Education specialists have differed about determining the best ways to detect the
talented. Since the appearance of the mental and psychological measurement movement, some
scholars adopted intelligence ratios as a criterion to identify the talented and others went to
rely on the degree of academic achievement. Each of these two methods has its own flaws and
mistakes and a large number of talented children were victims of these two methods.
Therefore the need to use other scales for the purpose of detection of talented children
appeared because they provide valuable information which may not be obtained easily
through objective tests and these scales are derived from consecutive studies of gifted andtalented children , or from the conduct of the life of the talented people and genius who left
their clear imprint in the history of human civilization and these scales are filled by teachers
or counselors staying stick to the talented children in school and some of them filled by
relatives and colleagues.
Therefore, the researcher has adopted two scales and makes a comparison between
them by extracting the psychometric properties in order to identify which one is better at
detecting talented.
The first measure is of (Renzulli, 1979) which estimates the behavioral traits of
gifted students in the areas of stimulus, learning, and creativity.
The second measure is of (Steinberg, 2010) in which he confirms on the three
abilities: analytical ability, creative ability, and the practical ability. He stressed on the
balance between these three abilities for the emergence of the talent of the child.
In order to achieve the goal of this research, the researcher has applied the scale on a
sample of gifted students consisted of (63) students into three schools for gifted students in
Baghdad, Najaf, and Basra. Twelve teachers were selected from schools who have teaching
experience of more than three years and are adjacent to the talented student monitoring his/her
behaviors. The researcher has reached, after extracting the psychometric characteristics of
each of the two scales, that both have high stability and high structure validity.
The researcher has recommended the adoption of the two scales as a basis for
detecting the talented by their teachers with the aim of sending those talented students to
private schools special for gifted students, or if these students are found in ordinary schools,
special classes and programs for the development and refinement of their talent are allocated
to them and make the utmost benefit of it. The researcher has suggested doing more on the
methods of the detection of talented and applied them early on the children before it is too
late.
Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an
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The research aims to identify the level of effectiveness of the teaching practices of science and mathematics teachers in light of the national framework for future skills in Omani schools. To achieve the objectives of the study, the researchers used the descriptive approach, as he designed a note card consisting of (30) phrases distributed on three axes: basic skills, practical skills, and technical skills. After verifying the validity and reliability of the tools, they were applied to a sample of (116) teachers. The results of the research revealed that the level of effectiveness of the teaching practices of mathematics teachers has recorded a medium degree with a mean (3.05). The results a
... Show MoreMalware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bel
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research goals
The current research aims to identify:
1. identify the effectiveness of teaching the University of Tikrit from the standpoint of their students
2. to identify the differences in
An impressed current cathodic protection system (ICCP) requires measurements of extremely low-level quantities of its electrical characteristics. The current experimental work utilized the Adafruit INA219 sensor module for acquiring the values for voltage, current, and power of a default load, which consumes quite low power and simulates an ICCP system. The main problem is the adaptation of the INA219 sensor to the LabVIEW environment due to the absence of the library of this sensor. This work is devoted to the adaptation of the Adafruit INA219 sensor module in the LabVIEW environment through creating, developing, and successfully testing a Sub VI to be ready for employment in an ICCP system. The sensor output was monitored with an Ardui
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