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1 CS 630: Cognitive Systems. Dario Salvucci, Drexel University.

Lecture 6:

Multitasking

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 2

Our Multitasking World

talking &

driving

cooking &

reading a book writing paper &

reading email

watching game &

talking to friends listening &

note-taking

The Challenges of Multitasking

■  Technological challenges

–  user interfaces, hardware, networking...

■  Scientific challenges –  how do we multitask?

–  when is multitasking easy or difficult?

–  how does it affect task performance?

■  Societal challenges

–  when is multitasking useful?

–  when is multitasking inappropriate?

–  when is multitasking dangerous?

The Multitasking Continuum

talking &

driving cooking &

reading a book writing paper &

reading email watching game &

talking to friends listening &

note-taking

(2)

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 5

The Multitasking Continuum

Concurrent Multitasking

(e.g., PRP, driver distraction)

Sequential Multitasking

(e.g., task interruptions)

seconds minutes hours

Time between Task Switches talking &

driving

cooking &

reading a book writing paper &

reading email watching game &

talking to friends listening &

note-taking

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 6

Threaded Cognition

■  Goal: Unifying theory of multitasking –  ... across the multitasking continuum –  ... across laboratory and real-world domains –  ... across different levels of abstraction

■  Approach: Computational cognitive modeling (obviously J)

–  Threaded cognition

–  in the ACT-R cognitive architecture

Threaded Cognition

■  Your brain is a “Thought Kitchen”

–  with resources and processes

•  central resource: the cook

•  other resources: oven, stove, mixer, etc.

Threaded Cognition

■  Concurrent multitasking is a basic skill—best represented by a simple general mechanism

■  Threaded cognition...

–  allows concurrent execution of multiple

“streams of thought” = threads

–  takes models A, B... predicts behavior of A+B

■  Theoretical components

–  (1) Resources that perform relevant processing

•  derived from the ACT-R architecture

–  (2) Processing principles that define task

allocation

(3)

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 9

Processing Principles (1) Threaded Processing

–  Cognition maintains a set of active goals that produce “threads” of processing

•  many domains are nicely represented as threads –  some are more obvious – e.g., driving + dialing –  some are less obvious – e.g., list-memory tasks

–  In ACT-R terms, this means maintaining multiple goals at a time

•  In the past, ACT-R had only one goal at a time

•  then it had a “goal stack” (inspired by tasks with a robust subgoal structure, like Tower of Hanoi)

•  now, several active goals

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 10

Processing Principles (2) Resource Exclusivity

–  Resources execute processing requests serially, exclusively for one request/task at a time

•  resources can be massively parallel themselves, within the resource

–  e.g., visual processing

•  but resources can serve only one goal at a time

–  (caveat: what about resources like motor? — are the hands independent? fingers? hands from feet? etc.)

Processing Principles (3) Resource Usage

–  Threads acquire and release resources in a greedy, polite manner.

•  greedy: used as soon as available

•  polite: threads free resources ASAP

(4) Conflict Resolution

–  When threads contend for the procedural resource, the thread with the highest urgency proceeds.

•  highest urgency = least recently used

•  simple mechanism for balancing thread processing

Threaded Models

■  Now let’s look at some models that use

threaded cognition…

(4)

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 13

Threads-1

(set-­‐task  "cs630.ThreadsTask”  

  (add-­‐dm          (type-­‐number              isa  type-­‐number)          (answer-­‐phone              isa  answer-­‐phone)    

(goal-­‐focus  type-­‐number)   (goal-­‐focus  answer-­‐phone)  

(p  type-­‐number*Bind-­‐Birst          =goal>  

               isa  type-­‐number                  current-­‐x  nil          ?visual-­‐location>  

               state  free                  buffer  empty        ?visual>  

               state  free                  buffer  empty    

==>  

       +visual-­‐location>  

               isa  visual-­‐location                  screen-­‐x  lowest   )  

(p  type-­‐number*Bind-­‐next          =goal>  

               isa  type-­‐number                  current-­‐x  =x          ?visual-­‐location>  

               state  free                  buffer  empty          ?visual>  

               state  free                  buffer  empty    

==>  

       +visual-­‐location>  

               isa  visual-­‐location                  screen-­‐x  lowest                  >  screen-­‐x  =x   )  

