Abstract / Description of output
Computer-based logic proofs are a form of `unnatural' language discourse, but the structure and process of proof can be observed in considerable detail, and analysis is leading to a number of general insights. We have been studying how students respond to multimodal logic teaching. First, psychological measures indicate that students' pre-existing cognitive styles have a significant impact on teaching outcome. Secondly, a large corpus of proofs has been gathered via automatic logging of proof development. Frequency analysis and cluster analysis of this corpus indicate that students' cognitive styles influence the structure of their logical discourse. Our current objective is to apply further statistical methods to the proof development logs, to derive various transition frequencies, and then construct process models which explain the differences in discourse style.
Original language | English |
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Title of host publication | AAAI Spring Symposium on Empirical Methods in Discourse Interpretation and Generation |
Publisher | AAAI Press |
Pages | 113-119 |
Number of pages | 7 |
Publication status | Published - 1995 |
Event | AAAI Spring Symposium on Empirical Methods in Discourse Interpretation and Generation - Palo Alto, CA, United States Duration: 27 Mar 1995 → 29 Mar 1995 |
Symposium
Symposium | AAAI Spring Symposium on Empirical Methods in Discourse Interpretation and Generation |
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Country/Territory | United States |
City | Palo Alto, CA |
Period | 27/03/95 → 29/03/95 |
Keywords / Materials (for Non-textual outputs)
- empirical study
- frequency analysis
- cognitive style
- language discourse
- computer-based logic proof
- discourse style
- significant impact
- psychologica measure
- automatic logging
- proof development
- general insight
- considerable detail
- logic teaching
- current objective
- pre-existing cognitive style
- various transition frequency
- logical discourse
- large corpus
- process model
- statistical method
- proof development log
- cluster analysis