Background: Educational environment is one of the most important determinants of an effective curriculum. Students' perceptions of their educational environment have a significant impact on their behavior and academic progress. Objective: 1. To identify students’ perception to the educational environment.2. To identify any gender or class level differences in the students’ perception.Type of the study: This is a descriptive cross-sectional studyMethodology: The study was carried out on convenient sample of 150 students of 2nd and 5th grade. This study was done in Al Kindy Medical College, Baghdad, Iraq and conducted during the period from the 1st of October 2013 till the end of March 2014, by using DREEM questionnaire a validated universal diagnostic inventory for assessing the quality of educational environment through direct interview. Inclusion criteria include any student from the 2nd and 5th class who agree to participate in the study. The data was entered into a Microsoft Excel spreadsheet and were analyzed using SPSS version 16. Student t test was done to find out the difference between the mean scores, P<0.05 was considered as statistically significant.Results: For all students (n= 150) the total DREEM score of a maximum possible of 200 was 110.18 , it was more positive than negative overall domain score, which means that the students had positive perception and more positive scores than negative. Total DREEM scores were significantly higher for females (M = 138.8; SD = 17.2) than males (M = 132.3; SD = 20.7), although all domains mean scores were higher for female than male, there was statistical significant difference regarding Students’ perception of learning, Students’ perception of atmosphere and Students’ social self-perception.Regarding the class level, 5th year students gave significantly higher total DREEM ratings (M = 139.1; SD = 17.4) than 2nd year students (M = 135; SD = 18.8). Second year students also gave significantly higher Students’ perception of learning (SPL) ratings than 5th year students and significantly higher Students’ perception of atmosphere ( SPA ) ratings higher than 5th year students. Conclusions: Students assessed the educational environment as more positive than negative;. The greatest difficulty was with ‘students’ perception of learning’.
Abstract
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abstract:
Objectives: The study aims to reveal the approach of Imam Al-Salmi in the weighting between the apparently conflicting texts, and to show the extent of his agreement and disagreement with the rest of the fundamentalists, and does he have vocabulary that can be used to elicit legal rulings in modern contemporary issues?
Method: The method of induction and analysis is one of the main tools to reach the research results. The study resorted to following the sayings of Imam Al-Salmi in various sources and fatwas and standing on them, then analyzing and applying them to the various branches of jurisprudence in the various jurisprudential chapters.
... Show MorePatients 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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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
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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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