The present research aims at the following:
- Measure Classroom environment of university Student (research sample)- Measure
Cognitive motive and Reflective Thinking of university Student (research Sample) .
- In order to Know the relationship between the Scores of Classroom environment and
Scores of cognitive motive and Scores of Reflective Thinking of university Student
(research Sample) .
Sample of research consisted of (500) Students for both genders distrivbted upon ten
colleges in Baghdad University , (5) Scientific Colleges , and (5) human Colleges , Sample
was chosen by using radom method Research instruments were three , Prepared by the researcher ,The first is to measure
classroom environment . The Second to measure Cognitive motive . The third to measure
Reflective Thinking .
The research verified the Validity of measurements and their items were analyzed
Statistically upon the sample consisted of (500) Students for both genders to extract the
discrimination power and the Validity of items . Reliadility was calculated by method
The Alpha kronbache method for internal constanc.
After fulfilling measurements preparations , the final application was applied upon the major
research Sample Consisted of (500) students of both genders. Number of Statistical methods
were used to answer of the research aims and hypotheses like person Coeffisient m (t-test) for
one sample two vaeiance analysis , multiple declivity analysis , Scheffe .
The most important result achievd by the researcher is that there is a Positive Conjunctive
relation of statistical significance between Classroom environment and cognitive motive
, also there is a Positive relationship of statistical significance between classroom
environmentand Reflectiv thinking .
That the erea of interachtion of Students With each other and the Organaztion of the Lesson
and Provide a list Supplies and teaching field interaction with Students and Contribute to its
clear and Signicant . The researcher set some recommendations and suggestions .
Cu X Zn1-XO films with different x content have been prepared by
pulse laser deposition technique at room temperatures (RT) and
different annealing temperatures (373 and 473) K. The effect of x
content of Cu (0, 0.2, 0.4, 0.6, 0.8) wt.% on morphology and
electrical properties of CuXZn1-XO thin films have been studied.
AFM measurements showed that the average grain size values for
CuXZn1-xO thin films at RT and different annealing temperatures
(373, 473) K decreases, while the average Roughness values increase
with increasing x content. The D.C conductivity for all films
increases as the x content increase and decreases with increasing the
annealing temperatures. Hall measurements showed that there are
two
Human resources constitute the most important recourses that the organization owned today, as it may have developed financial and technology resources to achieve their goals, but they are not able to use it with required efficiency and effective and quality desired unless there is human resources that have good skills, experiences and talents that able to directing and exploited ideally that compatible with market requirements, where today's market and business organizations which compete naturally inherent talent, so the task is to attracting and developing talented resources and preservation these talented resources from the challenges that facing organizations.
The research seek to achieve
... Show MoreForecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti
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