CSCL 2011 Keynote on Social Computing and eLearning
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CSCL 2011 Keynote on Social Computing and eLearning

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Ed H. Chi...

Ed H. Chi
Google Research (Work done at Xerox PARC)

CSCL2011 Keynote Abstract:

Our research in Augmented Social Cognition is aimed at enhancing the ability of a group of people to remember, think, and reason. Our approach to creating this augmentation or enhancement is primarily model-driven. Our system developments are informed by models such as information scent, sensemaking, information theory, probabilistic models, and more recently, evolutionary dynamic models. These models have been used to understand a wide variety of user behaviors, from individuals interacting with social bookmark search in Delicious and MrTaggy.com to groups of people working on articles in Wikipedia. These models range in complexity from a simple set of assumptions to complex equations describing human and group behaviors.

Indeed, increasingly, new social online resources such as social bookmarking sites and Wikis are becoming central in eLearning. By studying them, we further our understanding of how knowledge is constructed in a social context. In this talk, I will illustrate how a model-driven approach could help illuminate the path forward for social computing and social learning.

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CSCL 2011 Keynote on Social Computing and eLearning CSCL 2011 Keynote on Social Computing and eLearning Presentation Transcript

  • CSCL 2011 | Keynote Augmented Social Cognition: How SocialComputing is Changing eLearning Ed H. Chi GoogleResearch Work done whileat Palo AltoResearch Center(PARC) 2008-05-13 CSCL 2011 Keynote
  • 2008-05-13 CSCL 2011 Keynote
  • Prelude:  A  personal  learning  story  To:  chi@acm.org  From:  Brad  Barrish  <brad@…removed.for.privacy….com>  Subject:  Pancreatic  cancer  Date:  Thu,  1  Feb  2007  21:37:55  PST    Hey  Ed.  Im  a  fellow  del.icio.us  user  and  noticed  you  bookmark  a  lot      of  pancreatic  cancer  stuff.  Im  at  home  with  my  dad  who  was  diagnosed      a  little  over  a  year  ago  and  is  now  at  the  tale  end  of  things.  Ive      learned  a  lot  through  his  treatments  and  about  whats  out  there.  I      dunno  if  its  something  you  or  a  family  member  has,  but  just  wanted      to  drop  you  an  email.  Be  well.    Brad   2008-05-13 CSCL 2011 Keynote
  • Talk  in  3  Acts   The  Importance  of  Social  Signals  in  eLearning   n  Act  I:  The  Invisible   –  Social  Search   n  Act  II:  The  Visible   –  Shared  Annotations   n  Act  III:  The  Abstracted   –  Shared  Knowledge  Space   2008-05-13 CSCL 2011 Keynote
  • Act  I:    Invisible  Social  Signals  from  the  Crowd   Joint  work  w/  Todd  Mytkowicz,  Rowan  Nairn,  Lawrence  Lee     [Chi  and  Mytkowicz,  Hypertext2008]   [Kammerer  et  al.,  CHI2009]     2008-05-13 CSCL 2011 Keynote
  • Using  Information  Theory  to  Model  Social  Tagging  [Ed  H.  Chi,  Todd  Mytkowicz,  ACM  Hypertext  2008]   Concepts   Topics   Users   Documents   Noise   Tags   Decoding   Encoding   T1…Tn   2008-05-13 CSCL 2011 Keynote
  • Tagging  Behavior  H(Tag)  shows  tag  saturation   H(Doc  |  Tag),  browsability   2008-05-13 CSCL 2011 Keynote
  • Implication  I(Doc;  Tag)    Mutual  Information   Raise  in  avg.  tag  /  bookmark   2008-05-13 CSCL 2011 Keynote
