Using Large Language Models for (De-)Formalization and Natural Argumentation Exercises for Beginner's Students

TL;DR

This paper presents two systems utilizing large language models to automate the correction of formal logic translation exercises and natural language argumentation tasks for beginner students.

Contribution

It introduces novel applications of large language models for educational exercises in formal logic and argumentation, enhancing automated feedback capabilities.

Findings

Effective correction of logic translation exercises.

Automated assessment of natural language argumentation.

Potential to improve beginner students' learning experience.

Abstract

We describe two systems currently being developed that use large language models for the automatized correction of (i) exercises in translating back and forth between natural language and the languages of propositional logic and first-order predicate logic and (ii) exercises in writing simple arguments in natural language in non-mathematical scenarios.