%0 Conference Paper %1 Webb87b %A Webb, G. I. %B Proceedings of the First Australian Joint Conference on Artificial Intelligence (AI'87) %C Sydney %D 1987 %E Gero, J. %E Sudweeks, F. %I The University of Sydney Printing Service %K Based Computer Learning %P 488-502 %T Domain and Tutoring Knowledge in Computer-Aided Learning %X Previous approaches to the utilisation of expertise in computer-aided learning have emphasised expertise in the subject domain. By contrast, this paper details an approach that emphasises tutoring expertise and only relies on minimal domain expertise. This has several advantages. The intelligent use of restricted domain expertise enables the detailed evaluation of the students' understanding of the domain. This permits the provision of very flexible tuition that uniquely adjusts to each student's understanding of the domain. Further, due to the restricted nature of the domain knowledge that is required, the developmental overheads associated with a lesson are minimal. Finally, the type of domain knowledge required has a well defined semantics further enabling its intelligent manipulation. The approach described is domain independent. This paper describes the general system architecture, the knowledge representation formalism used and the tutoring strategies that are employed.

@inproceedings{Webb87b, abstract = {Previous approaches to the utilisation of expertise in computer-aided learning have emphasised expertise in the subject domain. By contrast, this paper details an approach that emphasises tutoring expertise and only relies on minimal domain expertise. This has several advantages. The intelligent use of restricted domain expertise enables the detailed evaluation of the students' understanding of the domain. This permits the provision of very flexible tuition that uniquely adjusts to each student's understanding of the domain. Further, due to the restricted nature of the domain knowledge that is required, the developmental overheads associated with a lesson are minimal. Finally, the type of domain knowledge required has a well defined semantics further enabling its intelligent manipulation. The approach described is domain independent. This paper describes the general system architecture, the knowledge representation formalism used and the tutoring strategies that are employed.}, added-at = {2016-03-20T05:42:04.000+0100}, address = {Sydney}, audit-trail = {Reconstructed paper posted}, author = {Webb, G. I.}, biburl = {https://www.bibsonomy.org/bibtex/26738454f2181a6067454c445f60986cf/giwebb}, booktitle = {Proceedings of the First Australian Joint Conference on Artificial Intelligence (AI'87)}, editor = {Gero, J. and Sudweeks, F.}, interhash = {f2890f8fa8f5f6b7ddeaa0567b43f24a}, intrahash = {6738454f2181a6067454c445f60986cf}, keywords = {Based Computer Learning}, location = {Sydney, Australia}, pages = {488-502}, publisher = {The University of Sydney Printing Service}, timestamp = {2016-03-20T05:42:04.000+0100}, title = {Domain and Tutoring Knowledge in Computer-Aided Learning}, year = 1987 }