Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis

Scott Crossly; Mihai Dascalu; Danielle S. McNamara; Ryan Baker; Stefan Trausan-Matu

Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis

Scott Crossly, Mihai Dascalu, Danielle S. McNamara, Ryan Baker, Stefan Trausan-Matu

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

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Abstract

This study uses Cohesion Network Analysis (CNA) indices to identify student patterns related to course completion in a massive open online course (MOOC). This analysis examines a subsample of 320 students who completed at least one graded assignment and produced at least 50 words in discussion forums in a MOOC on educational data mining. The findings indicate that CNA indices predict with substantial accuracy (76%) whether students complete the MOOC, helping us to better understand student retention in this MOOC and to develop more actionable automated signals of student success.

Original language	English
Title of host publication	Making a Difference: Prioritizing Equity and Access in CSCL
Subtitle of host publication	12th International Conference on Computer Supported Collaborative Learning
Editors	Brian K. Smith, Marcela Borge, Emma Mercier, Kyu Yon Lim
Publisher	International Society of the Learning Sciences
Pages	103-110
Volume	1
ISBN (Print)	978-0-9903550-0-7
Publication status	Published - 2017
Externally published	Yes
Event	Making a Difference: Prioritizing Equity and Access in CSCL: 12th International Conference on Computer Supported Collaborative Learning - Philadelphia, United States Duration: 18 Jun 2017 → 21 Jun 2017 https://cscl17.wordpress.com/

Conference

Conference	Making a Difference: Prioritizing Equity and Access in CSCL
Abbreviated title	CSCL 2017
Country/Territory	United States
City	Philadelphia
Period	18/06/17 → 21/06/17
Internet address	https://cscl17.wordpress.com/

Keywords

Cohesion Network Analysis
Massive Open Online Courses
prediction of completion rates
longitudinal analysis
ReaderBench framework

Access to Document

Crossley-Full-CSCL2017Accepted author manuscript, 755 KBLicence: CC BY-NC-ND

Rage: Realising an Applied Gaming Eco-system
Westera, W. (PI), Georgiadis, K. (CoI), Saveski, G. (CoI), van Lankveld, G. (CoI), Bahreini, K. (CoI), van der Vegt, W. (CoI), Berkhout, J. (CoI), Nyamsuren, E. (CoI), Kluijfhout, E. (CoI) & Nadolski, R. (CoI)
European Union
1/02/15 → 31/07/19
Project: Research

Cite this

Crossly, S., Dascalu, M., McNamara, D. S., Baker, R., & Trausan-Matu, S. (2017). Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis. In B. K. Smith, M. Borge, E. Mercier, & K. Y. Lim (Eds.), Making a Difference: Prioritizing Equity and Access in CSCL: 12th International Conference on Computer Supported Collaborative Learning (Vol. 1, pp. 103-110). International Society of the Learning Sciences. https://www.semanticscholar.org/paper/Predicting-Success-in-Massive-Open-Online-Courses-Crossley/ee1956363e37933662975195279a125c0d6adaf3

Crossly, Scott ; Dascalu, Mihai ; McNamara, Danielle S. et al. / Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis. Making a Difference: Prioritizing Equity and Access in CSCL: 12th International Conference on Computer Supported Collaborative Learning. editor / Brian K. Smith ; Marcela Borge ; Emma Mercier ; Kyu Yon Lim. Vol. 1 International Society of the Learning Sciences, 2017. pp. 103-110

@inproceedings{f0c8694721df4e3697b4e669994e653e,

title = "Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis",

abstract = "This study uses Cohesion Network Analysis (CNA) indices to identify student patterns related to course completion in a massive open online course (MOOC). This analysis examines a subsample of 320 students who completed at least one graded assignment and produced at least 50 words in discussion forums in a MOOC on educational data mining. The findings indicate that CNA indices predict with substantial accuracy (76%) whether students complete the MOOC, helping us to better understand student retention in this MOOC and to develop more actionable automated signals of student success.",

keywords = "Cohesion Network Analysis, Massive Open Online Courses, prediction of completion rates, longitudinal analysis, ReaderBench framework",