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 14

Threads-1

(p  type-­‐number*encode          =goal>  

               isa  type-­‐number          =visual-­‐location>  

               isa  visual-­‐location                  screen-­‐x  =x          ?visual>  

               state  free                  buffer  empty  

==>  

       +visual>  

               isa  move-­‐attention                  screen-­‐pos  =visual-­‐location          =goal>  

               current-­‐x  =x   )  

(p  type-­‐number*type          =goal>  

               isa  type-­‐number          =visual>  

               isa  text                  value  =digit          ?manual>  

               state  free  

==>  

       +manual>  

               isa  press-­‐key                  key  =digit   )  

(p  type-­‐number*done          =goal>  

               isa  type-­‐number                  current-­‐x  =x          ?visual-­‐location>  

               state  error  

==>  

       -­‐goal>  

)  

Threads-1

(p  answer-­‐phone*encode          =goal>  

               isa  answer-­‐phone          =aural-­‐location>  

               isa  audio-­‐event          ?aural>  

               buffer  empty                  state  free  

==>  

       +aural>  

               isa  ring                  event  =aural-­‐location   )  

(p  answer-­‐phone*done          =goal>  

               isa  answer-­‐phone          =aural>  

               isa  ring          ?vocal>  

               state  free  

==>  

       +vocal>  

               isa  speak                  string  "Hello!"  

       -­‐goal>  

)  

Threads-1

0.000 vision unrequested [vision~62]!

0.000 procedural start!

0.050 procedural ** TYPE-NUMBER*ENCODE ** [type-number]!

0.050 vision move-attention!

0.135 vision encoding-complete [text~66]!

0.185 procedural ** TYPE-NUMBER*TYPE ** [type-number]!

0.185 motor press-key "1"!

0.235 procedural ** TYPE-NUMBER*FIND-NEXT ** [type-number]!

0.235 vision find-location [vision~72]!

0.285 procedural ** TYPE-NUMBER*ENCODE ** [type-number]!

0.285 vision move-attention!

0.300 audio audio-event [audio-event~63]!

0.300 audio unrequested [audio-event~63]!

0.350 procedural ** ANSWER-PHONE*ENCODE-SOUND ** [answer-phone]!

0.350 audio attend-sound!

0.370 vision encoding-complete [text~75]!

0.435 motor preparation-complete!

0.485 motor initiation-complete!

0.585 motor output key 1!

0.735 motor finish-movement!

0.785 procedural ** TYPE-NUMBER*TYPE ** [type-number]!

0.785 motor press-key "2"!

0.835 procedural ** TYPE-NUMBER*FIND-NEXT ** [type-number]!

0.835 vision find-location [vision~84]!

0.850 audio audio-encoding-complete [ring~78]!

0.885 procedural ** TYPE-NUMBER*ENCODE ** [type-number]!

0.885 vision move-attention!

0.935 motor preparation-complete!

(5)

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 17

Threads-1

0.935 procedural ** ANSWER-PHONE*DONE ** [answer-phone]!

0.935 declarative store chunk [answer-phone]!

0.935 speech speak "Hello!"!

0.970 vision encoding-complete [text~87]!

0.985 motor initiation-complete!

1.085 motor output key 2!

1.085 speech preparation-complete!

1.135 speech initiation-complete!

1.135 speech output-speech "Hello!"!

1.235 motor finish-movement!

1.285 procedural ** TYPE-NUMBER*TYPE **!

1.285 motor press-key "3"!

1.335 procedural ** TYPE-NUMBER*FIND-NEXT **!

1.335 vision find-location [vision~95]!

1.385 procedural ** TYPE-NUMBER*ENCODE **!

1.385 vision move-attention!

1.435 speech finish-movement!

1.435 motor preparation-complete!

1.470 vision encoding-complete [text~98]!

1.485 motor initiation-complete!

1.585 motor output key 3!

1.735 motor finish-movement!

1.785 procedural ** TYPE-NUMBER*TYPE **!

...!

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 18

Threads-2

(set-­‐task  "cs630.ThreadsTask")    

(add-­‐dm          (start  isa  goal)   )  

 

(goal-­‐focus  start)  

(p  start-­‐multitasking          =goal>  

               isa  goal  

==>  

       +goal>  

               isa  type-­‐number          +goal>  

               isa  answer-­‐phone   )  

...  

 

<  same  as  before>  

Threads-2

0.000 vision unrequested [vision~62]!

0.000 procedural start!

0.050 procedural ** START-MULTITASKING **!

0.050 declarative store chunk [start] (start isa goal)!

