Abstract. The libre software development model has shown how combining collective intelligence can lead to revolutionary methods that underpin major software advancements. This pap...
Bayesian networks are commonly used in cognitive student modeling and assessment. They typically represent the item-concepts relationships, where items are observable responses to ...
In this paper, we introduce a new, formal model of learning object metadata. The model enables more formal, rigorous reasoning over metadata. An important feature of the model is t...
In this poster, we will propose a framework for finding, recommending and inserting learning objects in a digital repository level, exploiting the user context that is captured fro...
Due to the information growth, distributed environments are offered as a feasible and scalable solution where Peerto-Peer networks have become more relevant. They bring many advan...
Abstract. Nowadays, engineering studies are characterized by high mobility of students, lecturers and workforce and by the dynamics of multinational companies where "classes&q...
Aldo Bongio, Jan van Bruggen, Stefano Ceri, Valent...
Abstract. L2C - Learning to Collaborate - is an ongoing research project addressing the design of effective immersive simulation-based learning experiences supporting the developme...
Abstract. Most classification methods assume that the samples are drawn independently and identically from an unknown data generating distribution, yet this assumption is violated ...
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...