Ecological design of interface

The ecological design of interface ( EID ) is a method of design of interface which appeared specifically for the complex systems sociotechnic, time-reality, and dynamics. It was applied in various fields of which the Control process (Nuclear plants, factories petrochemical), Aviation, and the Medicine.

EID differs from other methodologies of design such as . EID is based on two key concepts resulting from research in cognitive Genius: the hierarchy of abstraction (AH) and model-tallies it SRK (for Skills, Rules, Knowledge, i.e. Skills, Rules, Knowledge).

The goal of EID is to make perceptivement (visible, audible) obvious to the user constraints and complex relations of the environment of work. In return, that makes it possible to allocate more cognitive resources with high level cognitive processes such as the resolution of problem and decision making. Thus, EID contributes to improve the performance of the user and the total reliability of the system vis-a-vis the events anticipated and not anticipated of a complex system.

Highlights

Origin and history of EID

The ecological design of interface was proposed as model-tallies of design of interface by Kim Vicente and Jens Rasmussen with end of the year 80 and with beginning of the year 90 following intensive research in the field of the fallibility of the system human in the national laboratory of Riso in Denmark (Rasmussen & Vicente, 1989; Vicente, 2001). The ecological term draws its origin of a current of psychology developed by James J. Gibson known under the name of ecological Psychology. This research field in psychology is interested in the relations human-environment, in private individual in relation with human perception in natural environments rather than in the environments of laboratory. EID borrows from ecological psychology in the fact that constraints and relations of work environment in one system complexes are reflected perceptivement (through the interface); and thus, act on the human behavior. To implement such ecological design, the following analytical tools were adopted: the hierarchy of abstraction (AH) and model-tallies it developed SRK previously by researchers at the National laboratory of Risø. Approach EID was applied for the first time and was evaluated on systems of nuclear plant (Vicente & Rasmussen, 1990, 1992). To date, EID was applied in various complex systems of which the management of data-processing network, anesthesiology, the system of military control, and them planes (Vicente, 2002; Burns & Hajdukiewicz, 2004).

Motivation

Fast projections of the technologies accompanied by the requirements economic led to a remarkable increase in the complexity of the engineering of the systems (Vicente, 1999a). Consequently, it became increasingly difficult for the originators to anticipate the events who could occur in such systems. Not anticipated events cannot by definition not be guessed in advance and thus be avoided by means of formation, procedures, or automation. A system sociotechnic based only on known scenarios frequently loses flexibility to face the unforeseen events. The safety of the system is often compromised by inhabileté of the operator to adapt to new and nonfamiliar situations (Vicente & Rasmussen, 1992). ecological design of interface tries to provide to the operator the tools and information necessary to become an agent solving them actively problems rather than a passive agent of monitoring, particularly with cours du course of unforeseen events. Interfaces conceived according to method EID aim at decreasing the mental effects of work during dealt with of the nonfamiliar and not anticipated events, which are known to increase the psychological pressure (Vicente, 1999b). Of this manner, the cognitive resources can be released to help with to solve the problems in an efficient way.

In addition to providing to the operators the means of managing them successfully not anticipated events, EID is also proposed for the systems which require with the users to become experts (Burns & Hajdukiewicz, 2004). Through the use of the hierarchy of abstraction (AH) and it model-tally SRK (Skills, Rules, Knowledge), EID allows the users beginners to generally acquire more easily of the mental models which take several years of experiment and formation to develop. In the same way, EID provides a base for a continuous training and for distributed groupware (Vicente, 1999b). When they are confronted with a system sociotechnic complexes, it is not always possible for originators to ask for to the operators which types of information they would like to see since each person includes/understands the system on a level different (but seldom entirely) and gives answers very different. EID model-tallies makes it possible to the originators to determine which types of information are necessary when it is not possible or feasible to question the users (Burns & Hajdukiewicz, 2004). It is not in the intention of the EID to replace methodologies of design existing such as UCD and the analysis of the task, but to supplement them.