  • TagSearch:  MapReduce  Implementation   Tags URLs P(URL|Tag) P(Tag|URL) n  Spreading  Activation  in  a  bi-­‐graph   n  Computation  over  a  very  large  data  set   –  150  Million+  bookmarks   2008-05-13 CSCL 2011 Keynote
  • TagSearch:  Use  Semantic  Analysis  to   Reduce  Noise          http://mrtaggy.com    Semantic Similarity Graph Web Tools Reference Guide Howto Tutorial Tips Help Tip Tutorials Tricks 2008-05-13 CSCL 2011 Keynote
  • 2008-05-13 CSCL 2011 Keynote
  • Experiment  Design    [Kammerer  et  al.  CHI2009]  n  2  interface  x  3  task  domain  design   –  2  Interface  (between-­‐subjects)   n  Exploratory  vs.  Baseline   –  3  task  domains  (within-­‐subjects)   n  Future  Architecture,  Global  Warming,  Web  Mashups  n  30  Subjects  (22  male,  8  female)   –  Intermediate  or  advanced  computer  and  web  search  skills   –  Half  assigned  Exploratory,  half  Baseline.  n  For  each  domain,  single  block  with  3  task  types:   –  Easy  and  Difficult  Page  Collection  Task  [6min  each]   –  Summarization  Task  [12min]   –  Keyword  Generation  Task  [2min]   2008-05-13 CSCL 2011 Keynote
  • Evauation  Results  [Kammerer  et  al.,  CHI2009]  n  Exploratory  interface  users:   –  performed  more  queries,     –  took  more  time,     –  wrote  better  summaries  (in  2/3  domains),     –  generated  more  relevant  keywords  (in  2/3  domains),  and   –  had  a  higher  cognitive  load.  n  Suggestive  of  deeper  engagement  and  better  learning.  n  Some  evidence  of  scaffolding  for  novices  in  the  keyword   generation  and  summarization  tasks.   2008-05-13 CSCL 2011 Keynote
  • Act  II:  Visible  Social  Signals  from    Shared  Highlighting   Kudos  to  Lichan  Hong,  Les  Nelson       [Hong  et  al,  AVI2008]     [Nelson  et  al.,  HCII  2009]   2008-05-13 CSCL 2011 Keynote
  • Finding  a  Restaurant  n  Appropriate  for   the  occasion   2008-05-13 CSCL 2011 Keynote
  • Heuristics   Poor heuristic Good heuristic 2008-05-13 CSCL 2011 Keynote
  • “Hints”   Solo Cooperative (“good hints”) 2008-05-13 CSCL 2011 Keynote
  • SparTag.us:  Social  Highlighting   2008-05-13 CSCL 2011 Keynote
  • SparTag.us:  Social  Highlighting   n  In  situ  tagging  while  reading   n  Highlighting   n  Shared  notebooking     n  Sharing!   2008-05-13 CSCL 2011 Keynote
  • Highlighting  as  Importance    Indicator  recall first-visit 2008-05-13 CSCL 2011 Keynote
  • Evaluation  Task  &  Metric  [Nelson  et  al.,  HCII2009]  n  Sensemaking  task   –  Find  and  read  material  about   Enterprise  2.0  mashups  in  order  to   write  two  essays  n  Seeds:   expert  content  for  scaffolding   –  Tags  from  del.icio.us   –  URLs  from  Google/PageRank   –  Constructed  and  then  shared  through  social  mechanisms  (i.e.,  a   SparTag.us   friend )  n  Performance  Measures   –  Learning  gain:  Pre/Post  Knowledge  Test   Posttest score - Pretest score Gain = Max score - Pretest score 2008-05-13 CSCL 2011 Keynote
  • Procedure   SparTag.us   SF with   Friend   SparTag.us  Demographics   SO Only   Posttest   &  Pretest   Without   WS SparTag.us   2008-05-13 CSCL 2011 Keynote
  • Results:  Learning  Gain  N=18    SparTag.us  +  Friend  superior  to  both  individual  conditions  No  difference  between  the  two  control  conditions   2008-05-13 CSCL 2011 Keynote
