The current research aims to evaluate the activities and evaluation questions implied in the content of the computer textbook for the fifth preparatory grade according to the creative thinking and developing suggestions through answering the following question: what is the percentage of creative thinking skills in the content of the computer textbook for the fifth Preparatory grade students issued by the Iraqi Ministry of Education/ Directorate General of the curriculum in the academic year (2019-2020)? The researchers followed the descriptive-analytical approach. The research community was determined by the content of the computer textbook for the fifth preparatory grade. As for the research sample, it was limited to all activities and evaluation questions implied in the textbook. To design the content analysis tool, the researcher depended on the creative thinking skills, as well as adopted the unity of the explicit idea in the analysis process. The results showed that the percentages of availability of creative thinking skills (fluency, flexibility, originality, elaboration, and sensitivity to problems) in the activities and evaluation questions implied in the content of the computer textbook are (63.27%, 14.29%, zero, 10.20 %, 12.24%) respectively. The researcher suggested developing the aforementioned skills
(86)
(88)
(3)
(7)
(5)
(4)
(4)
This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3
... Show More
The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
The main objective of this research is to use the methods of calculus ???????? solving integral equations Altbataah When McCann slowdown is a function of time as the integral equation used in this research is a kind of Volterra
In thisˑ paperˑ, we apply the notion ofˑ intuitionisticˑ fuzzyˑ n-fold KU-ideal of KU-algebra. Some types of ideals such as intuitionistic fuzzy KU-ideal, intuitionisticˑ fuzzy closed idealˑ and intuitionistic fuzzy n-fold KU-ideal are studied. Also, the relations between intuitionistic fuzzy n-fold KU-ideal and intuitionistic fuzzy KU-ideal are discussed. Furthermore, aˑ fewˑ results of intuitionisticˑ fuzzyˑ n-ˑfold KU-ideals of a KU-algebra underˑ homomorphismˑ are discussed.
(3)
(1)