Learning with the Crowd Haythornthwaite OII Bellwether oct 17 2014.pptx

Picture by Ksenia Cheinman

Bellwether From Wikipedia, the free encyclopedia This article is about bellwethers in general. For Connie Willis's book, see Bellwether (novel).

A bellwether; one that leads or indicates trends.

The term is derived from the Middle English bellewether and refers to the practice of placing a bell around the neck of a castrated ram (a wether) leading his flock of sheep. The movements of the flock could be noted by hearing the bell before the flock was in sight.

Background image: http://melstampz.blogspot.ca/ Ceramic ram, V&A

INDIVIDUALLY AND COLLECTIVELY by common media use, interest, location

#oiibellwether, #lak14, #las14, #SMSociety14, #hcsmca

Current conditions around online practice have created the ‘Perfect Storm’ for Learning with the Crowd

https://socialmediaandsociety.com/wp-content/uploads/2014/09/net_sep27-210x210.png

Netlytic sw

Online learning + retrievable online resources {open access + participatory culture + search engines} + net generation + technology infrastructures

Social Media & Society Conference “More than 2,000 tweets on day 1 of #SMSociety14” Anatoliy Gruzd

!  How I got to this topic ◦  Networks & Communities ◦  Studies of e-learners ◦  E-learning

!  The turn to crowds ◦  Crowds & Communities ◦  Massive open online learning

(MOOCs) !  Futures

E-learning as a transformation in how, where, when and with whom we learn

!  How does the ‘lean’ medium of the Internet support collaboration, community?

!  How do we learn, co-construct knowledge and work together online?

!  What do people do together (online) that leads them to say they belong to a (virtual) community?

!  How do the Internet and new media structure who talks to whom?

!  How can we make theoretical sense of driving forces associated with the multiple changes and practices associated with the Internet?

!  What motivates participation in online crowds and communities?

!  Can we ‘see’ learning in an online transcript? learning analytics

What’s your research question about the Internet – for learning or other interaction or outcome?

#oiibellwether

Actors – people, groups or organizations – tied by relations that form networks, analyzed and displayed as graphs !  Asking network questions

uncovers relationships and structures ◦  Who talks to whom about what

and via which media ◦  Actors who are stars, brokers ◦  Structures: dense or sparse

networks, cliques, clusters, structural holes

!  Outcomes ◦  Relational constructs: strong and

weak ties, homophily ◦  Social capital, inclusion, awareness,

information access, resource availability

Collaboration network – who works with whom in an online learning class

SNA: An approach, method and vocabulary for analyzing social structures

EMERGENT PATTERNS

Unscheduled Meetings Scheduled Meetings Email

Co-located Computer Scientists: Guttman scaling for overall communication: CR=.92. Order: face-to-face, unscheduled, scheduled, email, other

Chat Discussion boards Email Distance Learners: Guttman scaling, overall communication all term CR=.99: Chat, Webboard, Email, Phone

Class F97: Collaborative work via Chat and Email by Time

Chat

Email

Group projects; Webboard also used for discussion, connected all to all.

Time 1 Time 2 Time 3

Time 1 Time 2 Time 3

!  Wide connectivity, low frequency ◦  Discussion boards, Chat ◦  Group-mandated media ◦  Group-wide, public ◦  Communicate with the

group as a whole

!  Interaction patterns reflect tasks as set by authorities

!  Selected connectivity, high frequency ◦  Email, Phone ◦  Optional media ◦  Person-to-person, private ◦  Communicate with

friends and co-workers

!  Interaction patterns reflect needs of participants

!  An authority-organized means of connectivity provides a latent tie structure on which ties may grow ◦  This lecture, an online forum, office meetings, a MOOC ◦  Where connections are technically made but not yet activated

socially !  A change in that means of connectivity disrupts weak ties ◦  Meetings no longer occur, a virtual community shuts down, a

class ends ◦  Because weak ties only connected because of the group

organized forum !  A change does not disrupt strong ties ◦  Chat doesn’t work, they move to email, to twitter, to online

forums ◦  Because strong ties have other means of communication (media

multiplexity) and more commitment to connect

!  Using online means to start a community

!  Here a sample of the twitter network of the Health Care Social Media Canada

!  Aim of organizer Colleen Young was to encourage a self-sustaining learning community ◦  Network shows this

kind of configuration #hcsmca Twitter Network (one month, Nov-Dec 2012)

Tie = mentions or replies in messages Gruzd & Haythornthwaite, 2013

What would you look for in #hcsmca transcripts to show or discover learning?

