creating an action plan for learning analytics
TRANSCRIPT
Creating an action plan for learning analytics
Dr Doug ClowInstitute of Educational Technology, The Open University, UK
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Where are you starting from? (1)
a) Manager
b) Academic / lecturer / teacher
c) L&T / acad developer / ed tech / IT
d) Vendor / consultant
e) Something else
cc licensed ( BY ) flickr photo by Swaminathan: http://flickr.com/photos/araswami/2168316216/
Photo (CC)-BY Robert Couse-Baker https://www.flickr.com/photos/29233640@N07/15551695380
Where are you starting from? (2)
a) I have no idea about learning analytics
b) I’m dipping my toe in the water
c) I’m doing a few little things
d) I’m making significant efforts
e) I could be giving this talk
1. Where do you want to get to?
2. Where are you now?
3. What are the next steps?
1. Where do you want to get to?
2. Where are you now?
3. What are the next steps?
What is learning analytics?
• the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs – First International Conference on Learning Analytics And Knowledge (LAK11), Banff, Alberta, Feb 27-
Mar 1, 2011
Photo (CC)-BY Cris: http://flickr.com/photos/chrismatos/6917786197/
Photo public domain: http://commons.wikimedia.org/wiki/File:DESYNebelkammer.jpg
- Erik Duval http://erikduval.wordpress.com/2012/01/30/learning-analytics-and-educational-data-mining/
“collecting traces that learners leave behind and using those traces to improve learning”
Clow, LAK12, 2012
examples
University Dashboard (Google Image search)
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Predictive modelling
• Place students in one of three risk groups => traffic light
• Trigger for interventions
• Retention and grade improvements
Image (cc) Darwin Bell http://www.flickr.com/photos/darwinbell/296553221/
“The predictive model was used as a trigger for intervention emails to the student.”
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Image (cc) Darwin Bell http://www.flickr.com/photos/darwinbell/296553221/
From: [email protected] are in trouble. The computer predictive model gives you a 87.4322% chance of failing this course. You must see a teacher immediately.
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Image (cc) Darwin Bell http://www.flickr.com/photos/darwinbell/296553221/
From: [email protected] are in trouble. The computer predictive model gives you a 87.4322% chance of failing this course. You must see a teacher immediately.
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Hi AlexAre you Ok? I noticed you haven’t logged on this week, and I know you struggled with the last assessment. We can work through this together - let’s have a chat as soon as possible.Pat.
Course choice
• Degree requirements
• Your record to date
• Previous student success
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Personalised study choice recommendations
Photo (CC)-BY-SA Lauren Macdonald https://www.flickr.com/photos/42386632@N00/8528725328
Social Network Analysis
• Social Networks Adapting Pedagogic Practice
• Network visualisations of forum activity data from VLE
• See patterns
• Spot central anddisconnected
• Identify at-risk
• Improve teaching
what else could you do?
What data do we have about learners?
• Demographics
• Previous educational experience
• Grades, scores, achievements, struggles
• Attendance, location, gaze
• Software logs
• Online tracking
• Other online activity (tracking)
• … more every week.
20Photo (CC)-BY-SA AJ Cann https://www.flickr.com/photos/ajc1/15574010080/
What can we do with that data?
• Identify learners who need help– Simple or predictive
• Trigger interventions
– Via teacher, or direct
• Learn which interventions work
• Build a complete cognitive learning system
• Suggest resources or source of help– Learners like you found this helpful
– This person might be able to help you
21Photo (CC)-BY-NC Pulpolux https://www.flickr.com/photos/pulpolux/8735428280
1. Where do you want to get to?
What’s the one thing you most
want to do at your institution?
1. Where do you want to get to?
2. Where are you now?
3. What are the next steps?
24Greller & Drachsler (ET&S, 2012)
Stakeholders
• Institution– Senior management
– Deans, Heads of Department
• Teachers
• Learners
• Others– IT, Learning & Teaching Centre,
Registry, Library, Estates
25Photo (CC)-BY-NC-SA David Kracht https://www.flickr.com/photos/dave_kr8/15158177186
Internal limitations
• Competences– Specification
– Deployment
– Maintenance
– Data interpretation
– Action
• Acceptance
• Resources
26Photo (CC)-BY-NC UK Ministry of Defence https://www.flickr.com/photos/defenceimages/11052581603
External constraints
• Conventions (ethics)– privacy, accessibility, equality and diversity,
transparency, accountability
• Norms (legislation, policy)– Data Protection, Freedom of Information,
Equality and Diversity
27Photo (CC)-BY-NC-ND Massmo Relsig https://www.flickr.com/photos/99574551@N04/9622288599
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Does your university learn about its students?
