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ascilite-webinar-oct2012

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Ascilite webinar series: http://www.ascilite.org.au/index.php?p=news_detail&item=240 …

Ascilite webinar series: http://www.ascilite.org.au/index.php?p=news_detail&item=240

A slightly different version of the Macquarie University keynote at http://www.slideshare.net/sbs/our-learning-analytics-are-our-pedagogy

I swapped out more general critiques of big data, for more detail on Dispositional and Discourse Learning Analytics

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  • 1. Ascilite Webinar, Oct 2012Our Learning Analyticsare Our Pedagogy Simon Buckingham Shum @ http://twitter.com/sbskmi Knowledge Media Institute, The Open University UK http://simon.buckinghamshum.net 1
  • 2. learning objective: walk out withbetter questions + lightning overview of learning analytics + glimpses of how analytics might nurture learning for the new terrain we face 2
  • 3. Musicality ≠ Musical Reproduction In those early days the children were taught from the start to develop their own voice, whether literally singing, or through the instrument they played. They were not taught music, but musicality. Central to this tuition were the partimenti, many pages of detailed music notes which pose many questions, but leave the pupil to find the solutions. The music is not a literal transcript, which the musician reads and reproduces. set of rules and then The partimenti establish, at the start, a pose a set of conflicts for the musician to resolve, in their own way. 3http://bit.ly/onmusicality
  • 4. is educationpoised to become a data-driven enterprise and science ? 4
  • 5. Possibly 90% of the digital data we havetoday was generated in the last 2 years Volume outstrips old infrastructure Variety Internet of things, e-business transactions, environmental sensors, social media, audio, video, mobile… Velocity The speed of data access and analysis is exploding A quantitative shift on this scale is in fact a qualitative shift, requiring new ways of thinking about societal phenomena 5
  • 6. edX: “this is big data, giving us the chanceto ask big questions about learning” Will the tomorrow’s educational researcher be as helpless without an analytics infrastructure, as a geneticist without genome databases, or a physicist without CERN? 6
  • 7. Lifelogging: explosion of data captureand sharing about personal activities http://www.mirror-project.eu http://quantifiedself.com/guide 7
  • 8. Educational Data Mining research community
  • 9. Learning Analytics research community
  • 10. Learning Analytics research communityhttp://www.educause.edu/library/learning-analytics
  • 11. different levels of analytic 11
  • 12. ‘Learning Analytics’ and‘Academic Analytics’Long, P. and Siemens, G. (2011), Penetrating the fog: analytics in learning and education. Educause Review Online,46, 5, pp.31-40. http://www.educause.edu/ero/article/penetrating-fog-analytics-learning-and-education 12
  • 13. Macro/Meso/Micro Learning Analytics Macro: region/state/national/international
  • 14. Macro/Meso/Micro Learning Analytics Macro: region/state/national/international Meso: institution-wide
  • 15. Macro/Meso/Micro Learning Analytics Macro: region/state/national/international Meso: institution-wide Micro: individual user actions (and hence cohort) Will institutions be dazzled by the dashboards, or know what questions to ask at each level?