0.050 declarative store chunk [type-number~65]!

0.100 procedural ** TYPE-NUMBER*ENCODE ** [type-number~65]!

0.100 vision move-attention!

0.185 vision encoding-complete [text~70]!

0.235 procedural ** TYPE-NUMBER*TYPE ** [type-number~65]!

0.235 motor press-key "1"!

0.285 procedural ** TYPE-NUMBER*FIND-NEXT ** [type-number~65]!

0.285 vision find-location [vision~76]!

0.300 audio audio-event [audio-event~63]!

0.300 audio unrequested [audio-event~63]!

0.335 procedural ** TYPE-NUMBER*ENCODE ** [type-number~65]!

0.335 vision move-attention!

0.385 procedural ** ANSWER-PHONE*ENCODE-SOUND ** [answer-phone~67]!

0.385 audio attend-sound!

...!

0.835 procedural ** TYPE-NUMBER*TYPE ** [type-number~65]!

0.835 motor press-key "2"!

0.885 audio audio-encoding-complete [ring~82]!

0.885 procedural ** TYPE-NUMBER*FIND-NEXT ** [type-number~65]!

0.885 vision find-location [vision~88]!

0.935 procedural ** ANSWER-PHONE*DONE ** [answer-phone~67]!

0.935 declarative store chunk [answer-phone~67]!

0.935 speech speak "Hello!"!

...!

Threads-3

(set-­‐task  "cs630.ThreadsTask")    

(add-­‐dm          (type-­‐number              isa  type-­‐number)   )  

 

(goal-­‐focus  type-­‐number)    

...  

(p  handle-­‐sound*encode          =goal>  

       =aural-­‐location>  

               isa  audio-­‐event          ?aural>  

               buffer  empty                  state  free  

==>  

       +aural>  

               isa  ring                  event  =aural-­‐location          +goal>  

               isa  handle-­‐sound          +goal>  =goal   )  

(p  handle-­‐sound*phone          =goal>  

               isa  handle-­‐sound          =aural>  

               isa  ring          ?vocal>  

               state  free  

==>  

       +vocal>  

               isa  speak                  string  "Hello!"  

       +goal>  

               isa  converse   )  

(6)

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 21

Threads-3

0.000 vision unrequested [vision~62]!

0.000 procedural start!

0.050 procedural ** TYPE-NUMBER*ENCODE **!

0.050 vision move-attention!

0.135 vision encoding-complete [text~66]!

0.185 procedural ** TYPE-NUMBER*TYPE **!

0.185 motor press-key "1"!

0.235 procedural ** TYPE-NUMBER*FIND-NEXT **!

0.235 vision find-location [vision~72]!

0.285 procedural ** TYPE-NUMBER*ENCODE **!

0.285 vision move-attention!

0.300 audio audio-event [audio-event~63]!

0.300 audio unrequested [audio-event~63]!

0.350 procedural ** HANDLE-SOUND*ENCODE **!

0.350 declarative store chunk [type-number]!

0.350 audio attend-sound!

0.370 vision encoding-complete [text~75]!

0.435 motor preparation-complete!

0.485 motor initiation-complete!

0.585 motor output key 1!

0.735 motor finish-movement!

0.785 procedural ** TYPE-NUMBER*TYPE ** [type-number~80]!

0.785 motor press-key "2"!

0.835 procedural ** TYPE-NUMBER*FIND-NEXT ** [type-number~80]!

0.835 vision find-location [vision~87]!

0.850 audio audio-encoding-complete [ring~81]!

0.885 procedural ** TYPE-NUMBER*ENCODE ** [type-number~80]!

0.885 vision move-attention!

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 22

Threads-3

0.935 motor preparation-complete!

0.935 procedural ** HANDLE-SOUND*PHONE ** [handle-sound~79]!

0.935 declarative store chunk [handle-sound~79]!

0.935 speech speak "Hello!"!

0.970 vision encoding-complete [text~90]!

0.985 motor initiation-complete!

1.085 motor output key 2!

1.085 speech preparation-complete!

1.135 speech initiation-complete!

1.135 speech output-speech "Hello!"!

1.235 motor finish-movement!

1.285 procedural ** TYPE-NUMBER*TYPE ** [type-number~80]!

1.285 motor press-key "3"!

1.335 procedural ** TYPE-NUMBER*FIND-NEXT ** [type-number~80]!

1.335 vision find-location [vision~100]!

