MessageLens: A Visual Analytics System to Support Multifaceted Exploration of MOOC Forum Discussions

Autor: Jian-Syuan Wong, Xiaolong “Luke” Zhang
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Visual Informatics, Vol 2, Iss 1, Pp 37-49 (2018)
Druh dokumentu: article
ISSN: 2468-502X
DOI: 10.1016/j.visinf.2018.04.005
Popis: Massive Open Online Courses (MOOCs) often provide online discussion forum tools to facilitate learner interaction and communication. Having massive forum messages posted by learners everyday, MOOC forums are regarded as an important source for understanding learners activities and opinions. However, the high volume and heterogeneity of MOOC forum contents make it challenging to analyze forum data effectively from different perspectives of discussions and to integrate diverse information into a coherent understanding of issues of concern. In this paper, we report a study on the design of a visual analytics tool to facilitate the multifaceted analysis of online discussion forums. This tool, called MessageLens, aims at helping MOOC instructors to gain a better understanding of forum discussions from three facets: discussion topic, learner attitude, and communication among learners. With various visualization tools, instructors can investigate learner activities from different perspectives. We report a case study with real-world MOOC forum data to present the features of MessageLens and a preliminary evaluation study on the benefits and areas of improvement of the system . Our research suggests an approach to analyzing rich communication contents as well as dynamic social interactions among people. Keywords: Multifaceted analysis, MOOC forum, visual analytics
Databáze: Directory of Open Access Journals