  • 16. Macro/Meso/Micro Learning Analytics Macro: region/state/national/international
  • 17. US states are getting the infrastructurein placedataqualitycampaign.org 17
  • 18. Shared Learning Collaborativehttp://slcedu.org 18
  • 19. National league tables for English schools 19
  • 20. Macro/Meso/Micro Learning Analytics Meso: institution-wide
  • 21. Business Intelligence companies see aneducation market opening up These are pedagogically agnostic: they seek to optimize operational efficiency whatever the sector These may make pedagogical assumptions: how will learning design and assessment regimes shape the analytics they offer?http://www.sas.com/industry/education/highered 21
  • 22. Business Intelligence companies see aneducation market opening up …but do they know anything about the roles that language plays in learning and knowledge construction? 22
  • 23. BI+HigherEd communities of practice 23
  • 24. Macro/Meso/Micro Learning Analytics Micro: individual user actions (and hence cohort)
  • 25. Analytics in your VLE:Blackboard: feedback to studentshttp://www.blackboard.com/Platforms/Analytics/Overview.aspx 25
  • 26. Purdue University Signals: real time traffic-lights for students based on predictive model Premise: academic success is defined as a function of aptitude (as measured by standardized test scores and similar information) and effort (as measured by participation within the online learning environment). Using factor analysis and logistic regression, a model was tested to predict student success based on: •  ACT or SAT score •  Overall grade-point average Predicted 66%-80% •  CMS usage composite of struggling •  CMS assessment composite students who •  CMS assignment composite needed help •  CMS calendar composite Campbell et al (2007). Academic Analytics: A New Tool for a New Era, EDUCAUSE Review, vol. 42, no. 4 (July/August 2007): 40–57. http://bit.ly/lmxG2x 26
  • 27. Desire2Learn visual analytics & predictive modelswhich can be interrogated on different dimensionshttp://www.desire2learn.com/products/analytics 27
  • 28. Desire2Learn visual analytics & predictive modelswhich can be interrogated on different dimensionshttp://www.desire2learn.com/products/analytics 28
  • 29. Socrato: train for SATshttp://www.socrato.com 29
  • 30. Khan Academy: more data to teachers,finer-grained feedback to studentshttp://www.thegatesnotes.com/Topics/Education/Sal-Khan-Analytics-Khan-Academy 30
  • 31. Adaptive platforms generate fine-grained analyticshttps://grockit.com/research 31
  • 32. Adaptive platforms generate fine-grainedanalytics http://knewton.com
  • 33. The VLE—BI—ITS convergence 33
  • 34. Hard distinctions between Learning +Academic analytics may dissolve…as they get joined up, each level enriches the others Macro: region/state/national/international Meso: institution-wide Micro: individual user actions (and hence cohort) Aggregation of user tracesenriches meso + macro analytics with finer-grained process data
  • 35. Hard distinctions between Learning +Academic analytics may dissolve…as they get joined up, each level enriches the others Macro: region/state/national/international Meso: institution-wide Micro: individual user actions (and hence cohort) Aggregation of user traces Breadth + depth from macroenriches meso + macro analytics + meso levels add power to with finer-grained process data micro analytics
  • 36. questions/comments? 36
  • 37. but how do we do analytics forthis kind of learning?... 37
  • 38. Learning analytics for this?“We are preparing students for jobs that do not exist yet, that will use technologies that have not been invented yet, in order to solve problems that are not even problems yet.” “Shift Happens” http://shifthappens.wikispaces.com 38
  • 39. Learning analytics for this?“While employers continue to demand high academic standards, they also now want more. They want people who can adapt, see connections, innovate, communicate and work with others. This is true in many areas of work. The new knowledge-based economies in particular will increasingly depend on these abilities. Many businesses are paying for courses to promote creative abilities, to teach the skills and attitudes that are now essential for economic success…” All our Futures: Creativity, culture & education, May 1999 39
