Leaf: Multiple-Choice Question Generation
Kristiyan Vachev, Momchil Hardalov, Georgi Karadzhov, Georgi Georgiev,, Ivan Koychev, Preslav Nakov
TL;DR
Leaf is a system that automatically generates multiple-choice questions from factual text, aiming to streamline quiz creation for educational and industrial applications, including chatbots and MOOCs.
Contribution
It introduces Leaf, a novel system for automatic multiple-choice question generation from factual text, enhancing efficiency in educational content creation.
Findings
High-quality question generation demonstrated
Applicable in educational and industrial contexts
Code and demo available online
Abstract
Testing with quiz questions has proven to be an effective way to assess and improve the educational process. However, manually creating quizzes is tedious and time-consuming. To address this challenge, we present Leaf, a system for generating multiple-choice questions from factual text. In addition to being very well suited for the classroom, Leaf could also be used in an industrial setting, e.g., to facilitate onboarding and knowledge sharing, or as a component of chatbots, question answering systems, or Massive Open Online Courses (MOOCs). The code and the demo are available on https://github.com/KristiyanVachev/Leaf-Question-Generation.
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Taxonomy
TopicsEducational Technology and Assessment · Topic Modeling · Educational Assessment and Pedagogy