Yvonne Wærn Tema Kommunikation

1. Yvonne WærnTema Kommunikation Information Processing - In humans and machines April 24, 2001

2. Information Processing Psychology - IPP • Revolution and opposition against behaviorism • Behaviorism characterised psychology in general from about 1900 to about 1970.

3. What was behaviorism? • Theory to describe (explain and predict) behaviour in observable terms only: Stimulus - Response • Pavlov: conditioned reflex (dogs salivating) • Skinner: instrumental conditioning (pigeons playing table-tennis) • Watson: conditioned behaviour (Child afraid of rabbits) • Nowadays: Behavioural therapy (diverse phobias) • Some computer supported learning

4. Information Processing Psychology - • One of several approaches to model cognitive and mental processes - in opposition to behaviorism • (but still some behavioristic traits) • Other approaches with similar aim: • Gestalt Psychology, (contemporary with beh.) • Piaget (contemporary with behaviorism) • Bruner (inspired by Piaget)

5. Information Processing Psychology - ingredients • Model from the computer - • In contrast to previous cognitive models that were often statistical • A modelling language - production rules • In contrast to verbal descriptions • A qualitative method to derive information processes • In contrast to quantitative methods

6. IP- model from the computer (skipping psychology) • Model from the computer - (1956!) • Information processing: • Transformation of ”knowledge states” from start to goal: operations on symbols • Success: AI in form of ”The Logical Theorist” derived all theorems (and some more) in Russel & Whitehead’s volume on ”Logics”.

7. IP- model from the computer • Was this human information processing? • No: • people have ”bounded rationality” • Use heuristics • Use ”smart” ways of representing problems • Are restricted by their information processing apparatus

8. IP- modelling language • A modelling language - production rules • In contrast to verbal descriptions • If-then rules. The current state is matchted towards the system of rules. The first rule that ”matches” the current state is ”fired”. • Then a new state results, that is matched… • What does this remind us of?

9. Information Processing : methods A qualitative method to derive information processes • The think-aloud protocol was used to elicit data on sequential problem solving. • Hypotheses: people expressed (parts of) that what existed in their working memory - i.e. part of the current ”knowledge state”.

10. IPP - prerequisites-psychology reintroduced Since people are not computers, we have to use reverse engineering to understand the mechanisms by which they proceed: • Define problem • Identify process • Derive specific strategy from process • Derive general cognitive architecture from several studies

11. Define problem A problem exists when you have a goal and an initial state that does not correspond to the goal and you do not know how to get from the initial state to the goal

12. Define problem space A problem space consists of the hypothetical states that a problem solver goes through in its processing/transformation of the initial state to the goal state. Ex. Problem space = intitial state + operations required to reach goal state

13. Example of problem- Tower of Hanoi You have three disks on a peg (A) as in the figure. These should be moved to the right peg (C). You are only allowed to move one disk at a time. You can only place a smaller disk on top of a bigger one. A B C

14. Think aloud protocol-example :Tower of Hanoi First I put the smallest one here (on C) Then I put the nextsmallest here (on B) Then I take the biggest one - O no, that is not allowed, OK I move the smallest back to A And the next smallest to C Then I take the smallest to B And the next smallest to - where should it go...

15. A think-aloud protocol can be regarded as ”the top of the iceberg” • Toppen av isberget bild

16. Some production rules that may produce the think aloud protocol IF goal achieved THEN end If disc1 free THEN move disc1 If move disc1 THEN check if C is possible IF C possible THEN move disc1 to C IF C is not possible THEN move disc1 to A If disc2 free THEN move disc2 If move disc2 THEN check if B is possible If B empty, THEN move disc2 to B IF disc3 free THEN move disc3 IF move disc 3 THEN check if C is possible

17. What production rules may produce the shortest path? • Can production rules only solve this problem?

18. No: Rules are not sufficient! We need a system to interpret the rules! What can the system ”perceive”? How should the objects be represented? In what order are the productions tested? How will the actions performed be remembered?

