1. UI/CM L AB Ecological Interface Design (EID) I.INTRODUCTION  an attempt to extend the benefits of direct manipulation interfaces (DMI) to complex work domains A.Unanticipated Events  thee broad areas for events 1)familiar events 2)unfamiliar, but anticipated events 3)unfamiliar and unanticipated events  unanticipated events are the major cause of life-threatening accidents  mistakes

2. UI/CM L AB Ecological Interface Design (EID) II.PROBLEM FORMULATION A.Fundamentals  an interface  a control system  control theory 1.the Law of Requisite Variety states that complex systems require complex controllers 2.physical systems can be described by a set of constraints 3.every good controller must be, or possess, a model of the system it is controlling

3. UI/CM L AB Ecological Interface Design (EID) B.The Structure of the Design Problem  two questions pertinent to interface design Abstraction hierarchy as a psychologically relevant form of representing the constraints in a work domain in a way that operators to cope with unanticipated events SRK taxonomy as a useful framework for describing the various mechanisms that people have for processing info domain and operator as the organism-environment reciprocity

4. UI/CM L AB Ecological Interface Design (EID) III.THE ABSTRACTION HIERARCHY A.What Kind of Hierarchy?  the AH the class of stratified hierarchy by Mesarovic et al. (1970)  the AH specified by a means-end relationship between levels  the AH not a specific representation but rather a framework for developing representations for various work domains  five levels of constraints for process control systems – functional purpose, abstract function, generalized function, physical function, physical form

5. UI/CM L AB Ecological Interface Design (EID) B.Coping with Unanticipated Events: A Historical Overview  accident-causing errors by human operators with unfamiliar situations not anticipated by designers  the AH, which provides a framework for identifying and integrating the set of goal relevant constraints that are operating in a given work domain  as a set of models of the system, each defining a level of the hierarchy  higher levels represent relational info about system purpose, whereas the lower levels represent more elemental data about physical implementation

6. UI/CM L AB Ecological Interface Design (EID) D.Psychological Relevance  higher levels are less detailed than lower levels  makes complex systems look simpler  explicitly goal-oriented  an efficient form of search 1.possible to meaningfully map problem solving protocols onto an AH representation of the domain 2.subjects’ problem solving trajectories would begin at a high level of abstraction and gradually focus in on lower levels, thereby exploiting the goal-related constraint provided by the hierarchy

7. UI/CM L AB Ecological Interface Design (EID) IV.MULTIPLE LEVELS OF COGNITIVE CONTROL  three levels of info (signals, signs, or symbols) vs. three levels of cognitive control SBB (automated behavior patterns), RBB (a set of cue-action mappings), and KBB (PS operations on a symbolic representation) A.The Power of Perception  three levels of cognitive control into two general categories 1.perceptual processing (SBB, RBB) – fast, effortless, parallel 2.analytic PS (KBB) – slow, laborious, serial, more error prone due to WM

8. UI/CM L AB Ecological Interface Design (EID)  two characteristics of complex work domain 1.highly skilled and extensive experience in controlling the system 2.interface design needs specific application – generality not important  make perceptual processing an attractive possibility  empirical evidence?  Brunswick (1956), Hammond et al. (1987)  perception can be very effective  not always leads to superior performance but the conditions characteristics of complex work domains are propitious for perceptual processing

9. UI/CM L AB Ecological Interface Design (EID) B.The Propensity for Perceptual Processing Two Examples  Klein (1989) – a series of naturalistic DM in the domain of firefighting, military operations, engineering design; nonroutine events  Expect that DM as analytical rather than recognitional  Surprisingly, experts often relies on recognitional DM  Mental model less taxing, advantage for experience  Quickly generate plausible action alternatives rather than the complete set of possible alternatives  Recognitional DM much quicker than analytical  Kirlick (1989) – complex, supervisory control task

10. UI/CM L AB Ecological Interface Design (EID) More Examples and What Can Go Wrong  Hollnagel (1981) – surface/ deep control in process control  Fischoff et al. (1978), Smith (1989) in management DM C.Skill and Task Effects  Task complexity, experience – which level of cognitive control  Necessary to understand how the levels are related and what the activities associated with each other D.Interaction Between Levels  A framework for interface design must take this into account

11. UI/CM L AB Ecological Interface Design (EID) E.Implications for Interface Design  SBB in the form of time-space signals, RBB by familiar perceptual forms (signs), KBB by meaningful structures (Symbols)

12. UI/CM L AB Ecological Interface Design (EID) V.ECOLOGICAL INTERFACE DESIGN A.The Principles 1)SBB – To support interaction via time-space signals, the operator should be able to act to directly on the display, and the structure of the displayed information should be isomorphic to the part-whole structure of movements 2)RBB – Provide a consistent one-to-one mapping between the work domain constraints and the cues or signs provided by the interface  no consistent mapping between perceptual cues and actions  procedural traps –TMI

13. UI/CM L AB Ecological Interface Design (EID)  For operator to often effectively control by perceptual cues rather than by KBB  mental economy 3)KBB – Represent the work domain in the form of an abstraction hierarchy to serve as an externalized mental model that will support knowledge-based problem solving B.Limitations  Three issues pertaining to the use of AH 1.designers’ knowledge of the constraints governing the system 2.Robustness – empirical research needed 3.Limitations due to sensor technology 4.generalizability

14. UI/CM L AB Ecological Interface Design (EID) VI.WHAT IS THE CONTRIBUTION OF EID? A.Communicating the Information to the Operator Direct Manipulation Interfaces:  DMI allow users to directly act on what they see in the display but lack of the explanation of human information processing capability – SRK framework Object Displays :  Mapping the higher order perceptual relationships onto goal-relevant variables  Directly relevant to EID principle 2 – to support RBB, the perceptual cues (signs) should directly specify the process constraints

15. UI/CM L AB Ecological Interface Design (EID) Technology-Driven Display Design:  Computer graphics for building interfaces for complex technical systems – mimic or schematic diagrams  EID is top-down while technology-based is bottom-up B.Representing the Complexity in the Domain Operator Function Model:  Another formalism as an alternative to the AH  OFM (Mitchell and Miller, 1986) – a discrete control model 1)What data should be displayed? 2)How should those data be organized into screens? 3)How should context sensitivity be built into the display? 4)How can information be presented at various levels of detail?

16. UI/CM L AB Ecological Interface Design (EID)  Mappings are nondeterministic  Miller (1982) – structural vs. behavioral representation  A structural representation is one in which the structures that define the system are defied directly in some set of objects (AH) – complex systems where unanticipated events are the biggest threat to system safety  a behavioral representation is a representation of a dynamic system whose elements consist of system behavior (OFM) – situations where operators are required to dynamically select the relevant subset of data to carry out predictable tasks

17. UI/CM L AB Ecological Interface Design (EID) VII.EMPIRICAL EVALUATION  DURESS (Dual Reservoir System Simulation) a thermal-hydraulic process simulation  Physical/functional (P+F) interface and physical (P) interface  Functional variables to the higher levels of the AH  the P+F interface superior diagnosis performance to the P interface, primarily for experts  The higher-order functional info in the P+F interface is important for diagnosis, justifying for including higher levels of the AH in an interface  Superiority of the P+F interface in the memory task