The research aims at:
1 - Detection of the degree of social values (truthfulness, honesty, cooperation) of the
primary first class students who compose members of the research sample in general.
2 - Are there significant differences at the level (0,05%) between the average degree of
members of the research sample in the values (truthfulness, honesty, cooperation) among
students enrolled and not enrolled in kindergarten and in general.
3 - Are there significant differences at the level (0,05%) between the mean scores of
individuals in the sample values (truthfulness, honesty, cooperation) in the light of two
variables: A - Gender (male / female), b - enrolled and not enrolled in kindergarten.
Having in mind that the researchers followed the descriptive approach in the
analysis of their results which they reached through the search tool, which was subject to
the procedures of the construction methodology accepted by such researches.
The research shows the following results:
The average degrees of members of the research sample is higher than the average
premise.
The results of this research also indicate that there are significant differences
between enrolled and not enrolled students in the values of truthfulness and cooperation in
favour of students enrolled in kindergarten. These results don’t indicate the existence of
significant differences between enrolled and not enrolled in the value of honesty.
With regard to the third objective, the research results indicated that there were
significant differences between males and females in the value of truthfulness in favor of
females enrolled.
With regard to the value of honesty, in the light of variables (Gender, enrollment
and not enrollment in the kindergarten) it was in favor of females.
With regard to whether or not to attend kindergarten, the results show no
significant differences between enrolled and not enrolled in kindergarten.
With regard to the value of cooperation, the results of research show that there are no
significant differences between the sexes.
With regard to enrollment and non-enrollment, the research results were for the
benefit of children enrolled in kindergarten.
The researchers and in the light of the results also present certain
recommendations.
This study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b
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The importance of this study highlights the fact that the Iraqi universities are an important tributary among the tributaries of human development, especially in spreading the education of the voluntary work in literacy field and confirming the connection between the students and their society and their role in solving one of the prominent challenges that face the development, i.e., literacy.
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The study aims to investigate the effect of the Six Thinking Hats Strategy on the achievement of essay writing skills among third-year students in Arabic Language and Literature who are Persian speakers enrolled in the course of Essay Writing (III) at Shiraz University for the academic year 2019-2020. The sample of the study consisted of (15) male and female students who were taught according to the pre-posttest, using the quasi-experimental approach. After applying the statistical analysis on the scores of the post-test, the results showed that there are statistically significant differences in the average of students' achievement in the skills of essay writing in terms of using the Six Thinking Hats Strategy. The results also proved th
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The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca
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