cognitive models for GUI design

Transcription

1 cognitive models for GUI design Ch (pp ) 1/56

2 Alternative Models Mental model Cognitive model Conceptual model 2/56

3 Cognitive models They model aspects of user: understanding knowledge intentions processing Common categorisation: Competence: What users ideally should do versus Performance: What users actually do 3/56

4 Common assumptions about the architecture of the human mind Long-term/Short-term memory Problem spaces Interacting Cognitive Subsystems Connectionist Marvin Minsky, AI Lab, MIT: Society of Minds, /56

5 Cognitive models 1 Goal and task hierarchies (GOMS, CCT) 2 Linguistic notations (BNF, TAG) 3 Physical and device models (KLM) 4 Automating Inspection Methods (Common assumptions from above are not necessary here) 5/56

6 1 Goal and task hierarchies (GOMS, CCT) Granularity Where exactly do we start? Where exactly do we stop? Routine learned behaviour, not problem solving The unit task Conflict More than one way to achieve a goal Error 6/56

7 1.1 Goals, Operators, Methods and Selection (GOMS) Goals what the user wants to achieve Operators basic actions user performs Methods decomposition of a goal into subgoals/operators Selection means of choosing between competing methods 7/56

8 GOMS example GOAL: CLOSE-WINDOW. [select GOAL: USE-MENU-METHOD. MOVE-MOUSE-TO-FILE-MENU. PULL-DOWN-FILE-MENU. CLICK-OVER-CLOSE-OPTION GOAL: USE-CTRL-W-METHOD. PRESS-CONTROL-W-KEYS] For a particular user: Rule 1: Select USE-MENU-METHOD unless another rule applies Rule 2: If the application is GAME, select CTRL-W-METHOD 8/56

9 GOMS example Seminar on Cognitive Modeling for UI Design : CognitiveModelingForUIDesign/ index.htm 9/56

10 Use of GOMS: Before MultiModal Watch Station (MMWS) Source: 10/56

11 Use of GOMS: After MultiModal Watch Station (MMWS) Source: 11/56

12 1.2 Cognitive Complexity Theory (CCT) Two descriptions: User production rules Form: if condition then action (Device generalised transition networks) Example Cognitive model of editing with vi 12/56

13 CCT example: editing with vi Bill Joy wrote vi at the University of California, Berkeley, on a Lear-Siegler ADM3A terminal. On this machine, the Escape key was where the Tab key is nowadays, thus enabling users to very efficiently switch modes. Also, the keys h,j,k,l had arrows, explaining the usage of these keys for moving around. The ADM3A had no other keys that corresponded to arrows. 13/56

14 CCT example: editing with vi vi became the de facto standard Unix editor and a nearly undisputed hacker favorite outside of MIT until the rise of Emacs after about As of 2007 either vi or one of its clones can still be found on nearly all installations of Unix. The Single UNIX Specification specifies vi, so any system conforming to the Single UNIX Specification will have vi. 14/56

15 CCT example: editing with vi 15/56

16 Rules to model inserting a space Active rules: SELECT-INSERT-SPACE INSERT-SPACE-MOVE-FIRST INSERT-SPACE-DOIT INSERT-SPACE-DONE New working memory (GOAL insert space) (NOTE executing insert space) (LINE 5) (COLUMN 23) SELECT-INSERT-SPACE matches current working memory (SELECT-INSERT-SPACE IF (AND (TEST-GOAL perform unit task) (TEST-TEXT task is insert space) (NOT (TEST-GOAL insert space)) (NOT (TEST-NOTE executing insert space))) THEN ( (ADD-GOAL insert space) (ADD-NOTE executing insert space) (LOOK-TEXT task is 16/56 at %LINE %COLUMN)))

17 2 Linguistic notations Understanding the user's behaviour and cognitive difficulty based on analysis of language between user and system. Similar in emphasis to dialogue models Example Backus Naur Form (BNF) 17/56