#oiibellwether

Distribution of Learning Relations Interdisciplinary Teams: Science, social science, and education

Data = Number of pairs maintaining each type of relation

Learning relations can be used as input for analysis and design of collaborative and/or learning spaces

Haythornthwaite, 2006

Learning can be !  A relation that connects people ◦  teaching, learning, collaborative learning

!  The characterization of the tie ◦  learning relationship

!  A characterization of the outcome of relations ◦  learning community, community of inquiry, practice

!  The network outcome of relations ◦  social capital, knowledge held in the network

!  Derived from ambient influence ◦  news, gossip, common knowledge, culture, values

!  Who learns from whom? ◦  Who talks to, gives help to,

collaborates with whom? !  What do they learn from each

other? !  Which media support which

kinds of learning? !  What outcomes do

these relations build? ◦  Access to resources

Trust, mobility, equity, etc. !  What benefit accrues to the

network? ◦  social capital, shared

knowledge, resources !  How do resources flow in the

network

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Twitter – node size = accounts that are frequently mentioned, replied to or whose tweets are frequently retweeted

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Work in progress. SSHRC funded. Learning Analytics for the Social Media Age Gruzd, Haythornthwaite, Siemens, Paulin, Absar

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!  Technologies (hw, sw) ◦  Devices ◦  Media ◦  Telecomm networks ◦  Network Infrastructures ◦  Internet ◦  Apps ◦  Digital libraries ◦  Wikis ◦  LMS/VLE ◦  Blogs ◦  Twitter ◦  Crowdsourcing ◦  Data harvesting ◦  Text /data mining ◦  Analytics

!  Societal responses ◦  Privacy ◦  Copyright, creative commons ◦  Participatory culture ◦  Open source ◦  Open access ◦  Public knowledge ◦  Online journals ◦  Web sites ◦  Blogging ◦  Institutional repositories ◦  Wiki encyclopedia ◦  Online commerce ◦  Online courses, degrees ◦  Crowdsourcing, human computation ◦  Citizen science ◦  MOOCs ◦  Learning analytics ◦  Crowdsourcing the curriculum

Does anyone know how to get a non-breaking hyphen in a powerpoint slide?

#oiibellwether

!  Collaborative practices ◦  Learning communities, co-

construction of knowledge ◦  Entrepreneurial and self-

directed learning !  Embracing ‘perpetual

beta’ ◦ Co-creation and negotiation

of learning practice ◦  Expansive learning,

Community of Practice !  E-retrieval ◦ Online information literate ◦ Accessing resources and

people

!  Participatory practices ◦ Contributory as well as

retrieval ◦ Crowd and community

based !  Sociotechnical fluency ◦  Balancing the social and the

technical ◦  Across multimodalities,

multimedia

Adopting and becoming fluent in new practices

!  “A bottom-up approach reflects a community of practice ... As a result, questions about when it begins or ends, and whether it reaches its goals make less sense. A revised set of questions then arises.”

!  What does the community value? How does it evolve? How do members facilitate interaction?

!  Bruce, 2010

Boeing Aircraft flying boad ‘Thunderbird’, City of Vancouver Archives, public domain

!  Separate ◦  Programs, units,

universities ◦  Distance or continuing

education units ◦  Single courses ◦  Single degree

programs ◦  Online universities

!  Integrated ◦  Learning management

systems (LMS/ VLE) ◦  Blended ◦  On-campus ‘distance’

learning

25

Bringing e-learning in from the cold …

!  Familiar ◦  Challenge exams for credit

for degrees ◦  Credit for work experience ◦  Work placements,

internships, co-op programs ◦  Short courses – shorter

than the traditional term ◦  Teaching assistants ◦  Class of 25, 50, 100 ◦  Known learners ◦  Known locations ◦  Educational institutions

!  Not so familiar ◦  Longer courses – longer

than traditional ◦  Flexible course lengths ◦  Post-graduation courses as

part of university commitment ◦  Badges ◦  Exams ! portfolios ◦  Online ! multi-site, multi-

national, multi-cultural ◦  Bringing in past learners ◦  Crowds

"  Classes of 1000, 5000 + "  Unknown learners "  Unknown locations

! Outside crowd is pushing in ◦ Next generation learners ◦ Crowdsourced information becomes

mainstream – wikipedia, blogs, twitter ◦ Crowd members become resource nodes "  Experience makes teachers

"  e.g., Patients Like Me - patients explaining their experience, researching for others and themselves

◦ Validation of crowd knowledge "  Citizen journalists

Internet users-Adults • UK, 2013 - 73% • Australia, 2012 - 89% • Canada, 2010 - 80% • US, 2011 - 78%

