Identifiability: A Predictive Quantitative Measure for the Comparison of a Task Designed in Different Interaction Styles (original) (raw)
Related papers
Identifiability: A Predictive Quantitative Measure for the Comparison of a Task Designed
2005
This paper presents a predictive quantitative measure for the comparison of the performance of a task, when that task is designed in different interaction styles. The paper presents an extension of Task Knowledge Structures (Johnson and Johnson, 1991a) and based on this extension it presents identifiability, which is the evaluative and predictive measure that is the main focus of the paper. The paper then presents an experiment, which provides evidence towards the validity of the measure and its intended usage.
Identification Criteria in Task Modeling
2008
Task modeling consists of a fundamental activity that initiates usercentered design in user interface development. It is therefore important to reach the best task model possible and that the task modeling activity remains consistent when the task modeler changes. For this purpose, this paper introduces a set of criteria in order to identify tasks during task modeling in an unambiguous way that results into a task model exhibiting desired properties of quality such as completeness, consistency.
Modeling the Task: Leveraging Knowledge-in-the-Head at Design Time
A key problem in Human Computer Interaction is the evaluation and comparison of tasks that are designedin different interaction styles. A closely related problem is how to create a model of the task that allows thiscomparison. This paper tries to tackle these two questions. It initially presents a structure (Specific UserKnowledge Representation) that allows the creation of task models which allow direct comparisons betweendifferent interaction styles. The model allows the researcher or the designer to evaluate an interaction designvery early in the design process.
Towards a Theory-Based Form of Cognitive Task Analysis
2002
All forms of task analysis rely on the idea that human action can be decomposed, and that the decomposition can be used to reason about what people should do and know to complete a task. With simple technologies, the process of developing an analytic focus was readily tractable. The allocation of function among people in a team and between people and technology was straightforward. Tasks were thought of as primarily involving vigilance, perceptual-motor skill, memory, decision making, communications, or some simple combination of these capabilities. Today, the situation is less straightforward. As tasks have become more intricate, knowledge intensive and subject to increasingly integrated forms of technological support, traditional forms of task decomposition appear to have overly restricted scope. It is unlikely that there will be a universally applicable form of cognitive task analysis (CTA). Indeed, in this volume, the very diversity of approaches to the definition of CTA, and to its conduct at individual and team levels, well illustrates the extent of the wider problem. Methods or models developed to deal with specific situations are of undeniable value in that they are used to generate predictions about performance times, human error, or to support other forms of reasoning about how tasks are best carried out by a team in a setting. However, any method is likely to remain of limited utility if its use is restricted to a specific type of task, application domain, or technology. Ideally, the methods and models we develop should
2007
Unless one can decompose the particular task, in terms of desired learning outcomes and cognitive-process elements, there is almost no point to understanding knowledge structures, and unless one can gain access to those knowledge structures, in both the particular and the generic learners (expert, novice, or whatever), there is no dependable way to translate theory into practice. In short, one must know not only what learning operations the task requires, but also what operations the learner is and should be executing at each stage of the learning process. (Howell & Cooke, 1989, p. 160) This claim provides a succinct argument for the benefits of utilizing cognitive task analysis (CTA) methods to capture accurate and complete descriptions of the performance objectives, equipment, conceptual and procedural knowledge, and performance standards that experts use to perform complex tasks (Clark, Feldon, Van Merriënboer, Yates, & Early, in press). Experts are often called upon to provide their knowledge and skills for curriculum and materials development, teaching, and training. They also provide information for the development of knowledge-based computer systems that attempt to address undefined and ill-structured problems (McTear & Anderson, 1990). Historically, behavioral task analysis methods have served as the primary approach to capturing experts' observable actions for these purposes. However, replicating expert performance originating from behavioral analysis is problematic. Expertise, by its nature, is acquired as a result of continuous and deliberate practice in solving problems in a domain (Ericsson, Krampe, & Tesch-Römer, 1993). As new knowledge is acquired and practiced, it becomes automated and unconscious
Measurement of perceived task characteristics
Psychological Bulletin, 1981
Studies examining six psychometric properties of two currently popular measures of perceived task characteristics, the Job Diagnostic Survey and the Job Characteristic Inventory, are reviewed. The evidence indicates some support for the theoretical assumptions on which those scales are based, but it suggests serious difficulties as well. Alternative approaches to measurement of task characteristics and future directions for task design research are discussed. The need for more objective measures and for new theoretical paradigms is stressed.
Modelling Task Knowledge Structures in Demos 2000
2008
Abstract. Task Knowledge Structures provide an account of the knowledge structures that people possess and use when performing a task. Such models can be constructed using various techniques, such as direct observation, interviews, questionnaires, and others. TKS models can represent either knowledge structures that are possessed by a specific individual or, alternatively, a number of such individual TKS models can be amalgamated to form new TKSs.
2008
Characteristics of well-designed working tasks The characteristics of welldesigned tasks are theo retically based and empirically founded. Therefore, they became a guideline for task evaluation and task design. Although these standards (DIN EN ISO 92412 and DIN EN 6142) refer to operating machines and visual display unit (VDU) work, the characteristics are of a generic kind, and thus might be useful for the evaluation and design of further types of working tasks as well. Integrating both standards cited the following list of required characteristics concerning welldesigned working tasks results: • The working tasks should not be partialized into fragments, but rather be complete and meaning ful units. • The tasks should contribute to the total output of an organization in an identifiable and consider able manner.
Conceptualizing Structurable Tasks in the Development of Knowledge-Based Systems
Decision Sciences, 1996
Conventional approaches to knowledge-based system (KBS) development are not appropriate for building KBSs when the application task is structurable (i.e., exhibits a certain degree of ill structure). Building a KBS for structurable tasks requires an understanding of the problem-solving strategies used by an expert to manage the ill structure, while at the same time relying on domain theories to understand the structured parts of the task. This paper presents a methodology for developing a knowledge model for structurable tasks during the conceptualization stage of KBS development. This is equivalent to building a logical model for design during the development of conventional information systems. The methodology relies on prior research on the decomposition and characterization of a task based on its various attributes. The paper also illustrates the use of the methodology in the case of KBS development for financial hedging. The paper concludes with some observations about the potential impact of this methodology on other stages in the KBS development process.