It is important today to prepare pre-service teachers to integrate social media tools into their lessons and to teach them how to use social media as a learning environment for educational context. Based on this, an undergraduate course was designed to fulfil this need. Hence, the purpose of this study is to investigate the behaviours and perceptions of 27 pre-service teachers enrolled to a 14-week social-media enriched blended course. Facebook was used to support an out-of-class teaching and learning process. During the course, students developed educational content and were informed on how to use social media as a learning environment in an educational context. After implementation, they were asked to respond to an open-ended questionnaire related to the 14-week course process and social media usage in lessons. According to the findings, pre-service teachers stated that the use of social media tools, in addition to face-to-face learning, can enhance the dissemination of announcements, communication between students and instructor, the sharing of instructional activities, discussions, and the use and creation of multimedia tools and applications 24x7, by extending the limits of normal class hours. Most also stated that they would use Facebook for material and announcement sharing once they were in-service teachers. In addition to Facebook, they emphasised that they would also use Prezi, Glogster, MindMeister and Edmodo for their lessons and that they had learnt new concepts and social media tools during the course. They also suggested increasing the number of course hours and reducing course content per course session.
Social networks are progressively being considered as an intense thought for learning. Particularly in the research area of Intelligent Tutoring Systems, they can create intuitive, versatile and customized e-learning systems which can advance the learning process by revealing the capacities and shortcomings of every learner and by customizing the correspondence by group profiling. In this paper, the primary idea is the affect recognition as an estimation of the group profiling process, given that the fact of knowing how individuals feel about specific points can be viewed as imperative for the improvement of the tutoring process. As a testbed for our research, we have built up a prototype system for recognizing the emotions of Facebook users. Users' emotions can be neutral, positive or negative. A feeling is frequently presented in unpretentious or complex ways in a status. On top of that, data assembled from Facebook regularly contain a considerable measure of noise. Indeed, the task of automatic affect recognition in online texts turns out to be more troublesome. Thus, a probabilistic approach of Rocchio classifier is utilized so that the learning process is assisted. Conclusively, the conducted experiments confirmed the usefulness of the described approach.