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Overview
Jisc Learning Analytics
Learning Analytics
Background
Jisc Learning Analytics Services
User views of products
Timeline and next steps
Student...
About Jisc…
Learning Analytics - Initial Meetings 2015 3
It operates shared digital
infrastructure and services,
negotiate...
What does Jisc do?
Does 4 things…
Providing and developing a
network infrastructure and
related services that meet the
nee...
Co-design challenges
Research at risk (R@R)
Prospect to alumnus (P2A) Learning analytics
Digital learning & capabilitiesIm...
About Learning Analytics…
6Learning Analytics - Initial Meetings 2015
Effective Learning Analytics Challenge
Rationale
Universities and colleges don't have enough useful data about students an...
What do we mean by Learning Analytics?
The application of big data techniques such as machine based learning
and data mini...
About Learning Analytics…
Products and Solutions
9Learning Analytics - Initial Meetings 2015
Jisc’s Learning Analytics Project
10
Three core strands:
Learning
Analytics Service
Toolkit Community
Jisc Learning Analyt...
Jisc’s Learning Analytics Service
Walkthrough
11
Learning
Analytics Service
Learning Analytics - Initial Meetings 2015
Learning Analytics - Initial Meetings 2015 12
Jisc Learning Analytics Architecture
Learning Analytics - Initial Meetings 2015 13
Learning Analytics - Initial Meetings 2015 14
Data collection
About the student Activity data
TinCan
(xAPI)ETL
A user perspective…
15Learning Analytics - Initial Meetings 2015
Dashboards
16
Visual tools to allow lecturers, module leaders,
senior staff and support staff to view:
» Student engagemen...
17Learning Analytics - Initial Meetings 2015
Learning Analytics - Initial Meetings 2015 18
First version will include:
» Overall engagement
» Comparisons
» Self declared data
» Consent management
Bespoke developme...
20Learning Analytics - Initial Meetings 2015
Alert and Intervention System
Tools to allow management of interactions with students
once risk has been identified:
» Cas...
22Learning Analytics - Initial Meetings 2015
Timeline and next steps…
23Learning Analytics - Initial Meetings 2015
Jisc Project in numbers
Expressions of interested: 70
Engaged in activity: 33
Discovery to Sept 16: agreed (25), completed...
Learning Analytics - Initial Meetings 2015 25
Profile Aim Activity Data Sources
Russell Group Retention of widening partic...
Example HE Activity
Learning Analytics - Initial Meetings 2015 27
Phase 1&2
Sep 15 – Apr 16
Phase 2&3
Jan – Sept 16
Transition to
Service
Sept...
28
Jisc/Unicon
Discovery
Jisc Learning
Analytics
Implementation
Wish to
explore
readiness
and
products
Know you
are ready
...
Next Steps
Review Legal and Ethical issues – Code of Practice
Discovery Stage – See offers from Blackboard and Unicon
Tech...
Learning Analytics - Initial Meetings 2015 30
https://courses.alpha.jisc.ac.uk
The student app…
31Learning Analytics - Initial Meetings 2015
Student Learning Analytics App 32
When first logging in the
student is able to select their
institution from a pre-populat...
Student Learning Analytics App 33
The screen will be an activity
feed or timeline, we plan to
integrate this dynamic and
e...
Student Learning Analytics App 34
Stats – Provides an engagement
and attainment overview and
drilling down to gives
compar...
Student Learning Analytics App 35
The engagement and
attainment overview mirrors
what many fitness apps do: it
provides an...
Student Learning Analytics App 36
In the activity comparison
screen you’ll see a graph of your
engagement over time and ho...
Student Learning Analytics App 37
Starting an activity allows you
to select the module on which
you’re working, choose an
...
Student Learning Analytics App 38
Setting a target is the final bit of
functionality we want to include
in the app at this...
Student Learning Analytics App 39
Setting a target involves
selecting a learning activity from
a pre-populated list and
sp...