18 2.1 Backus-Naur Form (BNF) A BNF specification is a set of derivation rules, written as <symbol> ::= <expression with symbols> where <symbol> is a nonterminal, and the expression consists of sequences of symbols and/or sequences separated by the vertical bar, ' indicating a choice, or the plus, +, indicating a sequence, the whole being a possible substitution for the symbol on the left. Symbols that never appear on a left side are terminals. 18/56

19 2.1 Backus-Naur Form (BNF) Very common notation from computer science A purely syntactic view of the dialogue Terminals lowest level of user behaviour e.g. CLICK-MOUSE, MOVE-MOUSE Nonterminals ordering of terminals higher level of abstraction e.g. select-menu, position-mouse 19/56

20 Example of BNF Basic syntax: nonterminal ::= expression An expression contains terminals and nonterminals combined in sequence (+) or as alternatives ( ) draw line ::= select line + choose points + last point select line ::= pos mouse + CLICK MOUSE choose points ::= choose one choose one + choose points choose one ::= pos mouse + CLICK MOUSE last point ::= pos mouse + DBL CLICK MOUSE pos mouse ::= NULL MOVE MOUSE+ pos mouse 20/56

21 Measurements with BNF Number of rules (not so good) Number of + and operators Complications same syntax for different semantics no reflection of user's perception minimal consistency checking 21/56

22 Backus-Naur Form (BNF), example Consider this BNF for a US postal address <postal-address> ::= <name-part> <street-address> <zip-part> <name-part> ::= <personal-part> <last-name> [<jr-part>] <EOL> <personal-part> <name-part> <personal-part> ::= <name> <initial> ". <street-address> ::= [<apt>] <house-num> <street-name> <EOL> <zip-part> ::= <town-name> "," <state-code> <ZIP-code> <EOL> 22/56

23 Backus-Naur Form (BNF), example <postal-address> ::= <name-part> <street-address> <zip-part> <name-part> ::= <personal-part> <last-name> [<jr-part>] <EOL> <personal-part> <name-part> <personal-part> ::= <name> <initial> ".... This translates into English as "A postal-address consists of a name-part, followed by a street-address part, followed by a zip-code part. A personal-part consists of either a first name or an initial followed by a dot. A name-part consists of either: a personal-part followed by a last name followed by an optional "jr-part" (Jr., Sr., or dynastic number) and end-of-line, or a personal part followed by a name part (recursion in BNFs, covering the case of people who use multiple first and middle names and/or initials). 23/56

24 Backus-Naur Form (BNF), example... continued: <street-address> ::= [<apt>] <house-num> <street-name> <EOL> <zip-part> ::= <town-name> "," <state-code> <ZIP-code> <EOL> This translates into English as (continued) A street address consists of an optional apartment specifier, followed by a street number, followed by a street name. A zip-part consists of a town-name, followed by a comma, followed by a state code, followed by a ZIP-code followed by an end-of-line." 24/56

25 Optional: More on Backus-Naur Form (BNF) Programspråk is an optional course during year 2 or 3 for D and IT, held by Aarne Ranta. It uses BNFC ( Language-technology/BNFC/ ) in the labs. course_code=tin321 25/56

26 Two short exercises 1) Describe a person-number with words. An person-number consist of." 2) Then translate the text into BNF THEREAFTER 1) Describe a bank account number with words. An bank account number consist of." 2) Then translate the text into BNF 26/56

27 Some vocabulary (maybe not all is usefull for this problem) SWEDISH Bank Name Bankens namn t.ex. Nordea Bank Address Bankens Address Bank City Stad Bank Zip Code Postnummer Bank Country land Bank Phone tel nr. till banken Name on Bank Account Kontos ägare namn Account Number kontonummer Bank Routing No. sorteringskod för banken Check No. kontrollnummer Bank Swift Code Swift kod för banken, 8 el 11 tecken sök på banken eller swifts nätsidor Bank IBAN Code kontonummer i IBANform fås från banken 27/56

28 3 Physical and device models The Keystroke Level Model (KLM) Buxton's 3-state model Based on empirical knowledge of human motor system User's task: acquisition then execution. these only address execution Complementary with goal hierarchies 28/56

