The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on the understanding of thermodynamics, group work and self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq, for academic year 2011-2012. In this study, the pre and posttest were done and the instruments were administered to the students for data collection. Inferential statistics were employed to analyze data. The independent variables were the PBL, the PBL with lecture method, and the conventional teaching. Dependent variables of statistical analysis were posttest scores on the understanding of thermodynamics, group work skills, and self-directed learning skills. Covariates of statistical analysis were pretest scores of the understanding of thermodynamics, group work skills, and self-directed learning skills. The data were analyzed using statistical package social sciences (SPSS) version 19. Overall, the statistical results rejected all null hypotheses of this study. Thus, the use of PBL with lecture method enhances the understanding of thermodynamics better than using the PBL alone or using conventional teaching method. Using the PBL without or with lecture method promotes the skills of group work, and self-directed learning better than using the conventional teaching, among physics undergraduate.
Concurrently with the technological development that the world is witnessing the crime of money laundering to evolve faster and with multiple methods and its economic, political and social impacts raised increasingly. And for phenomenon dangerous the international community in recent years is keen to be considered combating money laundering as a general indication whereby verification of the international response the stats and its banks and financial institutions with international requirements mandated in this aspect, so the increasing interest the governments of countries in the laws and procedures that contribute to the reduction of the phenomenon of money laundering and avoid legislation economy and the banking and financial sectors
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On of the psychological disorders that the human encounters is guilty conscience, this feeling is negative and affects on the individual and on those around him and harms the psychological health of the individual.
since the university students slice is one of the important slices in the community which the country dependes on their abilities , their energies and their faculties in the construction and development, the university professors and specialists in the field of education and psychology who are around them should help them in achieving psychological balance and adjustment with themselves and with others, the following research objectives have been set :
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In this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τi ) which has
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Iraq has confronted a huge political transformations after 2003 which resembled and presented rapid changes from totalitarian regime into democracy's system , this phenomenon has become a feature embodied in a new political system, specifically is being a price for previous deprivation and despotism .So that, the nature of political work has been changed as a result of practicing new democratic values ,but the real challenges appeared by depending on the conformity and political compromise in dealing with all of crises and problems in the political life .
The future of political work in this nascent democracy could be prepared according to fulfillment an active doings values stretched on national unity and forgiveness from one side ,t
Abstract his study involved evaluation of side effects of two weight reduction pills that had been widely distributed in the last period. Two weight reduction compounds are studied, Reductil (containing chemical substances) and Chinese’s weight reduction herbs (containing natural substances). Two doses for each compound are used in this research; 5mg/ml and 0.5mg/ml for Reductil, while 30mg/ml and 10mg/ml for Chinese weight reduction herbs. To evaluate the toxic effects of these compounds, the following parameters were determined which include mitotic index (cytogenetic analysis), serum FSH and LH hormones level (follicles stimulation hormone/FSH and lutenising hormone/LH) and histological examination of female mice ovaries. Control group
... Show MoreThe present study aims to identify the most and the least common teaching practices among faculty members in Northern Border University according to brain-based learning theory, as well as to identify the effect of sex, qualifications, faculty type, and years of experiences in teaching practices. The study sample consisted of (199) participants divided into 100 males and 99 females. The study results revealed that the most teaching practice among the study sample was ‘I am trying to create an Environment of encouragement and support within the classroom which found to be (4.4623). As for the least teaching practice was ‘I use a natural musical sounds to create student's mood to learn’ found to be (2.2965). The study results also in
... Show MoreThe successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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