Jisc Learning AnalyticsToolkit
40
Toolkit
Learning Analytics - Initial Meetings 2015
Discovery …
The learning analytics discovery service is a way of
investigating your institution’s readiness for learning
a...
http://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics
Code of Practice
Learning Analytics - Initial Meeting...
Deeper Dive
http://repository.jisc.ac.uk/5661/1/Learning_Analytics_A-_Literature_Review.pdf
Literature review – basis
for ...
Code of Practice
Privacy
Validity
Responsibility
Access
Enabling positive
interventions
Minimising adverse impacts
Transpa...
45
Community
Community
Learning Analytics - Initial Meetings 2015
Project Blog, mailing list and
network events
Blog: http://analytics.jiscinvolve.org
Mailing: analytics@jiscmail.ac.uk
46L...
How can institutions get involved…
47
Toolkit
Learning Analytics - Initial Meetings 2015
Learning Analytics - Initial Meetings 2015 48
Phase 1&2
Sep 15 – Apr 16
Phase 2&3
Jan – Sept 16
Transition to
Service
Sept...
Timeline
Jun 15 Sep 15 Jan 16 Apr 16
3. Trial
Integration pt1
x 2
1. Jisc complete
contracts
2. Jisc Sandbox
4. Phase 1
Di...
50
Jisc/Unicon
Discovery
Jisc Learning
Analytics
Implementation
Wish to
explore
readiness
and
products
Know you
are ready
...
michael.webb@jisc.ac.uk
One Castlepark Tower Hill Bristol BS2 0JA
T 020 3697 5800
info@jisc.ac.uk jisc.ac.uk
Michael Webb
...
How’s the data collected?
52Learning Analytics - Initial Meetings 2015
Learning Analytics - Initial Meetings 2015 53
About the student Activity data
TinCan
(xAPI)ETL
Data collection
About the student’ data
Personal (demographic) data
Birthdate, gender etc.
Course data
mode of study, level etc.
Grade dat...
Activity data viaTin Can API
• People learn from interactions with other
people, content, and beyond.
• These actions can ...
Activity Data (trivial!) examples
56
Actor Action Object Result
Michael Accessed VLE
Sally Completed Basic MathsTest 85.0
...
57Learning Analytics - Initial Meetings 2015
‘Recipes’ are key
• ‘Recipes’ are a shared way of describing
activities..
• So the data from ‘accessing a course’ is the
s...
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Intro to jisc Learning Analytics March 16

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Overview of the Jisc Learning Analytics Project

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Intro to jisc Learning Analytics March 16

  1. 1. Overview Jisc Learning Analytics
  2. 2. Learning Analytics Background Jisc Learning Analytics Services User views of products Timeline and next steps Student App (additional slides) How data is included (additional slides) Learning Analytics - Initial Meetings 2015 2 Outline of session
  3. 3. About Jisc… Learning Analytics - Initial Meetings 2015 3 It operates shared digital infrastructure and services, negotiates sector-wide deals with IT vendors and commercial publishers, and provides trusted advice and practical assistance for universities and colleges. Jisc is the UK higher and further education sectors’ not-for-profit organisation for digital service and solutions.
