study aimed to recognize The relationship between Intrinsic Motivation Academy and Time Management among University students and measure Intrinsic Motivation Academy And Time Management for sample and Balancing Degrees of Basic Research on the two scales According to the Variable genders and Specialization, The sample consisted (350) students by (230) female (120) male , and the sample  responded scales of Intrinsic Motivation Academy for (Alwan & Attaat2009) and Time Management (Building tool), The Results of this study show that: There are statistically significant differences according to gender variable in Intrinsic Motivation Academy and Time Management in favor of the male, and there are statistica

  The research aims to know The Effect Of Flexible Grouping Strategy  and Three Step Interview strategy on achievement of the history material among student of the first literary class, The Researcher used the experimental design of the two experimental groups and the control group and with post test, researcher group (a) represent the experimental group taught according the Flexible Grouping Strategy  , and Division (c) to represent the second experimental group which studied according Three Step Interview strategy and Division (b ) to represent the control group taught in the traditional method, the number of students (99) students of (33) female students in each division. T

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

The current research aims to identify the effectiveness of a computerized program in developing mathematical skills among the first cycle students in basic education schools in the Sultanate of Oman. The two researchers used the quasi-experimental approach on an intentional sample consisting of (40) male and female students at Al Kawakeb School for Basic Education (1-4). Two of the basic fourth-grade classes and then randomly distributing them into two groups, one is experimental (20) male and female students who followed the computerized interactive program, and the other is (20) male and female students followed the traditional way. On the other hand, its reliability has reached (0.81), and the results of the research have concluded th

Abstract

This study aims to identify the level of emotional intelligence among principals of basic education schools in Al-Dakhiliya Governorate. The descriptive approach was used. A questionnaire of two parts was utilized; its second part included (27) items divided into five dimensions related to emotional intelligence. The study sample consisted of (337) teachers representing 52% of the study sample were randomly selected. The study result showed that level of the emotional intelligence is high and the motivation dimension is the highest. There were no statistical differences at the level (α≤ 0.05) due to the impact of (the social type, the educational qualification, and the years of experience) in all the

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

A field study aimed at identifying the sources of mutual complaints among the Directorates of Education staff of their departments and management and run it in their daily dealings with principals in the province of Baghdad, and adopt approach. It was determined the research consists of (2357) male and female employees and 305 randomly stratified simple by the rate of (7%) from the research community as the number of sample reached (167) male and female employees, and selected sample was randomly stratified simple by the rate of (39.67%) of the research community, as the number of sample was (121) principals. It was constructed two questionnaires, the first included (28) items and the second contained (28) items. And the two researchers