Traditional education systems have developed very slowly although they have been used for centuries and cannot handle different learning styles and preparation levels. Many students who interact with one teacher who cannot answer each student's needs are identified by this system. As a result, some students may be frustrated and unable to achieve their educational opportunities. An Intelligent Tutoring System (ITS), a software that provides students with personalized instruction tailored to the style and speed of students, is of interest to teachers to improve student learning. To assess the effectiveness of ITS, a systematic review of the latest literature was performed by using carefully renovated protocols that provide data to support meta-study of the effectiveness of ITS. The research question that guides this article is: “Does ITS enhance the education of the students more than the traditional education?” One way ANOVA test, t-test, and KNIME program were performed. The results that came from this study back the conclusion that ITS significantly improves students learning more than traditional teaching methods.

Cognitive tutor --- intelligent tutoring system --- intelligent coaching --- intelligent agent system

This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to 92.19%, availability 92.375%, and reliability 100%. The proposed system managed five devices. The NSFM implemented using Java and C# languages.

هذا البحث يهدف الى اقتراح طريقة جديدة لنظام الإدارة الذاتية للاخطاء في الشبكة (NSFM) تعتمد على تقنيتين هما تقنية الوكيل الذكي لغرض دعم تلقائية مهام ادارة الخطأ والتقنية الثانية هي تقنية ادارة نوافذ الادوات القياسية (WMI) التي تحدد الخطا بشكل اسرع وبغض النظر عن نوع الموارد المستخدمة (الاجهزة). يعمل النظام المقترح لادارة الخطا على تقليل عبء سير وتبادل البيانات عبر الشبكة من خلال تقليل الطلب والاستجابة بين الخادم والزبون مما حقق وقت توقف اقل في حالة ظهور خطأ عند الزبون. تم قياس اداء النظام المقترح من خلال ثلاثة مقايس : الكفاءة و التواجدية و الموثوقية. تم تحقيق معدل كفاءة عالية بالاعتماد على الاخطاء الحاصلة في النظام وصل الى (92.19%), و التواجدية (92.375%) و الموثوقية (100%). وقد تمكن النظام من ادارة خمسة انواع من الاجهزة وقد تم استخدام لغة الجافا وC#.

Network Self-Fault Management --- Intelligent Agent --- Fault Detection --- Fault Identification --- Fault Recovery. --- ادارة الاخطاء الذاتية في الشبكة --- الوكيل الذكي --- اكتشاف الخطأ --- تحديد الخطأ --- ايجاد حل للخطأ