has sample consisted of two divisions seminars Mentzmtin in junior high school Diyala for Boys, and divided the sample of (60) called on the two groups, the first pilot of ( 30) student, and the other officer and number (30), student, and studied researchers experimental group theory TRIZ, while he studied the officer in the traditional manner, the researcher conducted a pa
Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of
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