Understanding MOOC students: Motivations and behaviours indicative of MOOC completion

B. K. Pursel; L. Zhang; K. W. Jablokow; G. W. Choi; D. Velegol

doi:10.1111/jcal.12131

Understanding MOOC students: Motivations and behaviours indicative of MOOC completion

B. K. Pursel, L. Zhang, K. W. Jablokow, G. W. Choi, D. Velegol

Administration, Leadership & Technology

Research output: Contribution to journal › Article › peer-review

Abstract

Massive open online courses (MOOCs) continue to appear across the higher education landscape, originating from many institutions in the USA and around the world. MOOCs typically have low completion rates, at least when compared with traditional courses, as this course delivery model is very different from traditional, fee-based models, such as college courses. This research examined MOOC student demographic data, intended behaviours and course interactions to better understand variables that are indicative of MOOC completion. The results lead to ideas regarding how these variables can be used to support MOOC students through the application of learning analytics tools and systems.

Original language	English (US)
Pages (from-to)	202-217
Number of pages	16
Journal	Journal of Computer Assisted Learning
Volume	32
Issue number	3
DOIs	https://doi.org/10.1111/jcal.12131
State	Published - Jun 1 2016

Keywords

Completion
Engagement
Learning analytics
MOOC
Motivation
Persistence

ASJC Scopus subject areas

Education
Computer Science Applications

Access to Document

10.1111/jcal.12131

Cite this

@article{507d7e1fc96447e9ad37e1e9f26d2acd,

title = "Understanding MOOC students: Motivations and behaviours indicative of MOOC completion",

abstract = "Massive open online courses (MOOCs) continue to appear across the higher education landscape, originating from many institutions in the USA and around the world. MOOCs typically have low completion rates, at least when compared with traditional courses, as this course delivery model is very different from traditional, fee-based models, such as college courses. This research examined MOOC student demographic data, intended behaviours and course interactions to better understand variables that are indicative of MOOC completion. The results lead to ideas regarding how these variables can be used to support MOOC students through the application of learning analytics tools and systems.",

keywords = "Completion, Engagement, Learning analytics, MOOC, Motivation, Persistence",

author = "Pursel, {B. K.} and L. Zhang and Jablokow, {K. W.} and Choi, {G. W.} and D. Velegol",

note = "Publisher Copyright: {\textcopyright} 2016 John Wiley & Sons Ltd.",

year = "2016",

month = jun,

day = "1",

doi = "10.1111/jcal.12131",

language = "English (US)",

volume = "32",

pages = "202--217",

journal = "Journal of Computer Assisted Learning",

issn = "0266-4909",

publisher = "Wiley-Blackwell",

number = "3",

}

TY - JOUR

T1 - Understanding MOOC students

T2 - Motivations and behaviours indicative of MOOC completion

AU - Pursel, B. K.

AU - Zhang, L.

AU - Jablokow, K. W.

AU - Choi, G. W.

AU - Velegol, D.

PY - 2016/6/1

Y1 - 2016/6/1

N2 - Massive open online courses (MOOCs) continue to appear across the higher education landscape, originating from many institutions in the USA and around the world. MOOCs typically have low completion rates, at least when compared with traditional courses, as this course delivery model is very different from traditional, fee-based models, such as college courses. This research examined MOOC student demographic data, intended behaviours and course interactions to better understand variables that are indicative of MOOC completion. The results lead to ideas regarding how these variables can be used to support MOOC students through the application of learning analytics tools and systems.

AB - Massive open online courses (MOOCs) continue to appear across the higher education landscape, originating from many institutions in the USA and around the world. MOOCs typically have low completion rates, at least when compared with traditional courses, as this course delivery model is very different from traditional, fee-based models, such as college courses. This research examined MOOC student demographic data, intended behaviours and course interactions to better understand variables that are indicative of MOOC completion. The results lead to ideas regarding how these variables can be used to support MOOC students through the application of learning analytics tools and systems.

KW - Completion

KW - Engagement

KW - Learning analytics

KW - MOOC

KW - Motivation

KW - Persistence

UR - http://www.scopus.com/inward/record.url?scp=84960935301&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84960935301&partnerID=8YFLogxK

U2 - 10.1111/jcal.12131

DO - 10.1111/jcal.12131

M3 - Article

AN - SCOPUS:84960935301

SN - 0266-4909

VL - 32

SP - 202

EP - 217

JO - Journal of Computer Assisted Learning

JF - Journal of Computer Assisted Learning

IS - 3

ER -

Understanding MOOC students: Motivations and behaviours indicative of MOOC completion

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this