Research Summary The aim of the search for knowledge of the effect generative learning strategy in: 1 - Achievement of the second grade. 2 - Systemic thinking for the second grade students when studying the biology. The study sample increased (60) students distributed into two equal experimental and control groups. Prepare the test of 40 pieces of multiple choice type and prepare a test for systematic thinking according to three skills 1. Understand the relationships between the parts of the systemic form and complement the sentences given 2 - complement the relationships between parts of the systemic form 3. Building the systemic form. It was a search result 1- There is a difference of statistical significance (at level 0.05) between the mean scores of the experimental group taught by the generative learning strategy and the mean of the control group, which is taught in the usual way in the collection of biology for the second grade, average and for the benefit of the experimental group. 2 - There is a difference of statistical significance (at the level of 0.05) between the average score of the experimental group in systemic thinking taught by the generative learning strategy of and the birth of the average control group, which is taught in the usual way in the biology of the second grade average and for the benefit of the experimental group.
Ajloun Governorate is considered the smallest governorate in Jordan in terms of area, and its population density rises to 472.2 people/ km2 and is distributed among five municipalities. The Al-Shafa municipality is one of these municipalities. Al-Shafa is rich in its natural and human resources, and the first municipal council was established in it in 2001.
This study seeks to achieve the following general objective: inventory the natural and human resources that Al-Shafa enjoys, and highlight the role of Al-Shafa municipality in achieving and settling sustainable development for the local community. Certain content, which are: the comprehensive approach to geographical reality, the descriptive
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThe analysis of the orientations of Iraqi art commodification contributed to the discovery of deliberation, which was founded in the deliberative discourse in the trends towards commodification in the Iraqi art, since the important transformations in social structures and relations produced a dictionary with new vocabulary and tools that replaced the traditions and norms that have been in circulation for a century. Deliberation and commodification have become more prevalent in the mechanics and trends of the art where the pace of change is becoming increasingly frantic towards the market. The general market for art constitutes one of the most effective phenomena within contemporary art, that there has been a proliferation of sales auctio
... Show MoreThe study aimed to achieve the following: Developing comprehensive quality standards for evaluating the curricula of Arabic Language Departments in Colleges of Education at Iraqi universities. Evaluating the curricula of Arabic Language Departments in light of comprehensive quality standards. The study was delimited to: The Arabic language curricula—namely (grammar, morphology, literature, rhetoric, criticism, and prosody)—taught in Arabic Language Departments across their four academic years for the academic year (2010/2011). Arabic Language Departments in Colleges of Education at Iraqi universities (Baghdad, Diyala, Mosul, Basra, and Babylon). Faculty members of Arabic Language Departments in Colleges of Education at Iraqi universitie
... Show MoreThe problem of the current research addressed the close link between the psychological stress and social isolation as behavior and experience, as well as, the stress of the displaced pupils by the sense of alienation and isolation from the society to which they had moved. It reflects a sense of mystery to the displaced pupils about their lives in the present and future. Therefore, the current research aims to identify the psychological presence and the level of social isolation among secondary school displaced pupils and identify whether there were statistically significant differences in the variables between the displaced pupils (males-females). Moreover, it attempts to identify the relationship between psychological stress and social
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
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