The study aimed to identify the degree of availability of design Thinking Indicators in The content of the Arabic Language Curricula at the secondary stage in the Syrian Arab Republic; to achieve the goal of the study. The researcher used the Descriptive Approach based on the analysis method according to the Cognitive Theory. The study tools consist of a list of Design Thinking Indicators and a Content Analysis Tool. The researcher completed the Validity and Reliability procedures for the tools. After applying them, the results of the study resulted in the following: Greater Interest than other sub-skills. The results also showed a Divergence of care for the sub-skills and the Difference in their recurrence rate, and the Omission of some sub-skills that did not have any opportunity to be trained on, sub-indicators of Design Thinking.
Research summary
Praise be to God, Lord of the worlds, and prayers and peace be upon the one who was the most eloquent of people in language and the most eloquent of them in eloquence, our Master Muhammad (peace and blessings of God be upon him).
To proceed... There is no doubt that many studies have preceded me in talking about chalk, each according to his own destination and view, and what I do not deny is that I benefited a lot from it, and it provided me with a lot of valuable information, and I liked to be one of those study pens, trying as much as possible To add something new and different in the study, far from similarity and repetition. Especially in the Abbasid study.
The babble in the Abbasid society was d
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... Show MoreThis paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different
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