Social  Networking  Sites:    • Adults  -­‐  60%  • Non-­‐students  18-­‐24  -­‐  88%      • Community  College  -­‐  72%        • Undergrads  -­‐  86%    • Graduate  Students  -­‐  82%  

! Disseminating expert public knowledge ◦ Open access ◦ Creative commons ◦ MOOCs

! Reclaiming expertise ◦  Peer reviewed open access journals ◦ MOOC-based crowd dissemination from

recognized scholars and institutions

!  Crowd sourced ◦  Resources, observations, data ◦  Passive / involuntary – marketing ◦  Active / voluntary – wikipedia, blogging ◦  Citizen science – iSpot, Galaxy Zoo ◦  Remunerated – Mechanical Turk

!  Crowd analyzed ◦  Rating, ranking – thumbs up/down ◦  Crowd promoted (trending)

!  Crowd computed ◦  Human computation

!  Stored, mined, analyzed ◦  Text and data mined ◦  Learning crowds analyzed ◦  Learning processes in and by crowds

can be analyzed

www.seti.org/ -- https://www.naturewatch.ca/ -- www.openstreetmap.org/ http://www.ispotnature.org/communities/uk-and-ireland

•  Altruistic view of knowledge contributions – open access

•  Dismissive view – ‘all that twittering’

•  " •  LOL cats

•  Commercial view – ‘all that twittering’

•  ☺

NSA_quantum_cat.jpg http://cdn4.spiegel.de/images/image-584103-galleryV9-jhol.jpg

From Wikimedia Commons, the free media repository

!  The launch that Creative Commons has given to distributed knowledge

!  The practices of an advance guard re peer production

!  A generation brought up on e-participation and a participatory culture

!  Critical mass of resources

!  Established practices !  Practice with

emergence !  Change in half-life of

skills !  Trend to

enterpreneurial practices

•  If crowds are the way forward, what leads individuals to participate in crowdsourced knowledge projects?

•  How does what we’ve learned about e-learning and online organizing so far help us look at crowds?

Crowd-based !  Centralized effort

by anonymous strangers, contributing to common goal

!  Little expectation of persistence or continued commitment

!  Lightweight associations with each other and the collective enterprise

Community-Based !  Similar others, known and

continuously visible to each other, contributing to the community

!  Expectation of persistence over time and continued commitment

!  Heavyweight associations with each other and the collective enterprise

Lightweight association between contributors and to collective enterprise

‘Weight’  refers  to  the  commitment  and  engagement  with  the  producHon,    not  to  the  significance  of  the  product  itself.    

Heavyweight association between contributors and to collective enterprise

Crowd-­‐sourced,  Lightweight  

1.  ContribuHons  -­‐-­‐  Many,  simple,  discrete,  unconnected;  Anonymous,  impersonal  

2.  Learning  -­‐-­‐  LiPle  pre-­‐learning  or  commitment  

3.  Contributors  -­‐-­‐  Many,  lightly-­‐Hed    non-­‐networked  individuals  

4.  Control  -­‐-­‐  External  to  contributors  

5.  ReputaHon  -­‐-­‐  QuanHtaHve,  evaluator  status  not  important  

6.  MoHvaHon  -­‐-­‐  Coorienta)on  to  common  purpose  

Community-­‐sourced,  Heavyweight  

1.  ContribuHons  -­‐-­‐  Fewer,  diverse,  connected;  Named,  visible  aPribuHon  

2.  Learning  -­‐-­‐  ApprenHceship,  commitment  

3.  Contributors  -­‐-­‐  Fewer,  heavily-­‐Hed,  networked  individuals  

4.  Control  -­‐-­‐  Internal  to  community  

5.  ReputaHon  -­‐-­‐  QualitaHve,  evaluator  status  maPers  

6.  MoHvaHon  -­‐-­‐  Overall  purpose  and  group    interacHon  

Crowd model Lightweight participation

Community model Heavyweight participation

Any particular individual may participate in any venture in a lightweight manner or a heavyweight manner, e.g., lightly correcting minor aspects of Wiki entries or heavily engaging in discussion.

Crowd model Lightweight participation

Community model Heavyweight participation

Academia Wikipedia

Social Networking Sites Distributed Computing

Any particular initiative may show both lightweight and heavyweight aspects.

Casual mappers* more co-oriented to overall goals of open source projects !  free, anti-corporate

sentiment !  ‘It is important to help

others by providing digital maps that are available for free.’

