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Keynote address at the UTS Future of Learning Forum https://www.facebook.com/events/354394148064042/?source=1

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LEARNING ANALYTICS 
— an essential tool for learning in the future 
Simon Buckingham Shum 
Professor of Learning Informatics 
Director, Connected Intelligence Centre 
twitter @sbuckshum #UTSfuturelearn 
UTS CRICOS PROVIDER CODE: 00099F uts.edu.au
cic.uts.edu.au
3 
can 
we 
tell 
from 
your 
digital 
profile 
if 
you’re 
learning?
4 
Every educational product now comes with a “dashboard”…
5 
I was speaking at this event 
http://codeactsineducation.wordpress.com
6 
I asked Siri to find the conference website… 
“Find code acts in 
education”

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uts-learning-futures-learning-analytics

  • 1. LEARNING ANALYTICS — an essential tool for learning in the future Simon Buckingham Shum Professor of Learning Informatics Director, Connected Intelligence Centre twitter @sbuckshum #UTSfuturelearn UTS CRICOS PROVIDER CODE: 00099F uts.edu.au
  • 3. 3 can we tell from your digital profile if you’re learning?
  • 4. 4 Every educational product now comes with a “dashboard”…
  • 5. 5 I was speaking at this event http://codeactsineducation.wordpress.com
  • 6. 6 I asked Siri to find the conference website… “Find code acts in education”
  • 7. 7 I asked Siri to find the conference website… “Find code acts in education”
  • 8. h,ps://twi,er.com/Wiswijzer2/status/414055472451575808 8 “Note: check the huge difference between knowing and measuring…”
  • 10. Visualising “attainment” and “progress” 10
  • 11. ‘Joe’ may be developing curiosity, resilience, and collaboration skills, but these are left invisible
  • 12. CRITICAL: accounting tools are not neutral “accounting tools...do not simply aid the measurement of economic activity, they shape the reality they measure” Du Gay, P. and Pryke, M. (2002) Cultural Economy: Cultural Analysis and Commercial Life. Sage, London. pp. 12-13 12
  • 13. sta:s:cal analysis of educa:onal data is hardly new 13
  • 14. 14 Institutional/Academic Data and Analytics: current focus on summative data and trends for senior educational leaders and policymakers Macro: region/state/national/international
  • 15. 15 Institutional/Academic Data and Analytics: current focus on summative data and trends for senior educational leaders and policymakers Macro: region/state/national/international
  • 16. 16 Institutional/Academic Data and Analytics: current focus on summative data and trends for senior educational leaders and policymakers Macro: region/state/national/international Meso: institution-wide
  • 17. 17 NSW DEC • CESE Datahub (+ many comparable open data initiatives) https://data.cese.nsw.gov.au
  • 18. 18 UK RAISEonline data: schools live or die by this
  • 19. 19 Learning Analytics: Data explosion at the micro level enriching, and enriched by, the meso+macro levels Macro: region/state/national/international Meso: institution-wide Micro: individual student progress Learning Analytics UNESCO Policy Briefing — http://iite.unesco.org/publications/3214711
  • 20. Towards rapid formative feedback outcome intent researchers / educators / instrucGonal designers administrators / leaders / policymakers 20
  • 21. Faster feedback loops outcome could enable more rapid adaptation by students and teachers, and of learning resources and designs intent researchers / educators / instrucGonal designers administrators / leaders / policymakers 21 Towards rapid formative feedback
  • 25. 25
  • 26. Ed-Tech startups and venture capital 26 http://techcrunch.com/2014/02/19/google-capital-invests-40m-in-learning-analytics-firm-renaissance-learning-at-1b-valuation https://www.edsurge.com/n/2014-10-06-diving-into-data-analytics-tools-in-k-12
  • 27. Ed-Tech startups and venture capital “LearnCapital is a venture capital firm focused exclusively on funding entrepreneurs with a vision for better and smarter learning.” http://learncapital.com 27
  • 28. Hang on: algorithm designers in ed-tech startups are shaping the learning experience?… 28 Candace Thille (Stanford) “Why would universities outsource their core competency to ed-tech h,p://reinventors.net/roundtables/strategies-­‐for-­‐organizaGonal-­‐change vendors?”
