TV drama has gone through many developmental stages until it reached and settled in the form of TV series of thirty episodes. Alongside the development of the TV technologies and the widespread of satellite channels, the form of the TV drama has changed and the series has consisted of two parts and then parts multiplied until they amounted to ten parts and more. This form of TV drama has become an artistic phenomenon, that once the series is displayed on one of the channels and achieves a noticeable success, its producers work to produce a second part of that series and so on. This form of TV drama has remained away from being researched.
This has urged the researcher to accomplish this study entitled (TV series of multiple parts from the viewers' viewpoint) which aimed to know the viewers' opinions in many aspects of the TV drama with multiple parts. In the theoretical framework, the researcher studied the development stages of TV drama in the first section and the TV series with multiple parts in the second section. The researcher, in the third chapter, determined the descriptive approach as the questionnaire constitutes one of its main tools. The researcher designed the research tool, which is the questionnaire form that consists of seven questions covering what has been mentioned in the research aims. The research sample is limited to three hundred respondents from Baghdad aged between 15-40 years old
The study falls in Five chapters as follows:
Chapter One : definition of the Study including:
1. The problem of the study: the current study tries to answers two questions;
First: the effectiveness of the performance of the applicants in the department of Quran
Sciences and Islamic Education in the colleges of Education according the point of view of
their supervisors.
Second: what is the future vision for teacher training according to the assessment of the
performance of the applicant students?
2. The importance of the study: the application or the field training is of an important role
in the process of training the students for teaching; as it is considered the real scale of
success in the processes of ac
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
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