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Learning English through Scaffolded Assistance in Iraqi EFL Classroom
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Learning a foreign language is a highly interactive process, and a belief that communicative activities foster a great amount of linguistic production provides language practice and opportunities for negotiation of meaning during communicative exchanges. Thus, this study examines what benefits learner-centered classroom setting offers compared with that of teacher–centered classroom, and how less proficient learners accomplish their tasks and activities with scaffolded help during interaction with the help of proficient classmates and under the guidance of a skilful person, i.e., the teacher. The subjects participating in this study are 30 Iraqi 4th year college students in the Department of English, College of Arts , University of Baghdad for the academic year 2012-2013. The students were working with groups of two or three. Their task was to make up different conversations and after each conversation, the teacher asked some questions to the group.

                Five teacher-student interactions were analysed. The results showed that learner-centeredness was beneficial for language learning in the following respects: 1-it triggered more scaffolding offered by the teacher and 2-interaction between learners actively occurred in learner – centered lessons. In addition when the teacher engaged in interaction with the students, he basically used repetition, paraphrases and nonverbal devices such as varying the pace of his/her utterances, facial expressions and pauses as scaffolding.

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Publication Date
Tue Mar 21 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Impact of Deep Learning Strategy in Mathematics Achievement and Practical Intelligence among High School Students
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— To identify the effect of deep learning strategy on mathematics achievement and practical intelligence among secondary school students during the 2022/2023 academic year. In the research, the experimental research method with two groups (experimental and control) with a post-test were adopted. The research community is represented by the female students of the fifth scientific grade from the first Karkh Education Directorate. (61) female students were intentionally chosen, and they were divided into two groups: an experimental group (30) students who were taught according to the proposed strategy, and a control group (31) students who were taught according to the usual method. For the purpose of collecting data for the experimen

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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Publication Date
Wed Jun 04 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
Evaluation of the Accuracy of Machine Learning Classifiers and Spectral Indices in Land Cover Classification
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Population growth and economic and industrial development coupled have significantly accelerated the rate of Land Use and Land Cover (LULC) changes, particularly in developing countries, so finding optimum ways to observe these change has become a pressing issue. Quantification evaluation of these changes is crucial to comprehend and oversee land management conversion, therefore, it is necessary to evaluate the accuracy of various algorithms for LULC classification to determine the most effective classifier for Earth observation applications. The performance of Maximum Likelihood (ML), Support Vector Machines (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN) was examined in this study, based on Sentinel 2A satellite images. T

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Publication Date
Wed Jun 20 2018
Journal Name
Al-academy
The Reduction in the design structure ofThe emblems ofIraqi sports clubs is amodel
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   Singled current study on the subject of shorthand in structure designs logos (Iraqi sports clubs model), as the current study Tdmt four chapters, was in the first chapter defines the research problem and its significance, as well as the aim of the research in the know shorthand formal in structure designs logos (Iraqi sports clubs model ), and identifies Find time limits: - slogans Iraqi sports clubs for the years (1956 - 1970), because it represented the years to include designs slogans official Iraqi sports clubs that have been elected in this period for the purpose of examining the reality of the design in the current search. And it represented the spatial limits: - the Republic of Iraq - Iraqi slogans designs sports

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Publication Date
Mon May 06 2019
Journal Name
Journal Of Physical Education
Designing Teaching Aids and Their Effects on Learning and Retaining Diving and Cartwheel on Floor Exercises in Women’s’ Artistic Gymnastics
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Designing Teaching Aids and Their Effects on Learning and Retaining Diving and Cartwheel on Floor Exercises in Women’s’ Artistic Gymnastics

The research aimed at designing teaching aids that develop and help retain diving and cartwheel for third year college of physical education and sport sciences students in women’s artistic gymnastics. In addition to that, the researchers aimed at identifying the effect of these aids on learning and retaining cartwheel and diving in floor exercises. The researchers used the experimental method. The subjects were (20) third year female students from the college of physical education and sport sciences/ university of Baghdad sections K and H. the main experiment lasted for

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Publication Date
Sat Mar 26 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of applying the CAMELS banking assessment model asa control tool On Iraqi private commercial banks for the period 2016 -2020
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The banking sector is currently facing great challenges resulting from intense competition in the financial environment, and this is what makes the supreme audit bodies and the Central Bank audit as the highest supervisory authority on banks in order to achieve profit and not be exposed to loss, and this requires identifying the banking strengths and risks that constitute points Weakness that affects the future performance and the life of the bank, which requires special supervisory care, and from this point of view, the research aims to use the CAMELS model as a control tool in banks, through the use of its six indicators: capital adequacy, asset quality, management quality, profits, liquidity And sensitivity to market risks, th

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Publication Date
Sat Mar 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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Publication Date
Tue Nov 19 2024
Journal Name
Aip Conference Proceedings
CT scan and deep learning for COVID-19 detection
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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Publication Date
Mon Jun 30 2025
Journal Name
Ingénierie Des Systèmes D Information
Comparative Analysis of Four Programming Languages for Machine Learning
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