  • 40. Learning analytics for this?Think about the analytics products and initiativesreviewed above – where would you locate them on these dimensions?Creativity, Culture andEducation (2009)Changing Young Lives2012. Newcastle: CCE.http://www.creativitycultureeducation.org/changing-young-lives-2012 40
  • 41. Learning analytics for this? The Knowledge-Agency Window co-generation Expert-led enquiry Student-led enquiry Knowledge and use Teaching as Authenticity learning design Agency Identity Repetition, Pre-scribed Knowledge Abstraction Acquisition Expert-led teaching Student-led revision Teacher agency Student agencyRuth Deakin Crick, Univ. Bristol, Centre for Systems Learning & Leadership“Pedagogy of Hope”: http://learningemergence.net/2012/09/21/pedagogy-of-hope
  • 42. analytics grounded in the principles of good assessment for learning? (not summative assessment for grading pupils, teachers, institutions or nations) 42
  • 43. Assessment for Learning Few learning analytics arehttp://assessment-reform-group.org currently able to take o board the richness of this original conception of assessment for learning 43
  • 44. Assessment for Learninghttp://assessment-reform-group.org 44
  • 45. Assessment for Learninghttp://assessment-reform-group.org To what extent could automated feedback be designed and evaluated with emotional impact in mind? 45
  • 46. Assessment for Learninghttp://assessment-reform-group.org Can analytics identify proxies for such advanced qualities? 46
  • 47. Assessment for Learninghttp://assessment-reform-group.org Do analytics provide constructive next steps? 47
  • 48. Assessment for Learninghttp://assessment-reform-group.org How do we provide analytics feedback that does not disempower and de- motivate struggling learners? 48
  • 49. DispositionalLearning Analytics 49
  • 50. Musicality ≠ Musical Reproduction In those early days the children were taught from the start to develop their own voice, whether literally singing, or through the instrument they played. They were not taught music, but musicality. Central to this tuition were the partimenti, many pages of detailed music notes which pose many questions, but leave the pupil to find the solutions. The music is not a literal transcript, which the musician reads and reproduces. set of rules and then The partimenti establish, at the start, a pose a set of conflicts for the musician to resolve, in their own way. 50http://bit.ly/onmusicality
  • 51. Dispositions are important “Knowledge of methods alone will not suffice: there must be the desire, the will, to employ them. This desire is an affair of personal disposition.” John Dewey, 1933Dewey, J. How We Think: A Restatement of the Relation of Reflective Thinking to theEducative Process. Heath and Co, Boston, 1933 51
  • 52. Dispositions are important“The test of successful education is not the amount of knowledge that pupils take away from school, but their appetite to know and their capacity to learn.” Sir Richard Livingstone, 1941 52
  • 53. Dispositions are importantSlide from Guy Claxton: http://www.scribd.com/doc/26685380/Guy-Claxton-Learning-to-LearnPerkins, D.N., Jay, E., & Tishman, S. (1993). Beyond abilities: A dispositional theory of thinking. Merrill- 53Palmer Quarterly: Journal of Developmental Psychology, 39(1): 1-21.
  • 54. Dispositions are beginning to registerwithin the learning analytics communityBrown, M., Learning Analytics: Moving from Concept to Practice. EDUCAUSE Learning InitiativeBriefing, 2012. http://www.educause.edu/library/resources/learning-analytics-moving-concept-practice 54
  • 55. In your experience, what are the qualitiesshown by the most effective learners? Think about the most effective learners you’ve met/ mentored/taught Not necessarily the highest grade scorers, but the ones who showed a sustained appetite for learning What qualities/dispositions/attitudes did they bring? Type a few key words into the textchat… 55
  • 56. A ‘visual learning analytic’ 7-dimensional spider diagram of how the learner sees themself Basis for a mentored- discussion on how the learner sees him/herself, and strategies for strengthening the profile 56Bristol and Open University are now embedding ELLI in learning software.