  • 29. the core ques:on in slow mo)on 29
  • 30. 30 can we tell from your digital profile if you’re learning?
  • 31. 31 Who? can we tell from your digital profile if you’re learning?
  • 32. 32 Who? How? With what confidence? After what kinds of training? can we tell from your digital profile if you’re learning?
  • 33. 33 Who? How? With what confidence? After what kinds of training? can we tell from your digital profile if you’re learning? Sourcing which data, with what integrity?
  • 34. 34 Who? How? With what confidence? After what kinds of training? can we tell from your digital profile if you’re learning? Sourcing which data, with what integrity? What kind of learning? What kind of teaching?
  • 35. 35 what kinds of learners are we trying to create? – this should drive our analytics
  • 36. Let’s hear from the UTS graduates of 2026 36 http://learningemergence.net/2014/04/07/learning-dispositions-authentic-inquiry-in-a-primary-school
  • 37. The Knowledge – Agency Window Open-­‐ ended Enquiry Pre-­‐scribed curriculum Teacher-­‐directed enquiry Student led-­‐enquiry Content/Expert led teaching Student-­‐led revision Teacher Directed Learning Self-­‐directed Learning
  • 38. We worry about disengaged low achievers like Joe — but we need to worry about Emily too... 38 Guy Claxton: Constant change is here to stay: why schooling will always be about the future. UK ESRC Futures Meeting, May 2011. http://www.slideshare.net/edfutures/guy-claxton-esrc-futures-may11
  • 39. The Knowledge – Agency Window Open-­‐ ended Enquiry Pre-­‐scribed curriculum Teacher-­‐directed enquiry Student led-­‐enquiry Content/Expert led teaching Student-­‐led revision Teacher Directed Learning Self-­‐directed Learning
  • 40. The Knowledge – Agency Window Open-­‐ ended Enquiry Pre-­‐scribed curriculum Teacher-­‐directed enquiry Student led-­‐enquiry Content/Expert led teaching Student-­‐led revision Teacher Directed Learning Self-­‐directed Learning
  • 41. The Knowledge – Agency Window Open-­‐ ended Enquiry Pre-­‐scribed curriculum Teacher-­‐directed enquiry Student led-­‐enquiry Content/Expert led teaching Student-­‐led revision Teacher Directed Learning Self-­‐directed Learning
  • 42. So our analytics depends on what space we’re in Open-­‐ ended Enquiry Pre-­‐scribed curriculum Teacher-­‐directed enquiry Student led-­‐enquiry Authenticity Agency Identity Content/Expert led teaching Student-­‐led revision Teacher Directed Learning Self-­‐directed Learning
  • 43. 43 Analytics for the UTS learning model? http://www.uts.edu.au/research-and-teaching/teaching-and-learning/learning2014/new-approaches
  • 44. 44 Analytics for the UTS learning model? http://www.uts.edu.au/research-and-teaching/teaching-and-learning/learning2014/new-approaches
  • 45. Analytics for the UTS learning model? http://www.uts.edu.au/research-and-teaching/teaching-and-learning/learning2014/new-approaches
  • 46. 46 More efficient learning for mastering core skills “In this study, results showed that OLI-Statistics students [blended learning] learned a full semester’s worth of material in half as much time and performed as well or better than students learning from traditional instruction over a full semester.” Lovett M, Meyer O and Thille C. (2008) The Open Learning Initiative: Measuring the effectiveness of the OLI statistics course in accelerating student learning. Journal of Interactive Media in Education 14. http://jime.open.ac.uk/article/2008-14/352
  • 47. Learning analytics for this? “We’re looking at the profiles of what it means to be effective in the 21st century. […] Resilience will be the defining concept. When challenged and bent, you learn and bounce back stronger.” “Dispositions are now at least as important as Knowledge and Skills. …They cannot be taught. They can only be cultivated.” John Seely Brown US Dept. of Educ. http://reimaginingeducation.org conference (May 28, 2013) Dispositions clip: http://www.c-spanvideo.org/clip/4457327 47 Whole talk: http://www.c-spanvideo.org/program/SecD