  • URL  Kind   Code   Blog   B  Observation   Conference   C   Employment   E   My.Spartag.us   M   News   N   URL KindOpenSource   Code O   Blog Search  B S   Conference C Vendor   V   Employment E Wikipedia   MySpartagus M W   News Consultant   N X   OpenSource O Search S Vendor V Wikipedia W Consultant X 2008-05-13 CSCL 2011 Keynote
  • Von  Restorff  Isolation  Effect  [1933]  n  As  applied  to  highlights,  the  von  Restorff  isolation  effect   suggests  that  readers:  n  (a)  tend  to  focus  on  and    n  (b)  learn  what  is  marked,    n  whether  the  information  is  important  or  not.   –  Nist  and  Hogrebe  87   2008-05-13 CSCL 2011 Keynote
  • Act  III:    Abstracted  Knowledge:  The  Science  of  Understanding  Wikipedia   Kudos  to  Bongwon  Suh,  Niki  Kittur     [Kittur  et  al.,  CHI2007]   [Suh  et  al.,  WikiSym  2009]     2008-05-13 CSCL 2011 Keynote
  • Exponential  Growth  of  Wikipedia:  an  accepted  ‘fact’   Number of Articles (Log Scale) http://en.wikipedia.org/wiki/Wikipedia:Modelling_Wikipedia’s_growth 2008-05-13 CSCL 2011 Keynote
  • Growth  of  Edits   2008-05-13 CSCL 2011 Keynote
  • Something  happened  in  early  2007   2008-05-13 CSCL 2011 Keynote
  • Growth  of  Active  Editors  *In thousands 2008-05-13 CSCL 2011 Keynote
  • Slowing  Growth  in  Global  Activity  *In thousands 2008-05-13 CSCL 2011 Keynote
  • Earlier  Exponential  Growth  Model   n  Preferential  Attachment:  Edits  beget  edits   –  more  number  of  previous  edits,  more  number  of  new  edits   Growth rate depends on: N = current population r = growth rate of the population N(t) = N 0 " e rt dN = r" N dt Growth rate Current of population ! population! 2008-05-13 CSCL 2011 Keynote
  • Logistic  Growth  Model  n  Ecological  population  growth  model   –  Also  depend  on  environmental  conditions   –  K,  carrying  capacity  (due  to  resource  limitation)   dN N = rN(1" ) dt K 2008-05-13 CSCL 2011 Keynote
  • Match  to  Data:  #  of  New  Articles  n  Follows  a  logistic  growth  curve   New Article 2008-05-13 CSCL 2011 Keynote
  • Struggle  for  Existence  -­‐  Darwin  n  Biological  system   –  Competition  increases  as   population  hit  the  limits  of  the   ecology   –  Advantage  go  to  members  of  the   population  that  have  competitive   dominance  over  others  n  Analogy   –  Limited  opportunities  to  make   novel  contributions   –  Increased  patterns  of  conflict  and   dominance     2008-05-13 CSCL 2011 Keynote
  • “Showering”  Hypothesis  What  drives  contributions  to  Wikipedia?  Cooperation  is  not  the  main  driver?  n  Hypothesis:  Conflicts  drives  most  of  the  contributions.   –  How  do  we  measure  conflicts?  n  Conflicts  cause  coordination  costs  to  go  up.   –  How  to  measure  coordination  costs?  n  “negotiation  is  critical  to  helping  multiple  perspectives   to  converge  on  shared  knowledge.”     –  Stahl,  Group  Cognition,  Ch8,  2004   2008-05-13 CSCL 2011 Keynote
  • Conflict/Coordination  Effects  in  Wikipedia   (Kittur, Suh, Pendleton, Chi, CHI2007) 2008-05-13 CSCL 2011 Keynote
  • Ratio  of  Reverted  Contributions     Monthly Ratio of Reverted Edits 2008-05-13 CSCL 2011 Keynote
  • Visual  Analytics  over  Wikipedia  data  Mediator  Pattern  -­‐  Terri  Schiavo    [Suh,  et  al.,  VAST2007]   Anonymous (vandals/ spammers) Sympathetic to husband Mediators Sympathetic to parents 2008-05-13 CSCL 2011 Keynote