1.385 procedural ** TYPE-NUMBER*ENCODE ** [type-number~80]!

1.385 vision move-attention!

1.435 speech finish-movement!

1.435 motor preparation-complete!

1.470 vision encoding-complete [text~103]!

1.485 motor initiation-complete!

1.585 motor output key 3!

1.735 motor finish-movement!

1.785 procedural ** TYPE-NUMBER*TYPE ** [type-number~80]!

1.785 motor press-key "4"!

!

< “converse” goal is still active and proceeds here... >!

To the Laboratory...

■  Let’s look at threaded cognition in two laboratory tasks:

–  tracking & choice –  dual-choice tasks

Tracking & Choice

■  Manual tracking appears in many forms

(7)

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 25

Tracking

■  In many experiments, it’s much more controlled

–  either: try to keep a pointer on a target

–  or: try to keep a cursor within a target range

–  while the movement is generated using a pseudo-random forcing function

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 26

Tracking & Choice

■  Experiment: Martin-Emerson & Wickens (1992)

–  tracking: keep the cursor in the target area

•  hard vs. easy tracking, depending on forcing function

–  choice: see an arrow pointing {left, right}, press key to respond

•  arrow separated from target area by offset that varies between 0° and 35° of visual angle

target area cursor

choice stimulus

offset

Tracking & Choice

■  Experiment: Martin-Emerson & Wickens (1992)

Track.java

public void start () {

processDisplay();

Utilities.shuffle (offsetIndices);

offsetIndex = 0;

offsetCount = 0;

lastArrowTime = 5.0;

addPeriodicUpdate (.020);

}

void updateTarget (double time) {

double pi2 = 2 * Math.PI;

if (easy)

{

tx = (2.86 * Math.sin (0.00 + (pi2 * (time / 16.670)))) + (1.15 * Math.sin (1.57 + (pi2 * (time / 6.250)))) + (0.57 * Math.sin (3.93 + (pi2 * (time / 9.091))));

ty = (2.29 * Math.sin (0.79 + (pi2 * (time / 8.000))))

+ (1.72 * Math.sin (4.72 + (pi2 * (time / 11.110)))) + (1.72 * Math.sin (2.36 + (pi2 * (time / 50.000))));

}

else

...

<< move target to (tx,ty) >>

}

(8)

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 29

Track

(set-­‐task  "cs630.Tracking")    

(sgp          :v  nil          :emma  t   )    

(start-­‐hand-­‐at-­‐mouse)    

(add-­‐dm          (track-­‐goal  isa  track)          (choice-­‐goal  isa  choice)   )  

 

(goal-­‐focus  track-­‐goal)   (goal-­‐focus  choice-­‐goal)  

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 30

Track

;;  Tracking  Task    

(p  Bind-­‐target          =goal>  

               isa  track          ?visual-­‐location>  

               state  free                  -­‐  buffer  requested          ?visual>  

               state  free                  buffer  empty  

==>  

       +visual-­‐location>  

               isa  visual-­‐location                  kind  cross   )  

(p  move-­‐to-­‐target          =goal>  

               isa  track          =visual-­‐location>  

               kind  cross          ?visual>  

               state  free                  buffer  empty          ?manual>  

               state  free  

==>  

       +visual>  

               isa  move-­‐attention                    screen-­‐pos  =visual-­‐location          +manual>  

               isa  move-­‐cursor                  loc  =visual-­‐location   )  

(p  repeat-­‐track          =goal>  

               isa  track          =visual>  

               isa  cross          ?manual>  

               state  free  

==>  

)  

Track

;;  Choice  Task     (p  Bind-­‐arrow          =goal>  

               isa  choice          ?visual-­‐location>  

               state  free                  -­‐  buffer  requested          ?visual>  

               state  free                  buffer  empty  

==>  

       +visual-­‐location>  

               isa  visual-­‐location                  kind  text                  :attended  nil   )  

(p  arrow-­‐not-­‐found          =goal>  

               isa  choice          ?visual-­‐location>  

               state  error  

==>  

       -­‐visual-­‐location>  

)    

(p  encode-­‐arrow          =goal>  

       =visual-­‐location>  

               kind  text          ?visual>  

               state  free                  buffer  empty  

==>  

       +visual>  

               isa  move-­‐attention                    screen-­‐pos  =visual-­‐location   )  

(p  respond-­‐left          =goal>  

               isa  choice          =visual>  

               isa  text                  value  "<"  

       ?manual>  

               state  free  

==>  

       +manual>  

               isa  punch                  hand  left                  Binger  pinkie   )  

 

(p  respond-­‐right        ...  

