Data Wranglers: Human data interpreters to close the feedback loop
description
Transcript of Data Wranglers: Human data interpreters to close the feedback loop
Data Wranglers: Human data interpreters to close the feedback loop
Doug Clow Institute of Educational Technology The Open University, UK
The Open University
• Largest university in the UK
• 200,000 students
• 7,000 tutors
• 1,000 academic staff
• Supported open learning
Milton Keynes
At scale, each year
• 600 courses• > 200,000 students
• > 1 million assignments• > 1 billion views of OU/BBC coproductions
• > 3 million Moodle transactions per day
Photo (cc) Marieke IJsendoorn-Kuijpers http://www.flickr.com/photos/mape_s/333862026//
data wrangling
“Learning is a complex social activity” (Siemens, 2012)
• Lots of data• Lots of tools
• Humans to make sense
Photo CC (BY) Tobias Lindman on Flickr: http://www.flickr.com/photos/cowb0y2000/6243008944/
Data Wrangling• Institutional capacity
building• 8 Wranglers• Faculty link• Regular reports
Data
• Delivery data • Completion,
pass rates, demographics
Pelophylax perezi Photo CC (BY-SA) Paulo Brandão on Flickr: http://www.flickr.com/photos/paulobrandao/3567716506/
• Student feedback • Activity data
(Moodle)
Photo CC (BY) Preneur d’Image on Flickr: http://www.flickr.com/photos/surbykids/9368298544/
Report Process
• Briefing discussion• Data analysis and report writing• Draft discussion• Final report
Photo (cc)-BY-NC nataliej on Flickr: http://www.flickr.com/photos/nataliejohnson/2122722198/
• Scrutiny in draft• Standard document template• Executive summary• Recommendations
Quality assurance
Responsive ‘quick reports’
Photo (CC)-BY Mark Dumont on Flickr: http://www.flickr.com/photos/wcdumonts/9256493975/
Doing extras
reaction
users data
users data
users data
examples
Unique visits per week to VLE components for one course
Course use of Elluminate Students using Elluminate
None 18%
Informal 27%
General student support 35%
Specified activities not assessed 49%
Specified activities referenced in assessment 95%
Usage of Elluminate broken down by course use of Elluminate for one Faculty between 2011-2012.
conclusions
Photo CC (BY-NC-SA) quas on Flickr http://www.flickr.com/photos/quas/1703493/
Evaluation:• Data quality• Data quantity• Unevenness
• High cost• Slow• Bottom up
Photo CC (BY-NC) Alexey Kljatov on Flickr http://www.flickr.com/photos/chaoticmind75/9516811453/
It is only through the detailed process of engagement and dialogue between analysts, stakeholders and the data that insight and organisational change are developed.
• Gill Kirkup, Mary Thorpe, Alison Ashby & her team– esp. Vicky Marsh and Jim Peard
• Oliver Millard• Evaghn DeSouza• My fellow Data Wranglers
Thanks to …
Doug [email protected]@open.ac.uk
This work is licensed under a Creative Commons Attribution 3.0 Unported License
cc licensed ( BY ) flickr photo by David Goehring: http://flickr.com/photos/carbonnyc/33413040/
Doing extras• 60 points vs 30 points
Photo (CC)-BY Steve Snodgrass on Flickr: http://www.flickr.com/photos/stevensnodgrass/4034636727/
cc licensed ( BY ) flickr photo by zzpza: http://www.flickr.com/photos/zzpza/3269784239/
Workshops
• Integrated/joint Learning Design/Data Wrangling• Module production workshops
– Intensive all-week workshop– Many presentations (LTS, other relevant modules)– IET: Data Wrangling and Learning Design
(CC) Eoin Gardner on Flickr http://www.flickr.com/photos/18091975@N00/5310045271/
The impersonal is political
• Data used as weaponry in ongoing battles
Data
• Delivery data • Completion,
pass rates, demographics
Photo CC (BY-NC) ChaoticMind75 on Flickr: http://www.flickr.com/photos/chaoticmind75/8629790711/
• Student feedback • Activity data
(Moodle)