  • 57. ELLI: Effective Lifelong Learning InventoryWeb questionnaire 72 items (children and adult versions: usedin schools, universities and workplace) 57
  • 58. Validated as loading onto7 dimensions of “Learning Power” Being Stuck & Static Changing & Learning Data Accumulation Meaning Making Passivity Critical Curiosity Being Rule Bound Creativity Isolation & Dependence Learning Relationships Being Robotic Strategic Awareness Fragility & Dependence ResilienceUniv. Bristol and Vital Partnerships provides practitioner resourcesand tools to support their application in schools and the workplace 58
  • 59. Learning to Learn: 7 Dimensions of Learning PowerFactor analysis of the literature plus expert interviews: identified sevendimensions of effective learning power , since validated empirically withlearners at many levels. (Deakin Crick, Broadfoot and Claxton, 2004)
  • 60. Learning to Learn: 7 Dimensions of Learning PowerFactor analysis of the literature plus expert interviews: identified sevendimensions of effective learning power , since validated empirically withlearners at many levels. (Deakin Crick, Broadfoot and Claxton, 2004) 60
  • 61. Learning Warehouse 2.0 analytics platform User experience: Research-validated assessment tools Researcher interface Learning Communities Analytics: Real time ELLI Analytics reports Bespoke research reports Datasets: >40,000 ELLI profiles (data from other hosted apps) 61
  • 62. Adding imagery to ELLI dimensions toconnect with learner identity 62
  • 63. Working with Gappuwiyak School, N. Territory AUS (Ruth Deakin Crick, University of Bristol) http://bit.ly/srUSHE Changing & Learning: Strategic Awareness: The Drongo - Guwak Emu - Wurrpan Meaning Making: The Pigeon - Nabalawal Critical Curiosity: Sea Eagle - Djert Resilience: Brolga - GudurrkuLearning Relationships: Creativity: The Cockatoo - Ngerrk Bower Bird - Djurwirr 63
  • 64. Cohort analytics foreducators andorganizational leaders 64
  • 65. EnquiryBlogger:Tuning Wordpress as an ELLI-based learning journal Standard Wordpress editor Categories from ELLI Plugin visualizes blog categories, mirroring the ELLI spider 65
  • 66. Primary School EnquiryBloggersBushfield School, Wolverton, UKEnquiryBlogger: blogging for Learning Power & Authentic Enquiryhttp://learningemergence.net/2012/06/20/enquiryblogger-for-learning-power-authentic-enquiry
  • 67. EnquiryBlogger dashboard
  • 68. Could a platform generate an ELLI profile from user traces? Different social network patterns Questioning and in different challenging may contexts may load onto Critical load onto Curiosity Learning Relationships Repeated Sharing relevant attempts to pass resources from an online test other contexts may load onto may load onto Resilience Meaning MakingShaofu Huang: Prototyping Learning Power Modelling in SocialLearnhttp://www.open.ac.uk/blogs/SocialLearnResearch/2012/06/20/social-learning-analytics-symposium
  • 69. SocialLearn provides new possibilities of looking at learners learning ELLI works from what Now we can observe what learners say they do they actually do…Shaofu Huang: Prototyping Learning Power Modelling in SocialLearn 69http://www.open.ac.uk/blogs/SocialLearnResearch/2012/06/20/social-learning-analytics-symposium
  • 70. ELLI feedbacks inform development of learning Educator or leader s interventions Mentored discussionsShaofu Huang: Prototyping Learning Power Modelling in SocialLearn 70http://www.open.ac.uk/blogs/SocialLearnResearch/2012/06/20/social-learning-analytics-symposium
  • 71. How about SocialLearn learning disposition analytics? How do these feedbacks help people learn? What and where What kind of feedback should we look at? should we provide? Will we still have What is the most appropriate seven dimensions? way to do it?Shaofu Huang: Prototyping Learning Power Modelling in SocialLearn 71http://www.open.ac.uk/blogs/SocialLearnResearch/2012/06/20/social-learning-analytics-symposium
  • 72. LearningEmergence.net: embeddingdispositional analytics into practice + toolsEnquiryBlogger: Wordpress plugins for reflective learning journals 72
  • 73. Analytics forlearning conversations 73
