@inproceedings{c1fde23b98244f4a9c82e0da8ff162e0,
title = "Workshop on integrated learning analytics of MOOC post-course development",
abstract = "MOOC research is typically limited to evaluations of learner behavior in the context of the learning environment. However, some research has begun to recognize that the impact of MOOCs may extend beyond the confines of the course platform or conclusion of the course time limit. This workshop aims to encourage our community of learning analytics researchers to examine the relationship between performance and engagement within the course and learner behavior and development beyond the course. This workshop intends to build awareness in the community regarding the importance of research measuring multi-platform activity and long-term success after taking a MOOC. We hope to build the community's understanding of what it takes to operationalize MOOC learner success in a novel context by employing data traces across the social web.",
keywords = "Career development, Learning analytics, Learning outcomes, Long-term learning development, Massive online open courses",
author = "Yuan Wang and Dan Davis and Guanliang Chen and Luc Paquette",
year = "2017",
month = mar,
day = "13",
doi = "10.1145/3027385.3029430",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "506--507",
booktitle = "LAK 2017 Conference Proceedings - 7th International Learning Analytics and Knowledge Conference",
note = "7th International Conference on Learning Analytics and Knowledge, LAK 2017 ; Conference date: 13-03-2017 Through 17-03-2017",
}