  • WikiDashboard.com  2008-05-13 CSCL 2011 Keynote
  • Coda:  A  Challenge:  A  modified  logistic  model  n  Carrying  Capacity  as  a  function  of  time.   2008-05-13 CSCL 2011 Keynote
  • What  Did  We  Learn?  n  The  Common  Thread:   –  Utilization  of  Social  Signals  for  Learning  and  Information  Access   –  Whether  it  is  invisible,  visible,  and  abstracted.  n  The  Establishment  of  Common  Ground   –  Implicit  Coordination   –  Explicit  Coordination   –  Negotiation  n  “All  collective  actions  are  built  on  common  ground  and   its  accumulation.”   –  Clark  and  Brennan,  1991   2008-05-13 CSCL 2011 Keynote
  • Research  Vision  Augmented  Social  Cognition  n  Cognition:  the  ability  to  remember,  think,  and  reason;  the  faculty  of   knowing.  n  Social  Cognition:  the  ability  of  a  group  to  remember,  think,  and   reason;  the  construction  of  knowledge  structures  by  a  group.   –  (not  quite  the  same  as  in  the  branch  of  psychology  that  studies  the   cognitive  processes  involved  in  social  interaction,  though  included)  n  Augmented  Social  Cognition:  Supported  by  systems,  the   enhancement    of  the  ability  of  a  group  to  remember,  think,  and   reason;  the  system-­‐supported  construction  of  knowledge   structures  by  a  group.    Citation:  Chi,  IEEE  Computer,  Sept  2008   2008-05-13 CSCL 2011 Keynote
  • From  Rote  Learning  to  Interaction   2008-05-13 CSCL 2011 Keynote
  • Thank  you!   n  chi@acm.org   n  http://edchi.net   2008-05-13 CSCL 2011 Keynote
  • What  I  will  not  talk  about  …  n  Motivation   –  Cultural  and  economic  incentives   –  Personal  and  societal  values   –  Psychology  (e.g.  cognitive,  personality,  social)  n  Policy  and  Investment   –  Resources   –  Teacher  training   –  Technological  investment  n  With  the  Assumption  of  Motivation  and  Resources,   how  to  make  information  universally  accessible  and   useful  in  a  Web2.0  world?   2008-05-13 CSCL 2011 Keynote
  • 2008-05-13 CSCL 2011 Keynote
  • Lowering  Participation  /  Interaction  Costs  n  Interaction  costs   # People willing to produce for “free” determine  number  of   people  who  participate  n  Surplus  of  attention  &   motivation  at  small   transaction  costs  n  Therefore…  n  Important  to  keep   interaction  costs  low   Cost of participation 2008-05-13 CSCL 2011 Keynote
  • Using  Machine  Learning  to  Detect  Conflicts  n  Counting  ‘Controversial’  labels  n  5x  cross-­‐validation,  R2  =  0.897   10000 9000 Actual controversial revisions 8000 7000 6000 5000 4000 3000 2000 1000 0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Predicted controversial revisions 2008-05-13 CSCL 2011 Keynote
  • Collaborative  Knowledge  Building  n  “They  cannot  even  begin  to  coordinate  on  content   without  assuming  a  vast  amount  of  shared  information   or  common  ground….  And  to  coordinate  on  process,   they  need  to  update  their  common  ground  moment  by   moment.  All  collective  actions  are  built  on  common   ground  and  its  accumulation.”   –  Clark  and  Brennan,  1991  n  At  Web-­‐scale  social  learning,  what  we  know  about  the   nature  of  conflict  and  negotiation  is  woefully   inadequate.   2008-05-13 CSCL 2011 Keynote
  • Google  Plus  as  a  Research  Platform   2008-05-13 CSCL 2011 Keynote