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أساليب التعلم لدى طلبة معاهد الفنون الجميلة وعلاقتها ببعض المتغيرات
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التعلم هو المظهر الرئيسي في حياة البشرية المتحضرة ،الذي يعبر عن نشاطهم العقلي الذي وهبه الله سبحانه وتعالى ، وما على الإنسان ألا إن يستغل هذه إلهية الإلهية بأقصى ما يمكن للاستفادة منها, ومن هذا المنطلق لابد أن يعتمد المتعلم على طرق وأساليب منطقية في اكتساب المعرفة والتعامل مع المعلومات ومعالجتها ، وتعرف هذه (بأساليب التعلم styles learning) وهي الفروق الفردية في طرق التلقي والإدراك والتذكر والتفكير في تناول وتخزين المعلومات والاستفادة منها .                       

إذ يعتمد الغالبية من الطلبة على الحفظ الأصم أو السطحي دون الفهم والتحليل والتراكيب أو المقارنة والتطبيق ، فالحفظ عن ظهر قلب دون الفهم والاستيعاب يعد من أساليب التحصيل والتعلم السيئة ، في حين يجب على الطالب أن يربط ما يقرأ ، بحياتيه الشخصية والعملية ويطبقها في بيئته كي ترسخ المعلومات في ذهنه دون الكثير من العناء , وان لا يعتد في دراسته التحصيلية على التذكر وحدة ، وإنما ينبغي أن يفكر فيما يقرأ وان يستخدم كل حواسه في أثناء القراءة واكتساب المعلومات وان يستوعب ويفهم تطبيقات ما يقرأه  ويوظفه لدمجه مع خبراته وان يكون تفكيره تفكير نقديا"، وكل هذه العمليات العقلية تتأثر بأساليب تعلمه.            

 وتتضح أحد جوانب مشكلة البحث فيما نسميه بخبرات الفشل في تذكر المادة الدراسية واستيعابها ، ومستوى الأداء في الامتحانات وتحقيق النجاح ، كما يؤدي الفشل أيضا" إلى الشعور بضعف القدرة على التذكر والاسترجاع والتفكير الواضح وكما يؤدي إلى الشك في قدرة المتعلم بنفسه على الأداء الجيد والى شعور مبالغ فيه بالقلق والخوف من تكرار هذا الفشل.ومن الجدير بالذكر إن طلبة معاهد الفنون يواجهون نمطا" من الدراسة تختلف يواجهه في المرحلة المتوسطة ، فهو يتحمل مسؤولية تعلمه بدرجة كبيرة ، لذلك فالأساليب التي يستخدمها للتعامل مع المعلومات واكتسابها وتخزينها واسترجاعها قد تختلف عن تلك التي استخدمها في المراحل التعليمية السابقة .

 

             

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Evaluating Training Programs According to model Kirkpatrick / field research in the Health Maysan Directorate .
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This present paper aim at knowing  the process of evaluating the training program that could be applied  in Maysan Health office  for it significance and importance in field of management and vocational staff  preparations  of high  scientific experience in different fields of  Health.  The society of research includes staffs  working in Maysan Health Office  , of specialists ,  dentists, pharmacists, laboratories, nursing  and administrators. Their number is 100 employees, the researcher has designed questionnaire by depending on "Kirkpatrick"  for assessing  the training . The researcher has used   thorough survey and has entailed 90 questionnaire,

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Editorial: Current advances in anti-infective strategies
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Infectious diseases pose a global challenge, necessitating an exploration of novel methodologies for diagnostics and treatments. Since the onset of the most recent pandemic, COVID-19, which was initially identified as a worldwide health crisis, numerous countries experienced profound disruptions in their healthcare systems. To combat the spread of the COVID-19 pandemic, governments across the globe have mobilized significant efforts and resources to develop treatments and vaccines. Researchers have put forth a multitude of approaches for COVID-19 detection, treatment protocols, and vaccine development, including groundbreaking mRNA technology, among others.

This matter represents not only a scientific endeavor but also an essenti

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Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effect of SPAWN Strategy on the Life Skills among the Second Grade Intermediate Students
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The aim of the research is to find out the effect of the SPAWN strategy on the life skills of second-intermediate-grade students. This study stage represented the research community within the intermediate and secondary governmental daytime schools affiliated with the Directorate of Education of Diwaniyah. The experiment was applied in Al-Razai Intermediate School on a sample of second-grade intermediate students, including 66 students distributed into two groups: (32) students within the experimental group and (34) students within the control group. The two groups were equivalent with a number of variables (chronological age, intelligence test, previous information test, life skills scale). The results indicated that the two groups were

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
The predictive capacity of Coronavirus Impacts with Psychological Adjustment among University Students in Oman
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The present study was designed to determine the predictive capacity of Coronavirus’s impact, as well as, the psychological adjustment among university students in Oman. A total of (566) male and female students were employed to form the swtudy sample. The descriptive method was used. The findings showed that there is a significantly university student affected by Coronavirus; the dimensions of scale were arranged as follows: the Academic requirements of pandemic came first, the social communication came second, and the academic future stress came in third. The results also showed that Psychological Adjustment among University Students was affected by the Coronavirus pandemic, the average was low. Also, the result showed that the Corona

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian methods to estimate sub - population
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The aim of the research is to estimate the hidden population. Here، the number of drug users in Baghdad was calculated for the male age group (15-60) years old ، based on the Bayesian models. These models are used to treat some of the bias in the Killworth method Accredited in many countries of the world.

Four models were used: random degree، Barrier effects، Transmission bias، the first model being random، an extension of the Killworth model، adding random effects such as variance and uncertainty Through the size of the personal network، and when expanded by adding the fact that the respondents have different tendencies، the mixture of non-random variables with random to produce

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Mon Feb 12 2024
Journal Name
Mustansiriyah Journal Of Sports Science
The impact of the use of numbered head and brainstorming strategies to learn handspring on the Vault table in artistic gymnastics for Men
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The aim of the study was to identify the use of the strategies of numbered heads and brainstorming in learning handspring on the Vault table in artistic gymnastics for Men for the third grade students in the collage of Physical Education and Sport Sciences, as well as to identify the best group among the three research groups (number of heads numbered,, brainstorming strategies And the traditional style group) to learn the skill under study. Using the experimental method, the research subject included the third grade students in the collage of Physical Education and Sports Sciences / University of Baghdad, and randomly by lot, 12 students were selected for each of the three research groups. The study consisted of the arithmetic mean

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Self-Localization of Guide Robots Through Image Classification
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The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Scopus (4)
Crossref (8)
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