The research aimed at identifying the effect of using constructive learning model on academic achievement and learning soccer dribbling Skill in 2nd grade secondary school students. The researcher used the experimental method on (30) secondary school students; 10 selected for pilot study, 20 were divided into two groups. The experimental group followed constructive learning model while the controlling group followed the traditional method. The experimental program lasted for eight weeks with two teaching sessions per week for each group. The data was collected and treated using SPSS to conclude the positive effect of using constructive learning model on developing academic achievement and learning soccer dribbling Skill in 2nd grade secondary school students. Finally the researchers recommended benefiting from constructive learning model in improving and learning dribbling Skill.
HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023
The present study aimed to identify the exact location and its relation to cognitive
method (risk_caution) to university students. The sample consisted of (300) students who
were chosen randomly and equally. The study results indicated that students possess an
internal exact location and they also use risk cognitive method. The study also indicated that
there is a prophesies which is an exact location for others to reach to caution cognitive
method. Depending on these results, the study recommended to benefit from the results of the
study variables and from the measurement of the exact location and method of cognitive
(risk_caution) to identify male and female students and especially by consulting units at
college
Electronic learning was used as a substitute method for learning during the COVID-19 pandemic to conduct scientific materials and perform student assessment; this study aimed to investigate academic staff opinions toward electronic education. A cross-sectional study with a web-based questionnaire distributed to academic staff in different medical colleges in Iraq. After de-identification, data were collected and analyzed with statistical software to determine the significance between variables. A total of 256 participants were enrolled in the study: 83% were not satisfied or neutral to online learning, 80% showed a poor benefit from delivery of the practical electronic knowledge and 25% for theoretical sessions with a significant difference
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The aim of the study is to diagnose the real level of technology usage in teaching and learning EFL at university from teachers and students’ viewpoints, and see if it is possible to achieve something of the researchers’ dream - accessing top universities. Two questionnaires have been used to measure the range of technology usage in Colleges of Education for Women, Baghdad and Iraqi Universities, and College of Basic Education. The results have shown that the reality of using technology is still away from the dream. The results have been ascribed to two reasons: The first is the little knowledge of using technology in teaching, and the second is that technology is not included in the curriculum.
e current research aims to know the effect of fishbone strategy on achievement of chemistry and visual thinking among middle school students, the research sample consisted of 89 students divided into two experimental groups consisting of 44 students who studied fishbone strategy, and a control group that consisted of 45. A student studied in the usual way; the two groups were rewarded in a number of variables, and the researcher built two tools for the research: the first is an achievement test consisting in 30 paragraphs, and the second is a visual thinking test consisting in 18 paragraphs. Keywords: Chemistry, fishbone, seven grade, students, visual thinking..
ولاء طارق حميد, Mustansiriyah Journal of Sports Science, 2021
A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification
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Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm
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