Evaluation of an educational training platform using text mining

Nikolaos Spatiotis, Iosif Mporas, Isidoros Perikos, Michael Paraskevas

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Educational data mining (EDM) is an important research area that implements and develops methods and statistical techniques for discovering new insights in order to improve the performance of the education system. Collecting and analyzing data makes it possible to do new discoveries and test cases about learners and teachers. Analyzing feedback using text mining and sentiment/opinion analysis techniques, the learners and teachers opinions are categorized into positive or negative. Feedback can be collected in a variety of ways. In this paper, a large number of feedback and comments from learners who attended e-learning, life-long courses were collected from questionnaires. We present an opinion mining system, which is used to analyze automatically and classify these free-text user comments according to their polarity.

    Original languageEnglish
    Title of host publicationProceedings - 10th Hellenic Conference on Artificial Intelligence, SETN 2018
    PublisherACM Press
    ISBN (Electronic)9781450364331
    DOIs
    Publication statusPublished - 9 Jul 2018
    Event10th Hellenic Conference on Artificial Intelligence, SETN 2018 - Patras, Greece
    Duration: 9 Jul 201812 Jul 2018

    Publication series

    NameACM International Conference Proceeding Series

    Conference

    Conference10th Hellenic Conference on Artificial Intelligence, SETN 2018
    Country/TerritoryGreece
    CityPatras
    Period9/07/1812/07/18

    Keywords

    • Educational Data
    • Machine Learning
    • Opinion Mining
    • Sentiment Analysis
    • Text Mining

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