Developement of Bayesian Networks from Unified Modeling Language for Learner Modelling

Development of Bayesian Networks from Unified Modeling Language Artifacts

This paper examines how Bayesian Networks can be generated from development artifacts intrinsic in the Unified Process. The Unified Software Development Process models the relationship between functional requirements in the Use-Case model. These relationships are expanded in the Analysis Model and a clear mapping to design components is created. By exploiting the relationships intrinsic in the ...

Learner Modeling Based on Bayesian Networks

The work presented in this chapter lies within Learner modeling in an adaptive ed‐ ucational system construed as a computational modeling of the learner. All actions of the learner in a learning situation on an adaptive hypermedia systems are not limited to valid or invalid actions (true and false), but they are a set of actions that characterize the learning path of his formation. Thus, we can...

Dynamic Bayesian Networks for Language Modeling

Context and learner modelling for the mobile foreign language learner

Given the growing use of mobile devices, there is now increasing interest in the potential for supporting the mobile learner. However, there remains much research to be undertaken, to Wnd eVective ways of facilitating learning with mobile devices. This paper considers how to support the mobile language learner using a handheld computer. It introduces TenseITS, a language learning environment th...

Modeling Learner Affect with Theoretically Grounded Dynamic Bayesian Networks

Evidence of the strong relationship between learning and emotion has fueled recent work in modeling affective states in intelligent tutoring systems. Many of these models are based on general models of affect without a specific focus on learner emotions. This paper presents work that investigates the benefits of using theoretical models of learner emotions to guide the development of Bayesian n...