A large number of educational resources is now made available on the Web to support both regular classroom learning and online learning. However, the abundance of available content produced at least two problems: how to help students to find the most appropriate resources and how to engage them into using these resources and benefit from them. Personalized and social learning have been suggested as potential ways to address these problems. This work attempts to combine the ideas of personalized and social learning by providing navigation support through an open social student modeling visualization. A series of classroom studies exploited the idea of the approach and revealed promising results, which demonstrated the personalized guidance and social visualization combined helped students to find the most relevant resources of parameterized self-assessment questions for Java programming. Thus, this dissertation extend the approach to a larger collection of learning objects for cross content navigation and verify its capability of supporting social visualization for personalized E-Learning. The study results confirm that working with the non-mandatory system, students enhanced the learning quality in increasing their motivation and engagement. They successfully achieved better learning results. Meanwhile, incorporating a mixed collection of content in the open social student modeling visualizations effectively led the students to work at the right level of questions. Both strong and weak student worked with the appropriate levels of questions for their readiness accordingly and yielded a consistent performance across all three levels of complexities. Additionally, providing a more realistic content collection on the navigation supported open social student modeling visualizations results in a uniform performance in the group. The classroom study revealed a clear pattern of social guidance, where the stronger students left the traces for weaker ones to follow. The subjective evaluation confirms the design of the interface in terms of the content organization. Students' positive responses also compliment the objective system usage data. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]