Data visualisation

tools for teaching in

MOOCs

Manuel León Urrutia

@mleonurr

m.leon-

urrutia@soton.ac.uk

Madrid, 17

November

Overview

• Who we are

• What we do, why we do it

• How do we do it

• The impact of what we do

Our caseUniversity of Southampton & FutureLearn

• 15 MOOCs

• 50+ runs

• ½+ million learners (Futurelearn 5m+!)

• 200 + datasets

• 6 courses running at the moment

• A MOOC Dashboard developed and in use

• Different internal stakeholders starting to

use it

Is Learning Analytics the answer?

Massive Open Online Courses (MOOCs)

• have been long recognised for their

potential to provide insights on how

learning takes place online.

MOOC data analytics

• can lead to the identification of weaknesses

in the learning materials

Quantitative educational data analysis alone

• cannot address learners’ needs

[ Koller, 2012 ]

[ Bates, 2012 ]

[ Daniel, 2012 ]

Why do we do it? Data

value chain[Miller and Mork, 2013 ]

Why do we do it? Data

value chain

[Miller and Mork, 2013 ]

FutureLearn

Why do we do it? Data

value chain

[Miller and Mork, 2013 ]

UoS

Why do we do it? Data value chain

Terminology

• Courses

• Runs

• Learning Activities (“steps”)

• Learners vs. Fully-participating Learners

• Retention_step(c, r, s)

• Retention_week(c, r, w)

Datasets

Text files in Comma Separated

Values (CSV) format:

• enrolment data

• comments data

• step activity data

• quiz data

• peer review data

An Integrated toolset and data infrastructure:

the UoS MOOC Dashboard

MOOC Datasets

in .csv

Converted to SQL

Stored &

Hosted in UoS

Queried & Analysed by MOBS

Selecting a run in a course

through the MOOC dashboard

Case: Origin country

for all CM learners

Course comparison, data aggregation

All learners Learners between 18-25 years old

Course progress, daily

Use cases

RQ1: How can different roles involved in MOOCs

benefit from the MOOC Dashboard

RQ2: What features are most/least useful

RQ3: How can we improve the dashboard

Facilitators preliminary

impressionsComments viewer

• generally useful for filtering comments

• needs link to comments, back to platform

Demographics dashboard

• Satisfies curiosity

• Unlikely to be useful for interventions

Activity measures

• Useful to target particular steps, and dates or

events

• Not useful for interventions

Researhers preliminary

impressionsComments viewer

• Great potential for text mining

Demographics dashboard

• Useful to know MOOC populations better

Activity measures

• Useful to target particular steps, and dates or

events

• Useful to evaluate course

Future work

• Mixed methods study: use of the

dashboard by instructors

• Dashboard enhancement

• Aggregate cross-institution

analysis

• Aggregate cross-platform analysis

References

https://www.mendeley.com/groups/2754851/mo

oc-observatory/

@mleonurr