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CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses by Ken Wong, Eleni Stroulia Zach Dodds, Martin Jagersand
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CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

Jan 01, 2016

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Page 1: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

CMPUT 301: Lecture 16Task Analysis II

Lecturer: Martin JagersandDepartment of Computing Science

University of Alberta

Notes based on previous courses byKen Wong, Eleni Stroulia

Zach Dodds, Martin Jagersand

Page 2: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Overview:

• Last time:– Hierarchical analysis– Temporal plans– Knowledge based analysis

• Today:– Entity-relation based analysis– Using several of the above together

Page 3: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Understanding objects and actions:– list all objects involved– focus on the relationships between objects and

actions, rather than similarities– link actions with objects which help perform them– “object-based”

Page 4: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Objects of gardening firm:– tool shed with spade, garden fork, hoe– Ferguson tractor, with plow and harrow– owner (Vera)– two employees (Sam and Tony)– two growing fields– large glasshouse with humidity sensor– computer-controlled irrigation system

team

The kit

Page 5: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Classify objects into three types:– simple objects

– “things”

– e.g., spade, plow, glasshouse

– actors– humans and non-humans that do things

– e.g., Vera, Sam, Tony, Fergie, computer

– composite objects– objects which consist of other objects

– e.g., team, men, kit

Page 6: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Look at some attributes of objects:– Object Pump3 simple — irrigation pump

– Attributes– status: on/off/faulty

– capacity: 100 litres/minute

Page 7: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Only enough detail about attributes to describe their use in tasks:– Actions are e.g.,

– turning on and off irrigation pumps, done by user actor

– may not need pump capacity – only needed by repairman for replacement

• We can drop unwanted details later.

Page 8: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Look at actions that change the state of something:– agent (often an actor), action, patient– associated attributes– e.g.,

– Sam planted carrots

– gardener dug soil with spade

– irrigation controller turning on water

Page 9: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Message actions:– communication– perhaps in prelude to another action– e.g.,

– Vera telling Sam to dig the carrots

Page 10: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Identify roles:– actors fill in specific roles– an actor can have multiple roles– a role can have multiple actors– e.g.,

– Vera as worker

– Vera as manager

– Sam as worker

Page 11: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Object Sam human actor– Actions

– s1: drive tractor– s2: dig the carrots

• Object Vera human actor– Actions as worker

– v1: plant seed– v2: program irrigation controller

– Actions as manager– v3: tell Sam to dig the carrots

Page 12: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Object the men composite– Comprises

– {Sam, Tony}

• Object glasshouse simple– Attribute

– humidity: 0–100%

Page 13: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Object Irrigation Controller non-human actor– Actions

– ic1: turn on Pump1

– ic2: turn on Pump2

– ic3: turn on Pump3

Page 14: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Identify events:– things that happen– Different types e.g.,

– germination of “seed”(spontaneous action of seed, non-actor)

– humidity drops below 25%(no associated object)

– at midnight(timed)

Page 15: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Identify relationships between objects, actions, and events:– object to object

– e.g., Sam is subordinate to Vera

– action to object– e.g., (Sam) digs the carrots

Page 16: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Relations object–object– located in: ( Pump3, glasshouse )– located in: ( Pump1, Field1 )

Page 17: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Relations action–object– patient ( v3, Sam )

– i.e., Vera tells Sam to dig

– patient ( s2, the carrots )– i.e., Sam digs the carrots

– instrument ( s2, spade )– i.e., Sam digs the carrots with the spade

Page 18: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Entity-Relation-Based Techniques

• Relations action–event– before ( v1, m1 )

– i.e., seed must be sown before it can germinate

– triggers ( ev1, ic3 )– i.e., when humidity drops below 25%, the controller

turns on pump 3

– causes ( v2, ic1 )– i.e., the controller turns on pump 1 because Vera

programmed it

– etc.

Page 19: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Combining Approaches

• 0 To grow carrots– 1 Vera sows the seed– 2 seed germinates– 3 Vera programs controller– 4 controller waters field– 5 carrots grow– 6 Sam hoes– 7 Tony harvests carrots

Page 20: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Combining Approaches

• Plans:– plan 0

– do 1, 2, 5, when crop is mature do 7

– when rainfall is low, do 3, 4

– when weeds grow, do 6

Page 21: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Combining Approaches

• Look at a particular object and all the actions in which it participates:– life cycle diagram– many tasks

Combining Approaches

Page 22: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Combining Approaches

Page 23: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Combining Approaches

• Use knowledge-based (taxonomic) analysis:– identify commonalities of actions and relations– build inheritance hierarchy– “object-oriented”– e.g., Sam and Tony could do some things in

common

Page 24: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Sources of Information

• Need to collect information about tasks from various sources:– documentation– observation– initial analysis– sorting and classification

Page 25: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Sources of Task Information

• Documentation:– e.g., existing manuals, training materials, job

descriptions– job descriptions may only describe what people

are supposed to do, not what they actually do– equipment manuals may only describe

functions or features, not tasks

Page 26: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Sources of Task Information

• Observation:– formal or informal– in the field on in the lab– passive or active– note taking– video taping– talk aloud– walkthroughs– confirm task analyses

Page 27: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Sources of Task Information

• Interviews:– pose questions to domain experts directly– follow up on responses with more questions,

for more detail

Page 28: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Sources of Task Information

• Initial analysis:– following on from manuals, observation, or

interviews– build lists of objects (nouns) and actions

(verbs)

Page 29: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Sources of Task Information

• Sorting and classification:– use note cards of task objects– have a domain expert sort cards into piles by

similarity– use spatial arrangement– compare groupings among experts– use an outliner

Page 30: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Uses of Task Analysis

• Manuals:– use hierarchical task analysis to structure

training materials(“how to do it”)

– use knowledge-based techniques to structure a course or textbook(concepts and foundations)

Page 31: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Uses of Task Analysis

• Requirements capture:– task analysis of existing procedures– help in eliciting what the new system must do

and guiding its design– how the system is used versus what the system

does– compare new and old procedures

Page 32: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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Uses of Task Analysis

• Detailed interface design:– use task decomposition trees to design menus

and layout dialogs– or use roles and tasks within each role to design

menus– or use objects and what can be done to it to

design menus– use taxonomies for grouping– avoid too much “movement”

Page 33: CMPUT 301: Lecture 16 Task Analysis II Lecturer: Martin Jagersand Department of Computing Science University of Alberta Notes based on previous courses.

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End

• What did I learn today?

• What questions do I still have?