The Hierarchy of Abstraction (ha)

The hierarchy of abstraction is a functional decomposition on 5 levels used to model the work environment of the complex systems sociotechnic, or known more commonly like the field of work. In method EID, the hierarchy of abstraction is used for to determine which types of information should be posted on the interface of the system and how information should be laid out. Ha describes a system at various levels of abstraction while using relations end-means. To move downwards in the levels of model answers the question how certain elements of the system are implemented, whereas to move to the top reveals why certain elements exist. The elements of the highest level of the model define them objectives and goals of the system. Elements of the levels low of model indicate and describe the physical components (i.e the equipment) system. The relations Why-How are represented on the ha by connections Means-Ends. One ha is generally developed while following one systematic approach called Analyzes Field of Work (Vicente, 1999a). It is not rare for an analysis of the field of work to succeed with multiple models of ha; each one examining the system on a level of different physical detail (scale) which east defines by using another model called the Whole-and-part hierarchy (Burns & Hajdukiewicz, 2004). Each level in the ha is a complete but single description field of work.

Functional Purpose (Objective, Functional Goal, finality of the system)

The level of the functional goal (English FP) described the goals and them general objectives of the system. One ha included typically more than one goal of system so that the goals are opposed or are supplemented the ones them others (Burns & Hajdukiewicz, 2004). The relations between the goals indicate potential compromises and constraints inside the field of work of the system. For example, the goals of a refrigerator could to be to cool food at a certain temperature by using one minimum quantity of electricity.

Abstract function

The level of abstract function (English AF) described the laws under unclaimed and the principles which control the goals of the system. That can to be empirical laws in a physical system, legal laws in a social system, and even economic principles in one commercial system. In general, the laws and the principles relate to things which need to be preserved or which runs out through the system such as the masses (Burns & Hajdukiewicz, 2004). The principle of one refrigerator (as of a heat pump) is controlled by the second law thermodynamics.

General functions

The level of the generalized function explains the processes implied in laws and principles found on the level AF, i.e how each abstract function is reached. Causal relations exist between elements found on level GF. The cycle of refrigeration in one refrigerator consists in pumping heat starting from a place of low temperature (source) towards a place of higher temperature (tank).

Physical function

The level of the physical function reveals the physical components or equipment associated with the processes identified on level GF. Capacities and limitations of the components such as the maximum capacity are generally noted in the ha (Burns & Hajdukiewicz, 2004). A refrigerator is constituted of pipe of gas compressor and heat transfer which can exert a certain maximum pressure on a body of cooling.

Physical shape

The level of the physical shape (English PFo) described the state, localization, and the physical appearance of the components exposed to the NFP level. In the example of the refrigerator, the pipes of the exchanger of heat and it compressor of gas are laid out in a specific way, primarily in illustrating the localization of the components. Physical characteristics can include/understand things like the color, dimensions, and form.

Model-tallies SRK (Skills, Rules, Knowledge)

Model-tallies SRK or taxonomy SRK defines three types of behavior or psychological process present in the data processing of the operator (Vicente, 1999a). SRK model-tallies was developed by Rasmussen (1983) to help the originators to organize the requirements in information of a system and aspects of human cognition. In EID, the framework SRK is used to determine how information could to be posted to draw part of human perception and the skills psychomotor (Vicente, 1999b). By facilitating (helping) the behaviors based on the skills and the rules in the familiar tasks, of additional cognitive resources can be devoted to behaviors based on knowledge, which is important to manage not anticipated events. The three categories describe primarily the various ways in which information, for example, is extracted and included/understood starting from a man-machine interface:

Behavior based on the skills

A behavior based on the skills represents a type of behavior who requires very little or no conscious control to carry out an action once an intention is formed; also known under the denomination of behavior sensorimotor. The performance smooth, is automated, and consist of patterns (designs) of behavior highly integrated in majority of the controls based on the skills (Rasmussen, 1990). By example, to drive bicycle is regarded as a behavior based on skills in which little attention is necessary for control once that the skill is acquired. This automatism allows the operators to release from the cognitive resources, which can be used for high level cognitive functions like the solution to problem (Wickens & Holland, 2000).