author = "Scott Crossly and Mihai Dascalu and McNamara, {Danielle S.} and Ryan Baker and Stefan Trausan-Matu",

year = "2017",

language = "English",

isbn = "978-0-9903550-0-7",

volume = "1",

pages = "103--110",

editor = "Smith, {Brian K.} and Marcela Borge and Emma Mercier and Lim, {Kyu Yon}",

booktitle = "Making a Difference: Prioritizing Equity and Access in CSCL",

publisher = "International Society of the Learning Sciences",

note = "Making a Difference: Prioritizing Equity and Access in CSCL : 12th International Conference on Computer Supported Collaborative Learning, CSCL 2017 ; Conference date: 18-06-2017 Through 21-06-2017",

url = "https://cscl17.wordpress.com/",

}

Crossly, S, Dascalu, M, McNamara, DS, Baker, R & Trausan-Matu, S 2017, Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis. in BK Smith, M Borge, E Mercier & KY Lim (eds), Making a Difference: Prioritizing Equity and Access in CSCL: 12th International Conference on Computer Supported Collaborative Learning. vol. 1, International Society of the Learning Sciences, pp. 103-110, Making a Difference: Prioritizing Equity and Access in CSCL, Philadelphia, United States, 18/06/17. <https://www.semanticscholar.org/paper/Predicting-Success-in-Massive-Open-Online-Courses-Crossley/ee1956363e37933662975195279a125c0d6adaf3>

Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis. / Crossly, Scott; Dascalu, Mihai; McNamara, Danielle S. et al.
Making a Difference: Prioritizing Equity and Access in CSCL: 12th International Conference on Computer Supported Collaborative Learning. ed. / Brian K. Smith; Marcela Borge; Emma Mercier; Kyu Yon Lim. Vol. 1 International Society of the Learning Sciences, 2017. p. 103-110.

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

TY - GEN

T1 - Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis

AU - Crossly, Scott

AU - Dascalu, Mihai

AU - McNamara, Danielle S.

AU - Baker, Ryan

AU - Trausan-Matu, Stefan

PY - 2017

Y1 - 2017

N2 - This study uses Cohesion Network Analysis (CNA) indices to identify student patterns related to course completion in a massive open online course (MOOC). This analysis examines a subsample of 320 students who completed at least one graded assignment and produced at least 50 words in discussion forums in a MOOC on educational data mining. The findings indicate that CNA indices predict with substantial accuracy (76%) whether students complete the MOOC, helping us to better understand student retention in this MOOC and to develop more actionable automated signals of student success.

AB - This study uses Cohesion Network Analysis (CNA) indices to identify student patterns related to course completion in a massive open online course (MOOC). This analysis examines a subsample of 320 students who completed at least one graded assignment and produced at least 50 words in discussion forums in a MOOC on educational data mining. The findings indicate that CNA indices predict with substantial accuracy (76%) whether students complete the MOOC, helping us to better understand student retention in this MOOC and to develop more actionable automated signals of student success.

KW - Cohesion Network Analysis

KW - Massive Open Online Courses

KW - prediction of completion rates

KW - longitudinal analysis

KW - ReaderBench framework

M3 - Conference Article in proceeding

SN - 978-0-9903550-0-7

VL - 1

SP - 103

EP - 110

BT - Making a Difference: Prioritizing Equity and Access in CSCL

A2 - Smith, Brian K.

A2 - Borge, Marcela

A2 - Mercier, Emma

A2 - Lim, Kyu Yon

PB - International Society of the Learning Sciences

T2 - Making a Difference: Prioritizing Equity and Access in CSCL

Y2 - 18 June 2017 through 21 June 2017

ER -

Crossly S, Dascalu M, McNamara DS, Baker R, Trausan-Matu S. Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis. In Smith BK, Borge M, Mercier E, Lim KY, editors, Making a Difference: Prioritizing Equity and Access in CSCL: 12th International Conference on Computer Supported Collaborative Learning. Vol. 1. International Society of the Learning Sciences. 2017. p. 103-110

Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis

Abstract

Conference

Keywords

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Projects

Rage: Realising an Applied Gaming Eco-system

Cite this