  4. 4. What does Jisc do? Does 4 things… Providing and developing a network infrastructure and related services that meet the needs of the UK research and education communities Supporting the procurement of digital content for UK education and research Our network of national and regional teams provide local engagement, advice and support to help you get the most out of our service offer Our R&D work, paid for entirely by our major funders, identifies emerging technologies and develops them around your particular needs
  5. 5. Co-design challenges Research at risk (R@R) Prospect to alumnus (P2A) Learning analytics Digital learning & capabilitiesImplementing FELTAG Business intelligence Hosting platform Hosting platform
  6. 6. About Learning Analytics… 6Learning Analytics - Initial Meetings 2015
  7. 7. Effective Learning Analytics Challenge Rationale Universities and colleges don't have enough useful data about students and how they are learning. What they have they don’t analyse and interpret.They are missing opportunities to use technology to provide feedback to students.They need to support staff who could be using analytics and a standard set of tools and technologies to monitor and intervene. Who it affects and how Students are missing out on the possibility of an improved experience, better retention, and better achievement. Staff are missing the opportunity to develop skills to use analytics to improve support, teaching and curriculum design. Timescale Pilot tools and metrics 1-2 years Impact on retention, achievement and progression 3-4 years. Learning Analytics - Initial Meetings 2015 7
  8. 8. What do we mean by Learning Analytics? The application of big data techniques such as machine based learning and data mining to help learners and institutions meet their goals: For our project: » Improve retention (current project) » Improve achievement (current project) » Improve employability (current project) » Personalised learning (future project) 8Learning Analytics - Initial Meetings 2015
  9. 9. About Learning Analytics… Products and Solutions 9Learning Analytics - Initial Meetings 2015
  10. 10. Jisc’s Learning Analytics Project 10 Three core strands: Learning Analytics Service Toolkit Community Jisc Learning Analytics Learning Analytics - Initial Meetings 2015
  11. 11. Jisc’s Learning Analytics Service Walkthrough 11 Learning Analytics Service Learning Analytics - Initial Meetings 2015
  12. 12. Learning Analytics - Initial Meetings 2015 12 Jisc Learning Analytics Architecture
  13. 13. Learning Analytics - Initial Meetings 2015 13
  14. 14. Learning Analytics - Initial Meetings 2015 14 Data collection About the student Activity data TinCan (xAPI)ETL
  15. 15. A user perspective… 15Learning Analytics - Initial Meetings 2015
  16. 16. Dashboards 16 Visual tools to allow lecturers, module leaders, senior staff and support staff to view: » Student engagement » Cohort comparisons » etc… Based on either commercial tools from Tribal (Student Insight) or open source tools from Unicon/Marist (OpenDashBoard) Learning Analytics - Initial Meetings 2015
  17. 17. 17Learning Analytics - Initial Meetings 2015
  18. 18. Learning Analytics - Initial Meetings 2015 18
  19. 19. First version will include: » Overall engagement » Comparisons » Self declared data » Consent management Bespoke development by Therapy Box 19 Student App Learning Analytics - Initial Meetings 2015
  20. 20. 20Learning Analytics - Initial Meetings 2015
  21. 21. Alert and Intervention System Tools to allow management of interactions with students once risk has been identified: » Case management » Intervention management » Data fed back into model » etc… Based on open source tools from Unicon/Marist (Student Success Plan) 21Learning Analytics - Initial Meetings 2015
  22. 22. 22Learning Analytics - Initial Meetings 2015
  23. 23. Timeline and next steps… 23Learning Analytics - Initial Meetings 2015
  24. 24. Jisc Project in numbers Expressions of interested: 70 Engaged in activity: 33 Discovery to Sept 16: agreed (25), completed (11), reported (6) Over 1 millions records collected in real-time Moodle Historic DataTransformation: 41 millions records transformed from Moodle Log files to xAPI Blackboard DataTransformation: 12 millions blackboard records transformed from Blackboard Log to xAPI Learning Analytics - Initial Meetings 2015 24
  25. 25. Learning Analytics - Initial Meetings 2015 25 Profile Aim Activity Data Sources Russell Group Retention of widening participation + support for students to achieve 2.1 or better Discovery +Tribal Insight + Learning Locker Moodle + Student Records Research led University Retention, improve teaching, empowering students Discovery + OpenSource Suite + StudentApp Moodle + Attendance+ Student Records Teaching led University with WP mission Retention - requirement to make identifying students more efficient so they can focus on interventions Tribal Insight + Learning Locker Blackboard + Attendance + Student Records Research led University Student engagement Discovery + Student app + Learning Locker Moodle + Student Records Teaching Lead Understanding of how Learning Analytics can be used Discovery +Technical Integration Moodle
