Using Bayesian Networks to Manage Uncertainty in Student Modeling

By Cristina Conati, A. Gertner, Kurt VanLehn. User modeling and user-adapted interaction, 2002

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Student modeling approaches: A literature review for the last decade (2013, methodology): “In this system, also, a probabilistic student model with Bayesian networks is used in order to manage uncertainty (Conati et al., 2002).”
A review of recent advances in learner and skill modeling in intelligent learning environments (2012, methodology): “Among the best known are the ANDES Assessor (Conati et al. 2002; VanLehn et al. 2005), HYDRIVE (Mislevy and Gitomer 1995), and Zapata-Rivera and Greer’s (2004) inspectable student models.”
The Andes Physics Tutoring System: Lessons Learned (2005, result): “These results are described in ( Conati, Gertner, & VanLehn, 2002 ).”
Affect-aware tutors: recognising and responding to student affect (2009, methodology): “Additionally, machine-learning techniques are often used independent of hardware sensors to infer student cognition and affect (Conati et al., 2002; Murray and VanLehn, 2000; Baffes and Mooney, 1996; Mayo and Mitrovic, 2001).”
An Empirical Study of Online Supports among Patients (2010, unknown): “In other HMM models, Conati et al. (2002) examine students’ understanding of a math concept.”
User Models for Adaptive Hypermedia and Adaptive Educational Systems (2007, unknown): “An example of the second kind of model is the Bayesian student model for the physics domain in the tutoring system Andes [40], which divides”