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Integrated Problem Based Learning (PBL) Evaluation by Students in Kerbala Medical College
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Background: Scientific education aims to be inclusive and to improve students learning achievements, through appropriate teaching and learning. Problem Based Learning (PBL) system, a student centered method, started in the second half of the previous century and is expanding progressively, organizes learning around problems and students learn about a subject through the experience of solving these problems.Objectives:To assess the opinions of undergraduate medical students regarding learning outcomes of PBL in small group teaching and to explore their views about the role of tutors and methods of evaluation. Type of the study: A cross-sectional study.Methods: This study was conducted in Kerbala Medical Colleges among second year students. A self-administered questionnaire was prepared to evaluate the newly applied teaching system. The study analysis included simple descriptive analysis and determining association through t-test, chi square test and regression analysis and using structural equation models to determine simultaneous association between different students’ demographic characteristics and potential predictors using SPSS-20 and Amos software at a significance level of < 0.05.Results:A total of 131 undergraduate medical students participated in the study with a response rate of 94%. The majority (93%) have indicated that PBL strategy contributed effectively to their knowledge development with a similar majority (92%) considering PBL successful new teaching method. About 86% reported that would choose PBL rather than conventional method and also 86% would advise PBL for others. Similarly, high majority indicated that various PBL activities are essential. Regarding the tutors’ role in PBL, the majority (92%) indicated that this role was positive and fundamental. According to two thirds (68%) of participants PBL application in Kerbala Medical college was very good application while a higher majority described various PBL sessions as successful and positive and fundamental role of tutors was stressed by most students.Conclusions: This study highlighted the benefits of soliciting student impressions of effective small group teaching. The students’ emphasized group atmosphere and facilitation skills of tutor in learning.Key words: Problem Based Learning, Medical Education, Small Group Teaching, Team Based Learning, Kerbala Medical College

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Publication Date
Wed Mar 23 2022
Journal Name
Journal Of Educational And Psychological Researches
The effectiveness of a teaching program based on the McCarthy Model (4MAT) in developing creative writing skills and reflective thinking among university students
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The aim of this study was to determine the effect on using the McCarthy Model (4MAT) for developing creative writing skills and reflective thinking among undergraduate students. The quasi-experimental approach was adopted. And, in order to achieve the study objective, the educational content of Teaching Ethics (Approach 401), for the plan for the primary grades teacher preparation program  was dealt with by using a teaching program based on the McCarthy Model (4MAT) was used.

The study which was done had been based on the academic achievement test for creative writing skills, and the reflective thinking test. The validity and reliability of the study tools were also confirmed. The study was applied to a sample consisting of

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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Sun Mar 15 2020
Journal Name
Journal Of The College Of Education For Women
Second Language Learning and Its Relationship with the Third Language Learning: Statistical Study: China
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The exchanges in various fields,like economics, science, culture, etc., have been enhanced unceasingly among different countries around the world in the twenty-first century, thus, the university graduate who masters one foreign language does not meet the need of the labor market in most countries.So, many universities began to develop new programs to cultivate students who can use more foreign languages to serve the intercultural communication. At the same time, there is more scientific research emerged which is related to the relationship between the second and third languages. This humble research seeks to explain the relevant concepts and analyze the real data collected from Shanghai International Studies University in China, to expl

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Publication Date
Sun Apr 30 2023
Journal Name
Ingénierie Des Systèmes D Information
Performance Evaluation of Multi-Organization E-Government Based on Hyperledger Fabric Blockchain Platform
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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
Facial deepfake performance evaluation based on three detection tools: MTCNN, Dlib, and MediaPipe
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Publication Date
Fri Jun 19 2026
Journal Name
Journal Mustansiriyah Of Sports Science
Relationship between Cognitive style (risk taking VS Cautiousness) and performance of some ring skills for third stage female students in College of Physical Education and Sport Sciences / University of Baghdad
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Publication Date
Wed Apr 01 2020
Journal Name
International Journal Of Pharmaceutical Research
Effectiveness of Self-Instructional Strategy and the Traditional Teaching Approach on Nursing Students&#39; Knowledge toward Cardiopulmonary Resuscitation at the College of Nursing in University of Baghdad: Randomized Comparative Trial
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MM ABDUL-WAHHAB, SA AHMED, International Journal of Pharmaceutical Research, 2020 - Cited by 2

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Publication Date
Fri Jun 08 2018
Journal Name
Advances In Intelligent Systems And Computing
Improve Memory for Alzheimer Patient by Employing Mind Wave on Virtual Reality with Deep Learning
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Publication Date
Wed Sep 11 2024
Journal Name
Lecture Notes In Civil Engineering
An Image Processing Algorithm to Address the Problem of Stains Merge on Water Sensitive Papers and Its Impact on the Evaluation of Spray Quality Indicators
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There are many techniques that can be used to estimate the spray quality traits such as the spray coverage, droplet density, droplet count, and droplet diameter. One of the most common techniques is to use water sensitive papers (WSP) as a spray collector on field conditions and analyzing them using several software. However, possible merger of some droplets could occur after they deposit on WSP, and this could affect the accuracy of the results. In this research, image processing technique was used for better estimation of the spray traits, and to overcome the problem of droplet merger. The droplets were classified as non-merged and merged droplets based on their roundness, then the merged droplets were separated based on the average non-m

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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