  26. 26. Example HE Activity
  27. 27. Learning Analytics - Initial Meetings 2015 27 Phase 1&2 Sep 15 – Apr 16 Phase 2&3 Jan – Sept 16 Transition to Service Sept 16 – July 17 Jisc Learning Analytics Service Sept 2017
  28. 28. 28 Jisc/Unicon Discovery Jisc Learning Analytics Implementation Wish to explore readiness and products Know you are ready and what you want Want to get involved in tech work first Blackboard Discovery Unicon/Marist pre- implementation Tribal pre- implementation Other pre- implementation Blackboard Trial MoodleTrial Other Learning Analytics Implementation TechTrials Discovery Pre-implementation Implementation Learning Analytics - Initial Meetings 2015
  29. 29. Next Steps Review Legal and Ethical issues – Code of Practice Discovery Stage – See offers from Blackboard and Unicon Technical Overview – Register and enrol https://courses.alpha.jisc.ac.uk Technical Trials – Set up Learner Records Warehouse, install VLE plugin, identify and share, look data sets for student information Technical Implementation – chose preferred analytics solution (Tribal Student Insights or Unicon processor and dashboard). Jan 2016 onwards for implementation. Learning Analytics - Initial Meetings 2015 29
  30. 30. Learning Analytics - Initial Meetings 2015 30 https://courses.alpha.jisc.ac.uk
  31. 31. The student app… 31Learning Analytics - Initial Meetings 2015
  32. 32. Student Learning Analytics App 32 When first logging in the student is able to select their institution from a pre-populated lists of UK universities. If the students’ institution is using other parts of Jisc’s learning analytics architecture, in particular the learning analytics warehouse, then much more data will be available to the app.
  33. 33. Student Learning Analytics App 33 The screen will be an activity feed or timeline, we plan to integrate this dynamic and engaging concept, so essential to applications such asTwitter and Facebook. Photos or badges could be included next to the text.
  34. 34. Student Learning Analytics App 34 Stats – Provides an engagement and attainment overview and drilling down to gives comparative activity graphs. Log – Allows you to log time spent on specified activities e.g. reading for an assignment Target – Allows you set personal targets to improve your engagement e.g. study for 10 hours this week
  35. 35. Student Learning Analytics App 35 The engagement and attainment overview mirrors what many fitness apps do: it provides an overview of your “performance” to date. Critically here we show how you compare to others.This will be based on data about you and others held in the learning analytics warehouse.
  36. 36. Student Learning Analytics App 36 In the activity comparison screen you’ll see a graph of your engagement over time and how it compares with that of others. You can select a particular module or look at your whole course. You can compare yourself with people on my course, people on this module and top 20% of performers (based on grades). Comparing yourself to prior cohorts of students on a module might be of interest in the future too.
  37. 37. Student Learning Analytics App 37 Starting an activity allows you to select the module on which you’re working, choose an activity type from a drop-down list such as reading a book, writing an essay, or attending a lab, and select a time period you want to spend on the activity and whether you want a notification when that period is up. A timer is displayed in the image box and you can hit the Stop button when you’ve finished. The timer will continue even if you navigate away from the app.
  38. 38. Student Learning Analytics App 38 Setting a target is the final bit of functionality we want to include in the app at this stage.Again this is building on the success of fitness tracking apps where you set yourself targets as a way of motivating yourself.
  39. 39. Student Learning Analytics App 39 Setting a target involves selecting a learning activity from a pre-populated list and specifying how long you want to be spending on it. We added a “because” free text box so that learners can make it clear (to themselves) why they want to carry out the activity e.g. I want to pass the exam, tutor told me I’m not reading enough). Users may be more likely to select a reason from a pre- populated list than to fill in a text field but we’ll monitor this to see whether it’s being used.
