Reasoning Symbolically About Partially Matched Cases
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. Computer-aided Education. Pages 335-340.
Abstract
In teaching case-based argumentation skills, the CA TO program, an intelligent learning environment, guides students' assessments of partial matches between problems and cases by generating alternative interpretations of the similarities and differences. CA TO's Factor Hierarchy captures information about the significance of similarities and differences given the normative purposes of the domain classification. Its algorithms for emphasizing or downplaying significance tailor interpretations to the comparison context, block interpretations strongly contradicted by other factors and strategically determine how and how abstractly to characterize a difference. An empirical evaluation confirmed CATO's effectiveness in teaching basic argumentation skills.
@inproceedings{ijcai1997p50,
title = {Reasoning Symbolically About Partially Matched Cases},
author = {Ashley, Kevin D. and Aleven, Vincent},
booktitle = {Proceedings of the Fifteenth International Joint Conference on
Artificial Intelligence, {IJCAI-97}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Martha E. Pollack},
pages = {335--340},
year = {1997},
note = {Computer-aided Education},
url = {https://ijcai.org/proceedings/1997/50},
}
TY - CPAPER TI - Reasoning Symbolically About Partially Matched Cases AU - Ashley, Kevin D. AU - Aleven, Vincent T2 - Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97 PB - International Joint Conferences on Artificial Intelligence PY - 1997 SP - 335 EP - 340 UR - https://ijcai.org/proceedings/1997/50 ER -Copied
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