Level based on the rules

A behavior based on the rules is characterized by the use of rules and of procedures to select a sequence of action in one familiar situation of work (Rasmussen, 1990). The rules can be a whole of instructions acquired by an operator by experiment or data by the formative supervisors and operators.

The operators are not obliged to know the principles soutendant one system to exert a control based on the rules. For example, them hospitals have regulations highly proceduralized for alarms with fire. This is why, when somebody sees a fire it can follow them stages necessary to ensure the safety without any knowledge of control to be adopted in the event of fire.

Level based on knowledge

A behavior based on knowledge represents a more advanced level of reasoning (Wirstad, 1988). This type of control must be employed when the situation is new and unexpected. The operators must to know the basic principles and the laws which control the system. Since the operators need to establish explicit objectives (decisions) starting from their analysis of the system, the mental effects are typically higher than when they activate behaviors based on skills or on the rules.

See too

Cognition and Applied_psychology
Ecological psychology
Human factors and Ergonomics
IHM
Usability

References

Burns, C. Mr. & Hajdukiewicz, J.R. (2004). Ecological Interfaces Design. Boca Raton, FL: CRC Near. ISBN 0415283744

Rasmussen, J. (1983). Skills, rules, knowledge; signals, signs, and symbols, and other distinctions in human performance models. IEEE Transactions one Systems, Man and Cybernetics, 13,257-266.

Rasmussen, J. (1985). The role off hierarchical knowledge representation in decision making and system management. IEEE Transactions one Systems, Man and Cybernetics, 15,234-243.

Rasmussen, J. (1990). Mental models and the control off action in complex environments. In D. Ackermann, D. & M.J. Tauber (Eds.). Mental Models and Human-Computer Interaction 1 (pp.41-46). North-Holland: Elsevier Publishers Science. ISBN 044488453X

Rasmussen, J. & Vicente, K.J. (1989). Coping with human errors through system design: Implications for ecological interface design. International Newspaper off Man-Machine Studies, 31,517-534.

Vicente, K.J. (1999a). Cognitive Work Analysis: Toward Safe, Productive, and Healthy Work Computer-Based. Mahwah, NJ: Erlbaum and Associates. ISBN 0805823972

Vicente, K.J. (1999b). Ecological Interfaces Design: Supporting operator adaptation, continuous learning, distributed, collaborative work. Proceedings off the Human Centered Processes Conference, 93-97.

Vicente, K.J. (2001). Cognitive engineering research At Risø from 1962-1979. In E. Salted (ED.), Advances in Human Performance and Cognitive Engineering Research, Volume 1 (pp.1-57), New York: Elsevier. ISBN 076230748X

Vicente, K.J. (2002). Ecological Interfaces Design: Progress and challenges. Human Factors, 44,62-78.

Vicente, K.J. & Rasmussen, J. (1990). The ecology off human-machine systems II: Mediating " direct perception" in complex work domains. Ecological Psychology, 2,207-249.

Vicente, K.J. & Rasmussen, J. (1992). Ecological Interfaces Design: Theoretical foundations. IEEE Transactions one Systems, Man and Cybernetics, 22,589-606.

Wickens, C.D. & Hollands, J.G. (2000). Engineering Psychology and Human Performance (3rd ED.). Upper Saddle To rivet, NJ: Prentice Hall. ISBN 0321047117

Wirstad, J. (1988). One knowledge structures for process operators. In L.P. Goodstein, H.B. Andersen, & S.E. Olsen (Eds.), Task, Errors, and Mental Models (pp.50-69). London: Taylor and

Francis. ISBN 0850664012

External bonds

Institutions and organizations

Advanced Interfaces Design Lab (AIDL), University off Waterloo

Cognitive Engineering Lab (CEL), University off Toronto

Cognitive Engineering Research Group (CERG), University off Queensland

Human Factors and Ergonomics Society

IEEE Systems, Man and Cybernetics Society

Category: industrial technique

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