)  

Track

1849.957 procedural ** FIND-ARROW ** [choice-goal]!

1849.957 vision error!

1850.007 procedural ** ARROW-NOT-FOUND ** [choice-goal]!

1850.020 vision unrequested [vision~27824]!

1850.057 procedural ** FIND-TARGET ** [track-goal]!

1850.057 vision find-location [vision~27827]!

1850.107 procedural ** MOVE-TO-TARGET ** [track-goal]!

1850.107 vision move-attention!

1850.107 motor move-cursor vision~27827!

1850.107 motor preparation-complete!

1850.148 vision encoding-complete [cross~27832]!

1850.157 motor initiation-complete!

1850.242 eye preparation-complete [cross~27832]!

1850.315 eye execution-complete [cross~27832]!

1850.529 motor move cursor (255 10)!

1850.579 motor finish-movement!

1850.629 procedural ** REPEAT-TRACK ** [track-goal]!

1850.679 procedural ** FIND-ARROW ** [choice-goal]!

1850.679 vision find-location [vision~27836]!

1850.729 procedural ** ENCODE-ARROW ** [track-goal]!

1850.729 vision move-attention!

1850.864 eye preparation-complete [text~27839]!

1850.995 eye execution-complete [text~27839]!

1851.023 vision encoding-complete [text~27839]!

1851.073 procedural ** RESPOND-LEFT ** [choice-goal]!

1851.073 motor punch left pinkie!

1851.123 procedural ** FIND-TARGET ** [track-goal]!

...!

(9)

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 33

Track

■  Process timeline

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 34

Tracking & Choice

■  Results: Choice response time

Tracking & Choice

■  Results: Tracking error

Dual-Choice Tasks

■  A choice task means –  get a (simple) stimulus –  produce a (simple) response

■  Dual-choice tasks ask a person to do 2 choice tasks at almost the same time

■  Several factors are often varied in experiments using this paradigm

–  perceptual modality: visual / aural –  motor modality: manual / vocal

–  cognitive difficulty of stimulus

à

response

mapping

(10)

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 37

Dual-Choice Tasks

■  Example (with consistent S à R mappings) –  visual-manual task

–  aural-vocal task

O – – – – O – – – – O –

low tone

one mid tone

two high tone

three

CS 630: Cognitive Systems. Dario Salvucci, Drexel University. 38

Dual-Choice Tasks

■  In dual-choice tasks, there’s usually a delay between one stimulus and the other

–  called the “SOA” = “stimulus onset asynchrony”

–  e.g., if we start the aural-vocal task at time = 0, we might present the visual-manual task at time = {.000 .050 .150 .250 .500 1.000}

■  Compared to the single-task case, how long will the visual-manual task take when...

–  SOA is big?

(stimuli far apart)

–  SOA = 0?

(concurrent stimuli)

–  somewhere in between?

The PRP Effect

■  Psychological Refractory Period (PRP) effect –  “refractory” from analogy with cells returning

to normal after excitation (not a great analogy, but it stuck)

The PRP Effect

■  What causes the PRP effect?

■  For a long time, it was assumed to be a solid indicator of a “cognitive bottleneck”

■  A box-diagram depiction:

–  this is the “response-selection” bottleneck –  it’s also a bit misleading...

Is there really an inherent cognitive bottleneck?

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Experiments

■  Schumacher et al. (2001), Experiment 1 –  people can achieve perfect time-sharing!

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Experiments

■  Schumacher et al. (2001), Experiment 1 –  people can achieve perfect time-sharing!

–  table with final results after learning only...

Single-Task Dual-Task

Aural-Vocal 446 ms 456 ms

Visual-Manual 281 ms 283 ms

Experiments

■  Schumacher et al. (2001), Experiment 2 –  PRP effect comes from instructions /

constraints: do Task 1, then do Task 2

Perfect Time-Sharing

■  Perfect time-sharing follows readily from threaded cognition

–  in this case, everything works out perfectly; no

interference, no dual-task/PRP effect!

