%0 Conference Paper %1 Webb91e %A Webb, G.I. %B Proceedings of the IJCAI Workshop W.4: Agent Modelling for Intelligent Interaction %D 1991 %E Kay, J. %E Quilici, A. %K Based Computer Feature Learning Modeling, %P 128-136 %T An Attribute-Value Machine Learning Approach To Student Modelling %X This paper describes an application of machine learning to student modelling. Unlike previous machine learning approaches to student modelling, the new approach is based on attribute-value machine learning. In contrast to many previous approaches it is not necessary for the lesson author to identify all forms of error that may be detected or to identify the possible approaches to problem solving in the domain that may be adopted. Rather, the lesson author need only identify the relevant attributes both of the tasks to be performed by the student and of the student's actions. The values of these attributes are automatically processed by the student modeler to produce the student model.

@inproceedings{Webb91e, abstract = {This paper describes an application of machine learning to student modelling. Unlike previous machine learning approaches to student modelling, the new approach is based on attribute-value machine learning. In contrast to many previous approaches it is not necessary for the lesson author to identify all forms of error that may be detected or to identify the possible approaches to problem solving in the domain that may be adopted. Rather, the lesson author need only identify the relevant attributes both of the tasks to be performed by the student and of the student's actions. The values of these attributes are automatically processed by the student modeler to produce the student model.}, added-at = {2016-03-20T05:42:04.000+0100}, audit-trail = {Paper scanned and converted to word. PDF now up}, author = {Webb, G.I.}, biburl = {https://www.bibsonomy.org/bibtex/2ab38f7e690378b8c456a0370a44a5a87/giwebb}, booktitle = {Proceedings of the {IJCAI} Workshop {W.4}: Agent Modelling for Intelligent Interaction}, editor = {Kay, J. and Quilici, A.}, interhash = {d0dae04340cb30d64e19e21e17a7be37}, intrahash = {ab38f7e690378b8c456a0370a44a5a87}, keywords = {Based Computer Feature Learning Modeling,}, location = {Sydney, Australia}, pages = {128-136}, timestamp = {2016-03-20T05:42:04.000+0100}, title = {An Attribute-Value Machine Learning Approach To Student Modelling}, year = 1991 }