19. A cognitive architecture • Defines how rules are interpreted • In what order they are taken • What conditions prevail for how the rules may be written (for instance how many conditions and actions are possible for one rule) • How the results of actions are stored

20. From IP to HIP (Psychology has been changed to human) • Human beings differ from computers in several ways. • Therefore, we have to define a ”mechanism” that processes information in a similar way as a human being, a HIP: • Human Information Processor

21. A cognitive architecture for Human Information Processing (HIP) • Must comply with knowledge about human beings. • Knowledge from various sources: • Senso-motoric • Attention • Perception • Memory • Metacognition

22. Visual rendering of a Human Cognitive architecture (EPICS) (CHI 2001,p 130) Long-term memory Productions Cognitive processor Task Environ ment Production rule interpreter Auditory input Auditory proc. Visual input Working memory Visual proc. Vocal motor Manual motor

23. Important HIP characteristics to be considered • Perceptual capacities • (time for writing, time for retrieving) • Motor capacities • Eye and hand movements, time • Long-term memory (productions) • Time for writing, time for retrieving, type of productions • Working memory • (restricts amount of material on which productions may work)

24. Important HIP characteristics to be considered • Working memory • (restricts amount of material on which productions may work) • 5+/- 2 ”chunks” • What is a chunk? • A meaningful unit • What is that? Chunk på Zoo

25. Important HIP characteristics to be considered • Long-term memory (productions) • Time for writing, time for retrieving, type of productions • Long-term memory (declarative) • Semantic networds • Schemata Som Choklad-pudding

26. Characteristics of ingredients in the human information processor From Newell & Simon, 1972 rendered by Card, Moran & Newell, 1983 Bild from C,M&N

27. Applications of IP and HIP ideas • Rule-based systems: • Knowledge base systems • Intelligent tutoring • User modelling • HCI • Analytic models • Simulation models • Quasi-empirical approaches

28. HIP applied to HCI • Analytic model: • TAG: Task Action Grammar • Takes related tasks in a system, derives how many rules that have to be used to perform these tasks. The less rules, the easier to learn.

29. HIP applied to HCI • Simulation models • Different cognitive architectures: • ACT* • SOAR • Input data are processed through simulated user model • Results: reaction times

30. HIP applied to HCI • Quasi-empirical approach: • GOMS • Analyses a task from an expert’s actions: • Goals, Operations, Methods and Selection rules • Further applications of GOMS: • Cognitive walkthrough - what will a user find difficult in the system? (Goals, operations, methods analysed with respect to the designer’s knowledge about the user)

31. HIP applied to HCI • Further applications of GOMS: • Keystroke level calculations: How long will it take to perform a task with the system? • Has been used to compare different system solutions, for instance for telephone operators asking caller’s questions. • A small change in the time taken may mean much when many small tasks are performed by many persons.

32. Key-stroke level av GOMS • Task: Copy a word and position it at some place at the text • Method: Get the operations from the menu • 1. Time to identify the word • 2. Time to mark the word • 3. Time to move to the menu and find the word ”copy” • 4. Time to click on ”copy” • 5. Time to go to the position in the text were the word should be placed • 6. Time to click in order to move the cursor to this place • 7. Time to move to the menu and get the command ”paste”. • 8. Time to click for placing the word. • 9. Time for checking that the result is OK • The time for the handmovements is calculated according to ”Fitt’s law”

33. HIP applied to HCI • Learning - • The effect of prior knowledge • Positive (can use old rules): • Cognitive Complexity Theory (CCT) • Negative (interference with old rules) • Learning by doing • A problem solving approach is possible En tjusig morgon på kontoret

34. ”Search!” Mismatching models • Conceptual models versus device models versus the user’s model of the system • Designers have one particular (conceptual) model in their mind about how a system should work • The system is implemented to show a model (device model) that may not be the same. • When users work with the system they may construct yet another model of the system

35. Summary: There is a gulf between perception and execution. We may calculate the effects. Goals Intentions Evaluation Execution Perception System (Norman, 1986)

36. Recent uses of IPP-models(from CHI 2001) • Out of 69 papers, eight use some kind of theory. • HIP theory is used in all eight cases.

37. Recent uses of HIP-models(Examples from CHI 2001) • Ignoring Perfect Knowledge-in-the-world for Imperfect Knowledge-in-the head: Implications of rational analysis for Interface Design • Predicting the Effects of In-Car Interfaces on Driver Behavior Using a Cognitive Architecture • Towards Demystification of Direct Manipulation: Cognitive Modeling Charts the Gulf of Execution • Beyond Command Knowledge: Identifying and Teaching Strategic Knowledge for Using Complex Computer Applications

38. Conclusions • HIP-models have a narrow range of application • Within this range, they are surprisingly successful • More so than any other models or theories within HCI. How is success defined? How do we know which applications?