  • 48. Learning analytics for this? “It’s more than knowledge and skills. For the innovation economy, dispositions come into play: readiness to collaborate; attention to multiple perspectives; initiative; persistence; curiosity.” Larry Rosenstock LearningREimagined project: http://learning-reimagined.com Larry Rosenstock: http://audioboo.fm/boos/1669375-50-seconds-of-larry-rosenstock-ceo-of-hightechhigh-on-how-he-would-re-imagine-learning 48
  • 49. Survey-based analytics for learning dispositions (Ruth Deakin Crick, Univ. Bristol / UTS:CIC Visiting Professor) Deakin Crick et al (In Press). Developing Resilient Agency in Learning: the Crick Learning for Resilient Agency Profile. 49
  • 50. 50 Survey-based analytics for learning dispositions Mindful Agency Sense making Creativity Hope and optimism Collaboration Belonging Curiosity Deakin Crick et al (In Press). Developing Resilient Agency in Learning: the Crick Learning for Resilient Agency Profile. Rapid Visual Feedback to SGmulate Self-­‐Directed Change A framework for a coaching conversaGon
  • 51. Mindful Agency Sense making Creativity Hope and optimism Collaboration Belonging Curiosity Taking responsibility for my own learning over time through defining my purposes, understanding and managing my feelings, knowing how I go about learning & planning my learning journey carefully.
  • 52. Mindful Agency Sense making Creativity Hope and optimism Collaboration Belonging Curiosity Making connections between what I already know & new information & experience. Making meaning by linking my story, my new learning & my purpose.
  • 53. Mindful Agency Sense making Creativity Hope and optimism Collaboration Belonging Curiosity Using my intuition & imagination to generate new ideas & knowledge. Taking risks & playing with ideas and artefacts to arrive at new solutions.
  • 54. Mindful Agency Sense making Creativity Hope and optimism Collaboration Belonging Curiosity Wanting to get beneath the surface & find out more. Always wondering why and how.
  • 55. Mindful Agency Sense making Creativity Hope and optimism Collaboration Belonging Curiosity Being part of a learning community at work, at home, in education & in my social networks. Knowing I have social resources to draw on when I need them
  • 56. Mindful Agency Sense making Creativity Hope and optimism Collaboration Belonging Curiosity Being able to work with others, to collaborate and co-generate new ideas and artefacts. Being able to listen and contribute productively to a team.
  • 57. Mindful Agency Sense making Creativity Hope and optimism Collaboration Belonging Curiosity Having the optimism & hope that I can learn & achieve over time. Having a growth mindset; believing I can generate my own new knowledge for what I need to achieve
  • 58. Mindful Agency Sense making Creativity Hope and optimism Collaboration Belonging Curiosity 1 Dependent Openness to learning Closed An emotional orientation of being open & ready to invest in learning, having flexible self-belief, willing to persist & manage any self-doubt. A necessary pre-requisite for developing resilience in learning
  • 59. From self-report to behavioural analytics for learning dispositions? Mindful Agency Sense making Tagging/sharing/blogging/social patterns reveal how you see connections between ideas? Creativity Hope and optimism Collaboration Belonging Curiosity Social network patterns, teamwork effectiveness and initiation of relationships? Questioning, arguing and search behaviours reveal intrinsic curiosity and epistemic commitments?
