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Ecological Interface Design https://publicwiki.deltares.nl/display/BWN/Tool+-+Interactive+Dredge+Planning+Tool+Singapore
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So, what is EID? Designed for complex systems Attempts to mimic DMI Displays complex interactions and system constraints A display is ecological if it acts the same as the real world
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Why EID? It is possible for operators to encounter 3 classes of events: Familiar events Unfamiliar events Unanticipated events System complexity System constraints Support of mental models Design questions that arise from these fundamental principles How to describe domain complexity? How to communicate the information?
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Properties of an abstraction hierarchy All levels deal with the same system, using different models Each level has its own terms, concepts and principles Observer experience sets descriptive terms and levels of abstraction Functional requirements are set at low levels, where evolving states refer to lower level influences on higher levels Deeper understanding of the system is achieved by moving across hierarchy levels, higher levels refer to goals of operations farther down describes how operations are carried out
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Means-end approaches to problem solving People appear to map mental models in a way similar to the abstraction hierarchy Problem solving is a goal oriented approach All users may approach a problem differently based on mental models Operations are considered first at high levels Low leveled detail is accessed only when necessary to resolve the problem
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Skills, rules, knowledge taxonomy Information can be interpreted as signals, signs, or symbols The way it is interpreted determines the cognitive approach used Skill-based behavior (SBB) Rule-based behavior (RBB) Knowledge-based behavior (KBB) Vincente and Rasmussen use this framework to develop several recommendations for interface design based on previous research
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Perceptual VS analytical processing RBB and SBB are concerned with perception and action Fast and effortless, and proceeds in parallel, but only useful in familiar situations KBB is concerned with analytical problem solving Laborious and serial, but allows for dealing with novelty Based on this, the recommendation is to focus on perceptual processing. Research suggests that perception lead to more close judgments, thinking lead to more exact judgments, but with more extreme errors. Several studies found that perception was closely related to good performance People naturally prefer to adopt perceptual processing More complex and demanding tasks require more levels of abstraction, and more skilled operators require less levels of abstraction
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Recommendations Interfaces should support operator preference for lower levels of cognitive control Systems need to support both high and low level abstraction Control of the interface should allow for traveling between levels of abstraction, grouping information by contextual relevance
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Principles of EID: SSB I) SBB - To support interaction via time-space signals, the operator should be able to act directly on the display, and the structure of the displayed information should be isomorphic to the part-whole structure of movements The operator acts on interface components as direct controls Perception and actions follow the same conceptual constraints and groupings, where higher level information is an aggregation of lower level information
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Principles of EID: RBB 2) RBB -Provide a consistent one-to-one mapping between the work domain constraints and the cues or signs provided by the interface The interface uses alarms and displays that support a user’s cues for decision making, avoiding unnecessary mental translation of presented information Current interfaces do not have this, and it leads to procedural traps, because an adapted heuristic does not always provide accurate information in all situations
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Principles of EID: KBB 3) KBB -Represent the work domain in the form of an abstraction hierarchy to serve us un externalized mental model that will support knowledge-based problem solving Attempts to address the difficulty of accounting for all possible events by presenting the problem as an abstraction hierarchy in a perceptually salient diagram This external representation is intended to reduce the workload of recalling relevant information to solve problems
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Limitations What limitations can you see being associated with EID and the aforementioned principles? Designers Systems Technological
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An approach that focuses on cognitive functions, rather than physical and system constraints Addresses increased automation, and machines that can process information independently Proposes that other disciplines cannot account for a thinking computer, because their focus is on adapting an interface to human constraints Cognitive Systems Engineering
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Alternative solutions Rather than focus on responses of the system or the user to situations, the article proposes an information-processing model Information presented to the user or system from the environment Information from the user’s knowledge base Information from the system itself Psychology and systems are not always compatible, because logic cannot explain all human actions The paper proposes that the system be treated as an integrated gestalt, rather than two halves that compensate. Task distribution between the system and operator is nonlinear, dynamic and contextual Human performance problems are symptoms of poor interface design because the system is not represented properly
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Characteristics of cognitive systems Cognitive systems are an integrated gestalt that includes users and machine interfaces Cognitive systems are concept driven, their behaviors are goal oriented, adaptive, and access personal and contextual metaknowledge The development of an integrated cognitive system is driven by the internal model, the awareness of limitations, goals, and available knowledge Both users and machines are expected to make assumptions based on available information, but cognitive systems are meant to make these assumptions transparent and adaptable, and these assumptions should be capable of interacting These set characteristics should be task dependent, and dynamic, because situations change rapidly
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SRK in HMS Operators are not stimulus-response machines, and though skill and rule based actions are often most common, and often supported by the system, they should not be considered the most important Unanticipated situations are generally critical events that can lead to critical failures, and are difficult to support By considering the machine and operator as cognitive systems, it will better address shortcomings in HMS theory
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Generally composed of a two-way approach, where the system is afforded assumptions about the user (design), and the user’s model of the system is coordinated with the system’s properties (training) Cognitive system Engineering
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Cognitive task analysis Analyze and represent the cognitive activities utilized in tasks Used for Workload and assessments of the user Construct an expected mental model of operation Identifying decision making strategies of operators Categorizing human errors based on underlying mechanisms Human-Machine principles Metaprinciples that affect and interact with user’s cognitive function These principles can affect mental abstraction and attention to detail Interference when interfaces maladapt to incorrectly perceived abstractions Can lead to narrowing of attention
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Post-design evaluation Impossible to anticipate all real-world operations in cognitive systems engineering, requiring an iterative process Hollnagel and Woods suggest using alternative evaluation processes to investigate the content and empirical validity This evaluation can also supplement a cognitive task analysis
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Questions?
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