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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
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Physics
Capacitance-Voltage and Current-Voltage Characteristic for Multi- Walled Carbon Nanotubes Grown in Oxygen Atmosphere
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Carbon nanotubes were prepared by an arc-discharge method,
under different values of pressure of oxygen gas. The structure of
multi-walled carbon nanotubes powders has been characterized by
low-angle X-ray diffraction .The morphology of carbon nanotube
powder was examined by transmission electron microscope. The
capacitance-voltage and current- voltage (dark and illumination
current) characterization were measured under different values of
pressure (10-3, 10-4, 10-5) mbar of oxygen gas

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Publication Date
Sat Dec 01 2018
Journal Name
Applied Soft Computing
A new evolutionary algorithm with locally assisted heuristic for complex detection in protein interaction networks
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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Gravity Field Interpretation for Major Fault Depth Detection in a Region Located SW- Qa’im / Iraq
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This research deals with the qualitative and quantitative interpretation of Bouguer gravity anomaly data for a region located to the SW of Qa’im City within Anbar province by using 2D- mapping methods. The gravity residual field obtained graphically by subtracting the Regional Gravity values from the values of the total Bouguer anomaly. The residual gravity field processed in order to reduce noise by applying the gradient operator and 1st directional derivatives filtering. This was helpful in assigning the locations of sudden variation in Gravity values. Such variations may be produced by subsurface faults, fractures, cavities or subsurface facies lateral variations limits. A major fault was predicted to extend with the direction NE-

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Publication Date
Thu Jan 30 2020
Journal Name
Telecommunication Systems
Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends
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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Fri Mar 27 2020
Journal Name
Solid State Technology
Seepage and Slope Stability Analysis for Hemrin Earth Dam in Iraq Using Geo-Studio Software
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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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Publication Date
Fri Feb 24 2023
Journal Name
Membranes
Enhanced Antifouling in Flat-Sheet Polyphenylsulfone Membranes Incorporating Graphene Oxide–Tungsten Oxide for Ultrafiltration Applications
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In this study tungsten oxide and graphene oxide (GO-WO2.89) were successfully combined using the ultra-sonication method and embedded with polyphenylsulfone (PPSU) to prepare novel low-fouling membranes for ultrafiltration applications. The properties of the modified membranes and performance were investigated using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), contact angle (CA), water permeation flux, and bovine serum albumin (BSA) rejection. It was found that the modified PPSU membrane fabricated from 0.1 wt.% of GO-WO2.89 possessed the best characteristics, with a 40.82° contact angle and 92.94% porosity. The permeation flux of the best membrane was the highest. The pure water permeation f

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Publication Date
Fri Jun 27 2025
Journal Name
International On Applied Innovations In It (icaiit)
Green-Synthesized Calcium Oxide Nanoparticles for Adsorption, Antibacterial Applications, and Alleviating Water Stress in Fenugreek
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In this research, a novel synthesis of CaONPs has been developed via an environmentally friendly, green method. Garlic extract (Allium sativum) was used as a green-reducing and stabilizing agent for CaONPs. The average particle size of CaONPs was approximately 24.42 nm. The synthesized CaONPs were identified by using Fourier transform infrared (FT-IR) spectroscopy, U.V.-vis spectrum, X-ray diffraction (XRD), Field Emission-Scanning Electron Microscopy (FE-SEM), Transmission Electron Microscopy, transmission electron microscopy (TEM), Energy Dispersive X-ray spectroscopy (EDX), Atomic Force Microscopy (AFM), and zeta potential (Zp) analysis. The current study highlights the notable applications for CaONPs. First, an antimicrobial assay revea

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