Various theories on learning have been developed with increasing frequency in the last
few decades. In tandem with this, Multiple Intelligence theory appeared as a new approach to
education as well as an important theory in the field of language learning. Gardner explains
that all human beings have different intelligence fields and a potential to develop them. These
intelligences are (verbal-linguistic, logical-mathematical, visual-spatial, musical, bodilykinesthetic,
interpersonal, intrapersonal, naturalistic, and Existential).
This study aims at investigating Multiple Intelligences of Iraqi college EFL students. To
achieve the aims of the study, a questionnaire is adopted according to Birmingham model
which includes 40 items with a five point scale (this is not like me at all, this is a bit like me,
this is sometimes like me, I am like this more often than not, I am always like this), and
covers all types of Multiple Intelligence theory. The sample of the present study consists of
the first and second year female students from Department of English Language, College of
Education for Women/ University of Baghdad.
After ensuring the validity and reliability of the questionnaire, the researchers have applied
the questionnaire on 18th of May 2014. The results show that most of the Iraqi college
students prefer music with learning, as well as, musical, intrapersonal and interpersonal
intelligences as they most frequently used and accepted. Finally, conclusions,
recommendations and suggestions for future work are put forward.
Key Terms: Multiple Intelligences Theory, Learning.
התמצית השניות היא התורה שנזכרת כי המוצאים בלשון הערבית וכך בלשונות השמיות אינם הבטויים בעלי האותיות השלושיות , אלא בעלי שתי אותיות . לפי כך אפשר להשיב השורשים השלושיים לשורשים השניים . וכל אות שנאספה בשורש שׁניוני, יהיה לפי חוק ההתפתחות הלשונית , הוספות תחילית , תוכית , סופית , עם השארת החיבור המשמעתית בין השׁניוני והשׁלשׁי כמו היא ממושכת בין השׁלשׁי והרביעי ומה שרבה ההוספות . השרשים השניים מוצאים הם: אות וה
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DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio
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