CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Supporting social navigation on the World Wide Web
International Journal of Human-Computer Studies - Special issue: innovative applications of the World Wide Web
Footprints: history-rich tools for information foraging
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
EDUCO - A Collaborative Learning Environment Based on Social Navigation
AH '02 Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Applying Interactive Open Learner Models to Learning Technical Terminology
UM '01 Proceedings of the 8th International Conference on User Modeling 2001
Inspecting and Visualizing Distributed Bayesian Student Models
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
A web-based e-learning system for increasing study efficiency by stimulating learner's motivation
Information Systems Frontiers
Invoking social comparison to improve electronic brainstorming: beyond anonymity
Journal of Management Information Systems - Special section: Information technology and its organizational impact
International Journal of Human-Computer Studies
Student Models that Invite the Learner In: The SMILI:() Open Learner Modelling Framework
International Journal of Artificial Intelligence in Education
Evaluating the Effect of Open Student Models on Self-Assessment
International Journal of Artificial Intelligence in Education
International Journal of Artificial Intelligence in Education
AnnotatEd: A social navigation and annotation service for web-based educational resources
The New Review of Hypermedia and Multimedia
Toward Social Learning Environments
IEEE Transactions on Learning Technologies
Lifelong Learner Modeling for Lifelong Personalized Pervasive Learning
IEEE Transactions on Learning Technologies
Addictive links: the motivational value of adaptive link annotation
The New Review of Hypermedia and Multimedia - Adaptive Hypermedia
EC-TEL '09 Proceedings of the 4th European Conference on Technology Enhanced Learning: Learning in the Synergy of Multiple Disciplines
Open social student modeling: visualizing student models with parallel introspectiveviews
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
QuizMap: open social student modeling and adaptive navigation support with TreeMaps
EC-TEL'11 Proceedings of the 6th European conference on Technology enhanced learning: towards ubiquitous learning
IntrospectiveViews: an interface for scrutinizing semantic user models
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
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A large number of educational resources is now available on the Web to support both regular classroom learning and online learning. However, the abundance of available content produces at least two problems: how to help students find the most appropriate resources, and how to engage them into using these resources and benefiting from them. Personalized and social learning have been suggested as potential methods for addressing these problems. Our work presented in this paper attempts to combine the ideas of personalized and social learning. We introduce Progressor+, an innovative Web-based interface that helps students find the most relevant resources in a large collection of self-assessment questions and programming examples. We also present the results of a classroom study of the Progressor+ in an undergraduate class. The data revealed the motivational impact of the personalized social guidance provided by the system in the target context. The interface encouraged students to explore more educational resources and motivated them to do some work ahead of the course schedule. The increase in diversity of explored content resulted in improving students' problem solving success. A deeper analysis of the social guidance mechanism revealed that it is based on the leading behavior of the strong students, who discovered the most relevant resources and created trails for weaker students to follow. The study results also demonstrate that students were more engaged with the system: they spent more time in working with self-assessment questions and annotated examples, attempted more questions, and achieved higher success rates in answering them.