Improving student forum responsiveness: Detecting duplicate questions in educational forums

Manal Mohania*, Liyuan Zhou, Tom Gedeon

*Corresponding author for this work

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

    Abstract

    Student forums are important for student engagement and learning in university courses but require high staff resources to moderate and answer questions. In introductory courses, the content can remain almost unchanged each year, so the questions asked in the course forums do not see a lot of variety over different iterations, which provides an opportunity for automation. This paper compiles a dataset of forum threads and meta-information of the participants from the Web Design and Development course at the Australian National University for the purposes of duplicate question detection in educational forums. A state of the art neural network model is trained on the dataset to measure its usefulness. An accuracy of 91.8% is achieved, which is on par with what is achieved on other datasets with similar features. A high performing neural network for this dataset could potentially be used to create a live system that detects and reuses answers for duplicate questions on course forums.

    Original languageEnglish
    Title of host publicationNeural Information Processing - 26th International Conference, ICONIP 2019, Proceedings
    EditorsTom Gedeon, Kok Wai Wong, Minho Lee
    PublisherSpringer
    Pages410-421
    Number of pages12
    ISBN (Print)9783030367176
    DOIs
    Publication statusPublished - 2019
    Event26th International Conference on Neural Information Processing, ICONIP 2019 - Sydney, Australia
    Duration: 12 Dec 201915 Dec 2019

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11955 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference26th International Conference on Neural Information Processing, ICONIP 2019
    Country/TerritoryAustralia
    CitySydney
    Period12/12/1915/12/19

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