  • 74. Socio-cultural discourse analysis(Mercer et al, OU)•  Disputational talk, characterised by disagreement and individualised decision making.•  Cumulative talk, in which speakers build positively but uncritically on what the others have said.•  Exploratory talk, in which partners engage critically but constructively with each others ideas.Mercer, N. (2004). Sociocultural discourse analysis: analysing classroom talk as a socialmode of thinking. Journal of Applied Linguistics, 1(2), 137-168. 74
  • 75. Socio-cultural discourse analysis(Mercer et al, OU)•  Exploratory talk, in which partners engage critically but constructively with each others ideas. •  Statements and suggestions are offered for joint consideration. •  These may be challenged and counter-challenged, but challenges are justified and alternative hypotheses are offered. •  Partners all actively participate and opinions are sought and considered before decisions are jointly made. •  Compared with the other two types, in Exploratory talk knowledge is made more publicly accountable and reasoning is more visible in the talk.Mercer, N. (2004). Sociocultural discourse analysis: analysing classroom talk as a socialmode of thinking. Journal of Applied Linguistics, 1(2), 137-168. 75
  • 76. Analytics for identifying Exploratory talk Elluminate sessions can be very long – lasting for hours or even covering days of a conference It would be useful if we could identify where quality learning conversations seem to be taking place, so we can recommend those sessions, and not have to sit through online chat about virtual biscuitsFerguson, R. and Buckingham Shum, S. Learning analytics to identify exploratory dialogue within synchronous text chat. 761st International Conference on Learning Analytics & Knowledge (Banff, Canada, 27 Mar-1 Apr, 2011)
  • 77. Defining indicators of Exploratory Talk Category Indicator Challenge But if, have to respond, my view Critique However, I’m not sure, maybe Discussion of Have you read, more links resources Evaluation Good example, good point Explanation Means that, our goals Explicit reasoning Next step, relates to, that’s why Justification I mean, we learned, we observed Reflections of Agree, here is another, makes the perspectives of others point, take your point, your view 77
  • 78. Extract classified as Exploratory Talk Time Contribution 2:42 PM I hate talking. :-P My question was whether "gadgets" were just basically widgets and we could embed them in various web sites, like Netvibes, Google Desktop, etc. 2:42 PM Thanks, thats great! I am sure I understood everything, but looks inspiring! 2:43 PM Yes why OU tools not generic tools? 2:43 PM Issues of interoperability 2:43 PM The "new" SocialLearn site looks a lot like a corkboard where you can add various widgets, similar to those existing web start pages. 2:43 PM What if we end up with as many apps/gadgets as we have social networks and then we need a recommender for the apps! 2:43 PM My question was on the definition of the crowd in the wisdom of crowds we acsess in the service model? 2:43 PM there are various different flavours of widget e.g. Google gadgets, W3C widgets etc. SocialLearn has gone for Google gadgets 78
  • 79. Discourse analytics on webinar textchat Given a 2.5 hour webinar, where in the live textchat were the most effective learning conversations? Not at the start and end of a webinar Sheffield, UK not as sunny but if we zoom in on a peak… See you! as yesterday - still warm bye for now! Greetings from Hong Kong bye, and thank you Morning from Wiltshire, 80 sunny here! Bye all for now 60 40 20 0 9:28 9:32 10:13 11:48 12:00 12:05 12:04 9:36 9:40 9:41 9:46 9:50 9:53 9:56 10:00 10:05 10:07 10:07 10:09 10:17 10:23 10:27 10:31 10:35 10:40 10:45 10:52 10:55 11:04 11:08 11:11 11:17 11:20 11:24 11:26 11:28 11:31 11:32 11:35 11:36 11:38 11:39 11:41 11:44 11:46 11:52 11:54 12:03 -20 -40 Average Exploratory -60Wei & He extensions to: Ferguson, R. and Buckingham Shum, S. (2011). Learning Analytics to Identify Exploratory Dialogue within SynchronousText Chat. Proc. 1st Int. Conf. Learning Analytics & Knowledge. Feb. 27-Mar 1, 2011, Banff. ACM Press. Eprint: http://oro.open.ac.uk/28955
