Creating an action plan for learning analytics

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Creating an action plan for learning analytics

Dr Doug ClowInstitute of Educational Technology, The Open University, UK

@dougclowdougclow.orgdoug.clow@open.ac.uk

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CC-BY – You are free to:

copy, share, adapt, or re-mix;

photograph, film, or broadcast;

blog, live-blog, or post video of

this presentation provided that:You attribute the work to its author and respect the rights andlicences associated with its components.

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: DONOTREPLY@mail.example.comYou 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: DONOTREPLY@mail.example.comYou 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.

@dougclowdougclow.orgdoug.clow@open.ac.uk

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/