Workshop on Integrated Learning Analytics of MOOC Post-Course Development

Yuan  Wang; Daniel Davis; Guanliang Chen; Luc  Paquette

doi:10.1145/3027385.3029430

Workshop on Integrated Learning Analytics of MOOC Post-Course Development

Yuan Wang, Daniel Davis, Guanliang Chen, Luc Paquette

Web Information Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

3 Citations (Scopus)

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

Original language	English
Title of host publication	LAK 2017 Conference Proceedings of the 7th International Learning Analytics and Knowledge Conference
Place of Publication	New York, NY
Publisher	Association for Computer Machinery
Pages	506-507
Number of pages	2
ISBN (Electronic)	978-1-4503-4870-6
DOIs	https://doi.org/10.1145/3027385.3029430
Publication status	Published - 2017
Event	LAK 2017: 7th International Conference on Learning Analytics and Knowledge - Vancouver, BC, Canada Duration: 13 Mar 2017 → 17 Mar 2017 Conference number: 7 http://lak17.solaresearch.org/

Conference

Conference	LAK 2017
Abbreviated title	LAK'17
Country/Territory	Canada
City	Vancouver, BC
Period	13/03/17 → 17/03/17
Internet address	http://lak17.solaresearch.org/

Keywords

Learning analytics
massive online open courses
long-term learning development
learning outcomes
career development

Access to Document

10.1145/3027385.3029430

Cite this

@inproceedings{49c10b9923cc4456a4a38daece7694aa,

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 = "Learning analytics, massive online open courses, long-term learning development, learning outcomes, career development",

author = "Yuan Wang and Daniel Davis and Guanliang Chen and Luc Paquette",

year = "2017",

doi = "10.1145/3027385.3029430",

language = "English",

pages = "506--507",

booktitle = "LAK 2017 Conference Proceedings of the 7th International Learning Analytics and Knowledge Conference",

publisher = "Association for Computer Machinery",

note = "LAK 2017 : 7th International Conference on Learning Analytics and Knowledge, LAK'17 ; Conference date: 13-03-2017 Through 17-03-2017",

url = "http://lak17.solaresearch.org/",

}

Wang, Y, Davis, D, Chen, G & Paquette, L 2017, Workshop on Integrated Learning Analytics of MOOC Post-Course Development. in LAK 2017 Conference Proceedings of the 7th International Learning Analytics and Knowledge Conference. Association for Computer Machinery, New York, NY, pp. 506-507, LAK 2017, Vancouver, BC, Canada, 13/03/17. https://doi.org/10.1145/3027385.3029430

Workshop on Integrated Learning Analytics of MOOC Post-Course Development. / Wang, Yuan ; Davis, Daniel; Chen, Guanliang et al.
LAK 2017 Conference Proceedings of the 7th International Learning Analytics and Knowledge Conference. New York, NY: Association for Computer Machinery, 2017. p. 506-507.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Workshop on Integrated Learning Analytics of MOOC Post-Course Development

AU - Wang, Yuan

AU - Davis, Daniel

AU - Chen, Guanliang

AU - Paquette, Luc

N1 - Conference code: 7

PY - 2017

Y1 - 2017

N2 - 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

AB - 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

KW - Learning analytics

KW - massive online open courses

KW - long-term learning development

KW - learning outcomes

KW - career development

UR - https://dl.acm.org/citation.cfm?id=3029430

U2 - 10.1145/3027385.3029430

DO - 10.1145/3027385.3029430

M3 - Conference contribution

SP - 506

EP - 507

BT - LAK 2017 Conference Proceedings of the 7th International Learning Analytics and Knowledge Conference

PB - Association for Computer Machinery

CY - New York, NY

T2 - LAK 2017

Y2 - 13 March 2017 through 17 March 2017

ER -

Workshop on Integrated Learning Analytics of MOOC Post-Course Development

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Conference

Keywords

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