  • 80. Discourse analytics on webinar textchat Given a 2.5 hour webinar, where in the live textchat were the most effective learning conversations? Classified as “exploratory talk” (more substantive 100 for learning) 50 0 9:28 “non- 9:40 9:50 10:00 10:07 10:17 10:31 10:45 11:04 11:17 11:26 11:32 11:38 11:44 11:52 12:03 -50 exploratory” Averag -100Wei & He extensions to: Ferguson, R. and Buckingham Shum, S. (2011). Learning Analytics to Identify Exploratory Dialogue within SynchronousText Chat. Proc. 1st Int. Conf. Learning Analytics & Knowledge. Feb. 27-Mar 1, 2011, Banff. ACM Press. Eprint: http://oro.open.ac.uk/28955
  • 81. Discourse analysis (Xerox Incremental Parser)Detection of salient sentences in scholarly reports,based on the rhetorical signals authors use:BACKGROUND KNOWLEDGE: NOVELTY: OPEN QUESTION:Recent studies indicate … ... new insights provide direct evidence ... … little is known …… the previously proposed … ... we suggest a new ... approach ... … role … has been elusive Current data is insufficient …… is universally accepted ... ... results define a novel role ...CONRASTING IDEAS: SIGNIFICANCE: SUMMARIZING:… unorthodox view resolves … studies ... have provided important The goal of this study ...paradoxes … advances Here, we show ...In contrast with previous Knowledge ... is crucial for ... Altogether, our results ... indicatehypotheses ... understanding... inconsistent with past findings ... valuable information ... from studiesGENERALIZING: SURPRISE:... emerging as a promising approach We have recently observed ... surprisinglyOur understanding ... has grownexponentially ... We have identified ... unusual... growing recognition of the The recent discovery ... suggests Ágnes Sándor & OLnet Project: http://olnet.org/node/512 intriguing rolesimportance ...De Liddo, A., Sándor, Á. and Buckingham Shum, S., Contested Collective Intelligence: Rationale, Technologies, and a Human-MachineAnnotation Study. Computer Supported Cooperative Work, 21, 4-5, (2012), 417-448. http://oro.open.ac.uk/31052
  • 82. Human and machine analysis of a text for keycontributions Document 1 19 sentences annotated 22 sentences annotated 11 sentences same as human annotation Document 2 71 sentences annotated 59 sentences annotated 42 sentences same as human annotationhttp://technologies.kmi.open.ac.uk/cohere/2012/01/09/cohere-plus-automated-rhetorical-annotationDe Liddo, A., Sándor, Á. and Buckingham Shum, S., Contested Collective Intelligence: Rationale, Technologies, and a Human-MachineAnnotation Study. Computer Supported Cooperative Work, 21, 4-5, (2012), 417-448. http://oro.open.ac.uk/31052
  • 83. KMi’s Cohere: a web deliberation platform enabling semantic social network and discourse network analytics Rebecca is playing the role of broker, connecting 2 peers’ contributions in meaningful waysDe Liddo, A., Buckingham Shum, S., Quinto, I., Bachler, M. and Cannavacciuolo, L. Discourse-centric learning analytics. 1stInternational Conference on Learning Analytics & Knowledge (Banff, 27 Mar-1 Apr, 2011) http://oro.open.ac.uk/25829
  • 84. Discourse Network Analytics = Concept Network + Social Network AnalyticsDe Liddo, A., Buckingham Shum, S., Quinto, I., Bachler, M. and Cannavacciuolo, L. Discourse-centric learning analytics. 1stInternational Conference on Learning Analytics & Knowledge (Banff, 27 Mar-1 Apr, 2011) http://oro.open.ac.uk/25829
  • 85. Closing thoughts 85
  • 86. “The basic question is not what can we measure? The basic question is what does a good education look like?” (Gardner Campbell)http://chronicle.com/blogs/techtherapy/2012/05/02/episode-95-learning-analytics-could-lead-to-wal-martification-of-collegehttp://lak12.wikispaces.com/Recordings 86
  • 87. Our analytics promote values, pedagogy and assessment regimes. Are we clear which master our analytics serve? Are wehappy to be judged by them? 87
  • 88. LAnoirblanc.tumblr.comreactions to Learning Analytics in image and story Choose an image and email it to the site with your story… Instructions: h"p://www.educause.edu/sites/default/files/library/presenta7ons/ELI124/GS13/LAnoirblanc.pdf

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