Using bayesian networks and parameterized questions in independent study

The teaching paradigm is changing from a traditional model of teachers as suppliers of knowledge and toward a model of teachers as advisers who carefully observe students, identify their learning needs, and help them in their independent study. In this new paradigm, computers and communication technology can be effective, not only as means for knowledge transmission, but also as tools for automatically providing feedback and diagnosis in the learning process. We present an approach integrating parameterized questions from two computer systems (Megua and PmatE), combined with a Web application (Siacua) implementing a Bayesian user model, using already many hundreds of questions from each of the two systems. Our approach allows the students a certain level of independence and provides some orientation in their independent study, by giving feedback about answers to questions and also about the general progress in the study subject. This progress is shown in the form of progress bars computed by Bayesian networks where nodes represent “concepts” and knowledge evidences. Teachers use Megua for creating and organizing their own database of (parameterized) questions, make them available for students, and for seeing the progress of each student or class in every topic being studied