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Blended learning models that combine face-to-face and online learning are of great importance in modern higher education. However, their development should be in line with the recent changes in e-learning that emphasize a student-centered approach and use tools available on the Web to support the learning process. This paper presents research on implementing a contemporary blended learning model within the e-course "Hypermedia Supported Education". The blended model developed combines a learning management system (LMS), a set of Web 2.0 tools and the E-Learning Activities Recommender System (ELARS) to enhance personalized online learning. As well as incorporating various technologies, the model combines a number of pedagogical approaches, focusing on collaborative and problem-based learning, to ensure the achievement of the course learning outcomes. The results of the comparative study show the effectiveness of the proposed model in that students who performed personalized collaborative e-learning activities achieved better course results. These findings encourage the further application of the model to other computer science courses. Index Terms-Blended learning model, collaborative learning, recommender systems, Web 2.0. Natasa Hoic-Bozic (M'05) received the B.S. degree in mathematics and information science from the University of Rijeka, Rijeka, Croatia, in 1990, the M.S. degree in computer and information science from the University of Ljubljana, Slovenia, in 1997, and the Ph.D. degree in computing from the Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia, in 2002.She is currently an Associate Professor and Vice Head of the Department of Informatics, University of Rijeka. Her main research interests are in the fields of technology enhanced learning (e-learning), adaptive hypermedia, recommender systems, multimedia systems, blended learning approaches, and Web 2.0 tools for teaching and learning.

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The paper presents the work-in-progress with the aim to develop recommender system for personalization of activities in e-learning 2.0 environment. The main components of the proposed system are activity, student and group models, and recommender module. Activity model will be used for learning design representation and will include items that could be recommended to students: e-tivities, possible collaborators, tools, and advices. To provide recommendations tailored to the student's and group's characteristics, an important component of the system will include student and group models. The emphasis of the research is on the procedures for assessing the student's (group's) activity level based on the data collected from the third party services (Web 2.0 tools). Student's model will also represent knowledge level and preferences. The recommender module, as third component of the system, will include original pedagogical rules together with the algorithms that adapt known recommendations techniques to the educational context.