Question Generation and Adaptation Using a Bayesian Network of the Learner’s Achievements

M. Wißner, F. Linnebank, J. Liem, B. Bredeweg, E. André

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

This paper presents a domain independent question generation and interaction procedure that automatically generates multiple-choice questions for conceptual models created with Qualitative Reasoning vocabulary. A Bayesian Network is deployed that captures the learning progress based on the answers provided by the learner. The likelihood of concepts being known or unknown on behalf of the learner determines the focus, and the question generator adjusts the contents of its questions accordingly. As a use case, the Quiz mode is introduced.
Original languageEnglish
Title of host publicationArtificial Intelligence in Education
EditorsH.C. Lane, K. Yacef, J. Mostow, P. Pavlik
PublisherSpringer
Pages729-732
Number of pages4
ISBN (Print)9783642391118
DOIs
Publication statusPublished - 2013
Externally publishedYes

Publication series

NameLecture Notes in Computer Science
PublisherSpringer

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