The present study aimed to identify the learning gap between classroom-based education and artificial intelligence (AI)-based education among students of Colleges of Physical Education and Sports Sciences. It also sought to determine the effectiveness of classroom education and AI-based education in reducing the learning gap among these students. The research problem addressed the following questions: Are there statistically significant differences in the learning gap between students who learn through traditional classroom education and those who learn through AI-based education in Colleges of Physical Education and Sports Sciences? What is the nature of the learning gap between classroom education and AI-based education among these students? Which educational approach is more effective in reducing the learning gap? The results of the study indicated that there is a learning gap between classroom education and AI-based education among students of Colleges of Physical Education and Sports Sciences. The findings also revealed that the use of artificial intelligence technologies contributes to improving the quality of the educational process and enhancing the design of educational curricula. Furthermore, AI helps address individual differences among students by providing learning content that aligns with their needs and learning abilities. Based on these findings, the researcher recommends enhancing the integration of artificial intelligence in the educational process. AI technologies can provide advanced analytical tools that assist teachers in monitoring students' progress and diagnosing learning difficulties more accurately. In addition, several challenges still hinder the effective implementation of AI in education, which requires further efforts to overcome these obstacles and promote the successful integration of AI technologies in educational environments.
Colorectal cancer (CRC) is the most common gastrointestinal malignancy and one of the top ten common cancers worldwide with approximately 2 million cases. There are multiple risk factors that could lead to CRC emergence; of which are genetic polymorphisms. Excision repair cross-complementing group 2 (ERCC2) gene encodes for ERCC2 enzyme which plays a crucial role in maintaining genomic integrity by removing DNA adducts. Several studies suggested that there could be a link between genetic polymorphisms of ERCC2 gene and the risk of CRC development. Hence the present study aims to validate the relationship between the following ERCC2 single nucleotide polymorphisms (rs13181, rs149943175, rs530662943, and rs1799790) and CRC susceptibility. A t
... Show MoreIn this study, nano TiO2 was prepared with titanium isopropoxide (TTIP) as a resource to titanium oxide. The catalyst was synthesized using phosphotungstic acid (PTA) and, stearyl trimethyl ammonium bromide (STAB) was used as the structure-directing material. Characterization of the product was done by the X-ray diffraction (XRD), X-ray fluorescent spectroscopy (XRF), nitrogen adsorption/desorption measurements, Atomic Force Microscope (AFM) and Fourier transform infrared (FTIR) spectra, were used to characterize the calcined TiO2 nanoparticles by STAB and PWA. The TiO2 nanomaterials were prepared in three crystalline forms (amorphous, anatase, anatase-rutile). The results showed that the nanoparticles of anatase TiO2 have good cata
... Show MoreFinite Element Approach is employed in this research work to solve the governing differential equations related to seepage via its foundation's dam structure. The primary focus for this reason is the discretization of domain into finite elements through the placement of imaginary nodal points and the discretization of governing equations into an equation system; An equation for each nodal point or part, and unknown variables are solved. The SEEP / W software (program) is a sub-program of the Geo-Studio software, which is used by porous soil media to compensate for the problems of seepage. To achieve the research goals, a study was carried out on Hemrin dam, which located in the Diyala River 100 km northeast of Baghdad, Iraq. Thus, o
... Show MoreObjective: The aim of the study to evaluate the nursing care management for diabetes mellitus patient
with total hip replacement after fractured hip.
Methodology: A field study carried out on patients with diabetes mellitus and have total hip
replacement after fractured hip in orthopedic ward at the hospital of surgical specialization (malefemale)during
January 2002 to January 2003.Physical and psychological nursing
assessment
immediately after the surgery was done for the both subjects (control and experimental) and then a
scientific management with daily nursing care were provided to the experimental subject with daily
nursing care to the patient condition by using a scientific and practical methods and leave th
.
This work revealed the spherical aromaticity of some inorganic E4 cages and their protonated E4H+ ions (E=N, P, As, Sb, and Bi). For this purpose, we employed several evaluations like (0D-1D) nucleus independent chemical shift (NICS), multidimensional (2D-3D) off-nucleus isotropic shielding σiso(r), and natural bond orbital (NBO) analysis. The magnetic calculations involved gauge-including atomic orbitals (GIAO) with two density functionals B3LYP and WB97XD, and basis sets of Jorge-ATZP, 6-311+G(d,p), and Lanl2DZp. The Jorge-ATZP basis set showed the best consistency. Our findings disclosed non-classical aromatic characters in the above molecules, which decreased from N to Bi cages. Also, the results showed more aromaticity in E4 than E4H+
... Show MoreSensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar
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