Immersive virtual reality isn’t just for gaming. It’s poised to have a big impact on education as well, giving students an opportunity to interact with content in three-dimensional learning environments. Blended learning, according to the Inn sight Institute is "a formal education program in which a student learns at least inpart through online delivery of content and instruction with some element of student' control over time, place, path and/orpace". On the other hand, there are many disadvantage found in blended learning such as the learners with low motivation or bad study habits may fall behind, and many others. So, there is an essential need to improve and develop the theory of the blended learning by using virtual reality environments and get rid of these disadvantages to develop the faceto-face learning to add a lot of features such as excitement and make it more efficient. As well as affirms clarity of the scientific content of the lecture that the student may be miss them by absent or even mentally, so student can live atmosphere the lecture again and overcome the difficulties resulting from the using blended learning or traditional learning. Firstly, this approach is applied by building a specialized website application that allow using virtual reality feature in order to measure the effectiveness of this study on students, and then a questionnaires was designed and the information result of these questionnaires impact was gathered. It is found that, the most of students were excited, active and they understand the lecture in an easy way with a high Likert Scale (4.74), but they found difficulties in using VR tools which has a low Likert scale (2.66).

Abstract:The huge explosion of information over World Wide Web forces us to use information security methods to keep it away from intruders. One of these security methods is information hiding method. Advantage of this method over other security methods is hiding existence of data using carrier to hold this data embedding inside it. Image-based information hiding represents one of widely used hiding methods due to the image capability of holding large amount of data as well as its resistance to detectable distortion. In last decades, statistical methods (types of stego-analysis methods) are used to detect existing of hidden data. Therefore, areas that have color variation (edges area) are used to hide data instead of smooth areas. In this paper, Corners points are proposed to hide data instead of edges, this to avoid statistical attacks that are used to expose hidden message. Additionally, this paper proposes clearing least significant bit (CLSB) method to retrieve data from stego-image without sending pixels' map; this will increase security of the proposed cornerbased hiding method. Experimental results show that the proposed method is robust against statistical attacks compared with edge-and sequential-based hiding methods. SVM classifier also confirms the outperformance of the proposed method over the previous methods by using Corel-1000 image dataset.