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Electronic Proceedings in Theoretical Computer Science
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Teaching Intuitionistic and Classical Propositional Logic Using Isabelle

descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Conference object 08 Feb 2022Embargo end date: 01 Jan 2022 Denmark English Publisher:Open Publishing AssociationJournal:Electronic Proceedings in Theoretical Computer Science, volume 354, pages 71-85 (eissn: 2075-2180, Copyright policy )
Authors: Jørgen Villadsen; Asta Halkjær From; Patrick Blackburn;

doi: 10.4204/eptcs.354.6 , 10.48550/arxiv.2202.03567

arXiv: 2202.03567

Teaching Intuitionistic and Classical Propositional Logic Using Isabelle

Abstract

We describe a natural deduction formalization of intuitionistic and classical propositional logic in the Isabelle/Pure framework. In contrast to earlier work, where we explored the pedagogical benefits of using a deep embedding approach to logical modelling, here we employ a logical framework modelling. This gives rise to simple and natural teaching examples and we report on the role it played in teaching our Automated Reasoning course in 2020 and 2021.

In Proceedings ThEdu'21, arXiv:2202.02144

Country
Denmark
Related Organizations
Keywords

FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Logic in Computer Science (cs.LO)

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 4
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
Green
gold
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