29 3.1 Keystroke Level Model (KLM) six execution phase operators Physical motor: K - keystroking P - pointing (use Fitt s Law) H - homing D - drawing Mental M - mental preparation System R - response times are empirically determined. T execute = TK + TP + TH + TD + TM + TR 29/56

30 Fitt s Law for ann Estimation of Pointing Time T = a + b log2(d/s + 1) D: Distance to target S: Size of target a, b: Empirically estimated constants Original form of Fitt s Law, 1954, without a constant: T = log2(2a/w) 30/56

31 Fitt s Law, example 1: Width 40, Height 37 time = 0.0 Width 29, Height 22 time =? Width 63, Height 92 time =? 31/56

32 Fitt s Law, example 2: Demo application intro page Demo application program 32/56

33 Keystroke Level Model (KLM) 1. Move hand to mouse H[mouse] 2. Position mouse after bad character PB[LEFT] 3. Return to keyboard H[keyboard] 4. Delete character MK[DELETE] 5. Type correction K[char] 6. Reposition insertion point H[mouse]MPB[LEFT] 33/56

34 KLM example GOAL: ICONISE-WINDOW [select GOAL: USE-CLOSE-METHOD. MOVE-MOUSE-TO- FILE-MENU. PULL-DOWN-FILE-MENU. CLICK-OVER-CLOSE-OPTION GOAL: USE-CTRL-W-METHOD PRESS-CONTROL-W-KEY] compare alternatives: USE-CTRL-W-METHOD vs. USE-CLOSE-METHOD assume hand starts on mouse USE-CTRL-W-METHOD H[to kbd] 0.40 M 1.35 K[ctrlW key] 0.28 Total 2.03 s 34/56 USE-CLOSE-METHOD P[to menu] 1.1 B[LEFT down] 0.1 M 1.35 P[to option] 1.1 B[LEFT up] 0.1 Total 3.75 s

35 Exercise: Apply KLM Scenario: -- train ride ends, the user wants to delete all desk-top icons starting with T (temporary). -- Find and delete all icons starting with T -- Two conditions: Pad and Pin Exercise: -- Establish a KLM Model aiming to compare Pad and Pin -- Is clutching an issue for this task? 35/56 USE-PAD-METHOD H[to kbd] 0.40 M 1.35 K[ctrlW key] 0.28 Total x.y s USE-PIN-METHOD P[to menu] 1.1 B[LEFT down] 0.1 M 1.35 P[to option] 1.1 B[LEFT up] 0.1 Total z.x s

36 Hick Law Hick's law, named after British psychologist William Edmund Hick, or the Hick Hyman law (for Ray Hyman), describes the time it takes for a person to make a decision as a result of the possible choices he or she has. Given n equally probable choices, the average reaction time T required to choose among them is approximately T = b log 2 (n + 1) where b is a constant that can be determined empirically by fitting a line to measured data. 36/56

37 Hick Law (continued) Hick's law is sometimes cited to justify menu design decisions. However, applying the model to menus must be done with care. For example, to find a given word (e.g. the name of a command) in a randomly ordered word list (e.g. a menu), scanning of each word in the list is required, consuming linear time, so Hick's law does not apply. However, if the list is alphabetical and the user knows the name of the command, he or she may be able to use a subdividing strategy that works in logarithmic. 37/56

38 3.2 Buxton's 3-state model Mouse vs. light-pen transitions Andreas Kunz, ICVR, ETH Z 38/56

39 3.2 Buxton's 3-state model State 0-1 Transaction: State Transaction: 39/56

40 3.2 Buxton's 3-state model 40/56

41 Display-based interaction Most cognitive models do not deal with user observation and perception Some techniques have been extended to handle system output (e.g., BNF with sensing terminals, Display-TAG) but problems persist 41/56

42 Example: Automating Inspection Methods -- Analysis Support Web UIs 42/56

43 Optional: Modeling with Petri Nets -- Can be used to model any behavior -- No distinction between right or wrong behavior 43/56

44 Focus: Petri-net based modelling Paper: Overview inclduing AMME and evaluation: 44/56 Petri nets:

45 Focus: Petri-net based modelling Paper: 45/56

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