LogicLearner: A Tool for the Guided Practice of Propositional Logic Proofs
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arXiv
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| Auteurs principaux: | , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866910892289949696 |
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| author | Inamdar, Amogh Macar, Uzay Vazirani, Michel Tarnow, Michael Mustapha, Zarina Dittren, Natalia Sadeh, Sam Verma, Nakul Salleb-Aouissi, Ansaf |
| author_facet | Inamdar, Amogh Macar, Uzay Vazirani, Michel Tarnow, Michael Mustapha, Zarina Dittren, Natalia Sadeh, Sam Verma, Nakul Salleb-Aouissi, Ansaf |
| contents | The study of propositional logic -- fundamental to the theory of computing -- is a cornerstone of the undergraduate computer science curriculum. Learning to solve logical proofs requires repeated guided practice, but undergraduate students often lack access to on-demand tutoring in a judgment-free environment. In this work, we highlight the need for guided practice tools in undergraduate mathematics education and outline the desiderata of an effective practice tool. We accordingly develop LogicLearner, a web application for guided logic proof practice. LogicLearner consists of an interface to attempt logic proofs step-by-step and an automated proof solver to generate solutions on the fly, allowing users to request guidance as needed. We pilot LogicLearner as a practice tool in two semesters of an undergraduate discrete mathematics course and receive strongly positive feedback for usability and pedagogical value in student surveys. To the best of our knowledge, LogicLearner is the only learning tool that provides an end-to-end practice environment for logic proofs with immediate, judgment-free feedback. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_19280 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | LogicLearner: A Tool for the Guided Practice of Propositional Logic Proofs Inamdar, Amogh Macar, Uzay Vazirani, Michel Tarnow, Michael Mustapha, Zarina Dittren, Natalia Sadeh, Sam Verma, Nakul Salleb-Aouissi, Ansaf Discrete Mathematics Artificial Intelligence Human-Computer Interaction The study of propositional logic -- fundamental to the theory of computing -- is a cornerstone of the undergraduate computer science curriculum. Learning to solve logical proofs requires repeated guided practice, but undergraduate students often lack access to on-demand tutoring in a judgment-free environment. In this work, we highlight the need for guided practice tools in undergraduate mathematics education and outline the desiderata of an effective practice tool. We accordingly develop LogicLearner, a web application for guided logic proof practice. LogicLearner consists of an interface to attempt logic proofs step-by-step and an automated proof solver to generate solutions on the fly, allowing users to request guidance as needed. We pilot LogicLearner as a practice tool in two semesters of an undergraduate discrete mathematics course and receive strongly positive feedback for usability and pedagogical value in student surveys. To the best of our knowledge, LogicLearner is the only learning tool that provides an end-to-end practice environment for logic proofs with immediate, judgment-free feedback. |
| title | LogicLearner: A Tool for the Guided Practice of Propositional Logic Proofs |
| topic | Discrete Mathematics Artificial Intelligence Human-Computer Interaction |
| url | https://arxiv.org/abs/2503.19280 |