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The Effects of Problem-Based Learning on Self-Directed Learning Skills among Physics Undergraduates
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The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills better than the conventional teaching method.

Publication Date
Tue Jan 01 2019
Journal Name
البحوث التربوية والنفسية
An educational design based on the models of the constructivist theory of chemistry and its impact on the life skills of second-year middle school female students
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Publication Date
Sun Apr 06 2014
Journal Name
Journal Of Educational And Psychological Researches
Positive thinking and its relation to self academic motivation and the trend towards teaching profession among the students of education colleges
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The research aims to know the relation between positive thinking and self academic motivation, trend towards teaching profession. So a sample of (344) male and female student of the morning study of education colleges from the two universities of Baghdad and al Mustansria for the academic year 2012-2013.

So three tools had been used to achieve the procedures of the research which are: the scale of positive thinking constracted by Abdal satar Ibrahim year 2010, the scale of self academicmotivation constracted by (Gottfried) and adapted by Hanan Hussan year 2010, the scale of teaching profession trend constracted by Enayat Zaki year 1974.

And by using the statistical means of person

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Publication Date
Wed Aug 24 2022
Journal Name
Journal Of Tikrit University For Humanities
A Training Program Based on Integrating Future Thinking Skills and Classroom Interaction Patterns for Mathematics Teachers and Providing Their Students with Creative Solution Skills
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The research aims to recognize the impact of the training program based on integrating future thinking skills and classroom interaction patterns for mathematics teachers and providing their students with creative solution skills. To achieve the goal of the research, the following hypothesis was formulated: There is no statistically significant difference at the level (0.05) between the mean scores of students of mathematics teachers whose teachers trained according to the proposed training program (the experimental group) and whose teachers were not trained according to the proposed training program (the control group) in Pre-post creative solution skills test. Research sample is consisted of (31) teachers and schools were distribut

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Publication Date
Sun Jul 03 2011
Journal Name
Journal Of Educational And Psychological Researches
Effect of using the active learning in the achievement of third grade intermediate students in mathematics and them tendency towards the study of its
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Current research aims to find out:

  1. Effect of using the active learning in the achievement of third grade intermediate students in mathematics.
  2. Effect of using of active learning in the tendency towards the study of mathematics for students of third grade intermediate.

In order to achieve the goals of the research, the researcher formulated the following two hypotheses null:

  1. There is no difference statistically significant at the level of significance (0.05) between two average of degrees to achievement

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Publication Date
Fri Jan 01 2021
Journal Name
Basra Journal Of Science
Effects of Thicknesses of Two Different Gate Insulators on the Performance of Pentacene Based Organic Field Effect Transistor
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In this paper, a simulation of the electrical performance for Pentacene-based top-contact bottom-gate (TCBG) Organic Field-Effect Transistors (OFET) model with Polymethyl methacrylate (PMMA) and silicon nitride (Si3N4) as gate dielectrics was studied. The effects of gate dielectrics thickness on the device performance were investigated. The thickness of the two gate dielectric materials was in the range of 100-200nm to maintain a large current density and stable performance. MATLAB simulation demonstrated for model simulation results in terms of output and transfer characteristics for drain current and the transconductance. The layer thickness of 200nm may result in gate leakage current points to the requirement of optimizing the t

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
Predictability of Burnout in perceived self-competence among Mothers of Students with Disabilities at Sultanate of Oman
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Abstract

The current study aims to identify the predictability of burnout in perceived self-competence among mothers of students with disabilities in the Sultanate of Oman. The study sample consists of (484) respondents who were mothers of students with disabilities. The researcher developed a burnout Scale which consists of (19) items and a perceived self-competence Scale which consists of (20) items. A correlation descriptive design was used. The results showed that the level of burnout was low (Mean= 2.30), while the level of burnout was high (Mean= 3.87). Regarding the correlation coefficient, the results showed that there was a significant negative correlation between burnout and perceived self-competence. A

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