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jperc-1392
Evaluating the Science Experts Program at the Specialized Institute for Professional Training for Teachers in the Sultanate of Oman in Light of the Kirkpatrick Model
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Abstract

This study aims to identify the degree to which the first cycle teachers use different feedback patterns in the E-learning system, to identify the differences in the degree of use according to specialization, teaching experience, and in-service training in the field of classroom assessment as well as the interaction between them. The study sample consisted of (350) female teachers of the first cycle in the governmental schools in Muscat Governorate for the academic year 2020/2021. The study used a questionnaire containing four different feedback patterns: reinforcement, informative, corrective, and interpretive feedback. The psychometric properties of the questionnaire were verified in terms of validity and reliability. Among the most prominent findings of the study: were that reinforcement feedback was the most frequently used feedback pattern from the teachers of the first cycle, and informative feedback was the least used. Also, there were statistically significant differences between the teachers in the degree of use of feedback patterns attributed to the variables of specialization and teaching experience, while there were no statistically significant differences between the teachers in the degree of use of feedback patterns due to the in-service training in the field of classroom assessment and the 2-way interactions between the variables. The study concluded with a set of recommendations and suggestions, including emphasizing the importance of female teachers employing different feedback patterns for students in the process of continuous assessment and conducting more studies on different feedback patterns and their effectiveness at various educational levels and subjects. The general level of the impact of the science experts program was very good from the graduates’ point of view. The results also revealed that there were no statistically significant differences between the means of graduates’ degree of satisfaction with the training program due to the variables of gender, training cohort, and years of experience. There were also no statistically significant differences between the means of the graduates’ ratings on the impact of the training program due to the variables of gender and training cohort. The study ended with a set of recommendations for developing the program and suggestions for future research studies. The most important recommendations are:

Increase the number of field visits and continuing communication with graduates. The certificate obtained by graduates should have academic weight and the subjects taken in the training program should be equivalent to the master’s topics. Activating the professional learning communities in more effective ways to share experiences between teachers. Assign specific dates for teachers' training in the school calendar. Focus on improving the practical skills of teachers and not only theoretical parts.

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Publication Date
Sat Dec 17 2022
Journal Name
Iraqi Journal Of Laser
PDF S and U shape offset studying of the refractive index sensor based on coreless fiber: Aya R. Mejble* Hanan J.Taher
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Abstract:  Two different shapes of offset optical fiber was studied based on coreless fiber for refractive index (RI)/concentration (con.) measurement, and compare them. These shapes are U and S-shapes, both shapes structures were formed by one segment of coreless fiber (CF) was joined between two single mode (SMF) lead in /lead out with the same displacement (12.268µm) at both sides, the results shows the high sensitive was achieved in a novel S-shape equal 98.768nm/RIU, to our knowledge, no one has ever mentioned or experienced it, it’s the best shape rather than the U-shape which equal 85.628nm/RIU. In this research, it was proved that the offset form has a significant effect on the sensitivity of the sensor. Addi

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Publication Date
Wed Jul 02 2008
Journal Name
Iraqi Journal Of Science
Petrology, geochemistry and tectonic environment of the Shalair Metamorphhic Rock Group and Kater Rash Volcanic Group, Shalair Valley area, Northeastern Iraq
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Publication Date
Sat Nov 30 2024
Journal Name
Asia Pacific Journal Of Molecular Biology And Biotechnology
Random amplified polymorphic DNA-based polymerase chain reaction is an effective tool to examine the genotoxic effects of some food colors
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A large number of natural or synthetic dyes have been removed from both national and international lists of permitted food colors because of their mutagenic or carcinogenic activity. Therefore, this study aimed to use the Random Amplified Polymorphic DNA-Based Polymerase Chain Reaction (RAPD-PCR) assay as a feasible method to evaluate the ability of some food colors as genotoxin-induced DNA damage and mutations. Lactiplantibacillus plantarum was used as a bioindicator to determine the genotoxic effects by RAPD-PCR using M13 primer after treatment with some synthetic dyes currently used as food color additives, including Sunset Yellow, Carmoisine, and Tartrazine. Besides qualitative analysis, the bioinformatic GelJ software was used for clus

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Publication Date
Mon Jul 01 2019
Journal Name
Ceramics International
Surface structural features and optical analysis of nanostructured Cu-oxide thin film coatings coated via the sol-gel dip coating method
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Publication Date
Fri Jan 13 2023
Journal Name
Atmosphere
Impact of North African Sand and Dust Storms on the Middle East Using Iraq as an Example: Causes, Sources, and Mitigation
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This study aims to determine the reasons for the increase in the frequency of sand and dust storms in the Middle East and to identify their sources and mitigate them. A set of climatic data from 60 years (1960–2022) was analyzed. Sand storms in Iraq are a silty sand mature arkose composed of 72.7% sand, 25.1% silt, and 2.19% clay; the clay fraction in dust storms constitutes 70%, with a small amount of silt (20.6%) and sand (9.4%). Dust and sand storms (%) are composed of quartz (49.2, 67.1), feldspar (4.9, 20.9), calcite (38, 5), gypsum (4.8, 0.4), dolomite (0.8, 1.0), and heavy minerals (3.2, 6.6). Increasing temperatures in Iraq, by an average of 2 °C for sixty years, have contributed to an increase in the number of dust storm

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
The optical properties of mawsonite Cu6Fe2SNS8 [CFTS] thin films effected by red laser irradiation deposited via semi-computerized spray pyrolysis technique
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Publication Date
Mon Sep 30 2024
Journal Name
Open Veterinary Journal
Crude aqueous Proteus mirabilis extract with quorum sensing inhibitory activity can increase the susceptibility of multidrug resistant Pseudomonas aeruginosa to antimicrobials
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Background: Suppression of quorum sensing (QS) that regulates many virulence factors, including antimicrobial resistance, in bacteria may subject the pathogenic microbes to the harmful consequences of the antibiotics, increasing their susceptibility to such drugs. Aim: The current study aimed to make an aqueous crude extract from the soil Proteus mirabilis isolate with the use of the gas chromatography-mass spectrometry (GC-MS) technique for its analysis, and then, study the impact of the extract on clinical isolates of Pseudomonas aeruginosa. Methods: Preparation of crude extracts from P. mirabilis (both organic and aqueous), which were then analyzed by GC-MS to detect the bioactive ingredients. Furthermore, the extract’s capability to i

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Data And Network Science
The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

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