Faces are a unique feature of human being that can detect a great deal of information about age, health, personalities and feelings. Facial Expressions are the main sources in determining the internal impressions of the individual. RealTime system for facial expression recognition is able to detect and locate human faces in image sequences obtained in real environments then extracts expression features from these images finally recognize facial expressions. In this paper, the proposed system presents a real-time system for facial expression recognition that aims to recognize 8 basic facial expressions of students: anger, disgust, fear, happy, nervous, sad, surprise and natural inside E-learning environment. The primary objective is to use k-NN and SVM classifiers to test the efficiency of the proposed system and compared the results of them. There are some techniques has been used in this study for facial expression recognition such as Viola-Jones approaches to detect a face from images, Gabor Feature approach to extract features, and Principal Component Analysis (PCA) to select features and k-NN, SVM classifiers to recognize expressions from facial image.. The result showed that the SVM classifier has the best recognition rate in general thank-NN classifier. From these results, it can say that SVM classifier is more suitable for recognition of facial expression in a real-time system.
Abstract-Mobile computing is rapidly transforming the world in which we live, with the advent of iPhones, iPads, tablet computers, and Android smartphones. M-learning in the podcast form (MPF) is a recent development forconveying coursecontent to students in higher education. Context-aware technologies use temporal and environmental information to determine context. Thisstudy presents a theoretical framework for using context awareness, M-learning in the podcast forminvestigate the effectiveness of using MPF engagement with context-aware technology in Teaching and Learning a multimedia course. The framework is based on two principal dimensions (MPF andcontext-aware technology), and it contributes to support researchers in e-learning and ubiquitous learning. The study was conducted onstudents (n = 42) enrolled ina multimedia course (IS 450) at QassimUniversity.After finishing the course, theycompleted an online survey to give their feedback on the effectiveness of using MPF with context-aware technology.The results indicate that learners had a positive attitude towards usingMPF with context awarenesstechnology, and that they considered it a great way to develop their knowledge and receive course information.This study demonstrates the ability of context-aware technology to enhance the behaviour of learners by using m-learning in the podcast form.
The current research aims to use expert systems techniques to predict the training needs of trainees based on several factors related to the functional status of each employee (group, quality, job, training courses), which are essential factors in this forecasting process; because of the diversity of the training needs in light of the job conditions, technological and international development. So, the hold makers are imposed to identify these needs which are determined as the most important processes lead to success the training process. In this paper, three prediction algorithms were used: Bagging, NaviaBayes, and Neural Network to predict the training needs of the trainees in order to support and decision-making among the decision makers in education and increase the accuracy as well as the effectiveness of the training courses. The dataset consisted of 334 cases. The results of the experiments showed that the Bagging algorithm achieved the better accuracy against the rest of the algorithms.
Computer simulation programs are the most modern trend in electronic training systems, which aim at putting the trainee in flexible situations, imitating the actual training situations in terms of interacting with the content. It is also concerned with the proper representation of performances and with procedures that are characterized by simplicity and ease in light of specific rules and consistent with the trainee's own abilities which help to acquire the skills. Therefore, the current research aims at preparing a flexible e-training simulation model in the field of animation based on the interaction between the variable of the display speed pattern (slow-medium-fast) and the information view pattern (previous-next) and measuring the impact of interaction between them on the development of 3D animation skills for computer teachers. The research depended on The Experimental Approach and a sample of (30) computer teachers who were distributed randomly to (6) experimental groups according to the experimental design of the research and its independent variables. The findings are that there are statistically significant differences between the means of the total scores of the Experimental Group in the skill performance which is associated with animation design skills. These differences are due to the interaction between the display speed (slowmedium-fast) and the view pattern within the flexible etraining simulation model for the group which has dealt with the fast-speed simulation model and the previous training situation. This has made the group achieve the highest grades in terms of performance skill compared to other groups.
Abstract-Objective exams (OE) plays a major role in educational assessment as well as in electronic learning. The main problem in the traditional system of exams is a low quality of questions caused by some human factors, such as the traditional method for the development of the exam covers a narrow scope of curriculum topics. This does nothing for the separation of teaching process about the examination process. In this study we present a framework that generates three types of Objective exams questions (multiple choice questions (MCQ), true-false question (T/FQ), and complete Questions (CQ) from paragraphs of electronic course. The proposed framework consists of a lot of main stages, it uses both of the natural language processing (NLP) techniques to generate three types of questions (GFQ, T/FQ, and MCQ), and exam maker (EM), it uses the generated questions to produce the objective exams. The proposed system was evaluated by the extent of its ability to generate multiple objective questions. The questions that have been generated from the proposed system was presented to the three of the arbitrators specialists in the field of computer networks to express an opinion on the extent of their relationship to E-course and the accuracy of linguistic and scientific formulation. The results of the study showed an increase in the accuracy and number of the objective exams that were generated through the proposed system compared to the accuracy and number of the exams created by the traditional system this proves the efficiency of the proposed system.
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