A Collaborative Bayesian Net Editor to Medical Learning Environments

E. Boff, C.D. Flores, M. Silva, and R.M. Vicari (Brazil)


Probabilistic Reasoning, Collaborative Editor, Intelligent Agents, Collaborative Systems, Medicine, Education.


This paper presents the Social Agent that acts in the AMPLIA’s collaborative editor in order to improve collaboration. The Social Agent supports group formation and it makes a search among students of an Intelligent Tutoring Systems (ITS) or Intelligent Learning Environment (ILE) looking for suitable students to join in a workgroup. Thus, students can help others, during a common learning task. For such, these agents takes into account some affective and social aspects of the students. Collaborative learning is changing the learning environments design. Intelligent Tutoring Systems, Multi agent Systems (MAS), and Affective Computing are techniques and resources that are been used in order to improve the individual and personalized learning. Our research group has been developing an intelligent learning environment to promote collaborative learning, the AMPLIA system. AMPLIA is an Intelligent Probabilistic Multi-agent Environment to support the diagnostic reasoning development and the diagnostic hypotheses modeling of domains with complex and uncertain knowledge, like medical area. The AMPLIA environment provides also a collaborative Bayesian Net (BN) Editor, where the Social Agent acts, to allow students build their own networks and compare them with the expert network.

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