Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu tecfa.unige.ch Does a shared screen make a...

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Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Does a shared screen Does a shared screen make make

a shared understanding ?a shared understanding ?

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

NONO

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

shared screen shared screen

shared understanding shared understanding

WYSIWIS

Collaborative

learning

Groundingshared understandingshared understanding

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Restaurant

Kitchen

Private

Bar

Room5 Room6 Room7 Room8

Room1 Room2 Room3 Room4

Lobby Entrance

MLVMLVLisa JonesClaire & Rolf

Loretan

Colonel Von Schneider

Lucie Salève Heidi Zeller

Hans Wenger

Marie Salève

Oscar Salève

Jacques Salève

Giuzeppe Vesuvio

Ski jacketSki jacket

GunGun

PaintingPainting

InsuranceInsurance

NoteNote

Gun OylsterGun Oylster

PhoneLogPhoneLog

RegistryRegistry

WHO KILLED MONA-LISA?WHO KILLED MONA-LISA?

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

MOOAuberge Guest Room: 4You enter a largue blue room with a small window. You see Helmut, Ski Jacket, and Gun here.Obvious Exits: Out (to Lower Corridor).> look gunYou see an old Swiss army pistol.> ask helmut about last nightI stayed at the bar until 9 Pm and then went to bed.> page sherlock Interesting isn't? Sherlock has received your page.He pages « He lies ».Sherlock joins you.

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

> " Hi colleague

> ' Where are you?

> ask MS about last night

> look gun

> ask MS about last gun

> read insurance

> read all from DN2

> read Hans from DN2

> compare DN1 with DN2

MOO Whiteboard

> " skjhkjh

dfsdfsf

> ask Helmut about last night

> ask MS about mona

> look painting

> read all from DN1

> read Hans from DN1

> compare DN1 with DN1

MOO Whiteboard

20 pairs

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

??How does the whiteboard help to

• ground utterances

• share solutions

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Whiteboard roles:

• envisionning solutions

• grouding utterances

• explanatory schema

• deictics

• shared memory

• regulation

> " skjhkjh

dfsdfsf

> ask Helmut about last night

> ask MS about mona

> look painting

> read all from DN1

> read Hans from DN1

> compare DN1 with DN1

MOO Whiteboard

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

The whiteboard is the central space

for sharing information

(in this task)

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Communication8% Facts

14%

Inferences41%

Management33%

Technical4%

Communication8% Facts

14%

Inferences41%

Management33%

Technical4%

Communication1%

Facts49%Inferences

41%

Management9%

Communication1%

Facts49%Inferences

41%

Management9%

Persistent Non-Persistent

Persistent

Non Persistent

Display

Kn

owle

dge

Whiteboard

MOO dialogues

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Grounding varies according to Grounding varies according to problem solving variablesproblem solving variables

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Acknowlegment in MOO dialoguesAcknowlegment in MOO dialogues• Rate = 41% (90% in voice experiments)• Not related with MOO expertise • Not related with interactions parameters

• symmetry(ack+): 8% = symmetry(ack-): 8%• ack (short delay): 41% = ack (long delay): 41%; • ack (freq+.talkers): 41% = ack (freq-.talkers): 42%;• turnsIC (ack+): 0.9 = turnsIC (ack+): 0.9

• Related with problem sloving• N. actions (ack+):178 <<.05 N. actions (ack-) : 237 • redudancy (ack+): 6 <<.01 redudancy (ack-): 18

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

0.37

0.06

0.50

0.38

0

0.1

0.2

0.3

0.4

0.5

0.6

Talk Whiteboard

Facts

Inferences

Deg

ree

of s

hare

dnes

s

Acces

Visibility

Understanding

Agreement

Fact

s in

whi

tebo

ard

Fact

s in

talk

Infe

renc

es in

talk

Infe

renc

es in

whi

tebo

ard

Rat

e of

ack

now

ledg

men

t

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

.... and the subjects:

• maintain multiple conversational contexts

• are sensitive to space beyond any functional constraint

• negotiate across modalities

• (re-)allocate functions to tools in various ways

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Collect factsShare factsShare inferencesStore factsStore inferencesCoordinate action

MOOdialogue

MOOaction

Whiteboard

Notebook

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

Distributed CognitionDistributed Cognition

Reconfigurable because distributed Reconfigurable because distributed

Shared despite distrbutedShared despite distrbuted

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

How do agents co-How do agents co-construct culture construct culture

? ?

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

WYSIWIS-relaxedWYSIWIS-relaxed++

awareness toolsawareness toolsjhk slk hlkjsh lkjhsdl kgjhnbjhb sh rgl hc ,cg lkw kjehéeéhlk h jhk slk hlkjsh lkjhsdl kgjhnbjhb sh rgl hc ,cg lkw kjehéeéhlk h jhk slk hlkjsh lkjhsdl kgjhnbjhb sh rgl hc ,cg lkw kjehéeéhlk h jhk slk hlkjsh lkjhsdl

Pierre.Dillenbourg@tecfa.unige.ch, Traum@cs.umd.edu

shared understanding ?shared understanding ?