The purpose of this study is to compare the influence of three teaching methods, as represented by problem-based learning (PBL), the PBL with lecture method, and the conventional teaching on undergraduate physics students' group work skills among bachelor’s degree physics students. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The actual sample size comprises of 122 students, who were selected randomly from the physics department, college of education in iraq. Overall, the statistical results rejected null hypothesis of this study. Thus, using the PBL without or with lecture method enhances the skills of the group work among the bachelor’s degree physics students, better than using the conventional teaching.
Аннотация
в статье рассматриваются проблемы преподавания русской литературы в иракской аудитории.. Использование литературы в преподавании иностранного языка, как правило, имеет две цели. Первая-чисто лингвистическая .. Вторая цель, однако, ассоциируется больше с экстралингвистикой и представляет собой ознакомление студентов с различными аспектами русской жизни, культуры,
... Show MoreThe research aims to determine the role of functional alienation and its impact on Job Satisfaction in General Motors Company, that were selected to apply the field side being an important company in Iraq, the problem was research with difficulty in employees adapt and their sense of alienation in their work which is reflected negatively on the level of satisfaction with work in company searched. A questionnaire was adopted as the main tool for data collection research which included (31) items distributed on (50) employees in the company selected, on a randomly chosen and based on the statistical program ready by (SPSS). Sample of this study was the most important findings of the research are the weak management of the company i
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
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