  • 60. Analytics for the UTS learning model? http://www.uts.edu.au/research-and-teaching/teaching-and-learning/learning2014/new-approaches
  • 61. Analytics for the UTS learning model? Relatively simple: • How much/when library and other resources are accessed • Annotations on texts, images, movies • Video replays and rewinds • Learner-shared resources http://www.uts.edu.au/research-and-teaching/teaching-and-learning/learning2014/new-approaches
  • 62. Shifts in epistemic commitments? (Simon Knight, KMi Open U. UK) Does the way you search online reveal what you think counts as trustworthy knowledge? What is it to ‘know’ when we search? http://sjgknight.com/finding-knowledge/2014/02/knowledge-in-search Danish exams permit Net: http://sjgknight.com/finding-knowledge/2013/07/danish-use-of-internet-in-exams-epistemology-pedagogy-assessment Epistemic networks for epistemic commitments: http://oro.open.ac.uk/39254
  • 63. Shifts in epistemic commitments? (Simon Knight, KMi Open U. UK) Dimensions of Epistemic Belief Certainty The degree to which knowledge is conceived as stable or changing, ranging from absolute, to tentative and evolving Simplicity The degree to which knowledge is conceived as compartmentalised or interrelated, ranging from knowledge as made up of discrete and simple facts to knowledge as complex and comprising interrelated concepts Source The relationship between knower and known, ranging from the belief that knowledge resides outside the self and is transmitted, to the belief that it is constructed by the self Justification What makes a sufficient knowledge claim, ranging from the belief in observation or authority as sources, to the belief in the use of rules of inquiry and evaluation of expertise Knight, Simon; Buckingham Shum, Simon and Littleton, Karen (2014). Epistemology, assessment, pedagogy: where learning meets analytics in the middle space. Journal of Learning Analytics (In press). http://oro.open.ac.uk/39226
  • 64. 64 Analytics for the UTS learning model? http://www.uts.edu.au/research-and-teaching/teaching-and-learning/learning2014/new-approaches
  • 65. 65 Are fieldwork students competent?
  • 66. In the future, how might we track teamworking? (U. Sydney) Automatic student tracking from multiple digital tabletops in classroom Analyse the students’ activity traces for significant patterns Visualise on a teacher’s dashboard R. Martinez, K. Yacef, J. Kay, and B. Schwendimann. An interactive teacher’s dashboard for monitoring multiple groups in a multi-tabletop learning environment. Proceedings of Intelligent Tutoring Systems, pages 482-492. Springer, 2012.
  • 67. In the future, how might we track teamworking? R. Martinez, K. Yacef, J. Kay, and B. Schwendimann. An interactive teacher’s dashboard for monitoring multiple groups in a multi-tabletop learning environment. Proceedings of Intelligent Tutoring Systems, pages 482-492. Springer, 2012.
  • 68. Learning Technology KMi, OU AI & ArgumentaGon Learning DisposiGons Learning AnalyGcs SemanGc ScienGfic Human-­‐Centred InformaGcs Publishing Dialogue / Issue / Argument Mapping Social learning analytics — quantifying “professional identity”
  • 69. Visual analytics to filter a social learning network by topic and type of social tie Schreurs B, Teplovs C, Ferguson R, De Laat M and Buckingham Shum S. (2013) Visualizing Social Learning Ties by Type and Topic: Rationale and Concept Demonstrator. Proc. 3rd International Conference on Learning Analytics & Knowledge. Leuven, BE: ACM, 33-37. Open Access Eprint: http://oro.open.ac.uk/36891
  • 70. Visual analytics to filter a social learning network by topic and type of social tie Schreurs B, Teplovs C, Ferguson R, De Laat M and Buckingham Shum S. (2013) Visualizing Social Learning Ties by Type and Topic: Rationale and Concept Demonstrator. Proc. 3rd International Conference on Learning Analytics & Knowledge. Leuven, BE: ACM, 33-37. Open Access Eprint: http://oro.open.ac.uk/36891
  • 71. What epistemic contributions are learners making in the community? De Liddo, A., Buckingham Shum, S., Quinto, I., Bachler, M. and Cannavacciuolo, L. (2011). Discourse-centric learning analytics. 1st Int. Conf. Learning Analytics & Knowledge (Banff, 27 Mar-1 Apr). ACM: New York. Eprint: http://oro.open.ac.uk/25829 71 Rebecca is playing the role of broker, connecting different peers’ contributions in meaningful ways We now have the basis for recommending that you engage with people NOT like you…
