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التعلم التعاوني وأثره على التحصيل والاتجاه نحو الحاسب الآلي عند طلبة كلية التربية بجامعة بغداد
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هدفت هذه الدراسة إلى مقارنة أثر أسلوب التعلم التعاوني بالأسلوب التقليدي في التحصيل الدراسي، وعلاقته بالاتجاه نحو الحاسب الآلي عند طلبة كلية التربية بجامعة بغداد خلال دراستهم لمقرر الحاسب الآلي وقد تضمنت إجراءات الدراسة استخدام الأسلوب التجريبي، وذلك بتوزيع أربع شعب دراسية على مجموعتين: "مجموعة تجريبية" يتم تدريسها باستخدام أسلوب التعلم التعاوني، والمجموعة الثانية: "مجموعة ضابطة" يتم تدريسها بالطريقة التقليدية. وقد استخدم في هذه الدراسة مقياسان: الأول اختبار لقياس التحصيل الدراسي، والآخر استبانة لقياس الاتجاه نحو الحاسب الآلي. وقد تضمنت استبانة الاتجاه أربعة محاور، هي: الرأي تجاه الحاسب، القلق من الحاسب، والوعي بأهمية الحاسب، والخوف من دراسة المقرر. وقد تم تطبيق المقياسين مرتين: الأولى في بداية الفصل الدراسي، والذي نتج عنه عدم وجود فروق ذات دلالة إحصائية بين الطلبة سواء في معلوماتهن عن الحاسب، أو في اتجاههن نحوه، أو في خوفهن من دراسة مقرر الحاسب الآلي، ولكن ظهر تخوف كبير من قبل أغلبية أفراد العينة في محور الخوف من دراسة المقرر. أما التطبيق الثاني فكان في نهاية الفصل الدراسي، وأظهرت النتائج وجود فروق ذات دلالة إحصائية في كل من مستوى تحصيل الطلبة، وفي الثلاثة محاور الأولى من مقياس الاتجاه نحو الحاسب وذلك لصالح المجموعة التجريبية. أما المحور الرابع "الخوف من دراسة المقرر" فلم يظهر فرق ذو دلالة إحصائية بين المجموعتين يمكن إرجاعه إلى أسلوب التعلم، غير أن الفرق ظهر في ارتفاع متوسط الدرجات لأغلب أفراد العينة ما بين بداية الفصل الدراسي ونهايته، الأمر الذي أكد على أن مجرد تعلم الحاسب بغض النظر – عن الطريقة المتبعة – ساعد في تقليل الخوف من الدراسة عن الحاسب الآلي. أما الأسلوب التعاوني فكان عاملاً مساعداً في زيادة التحصيل الدراسي وبناء اتجاه جيد نحو الحاسب الآلي.

 

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Mon Jul 01 2013
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Political Sciences Journal
Towards Promoting Political Participation of Female - University Students - Field Study on Al-Quds Open University Female - Students - Rafah
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نحو تعزيز المشاركة السياسية للطالبات الجامعيات الفلسطينيات

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Wed Feb 20 2019
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Publication Date
Sun Oct 01 2017
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Publication Date
Sun Feb 25 2024
Journal Name
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Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Wed Jun 30 2021
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The Impact of the Strategic Leadership in Strategic Learning Exploratory Research at Anbar University
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Tue Nov 06 2018
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Publication Date
Thu Dec 31 2020
Journal Name
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Publication Date
Sat Jul 01 2017
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The effects of Internet use on university’s students: “A Study on a Sample of Jordanian University’s students "
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Publication Date
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