This study aimed to reveal the degree possession of secondary teachers for effective teaching skills from the perspective of the teachers themselves in the Mafraq governorate .To achieve the objective of the study(45) teachers were chosen randomly, also a questionnaire composed of 17 was prepared spread over three skill areas (planning, implementation, evaluation).
After application of the tool on the sample results of the study showed that the degree of ownership ranged between medium and high.
The results showed no differences in the degree of ownership due to the variables of sex in favor of females and variable qualification for the benefit of people with qualified Master higher, while differences are attributed to the experience it did not appear in the light of those the result researcher recommended the preparation of training programs based on effective teaching skills to enhance cognitive performance and performance piece for teachers and then transfer that knowledge to the impact in the classroom and the need for further studies of effective teaching skills of the other samples.
Key words: teaching skills of effective secondary school teachers
These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that. The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce
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The research aims to shed light on the trends in media discourse of the countries that signed the nuclear agreement and those affected by it b
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
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