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THE VALUE OF COLLABORATIVE LEARNING IN DEVELOPING STUDENT’S SPEAKING SKILLS
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The majority of Arab EFL (English as a Foreign Language) learners struggle with speaking English fluency. Iraqi students struggle to speak English confidently due to mispronunciation, grammatical errors, short and long pauses while speaking or feeling confused in normal conversations. Collaborative learning is crucial to enhance student’s speaking skills in the long run. This study aims to state the importance of collaborative learning as a teaching method to EFL learners in the meantime. In this quantitative and qualitative study, specific focus is taken on some of Barros’s views of collaborative learning as a teamwork and some of Pattanpichet’s speaking achievements under four categories: academic benefits, social benefits, generic skills, and negative aspects. 100 undergraduate students, whose level at the first academic year in College of Veterinary Medicine, the University of Baghdad-Iraq, have participated in this experimental study. The results of independent and dependent variables estimated Cronbach’s Alpha high internal consistency. The study data chooses the alternative hypothesis maintaining that the treatment effect was statistically significant. Collaborative learning correlates positively with development of Iraqi EFL learners of speaking skills on academic benefits, social benefits, and generic skills at the level of significance, unlike passive correspondence. It was risen with negative aspects. The main limitations of the current study were that of small sample size of Iraqi EFL learners among medical colleges. The results revealed merely one medical college among other colleges in medicine, science, social and human studies at the University of Baghdad. It has not covered other levels of undergraduate study. The study recommends additional investigations to explore the value of collaborative learning to achieve student’s speaking skills in human and social fields of the Arab and foreign learning communities

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Sat Jan 19 2019
Journal Name
Artificial Intelligence Review
Survey on supervised machine learning techniques for automatic text classification
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Publication Date
Wed Nov 06 2024
Journal Name
2024 17th International Conference On Development In Esystem Engineering (dese)
Improving Cardiovascular Prediction Performance Using Machine Learning Based Feature Selection
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Publication Date
Wed Dec 29 2021
Journal Name
Modern Sport
Building and measuring e-learning scale from the point of view of students of the College of Physical Education and Sports Sciences - University of Baghdad
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Abstract: The research covered five chapters:       So, the first chapter definition of the research is from the introduction to the research and its importance, as the importance of the research lies in an expression of the reality of e-learning as it is one of the new patterns of the educational process and its role in enhancing communication and interconnectedness between the learners from the students ’point of view Physical Education and Sports Sciences for Girls, University of Baghdad, as for the problem The research was, and through the researcher’s acquaintance with many previous studies, references and sources, and being a student at the College of Physical Education and Sports Sciences - University of

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Fri Dec 01 2023
Journal Name
Applied Energy
Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

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Publication Date
Sun Aug 01 2021
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
BUILDING AND RATIONING SCALE MANAGEMENT CONSTRAINTS OF E-LEARNING FROM THE PERSPECTIVE OF TEACHING THE FACULTY OF PHYSICAL EDUCATION AND SPORTS SCIENCE UNIVERSITY OF BAGHDAD
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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Sat Jan 01 2022
Journal Name
The International Journal Of Nonlinear Analysis And Applications
Developing Bulk Arrival Queuing Models with Constant Batch Policy Under Uncertainty Data Using (0-1) Variables
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This paper delves into some significant performance measures (PMs) of a bulk arrival queueing system with constant batch size b, according to arrival rates and service rates being fuzzy parameters. The bulk arrival queuing system deals with observation arrival into the queuing system as a constant group size before allowing individual customers entering to the service. This leads to obtaining a new tool with the aid of generating function methods. The corresponding traditional bulk queueing system model is more convenient under an uncertain environment. The α-cut approach is applied with the conventional Zadeh's extension principle (ZEP) to transform the triangular membership functions (Mem. Fs) fuzzy queues into a family of conventional b

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Publication Date
Sun May 22 2022
Journal Name
International Journal Of Early Childhood Special Education
A training program based on integrating futuristic thinking skills with classroom interaction patterns and its effect on the academic self- efficacy of mathematics teachers
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The research aims to identify the effect of the training program that is based on integrating futuristic thinking skills with classroom interaction patterns on mathematics teachers in order to provide their students with creative solution skills. The research sample consisted of 31teachers (15 teachers for the experimental group and 16 for the control groups). The researcher developed a measure for the academic self-efficacy consisting of (39) items. Its validity, reliability, coefficient of difficulty and discriminatory power were estimated. To analyze the findings, the researcher adopted the Mann-Whitney (U) test and the effect size, and the findings were as follows: There is a statistically significant difference at the significance leve

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