The current research aims to identify the effect of the learning mastery strategy using interactive learning as a therapeutic method on the achievement of secondary school students in mathematics. To achieve the research objective, the researcher selected second-grade middle school students at Al-Haybah Intermediate School for Boys and determined his research sample, which consisted of (77) students distributed into two sections: Section (A) the experimental group, with (38) students, and Section (B) the control group, with (39) students. The statistical equivalence of the two research sample groups was confirmed in the variables (intelligence test, previous achievement, and previous knowledge test). The researchers chose the partial design with two equivalent groups with a post-test to measure achievement, then controlling the extraneous variables. The experiment was applied in the first semester of the academic year (2024-2025). The results were analyzed statistically using SPSS-26 and using the t-test for two independent samples. The results showed that the students of the experimental group who studied according to the learning mastery strategy and using interactive learning techniques as a therapeutic method outperformed the students of the control group who studied with learning mastery. Using the traditional method as a therapeutic approach.
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
... Show MoreMany 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
... Show MoreAcademic achievement is a professional standard for measuring student levels in the first stages. Therefore, any indication of the level of achievement makes us in an attempt to employ students in evening schools. The researcher has developed a closed questionnaire of (36) paragraphs. A total of (164) male and (24) female students were chosen from evening schools. The result of this research revealed that the number of students was a reason for the low level of their achievement, the lack of laboratories, educational methods, and techniques of the most prominent problems confirmed by students in these schools. In addition, to support educational institutions with their necessary needs. The most important conclusion in this research is th
... Show MoreThe study aims to identify the impact of the implementation of the integrated education strategy in the curriculum of the Arabic language for the seventh grade on the academic achievement in the schools of the capital Amman. The researcher adopted the experimental method, where two divisions of the seventh grade students were chosen from the secondary school for girls. The sample of the study was 60 students divided into two equal groups: 30 students represented the experimental group (A) and (30) students represented the control group. To collect the needed data, a test of (40) Multiple Choices was used. The results showed statistically significant differences between the mean scores of the experimental group who were taught acc
... Show MoreAmputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte
... Show MoreThe study of vegetative change of cities is one of the most important studies related to human life because of its direct correlation with the temporal conditions that occur. These include the economic problems that force people to move and look for job opportunities in the city, which leads to an increase in the population density of cities, especially for cities with an important economic and administrative location as in the capital city of Baghdad. In this study, the effect of the increasing in population density was analyzed on the urban planning of Baghdad city. The decreasing in vegetation was due to the increasing of urban areas on the outskirts of the city, which led to an increase in its area. Moreover, urban cities increased t
... Show MoreDiabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
... Show MoreSocial interaction is the platform that enables people to connect and practice language. Active listening stimulates them to understand the language they are speaking. The problem of the study highlights that less attention to listening among speaking, reading, and writing skills causes the weakness of collaborative learning. This paper contributes to characterizing the effectiveness of collaborative learning in developing learner’s listening skills. It aims to underscore the role of target language learners as members of the learning groups and of the teacher in the collaborative learning process. 130 Iraqi EFL teachers from different colleges at the University of Baghdad participated in this study. The scores in the statistical data wer
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