Probabilistic Student Modelling to Improve Exploratory Behaviour Export

@article{bunt03, abstract = {This paper presents the details of a student model that enables an open learning environment to provide tailored feedback on a learner's exploration. Open learning environments have been shown to be beneficial for learners with appropriate learning styles and characteristics, but problematic for those who are not able to explore effectively. To address this problem, we have built a student model capable of detecting when the learner is having difficulty exploring and of providing the types of assessments that the environment needs to guide and improve the learner's exploration of the available material. The model, which uses Bayesian Networks, was built using an iterative design and evaluation process. We describe the details of this process, as it was used to both define the structure of the model and to provide its initial validation.}, address = {Hingham, MA, USA}, author = {Bunt, Andrea and Conati, Cristina}, citeulike-article-id = {4647097}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=858517}, citeulike-linkout-1 = {http://dx.doi.org/10.1023/A:1024733008280}, doi = {10.1023/A:1024733008280}, issn = {0924-1868}, journal = {User Modeling and User-Adapted Interaction}, keywords = {bayesian\_nets, bunt, conati, exploratory\_environments, intelligent\_support}, number = {3}, pages = {269--309}, posted-at = {2009-05-28 12:02:32}, priority = {0}, publisher = {Kluwer Academic Publishers}, title = {Probabilistic Student Modelling to Improve Exploratory Behaviour}, url = {http://dx.doi.org/10.1023/A:1024733008280}, volume = {13}, year = {2003} }

TY - JOUR ID - bunt03 L3 - citeulike-article-id:4647097 N2 - This paper presents the details of a student model that enables an open learning environment to provide tailored feedback on a learner's exploration. Open learning environments have been shown to be beneficial for learners with appropriate learning styles and characteristics, but problematic for those who are not able to explore effectively. To address this problem, we have built a student model capable of detecting when the learner is having difficulty exploring and of providing the types of assessments that the environment needs to guide and improve the learner's exploration of the available material. The model, which uses Bayesian Networks, was built using an iterative design and evaluation process. We describe the details of this process, as it was used to both define the structure of the model and to provide its initial validation. IS - 3 JF - User Modeling and User-Adapted Interaction SN - 0924-1868 AD - Hingham, MA, USA EP - 309 TI - Probabilistic Student Modelling to Improve Exploratory Behaviour PB - Kluwer Academic Publishers VL - 13 SP - 269 KW - bayesian_nets KW - bunt KW - conati KW - exploratory_environments KW - intelligent_support AU - Bunt, Andrea AU - Conati, Cristina PY - 2003/// UR - http://dx.doi.org/10.1023/A:1024733008280 ER -