crsra: A learning analytics tool for understanding student behaviour in massive open online courses

Aboozar Hadavand, John Muschelli, Jeffrey Leek

Research output: Contribution to journalArticle

Abstract

Due to the fundamental differences between traditional education and massive open online courses (MOOCs), and because of the ever-increasing popularity of the latter, more research is needed to understand current and future trends in MOOCs. Although research in the field has grown rapidly in recent years, one of the main challenges facing researchers remains the complexity and messiness of the data. Therefore, it is imperative to provide tools that pave the way for more research on this new subject. This paper introduces a package called crsra based on the statistical software R to help tidy and perform preliminary analysis on massive loads of data provided by Coursera. The advantages of the package are as follows: (a) faster loading and organizing of data for analysis, (b) an efficient method for combining data from multiple courses and even from across institutions, and (c) provision of a set of functions for analyzing student behaviours.

Original languageEnglish (US)
Pages (from-to)140-152
Number of pages13
JournalJournal of Learning Analytics
Volume6
Issue number2
DOIs
StatePublished - Aug 5 2019

Fingerprint

Students
learning
student
Education
popularity
trend
education
software

Keywords

  • Big data in education
  • Learning analytics tools
  • MOOCs
  • R package
  • Student progress

ASJC Scopus subject areas

  • Education
  • Computer Science Applications

Cite this

crsra : A learning analytics tool for understanding student behaviour in massive open online courses. / Hadavand, Aboozar; Muschelli, John; Leek, Jeffrey.

In: Journal of Learning Analytics, Vol. 6, No. 2, 05.08.2019, p. 140-152.

Research output: Contribution to journalArticle

@article{57ea90e958a64454b7c3b278b758b749,
title = "crsra: A learning analytics tool for understanding student behaviour in massive open online courses",
abstract = "Due to the fundamental differences between traditional education and massive open online courses (MOOCs), and because of the ever-increasing popularity of the latter, more research is needed to understand current and future trends in MOOCs. Although research in the field has grown rapidly in recent years, one of the main challenges facing researchers remains the complexity and messiness of the data. Therefore, it is imperative to provide tools that pave the way for more research on this new subject. This paper introduces a package called crsra based on the statistical software R to help tidy and perform preliminary analysis on massive loads of data provided by Coursera. The advantages of the package are as follows: (a) faster loading and organizing of data for analysis, (b) an efficient method for combining data from multiple courses and even from across institutions, and (c) provision of a set of functions for analyzing student behaviours.",
keywords = "Big data in education, Learning analytics tools, MOOCs, R package, Student progress",
author = "Aboozar Hadavand and John Muschelli and Jeffrey Leek",
year = "2019",
month = "8",
day = "5",
doi = "10.18608/jla.2019.62.10",
language = "English (US)",
volume = "6",
pages = "140--152",
journal = "Journal of Learning Analytics",
issn = "1929-7750",
number = "2",

}

TY - JOUR

T1 - crsra

T2 - A learning analytics tool for understanding student behaviour in massive open online courses

AU - Hadavand, Aboozar

AU - Muschelli, John

AU - Leek, Jeffrey

PY - 2019/8/5

Y1 - 2019/8/5

N2 - Due to the fundamental differences between traditional education and massive open online courses (MOOCs), and because of the ever-increasing popularity of the latter, more research is needed to understand current and future trends in MOOCs. Although research in the field has grown rapidly in recent years, one of the main challenges facing researchers remains the complexity and messiness of the data. Therefore, it is imperative to provide tools that pave the way for more research on this new subject. This paper introduces a package called crsra based on the statistical software R to help tidy and perform preliminary analysis on massive loads of data provided by Coursera. The advantages of the package are as follows: (a) faster loading and organizing of data for analysis, (b) an efficient method for combining data from multiple courses and even from across institutions, and (c) provision of a set of functions for analyzing student behaviours.

AB - Due to the fundamental differences between traditional education and massive open online courses (MOOCs), and because of the ever-increasing popularity of the latter, more research is needed to understand current and future trends in MOOCs. Although research in the field has grown rapidly in recent years, one of the main challenges facing researchers remains the complexity and messiness of the data. Therefore, it is imperative to provide tools that pave the way for more research on this new subject. This paper introduces a package called crsra based on the statistical software R to help tidy and perform preliminary analysis on massive loads of data provided by Coursera. The advantages of the package are as follows: (a) faster loading and organizing of data for analysis, (b) an efficient method for combining data from multiple courses and even from across institutions, and (c) provision of a set of functions for analyzing student behaviours.

KW - Big data in education

KW - Learning analytics tools

KW - MOOCs

KW - R package

KW - Student progress

UR - http://www.scopus.com/inward/record.url?scp=85073290421&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85073290421&partnerID=8YFLogxK

U2 - 10.18608/jla.2019.62.10

DO - 10.18608/jla.2019.62.10

M3 - Article

AN - SCOPUS:85073290421

VL - 6

SP - 140

EP - 152

JO - Journal of Learning Analytics

JF - Journal of Learning Analytics

SN - 1929-7750

IS - 2

ER -