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Register a new userاستخدام أساليب تكنولوجيا التعليم في التربية القرآنية و أثر ذلك على تعلم الفئات المستهدفة
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Damascus University ورقة بحثية
Publication date
2007
fields
Education
and research's language is
العربية
Authors
محمد عطا مدني( باحث )
Created by
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هدفت هذه الدراسة إلى التعرف على أساليب التربية القرآنية التـي اسـتخدمت فـي تربيتها للبشر تقنيات معينة، يمكن أن نعتبرها الآن ضمن مجال دراسات و أبحاث علم تكنولوجيا التعليم، و كذلك التعرف على المواقف التعليمية التي جاءت هذه الأساليب في إطارها، و تحليلها تربويا لمعرفة أثر استخدام هذه التقنيات على الفئة المستهدفة.
No English abstract
References used
اسكندر، كمال يوسف وغزاوى، محمد ذيبان: مقدمة في التكنولوجيا التعليمية، ط 1، مكتبة الفلاح الكويت، 1994 م.
الحمصي، محمد حسن: تفسير وبيان مفردات القرآن، دار الرشيد، دمشق، بيروت 1984 م.
الصوفي، عبد الله: معجم التقنيات التربوية، الطبعة الأولى، دار المسيرة عمان، 1997 م.
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This research aimed at investigating the effect of using computer on
the achievement of the students in curricula and teaching methods of
Islamic education in AL-alBayt University. The sample of the study
consisted of all the students in the curri
cula and teaching methods of
Islamic education course in Al-alBayt University in academic
2006/2007, and their numbers were (80) male and female students. The
sample consisted of (12) male and (28) female students who were taught
by using computer (experimental group),(13) male and (27) female
students who were taught by using traditional method (control group).
This study aimed at identifying the impact of information technology use on the
student's performance amongst Tishreen University faculties, and identifying which factors
relate to information technology use have contributed to the differences and
variations in
student's performance. Consequently, developing a mathematical model for classifying
students' performance using discriminant analysis.
The most important findings of this research are: There is a significant classification
impact of the availability of the following factors: sources and scientific references,
computing laboratories, the Internet, computing curriculum, tutors followed training
courses in student's performance classification. The findings showed that there is no
significant classification impact of the following two factors: foreign language proficiency
and the availability of data show facilities on the student's performance classification.
In addition, three discriminant functions are obtained which reflect student's
performance. Furthermore, the developed model classified studied sample members
correctly with 70.2%, which reflect a significant impact of the developed model on
classifying student's performance.
يهدف البحث إلى تحقيق الأهداف الآتية :
.1 التعرف على مستوى استخدام تكنولوجيا المعلومات في شركة الأمل لصناعة الادوية.
.2 التعرف على واقع أداء الشركة من منظور الاداء المتوازن.
.3 توضيح أثر استخدام تكنولوجيا المعلومات في أداء الشركة.
.4 وضع بعض الاقت
راحات و التوصيات على ضوء النتائج التي سيسفر عنها البحث و وضع
المقترحات اللزمة لتحسين دور تكنولوجيا المعلومات في تحسين الأداء للشركة
المدروسة .
This study aimed to determine the impact of the use of interactive
teaching method on achievement in Education for the National Socialist
eighth grade students from the stage of basic education. In Syrian Arab
Republic, Damascus Countryside Area G
houta Timor.
The study relied on the experimental method in order to detect the
impact of using interactive teaching method on achievement for eighth
grade students from the stage of basic education in schools as National
Socialism.
Non-autoregressive Transformer is a promising text generation model. However, current non-autoregressive models still fall behind their autoregressive counterparts in translation quality. We attribute this accuracy gap to the lack of dependency model
ing among decoder inputs. In this paper, we propose CNAT, which learns implicitly categorical codes as latent variables into the non-autoregressive decoding. The interaction among these categorical codes remedies the missing dependencies and improves the model capacity. Experiment results show that our model achieves comparable or better performance in machine translation tasks than several strong baselines.
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