Deriving Learner-Centric Platform Features Through Customer Review Mining

Title data

Grüneke, Timo:
Deriving Learner-Centric Platform Features Through Customer Review Mining.
In: Proceedings of the 32nd European Conference on Information Systems (ECIS). - Paphos, Cyprus , 2024

Official URL:

Abstract in another language

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.

Further data

Item Type:	Article in a book
Refereed:	Yes
Keywords:	MOOC; Topic Modeling; Learner Satisfaction; Digital Education
Institutions of the University:	Faculties > Faculty of Law, Business and Economics > Department of Business Administration Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XVII - Information Systems and Value-Based Business Process Management Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XVII - Information Systems and Value-Based Business Process Management > Chair Business Administration XVII - Information Systems and Value-Based Business Process Management - Univ.-Prof. Dr. Maximilian Röglinger Research Institutions Research Institutions > Affiliated Institutes Research Institutions > Affiliated Institutes > Branch Business and Information Systems Engineering of Fraunhofer FIT Research Institutions > Affiliated Institutes > FIM Research Center for Information Management
Result of work at the UBT:	Yes
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics
Date Deposited:	10 Mar 2025 07:26
Last Modified:	10 Mar 2025 07:26
URI:	https://eref.uni-bayreuth.de/id/eprint/92691