  • 72. 72 Analytics for the UTS learning model? http://www.uts.edu.au/research-and-teaching/teaching-and-learning/learning2014/new-approaches
  • 73. Real time traffic-lights for students based on predictive model (Purdue University Signals) Validate a statistical model from: • ACT or SAT score • Overall grade-point average • LMS usage composite • LMS assessment composite • LMS assignment composite • LMS calendar composite Predicted 66%-80% of struggling students who needed help Campbell et al (2703 07). Academic Analytics: A New Tool for a New Era, EDUCAUSE Review, vol. 42, no. 4 (July/August 2007): 40–57. http://bit.ly/lmxG2x
  • 74. Prototyping a social learning analytics dashboard 1 2 3 5 4 Your most recent mood comment: “Great, at last I have found all the resources that I have been looking for, thanks to Steve and Ellen. In your last discussion with your mentor, you decided to work on your resilience by taking on more learning challenges Your ELLI Spider shows that you have made a start on working on your resilience, and that you are also beginning to work on your creativity, which you identified as another area to work on. Ferguson R and Buckingham Shum S. (2012) Social Learning Analytics: Five Approaches. Proc. 2nd International Conference on Learning Analytics & Knowledge. Vancouver, 29 Apr-2 May: ACM: New York, 23-33. DOI: http://dx.doi.org/10.1145/2330601.2330616 Eprint: http://oro.open.ac.uk/32910 74
  • 75. 75 Analytics for the UTS learning model? http://www.uts.edu.au/research-and-teaching/teaching-and-learning/learning2014/new-approaches
  • 77. Teacher’s dashboard for EnquiryBlogger
  • 78. The hallmarks of educated writing/critical thinking Relevance Understanding & Knowledge Structure & Organisation Linguistic Accuracy Illustrations Referencing Argumentation 78
  • 79. Rhetorical functions of metadiscourse identified by the Xerox Incremental Parser (XIP) BACKGROUND KNOWLEDGE “Recent studies indicate …” “… the previously proposed …” “… is universally accepted ... “ NOVELTY ... new insights provide direct evidence ... ... we suggest a new ... approach ... ... results define a novel role ... OPEN QUESTION … little is known … … role … has been elusive Current data is insufficient … GENERALIZING ... emerging as a promising approach Our understanding ... has grown exponentially ... ... growing recognition of the importance ... CONTRASTING IDEAS … unorthodox view resolves … paradoxes … In contrast with previous hypotheses ... ... inconsistent with past findings ... SIGNIFICANCE studies ... have provided important advances Knowledge ... is crucial for ... understanding valuable information ... from studies SURPRISE We have recently observed ... surprisingly We have identified ... unusual The recent discovery ... suggests intriguing roles SUMMARIZING The goal of this study ... Here, we show ... Altogether, our results ... indicate 79
  • 80. XIP rhetorical parser applied to student writing Simsek, D., S. Buckingham Shum, Á. Sándor, A. De Liddo and R. Ferguson (2013). XIP Dashboard: Visual Analytics from Automated Rhetorical Parsing of Scientific Metadiscourse. 1st International Workshop on Discourse-Centric Learning Analytics, at 3rd International Conference on Learning Analytics & Knowledge. Leuven, BE (Apr. 8-12, 2013). http://oro.open.ac.uk/37391 80
  • 81. XIP rhetorical parser applied to student writing CONTRAST SUMMARY & CONTRIBUTION Simsek, D., S. Buckingham Shum, Á. Sándor, A. De Liddo and R. Ferguson (2013). XIP Dashboard: Visual Analytics from Automated Rhetorical Parsing of Scientific Metadiscourse. 1st International Workshop on Discourse-Centric Learning Analytics, at 3rd International Conference on Learning Analytics & Knowledge. Leuven, BE (Apr. 8-12, 2013). http://oro.open.ac.uk/37391 81
  • 83. h,p://th02.deviantart.net/fs71/PRE/f/2011/119/c/0/rabbit_shadow_by_plasGcx76-­‐d3f5qtd.jpg 83 Learners will leave an increasingly rich “digital shadow” Learning Analytics use this to provide rapid formative feedback (but this is of course an imperfect proxy for real experience)
  • 84. 84 Now the shadow can talk back! Let’s design shadows that learners + teachers value