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Dual-Choice Tasks

■  An inconsistent S à R mapping requires an extra step to retrieve the mapping

O – – – – – – O

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Dual-Choice Tasks

■  An inconsistent S à R mapping requires an extra step to retrieve the mapping

–  with possible interference, as here (A)

Dual-Choice Tasks

■  Increased perceptual difficulty makes perception for the tasks run into each other

O O O O O O O O

Dual-Choice Tasks

■  Increased perceptual difficulty makes perception for the tasks run into each other

–  with possible interference, as here (B)

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Problem State

■  Problem state = temporary information required during task execution

–  roughly speaking, a task’s “mental context”

–  in ACT-R: stored in the imaginal buffer

■  Example: Solving 3+4

–  encode “3”, then “+”, then “4”

–  all this is now held in the problem state / imaginal buffer

–  in this case, used to pass along information for retrieval

–  can also be used to remember new information

•  i.e., associate 3, +, 4, and then 7 with one another

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Problem State

■  Example: Writing a paper

–  what do you need to keep in mind as you’re writing a...

•  sentence?

•  paragraph?

•  section?

–  where do you maintain the least amount of information?

■  Example: Tracking, or Driving –  no problem state needed!

Memory & Interruptions

■  Memory clearly plays an important role in interruptions

■  What are the (at least two) important features of human memory?

–  information strengthens with use –  information decays over time

Memory for Goals

■  Memory for goals theory (Altmann &

Trafton, 2002) + ACT-R memory theory (Anderson et al., 2004)

–  to suspend a task, people encode (rehearse) the current goal until it’s readily available in memory

•  in ACT-R, each retrieval boosts a chunk’s activation, making it easier to recall

•  e.g., rehearse “I’m ordering a platypus” a few times

–  to resume the task, people simply recall the goal

•  in ACT-R, associated cues can facilitate recall

•  e.g., seeing computer, or browser on platypus web page

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Memory for Goals

■  Memory for goals as threads...

■  Encoding

■  Retrieval

Primary task Secondary task Primary task

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Memory for Goals

■  Memory for goals as threads...

■  Encoding

■  Retrieval

Rehearsal Retrieval

Primary task

Secondary task

Primary task

Memory for Goals

■  How many retrievals/rehearsals is a “good”

number for a typical interruption?

Interruption Study

■  Monk, Trafton, & Boehm-Davis (2008) –  explored effects of interruption duration &

demand

on primary-task resumption –  primary task: programming a VCR

–  interruption duration: 3, 8, or 13 seconds –  interrupting task

•  no-task: just wait

•  track: manual tracking task

•  n-back: compare current and previous letters (<,>)

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Interruption Study

■  Model

–  model for primary task

•  full model not needed…

•  specified declarative chunk to represent the goal

•  estimated time parameter for performing first action

–  models for interrupting tasks

•  no-task: trivially waits

•  tracking: does the tracking

•  n-back: simplified from previous work

(Juvina & Taatgen, 2007)

–  uses declarative resource to retrieve last item!

–  model for interruption process described earlier –  but when exactly should encoding occur?

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Interruption Study

■  Encoding strategies

–  S1: Encode during the entire interruption –  S2: Encode for n seconds, concurrently with

secondary task

–  S3: Encode until retrieval takes no more than n seconds, concurrently with the secondary task –  S4: Encode for n seconds prior to the

interruption, ending at the onset of the interruption

–  S5: Encode for a few (3) retrievals prior to the interruption, ending at the onset of the interruption

Interruption Study

Monk et al. (2008)

Interruption Study

Monk et al. (2008) Model – S1

(rehearse entire interruption)

no effect of duration

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Interruption Study

Monk et al. (2008) Model – S5

(rehearse few times before interrupt)

duration effect too large;

no n-back interaction

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Interruption Study

Monk et al. (2008) Model – S4

(rehearse for n sec before interrupt)

no n-back interaction

Interruption Study

Monk et al. (2008) Model – S3

(rehearse until retrieval < n sec)

strange n-back interaction (interference forces too much encoding!)

Interruption Study

Monk et al. (2008) Model – S2

(rehearse for n sec after interrupt)

Yes!

n-back interaction due to declarative interference

R2=.94

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Interruption Study

■  ACT-R model for S2 –  interleaved with tracking

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Interruption Study

■  ACT-R model for S2

–  interleaved with the N-back task

Interruption Study

■  Tracking error

–  data: slight effect for 3-sec interruption across three experiments (albeit not conclusive) –  model: S2 & S3 show this effect due to encoding

■  Bottom line: Memory-intensive interruptions

(like N-back) are especially disruptive

because they interfere with rehearsal

References

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