• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Deriving Learner-Centric Platform Features Through Customer Review Mining
 
  • Details
  • Full
Options
2024
Conference Paper
Title

Deriving Learner-Centric Platform Features Through Customer Review Mining

Abstract
In an age where digital platforms are revolutionizing education, our study critically examines MOOCs, focusing on the nuanced interplay between platform product features and learner satisfaction. By analyzing 142,976 Coursera reviews using natural language processing (NLP) and supplementing this with data from various platforms, we uncover specific platform features to research learner satisfaction in the future. This deep dive, utilizing Latent Dirichlet Allocations (LDA) for topic modeling, reveals insights into what learners’ value in their online education journey. Thereby, we identify 32 essential features, categorized into seven structural characteristics. This research not only fills a significant gap in understanding the crucial role of platform features in shaping learner satisfaction in MOOCs but also offers insights for platform providers to act on. These insights are key to enhancing the digital learning experience, ensuring that platforms meet and exceed the evolving expectations of learners in this dynamic educational landscape.
Author(s)
Grüneke, Timo
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Mainwork
ECIS 2024, 32nd European Conference on Information Systems. Proceedings  
Conference
European Conference on Information Systems 2024  
Link
Link
Language
English
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024