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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