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Main Difficulties Faced by EFL Students in Language Learning
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Many undergraduate learners at English departments who study English as a foreign language are unable to speak and use language correctly in their post -graduate careers. This problem can be attributed to certain difficulties, which they faced throughout their education years that hinder their endeavors to learn. Therefore, this study aims to discover the main difficulties faced by EFL students in language learning and test the difficulty variable according to gender and college variables then find suitable solutions for enhancing learning. A questionnaire with 15 items and 5 scales were used to help in discovering the difficulties. The questionnaire was distributed to the selected sample of study which consists of 90 (male and female) students selected randomly from the 3rd and 4th year class levels at English departments from colleges of Languages and Education (Ibn-Rushd) at the University of Baghdad. The results of the study showed that EFL students face difficulties in language learning such as the role of society in discouraging English language learning, the learners’ shyness, which prevents them from speaking English in fear of making mistakes, lack of motivation, and the influence of class size and crowdedness. After analyzing the results, some recommendations and suggestions were presented to solve the problem and eliminate difficulties.

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
The impact of learning strategies in the collection of biology and their systemic thinking
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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 th

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Publication Date
Sat Feb 02 2019
Journal Name
Journal Of The College Of Education For Women
Language Teaching & Leaning Problems at the Iraqi university level: Image & Reality
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Language Teaching & Leaning Problems at the Iraqi university level: Image & Reality

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Publication Date
Fri Jan 05 2018
Journal Name
Asian Quarterly: An International Journal Of Contemporary Issue
Refugees and the Challenges for Language Education (LE): A Theoretical Study
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DBN Rashid, Asian Quarterly: An International Journal of Contemporary Issue, 2018

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Publication Date
Wed Jan 01 2025
Journal Name
The International Journal Of Humanities Education
Applying Corpus Pedagogical Stylistic Approach to Systemize Learners’ Poetic Language Analyses
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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of College Of Education
Recognition the Arabic Characters Based on the Characteristics of Arabic Language
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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Single Quranic between the root of language and meaning of Quranic
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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of The College Of Languages (jcl)
analyzethe Surface Structure of Persian Language: تجزيه ى روساختى جمله فارسى
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  The sentence is one building unit in a music that has a full  meaning which in the end takes a long silence .The sentence bases made the sentences with  intransitive verb ( non connection ) and the sentences are   made with general verb (connection ) .The sentence parts :Verbal sentence –supportive sentence , sentence without a verb .

The method of divide the sentence into these syntax  units ( face division ) or (analysis and to each of the syntax units resulted from dividing the sentence to sections made to the end the characterizes the  smaller syntax units ,the words .The method of analyze the surface structure of Persian language sentence  is exchange method.   &nbsp

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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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

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