Background: Scientific education aims to be inclusive and to improve students learning achievements, through appropriate teaching and learning. Problem Based Learning (PBL) system, a student centered method, started in the second half of the previous century and is expanding progressively, organizes learning around problems and students learn about a subject through the experience of solving these problems.Objectives:To assess the opinions of undergraduate medical students regarding learning outcomes of PBL in small group teaching and to explore their views about the role of tutors and methods of evaluation. Type of the study: A cross-sectional study.Methods: This study was conducted in Kerbala Medical Colleges among second year students. A self-administered questionnaire was prepared to evaluate the newly applied teaching system. The study analysis included simple descriptive analysis and determining association through t-test, chi square test and regression analysis and using structural equation models to determine simultaneous association between different students’ demographic characteristics and potential predictors using SPSS-20 and Amos software at a significance level of < 0.05.Results:A total of 131 undergraduate medical students participated in the study with a response rate of 94%. The majority (93%) have indicated that PBL strategy contributed effectively to their knowledge development with a similar majority (92%) considering PBL successful new teaching method. About 86% reported that would choose PBL rather than conventional method and also 86% would advise PBL for others. Similarly, high majority indicated that various PBL activities are essential. Regarding the tutors’ role in PBL, the majority (92%) indicated that this role was positive and fundamental. According to two thirds (68%) of participants PBL application in Kerbala Medical college was very good application while a higher majority described various PBL sessions as successful and positive and fundamental role of tutors was stressed by most students.Conclusions: This study highlighted the benefits of soliciting student impressions of effective small group teaching. The students’ emphasized group atmosphere and facilitation skills of tutor in learning.Key words: Problem Based Learning, Medical Education, Small Group Teaching, Team Based Learning, Kerbala Medical College
The current study aims to develop a proposed educational program based on augmented reality (AR) technology, in addition to assessing its effectiveness in developing research and historical imagination skills of the Humanities Track's female students at the secondary stage, as well as assessing the correlative and predictive relationships between the amount of growth for the two dependent variables. To achieve this, a secondary school in the city of Makkah Al-Mukarramah was chosen, and an available random sample of (30) female students from the study population was selected. The quasi-experimental approach was followed by this study, particularly one group design. In addition, two tools were used to collect study data, namely: a test of
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This research is designed to estimate potential protective effect of vinpocetine on neurotoxicity stimulated by lead acetate in rats.
Eighteen adult rats of both sexes were randomly enrolled into three groups. Each group includes 6 rats as followings: Group I- Rats were given 0.3ml normal saline solution orally; then intraperitoneal injection of 100μl of the normal saline was given 1h later; this group was considered as control. Group II- Rats were given an intraperitoneal injection of 20mg/kg lead acetate
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... Show MoreMany managers in geometrical and technical organizations prefer to deal with quantitative values to choose between the available options and choose the best alternative to avoid randomization and bias in decision making. One of them Baghdad Water Department, which seeks to develop the quality of its product (drinking water) and achieve its objectives under increasing growing population and the demand for water, Some of TQM tools, especially the statistical, have this ability because there is chance to use historical data and experiment of employees in Application . Two statistical tools were applied: the nominal group technique, matrix data analysis technique as well as the brainstorming tool to search for the best o
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... Show MoreOften times, especially in practical applications, it is difficult to obtain data that is not tainted by a problem that may be related to the inconsistency of the variance of error or any other problem that impedes the use of the usual methods represented by the method of the ordinary least squares (OLS), To find the capabilities of the features of the multiple linear models, This is why many statisticians resort to the use of estimates by immune methods Especially with the presence of outliers, as well as the problem of error Variance instability, Two methods of horsepower were adopted, they are the robust weighted least square(RWLS)& the two-step robust weighted least square method(TSRWLS), and their performance was verifie
... Show MoreLinear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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