!  ‘Digital map data should be available for free only for non-commercial applications

* participating in a lightweight manner

Serious mappers** significantly more co-oriented to community and community goals: ◦  ‘OSM community is important to

me’ ◦  ‘I want to be recognized as an

active OSM contributor’ ◦  Gaining new perspectives, filling

gaps, correcting errors !  Significantly more motivated

by all items loading on factors relating to: ◦  self-efficacy re local knowledge,

learning, monetary reward

** participating in a heavyweight manner

Budhathoki & Haythornthwaite, 2013

MOOC (Cormier) !  An emerging e-learning technology, ideally building on e-learning

background ◦  ‘syllabus as promise’ (from Ellison’s ‘profile as promise’ for dating sites)

Distinct types emerging !  cMOOCs ◦  First – connectivism (Siemens; Downes) learning motivated – open,

online, multimedia ◦  Promise of a learning community

!  xMOOCs ◦  Attention getter – large numbers, high profile scholars and institutions ◦  Promise of expert knowledge

!  unMOOCs … you heard it here first ;) ◦  ‘un’ as in ‘nconference’ – unstructured, emergent syllabus, building

‘airplanes in the air’ (Bruce), ‘crowdsourcing the curriculum’ (Paulin) ◦  Promise of participant relevance

unMOOC ala unconference

If you crowdsource the curriculum, who owns it?

#bellwether

cMOOC – intentionally community organized !  Participatory, reflective learning network !  Requires contribution and attention within the learning community !  Will succeed where engagement emerges

xMOOC – crowd organized !  A resource node, no prerequisite to join, drop in or out as desired !  Learning as authority led, predicated on reputation of scholar/instituion !  Will succeed where tasks and learning match the incoming learners !  xMOOC perhaps a latent tie structure on which ties can grow

un-MOOC – crowdsourcing the meaning of the community !  Much more for learners to bring to the table; a pioneer mentality !  Requires expert learning processes, a knowledge-building environment !  Will succeed where draws on what we have learned from online

interaction and about knowledge-building (Scardamalia & Bereiter, 2006)

!  What do we do with a million learners, a billion contributions? ◦  Learning Analytics -- for the crowd and about the crowd ◦  Online interaction as crowdsourced data on learning

habits, success, trajectories "  Show participant interaction and progress "  Of all participants and of individuals in comparison to others "  Learning and crowd patterns at start, middle and end of

interaction and of learning

!  Human computation, human-machine alliances ◦  Crowdsourcing the curriculum as human

computation resource – syllabus, evaluating ◦  Machine data collection and analysis, human use

!  A major transformation in how, where, when and with whom we learn

!  Starting a new disruptive phase with MOOCs !  Happening because of the ‘perfect storm’ of

technical and social conditions !  Expect more ◦  Learning with the crowd and building knowledge with

the community ◦  Crowdsourcing the curriculum ◦  Questions about who owns the curriculum ◦  Analytics and human-machine alliances in learning

about learning with the crowd

!  Haythornthwaite, C. (2008). Learning relations and networks in web-based communities. International Journal of Web Based Communities, 4(2), 140-158. http://www.inderscience.com/info/inarticle.php?artid=17669

This paper is open access as part of a 10 year anniversary initiative; my letter to the editor re changes in those 10 years can be found in the 2014 editorial for IJWBC 10(2): http://www.inderscience.com/browse/getEditorial.php?articleID=3848

!  Haythornthwaite, C. & De Laat, M. (2011). Social network informed design for learning with educational technology. In A.D. Olofsson & J. O. Lindberg, (Eds.). Informed Design of Educational Technologies in Higher Education: Enhanced Learning and Teaching (pp. 352-374). IGI Global.

!  Haythornthwaite, C. (Jan. 2009). Crowds and communities: Light and heavyweight models of peer production. Proceedings of the 42nd Hawaii International Conference on System Sciences. Los Alamitos, CA: IEEE Computer Society. http://hdl.handle.net/2142/9457

!  Gruzd, A. & Haythornthwaite, C. (2013). Enabling community through social media. Journal of Medical Internet Research. 2013;15(10):e248. http://www.jmir.org/2013/10/e248/. doi: 10.2196/jmir.2796 PMID: 24176835.

!  Haythornthwaite, C., De Laat, M. & Dawson, S. (Eds.) (2013). Learning analytics. American Behavioral Scientist, 57(10), whole issue.

!  Budhathoki, N. & Haythornthwaite, C. (2013). Motivation for open collaboration: Crowd and community models and the case of OpenStreetMap. American Behavioral Scientist, 57(5), 548 - 575. DOI: 10.1177/0002764212469364

!  Paulin, D. & Haythornthwaite, C. (forthcoming). Crowdsourcing the curriculum: Redefining e-learning practices through peer-generated approaches. The Information Society.