Data stored
Changed capacity to act
Photo (CC)-BY-NC Steve Evans https://www.flickr.com/photos/babasteve/15531002668
Understanding
29Greller & Drachsler (ET&S, 2012)
2. Where are you now?
What’s the biggest challenge at
your institution?
OU Analytics Project
Intervention and EvaluationData VisualisationsEthics FrameworkPredictive ModellingLearning Experience Data
Professional DevelopmentSmall Data Student Tools
Enrolment Attendance Submission MarksUsage
Programme
Courses & Units
Mandatory
Sessions Resources Assignments
Leader Tutor Marker
Board
Outcome
Department
HeadDean
Faculty
Left, Failed, Withdrew
Resit Work
Timetable
Curriculum
HierarchyLearning
Resources
Provider
Type
Assessment
Staff
Admission
Entry
Targets
Entry
Quals.
Application
Enquiry
Bio-
demographics
Student
R&A
Course Entry
Employment or
Study (elsewhere)
Satisfaction
Questions
Surveys
Type
AccommodationProgression
Level &
Subject Grad
Data Warehouse Lines of Enquiry
Student
R&A Course Entry
Engagement
Curriculum Hierarchy
Staff
Partial coverage
Opening 2015
Opening 2015
Terminating at Course
Delays expected
Timetable
Surveys
Learning Resources
Assessment
Opening 2015
Partial coverage
Opening 2015
Good coverage
Further Study
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International licence | Mark Stubbs (@thestubbs)
University
Laying foundations for Learning Analytics at MMU
1. Where do you want to get to?
2. Where are you now?
3. What are the next steps?
www.laceproject.euLearning Analytics Community Exchange (FP7)
• Coordination and Support
• Evidence Hub
• Events
• Publications, briefings, webinars
www.laceproject.eu
• Blog bit.ly/lace-blog
• Newsletter bit.ly/lace-newsletter
• FAQs bit.ly/lace-faqs
• Learning Analytics Review bit.ly/lace-review-papers
• Become an Associate Partner!
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• Current state of play in UK HE & FE• Code of practice for learning analytics• Network meeting, 20 Feb 2014, UEL
http://analytics.jiscinvolve.org/
Effective Learning Analytics
• LAK conferences
• LASI workshops
• Flare local meetings
• Storm PhD training
• Journal of LA
• … and more!
www.solaresearch.org
Photo (CC)-BY J. Aaron Farr on Flickr https://www.flickr.com/photos/jaaronfarr/2372892211
Learning Analytics Masters Program (LAMP)
Open Learning Analytics (OLA)
3. What are the next steps?
What one specific, concrete
thing will you do next?
Organisingacademics is like herding cats … but they will come if you leave a saucer of cream.
- Lewis Elton
Photo (CC)-BY-ND Brian Leon https://www.flickr.com/photos/ncbrian/1459269613
Photo (CC)-BY Steve Dunleavy: http://flickr.com/photos/stevedunleavy/5142841381/
The journey of a thousand miles begins with a single step.
– Laozi , Tao Te Ching
Test what you do
• Does it work?
• You’ll have data!
Photo (CC)-BY Kevin Dooley https://www.flickr.com/photos/pagedooley/6613526021/
Towards Evidence-Based Practice
www.laceproject.eu@laceproject
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LACE Annual Meeting: Lunch!1.30pm, Fox Bar, just outside the building
Thanks to:People:
• LACE at the OU: Rebecca Ferguson, Bart Rientes,
Simon Cross, Linda Norwood Michelle Bailey,
Rebecca Wilson, Evaghn De Souza, Natalie
Eggleston, Oliver Millard, Gary Elliot-Citigottis.
• LACE project partners: CETIS (Bolton), OUNL,
Skolverket, HIOA, Kennisnet, ITS, ATiT.
• The learning analytics community, including SoLAR,
IEDMS, those I’ve met at LAK and LASI
• Bett and venue staff
Funders:
• LACE: European Commission 619424-FP7-ICT-2013-11
“Learning Analytics: Making Learning Better?” by Doug Clow, Institute of Educational Technology, The Open University, was presented at Bett, London, on 23 January 2015.
This work was undertaken as part of the LACE Project, supported by the European Commission Seventh Framework Programme, grant 619424.
These slides are provided under the Creative Commons Attribution Licence: http://creativecommons.org/licenses/by/4.0/. Some images used may have different licence terms.
www.laceproject.eu@laceproject
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cc licensed ( BY ) flickr photo by David Goehring: http://flickr.com/photos/carbonnyc/33413040/