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Making social learning visible: some provocations for Connected Learning Analytics dashboard concepts Simon Buckingham Shum Professor of Learning Informatics Director, Connected Intelligence Centre @sbuckshum cic.uts.edu.au

Provocations for CLA Dashboard

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Page 1: Provocations for CLA Dashboard

Making social learning visible: some provocations for Connected Learning Analytics dashboard concepts

Simon Buckingham Shum Professor of Learning Informatics Director, Connected Intelligence Centre @sbuckshum

cic.uts.edu.au

Page 2: Provocations for CLA Dashboard

To nurture skillful social learners (prev talk)…

…invisible + ephemeral social processes need to be made visible + persistent

…for which we need analytics to aggregate + visualise data meaningfully

as proxies for social + personal learning 2

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Bridging the data—meaning gulf

3

logs of user actions (xAPI triples)

meaningful, timely representations

how students and educators think about learning (not necessarily the same thing)

Page 4: Provocations for CLA Dashboard

Bridging the data—meaning gulf

4

logs of user actions (xAPI triples)

meaningful, timely representations

how students and educators think about learning (not necessarily the same thing)

sensem

aking  

ac+o

n/interven

+on  

Page 5: Provocations for CLA Dashboard

Bridging the data—meaning gulf

5 logs of user actions (xAPI triples)

meaningful, timely representations

how students and educators think about learning (not necessarily the same thing)

Bloo

m’s  ta

xono

my,  etc  

Ope

ra&o

n  ...  W

ayfin

ding  …  Sen

semaking  …  Inno

va&o

n  

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All of the following are possible in closed learning platforms

‘Technically straightforward’ to apply to an xAPI LRS?

But which are of most interest? 6

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textchat + videoconf replay + analytics

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FlashMeeting (Open University’s Knowledge Media Institute)

8 http://flashmeeting.open.ac.uk

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FlashMeeting (Open University’s Knowledge Media Institute)

9 http://flashmeeting.open.ac.uk

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social network analytics

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Learning  Technology  

KMi,  OU  

AI  &  Argumenta&on  

Learning  Disposi&ons  

Human-­‐Centred    Informa&cs  

Learning  Analy&cs  

Seman&c  Scien&fic    Publishing  

Dialogue  /  Issue  /  Argument  Mapping  

Social learning analytics — quantifying “professional identity”

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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

Adding topic and type of social tie to filter SN

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Adding topic and type of social tie to filter SN

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

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discourse analytics

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analytics that look beneath the surface, and quantify linguistic proxies for ‘deeper learning’

Beyond number / size / frequency of posts; ‘hottest thread’

http://ww

w.glennsasscer.com

/wordpress/w

p-content/uploads/2011/10/iceberg.jpg

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Discourse analytics on webinar textchat

Ferguson, R. and Buckingham Shum, S., Learning analytics to identify exploratory dialogue within synchronous text chat. In: 1st International Conference on Learning Analytics and Knowledge (Banff, Canada, 2011). ACM

Can we spot the quality learning conversations in a 2.5 hr webinar?

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Average Exploratory

Discourse analytics on webinar textchat

Sheffield, UK not as sunny as yesterday - still warm

Greetings from Hong Kong

Morning from Wiltshire, sunny here!

See you!

bye for now!

bye, and thank you

Bye all for now

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…

Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc. 3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664

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Average Exploratory

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 but if we zoom in on a peak…

Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc. 3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664

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Discourse analytics on webinar textchat

-100

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Averag

Classified as “exploratory

talk”

(more substantive for learning)

“non-exploratory”

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 but if we zoom in on a peak…

Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc. 3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664

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writing analytics

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Visualizations of writing cohesion

21 Whitelock, D., D. Field, J. T. E. Richardson, N. V. Labeke and S. Pulman (2014). Designing and Testing Visual Representations of Draft Essays for Higher Education Students. 2nd International Workshop on Discourse-Centric Learning Analytics, Fourth International Conference on Learning Analytics and Knowledge, Indianapolis, Indiana, USA. https://dcla14.files.wordpress.com/2014/03/dcla14_whitelock_etal.pdf

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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

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AWA: Academic Writing Analytics tool

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AWA: Academic Writing Analytics tool

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AWA: Academic Writing Analytics tool

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dispositional analytics

making dispositions visible, quantifiable, and improvable

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“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 High Tech High

San Diego hightechhigh.org

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

Knowledge, Skills & Dispositions

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“It’s vital to know that … focusing on learning is not smoke and mirrors. It’s not just some clever idea among the intelligentsia. It’s really important.

And it’s really, really important that we can measure it, demonstrate it, and develop a language for it.”

Mark Moorhouse Matthew Moss High School,

Rochdale, UK

http://youtu.be/kayzkma1TIM — Learning Futures channel: http://bit.ly/lfmovies MMHS website: http://www.mmhs.co.uk/learning

Measuring learning to learn

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Deakin Crick, R., S. Huang, A. Ahmed Shafi and C. Goldspink (2015). Developing Resilient Agency in Learning: The Internal Structure of Learning Power. British Journal of Educational Studies: Published online: 24 Mar 2015. http://dx.doi.org/10.1080/00071005.2015.1006574 29

Evidencing learning dispositions: CLARA survey (Ruth Deakin Crick, UTS)

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Structural Equation Model underpinning CLARA

Deakin Crick, R., S. Huang, A. Ahmed Shafi and C. Goldspink (2015). Developing Resilient Agency in Learning: The Internal Structure of Learning Power. British Journal of Educational Studies: Published online: 24 Mar 2015. http://dx.doi.org/10.1080/00071005.2015.1006574

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Mindful Agency

Sense making

Creativity

Curiosity Belonging

Collaboration

Hope and optimism

Immediate visual analytic generated by CLARA (Individual and cohort profiles + detailed reports + spreadsheets enabling further analysis)

Rapid Visual Feedback to Stimulate Self-Directed Change

A framework for a coaching conversation

+

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Mindful Agency

Sense making

Creativity

Curiosity Belonging

Collaboration

Hope and optimism

Behavioural analytics for learning dispositions?

Social network patterns, teamwork effectiveness and

initiation of relationships?

Questioning, arguing and search behaviours reveal

intrinsic curiosity and epistemic commitments?

Tagging/sharing/blogging/social patterns reveal how you see connections between ideas?

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From blog feeds (to xAPI?)

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Mood View widget

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Dashboard view

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Teacher’s dashboard for EnquiryBlogger

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a learning design patterns tool?

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CompendiumLD: for OU Learning Design

OU LDI Project led by Grainne Conole: http://compendiumld.open.ac.uk

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(screenshots from CLAtoolkit demo)

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Harvesting social media activity as xAPI triples

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Harvesting social media activity as xAPI triples

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Facebook  

TwiOer  

Integrated  data  stream  

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Harvesting social media activity as xAPI triples

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