Reasoning Symbolically About Partially Matched Cases

Abstract

In teaching case-based argumentation skills, the CATO program, an intelligent learning environment, guides students ' assessments of partial matches between problems and cases by generating alternative interpretations of the similarities and differences. CATO'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. 1

Cite

Text

Ashley and Aleven. "Reasoning Symbolically About Partially Matched Cases." International Joint Conference on Artificial Intelligence, 1997.

Markdown

[Ashley and Aleven. "Reasoning Symbolically About Partially Matched Cases." International Joint Conference on Artificial Intelligence, 1997.](https://mlanthology.org/ijcai/1997/ashley1997ijcai-reasoning/)

BibTeX

@inproceedings{ashley1997ijcai-reasoning,
  title     = {{Reasoning Symbolically About Partially Matched Cases}},
  author    = {Ashley, Kevin D. and Aleven, Vincent},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {1997},
  pages     = {335-341},
  url       = {https://mlanthology.org/ijcai/1997/ashley1997ijcai-reasoning/}
}