Macro MOOC learning analytics: exploring trends across global and regional providers
Name
multi-platform-analytics-LAK-pre-print.pdf
Description
Accepted version
Size
3.66 MB
Format
Adobe PDF
Checksum (MD5)
f3c23a5748606d45ab8d815ba8656322
Author(s)
Ruipérez-Valiente, José A
Jenner, Matt
Staubitz, Thomas
Li, Xitong
Rohloff, Tobias
Halawa, Sherif
Turro, Carlos
Cheng, Yuan
Zhang, Jiayin
Despujol, Ignacio
Date Issued
2020
Journal
ACM International Conference Proceeding Series
Publisher
ACM
Citation
Ruipérez-Valiente, José A, Jenner, Matt, Staubitz, Thomas, Li, Xitong, Rohloff, Tobias et al. 2020. "Macro MOOC learning analytics: exploring trends across global and regional providers." ACM International Conference Proceeding Series.
Version
Author's final manuscript
Abstract
© 2020 Association for Computing Machinery. Massive Open Online Courses (MOOCs) have opened new educational possibilities for learners around the world. Most of the research and spotlight has been concentrated on a handful of global, English-language providers, but there are a growing number of regional providers of MOOCS in languages other than English. In this work, we have partnered with thirteen MOOC providers from around the world. We apply a multi-platform approach generating a joint and comparable analysis with data from millions of learners. This allows us to examine learning analytics trends at a macro level across various MOOC providers, with a goal of understanding which MOOC trends are globally universal and which of them are context-dependent. The analysis reports preliminary results on the differences and similarities of trends based on the country of origin, level of education, gender and age of their learners across global and regional MOOC providers. This study exemplifies the potential of macro learning analytics in MOOCs to understand the ecosystem and inform the whole community, while calling for more large scale studies in learning analytics through partnerships among researchers and institutions.
MIT Department
Massachusetts Institute of Technology. Program in Comparative Media Studies/Writing
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3375462.3375482