  40. 40. Jisc Learning AnalyticsToolkit 40 Toolkit Learning Analytics - Initial Meetings 2015
  41. 41. Discovery … The learning analytics discovery service is a way of investigating your institution’s readiness for learning analytics. The process will investigate strategic, technical, process and data readiness, providing recommendations for action before moving on to deploy a learning analytics solution. 41Learning Analytics - Initial Meetings 2015
  42. 42. http://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics Code of Practice Learning Analytics - Initial Meetings 2015 42
  43. 43. Deeper Dive http://repository.jisc.ac.uk/5661/1/Learning_Analytics_A-_Literature_Review.pdf Literature review – basis for the code of practice Learning Analytics - Initial Meetings 2015 43
  44. 44. Code of Practice Privacy Validity Responsibility Access Enabling positive interventions Minimising adverse impacts Transparency and consent Learning Analytics - Initial Meetings 2015 44
  45. 45. 45 Community Community Learning Analytics - Initial Meetings 2015
  46. 46. Project Blog, mailing list and network events Blog: http://analytics.jiscinvolve.org Mailing: analytics@jiscmail.ac.uk 46Learning Analytics - Initial Meetings 2015
  47. 47. How can institutions get involved… 47 Toolkit Learning Analytics - Initial Meetings 2015
  48. 48. Learning Analytics - Initial Meetings 2015 48 Phase 1&2 Sep 15 – Apr 16 Phase 2&3 Jan – Sept 16 Transition to Service Sept 16 – July 17 Jisc Learning Analytics Service Sept 2017
  49. 49. Timeline Jun 15 Sep 15 Jan 16 Apr 16 3. Trial Integration pt1 x 2 1. Jisc complete contracts 2. Jisc Sandbox 4. Phase 1 Discovery 5. Phase 1 implementation x 6 8. Phase 2 implementation x 6 - 12 6. Trial Integration pt2 x 2 7. Phase 2 Discovery x 6- 12 Learning Analytics - Initial Meetings 2015 49
  50. 50. 50 Jisc/Unicon Discovery Jisc Learning Analytics Implementation Wish to explore readiness and products Know you are ready and what you want Want to get involved in tech work first Blackboard Discovery Unicon/Marist pre- implementation Tribal pre- implementation Other pre- implementation Blackboard Trial MoodleTrial Other Learning Analytics Implementation TechTrials Discovery Pre-implementation Implementation Learning Analytics - Initial Meetings 2015
  51. 51. michael.webb@jisc.ac.uk One Castlepark Tower Hill Bristol BS2 0JA T 020 3697 5800 info@jisc.ac.uk jisc.ac.uk Michael Webb Director ofTechnology and Analytics 51
  52. 52. How’s the data collected? 52Learning Analytics - Initial Meetings 2015
  53. 53. Learning Analytics - Initial Meetings 2015 53 About the student Activity data TinCan (xAPI)ETL Data collection
  54. 54. About the student’ data Personal (demographic) data Birthdate, gender etc. Course data mode of study, level etc. Grade data Assignment, module etc. (aligned with HESA data) 54Learning Analytics - Initial Meetings 2015
  55. 55. Activity data viaTin Can API • People learn from interactions with other people, content, and beyond. • These actions can happen anywhere and signal an event where learning could occur. • When an activity needs to be recorded, the application sends secure statements in the form of “Actor, verb, object” or “I did this” to the Learning Record Store (LRS.) from: http://tincanapi.com/ 55Learning Analytics - Initial Meetings 2015
  56. 56. Activity Data (trivial!) examples 56 Actor Action Object Result Michael Accessed VLE Sally Completed Basic MathsTest 85.0 Kim Module CommentAdded https://registry.tincanapi.com Learning Analytics - Initial Meetings 2015
  57. 57. 57Learning Analytics - Initial Meetings 2015
  58. 58. ‘Recipes’ are key • ‘Recipes’ are a shared way of describing activities.. • So the data from ‘accessing a course’ is the same whether Moodle or Blackboard is used. • The same holds for.. • ‘Attend a lecture’ • ‘Borrow a book’ • … 58Learning Analytics - Initial Meetings 2015

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