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Psychophysiological Test Methods and Procedures
Published in Samuel G. Charlton, Thomas G. O’Brien, Handbook of Human Factors Testing and Evaluation, 2019
Artifacts are signals that are not wanted and contaminate the physiological data of interest. Artifacts in the laboratory are usually not as much of a problem as in the field. Laboratory experiments can be cheaply rerun or extra data can be collected to replace any contaminated data. With test and evaluation the expenses are usually much higher, so repeating data collection may not be feasible. Further, in most test and evaluation situations, operators are naturally free to move about and cannot be restrained from talking and doing other artifact-causing behaviors. Also, the data of most interest can be accompanied by the sorts of activities that produce artifacts. Therefore, artifacts cannot be avoided, and methods must be used to either reduce or remove these artifacts from the data of interest. Cutmore and James (1999) provide an overview of the various artifacts encountered in psychophysiological research with suggestions on how to avoid and correct them.
Task Analysis
Published in Julie A. Jacko, The Human–Computer Interaction Handbook, 2012
Catherine Courage, Jhilmil Jain, Janice Ginny Redish, Dennis Wixon
Although you will not get a true environmental analysis (seeing the users work in their own settings), you can still get a lot of data about users and tasks. When you do task analysis in the lab, make sure you ask the users to bring artifacts relevant to the task being discussed (Butler 1996). These are any objects that participants use to complete their tasks or that result from the task. Artifacts could be a calendar, a procedure manual, a physical form, a computer-generated report, and so on.
Quality Assurance Plans
Published in Boyd L. Summers, Effective Processes for Quality Assurance, 2019
QA Plans reference standards and guidelines expected to be used on programs and projects to describe how processes determine compliance with these standards and guidelines. Always document relevant artifacts by reference and refer to the following standards and guidelines that may be relevant to the QA Plans. Artifacts are pieces of information that are produced, modified, or used by processes to define an area of responsibility, and are subject to version control.
Extending a Theory of Slow Technology for Design through Artifact Analysis
Published in Human–Computer Interaction, 2022
William Odom, Erik Stolterman, Amy Yo Sue Chen
Through its application, artifact analysis can iteratively lead to stable and well-formed definitions of artifact qualities that can inform the design of new artifacts. The outcome of an artifact analysis is critical and theoretical but it also has a practical purpose. It is critical in the sense that it intentionally challenges intuitive or everyday understandings of artifacts and their qualities, and makes it possible to ask new questions. It is theoretical in the sense that it leads to conceptual constructs that make it possible to more precisely define artifact qualities, their relationships and trade-offs. Our treatment of the term ‘theory’ is aligned with Gaver (2012) and Redström’s (2017) related arguments that design theory should not be seen as conclusive and fixed, but rather as unfolding and transitional. We do not aim to create a comprehensive theory of design but rather view theory as “an annotation of realised design examples, and particularly portfolios of related pieces” (W. Gaver, 2012, p. 937). By drawing on basic terms and definitions of slow technology as formulated in Hallnäs and Redström (2001) original visionary work, we aim to work toward more complex concepts through first-hand insights of design practice. Artifact analysis offers a structured approach to supporting this process.
A High-Frequency Algorithmic Trading Strategy for Cryptocurrency
Published in Journal of Computer Information Systems, 2020
In DSR, researchers seek to create Information Technology artifacts, which serve to extend the knowledge base.35 The artifacts can be in a form of constructs, models, methods, instantiations, and design theories.35,36 There are two research activities: build and evaluate. In build, research artifacts are created with roots in theoretical foundation; in evaluation, the artifacts are being benchmarked to expound its utility. Seminal research has discussed DSR at length, all highlighted the problem-solving aspects of the artifacts combined with the contribution to the knowledge base.5,35,37,38
Uncovering the specificities of CAD tools for industrial design with design theory – style models for generic singularity
Published in International Journal of Design Creativity and Innovation, 2018
Pierre-Antoine Arrighi, Pascal Le Masson, Benoit Weil, Akin Kazakçi
During the design process, the engineer configured a pre-established and mandatory set of DPs to achieve known FRs. The engineer used commands and functions step by step to construct the virtual mock-up, and by doing this generated what is known as a design tree. The design tree contained the functions and parameters, and the relationships among the different geometric entities. For instance, the designer specified certain dimensions of the tank to meet the volume criteria. The design tree also specified certain thickness parameters, for example, the position of ribs, to ensure the stiffness criteria (see Figure 1). A single product was not designed; instead, a parameterized and reconfigurable base of rules were produced that could generate a family of products. The result of the design in engineering CAD was not a single product but rather an algebra of rules. This algebra of rules defines how the components are spatially positioned, in addition to the links between them, the functions, and their parameters. This algebra can be mapped to an infinity of solutions. The engineer guaranteed that the set of created rules was robust to variations in DPs (e.g., different materials or manufacturing methods) or even FRs (e.g., modified volume requirements or a new legal regulation created during the design process). Clearly, the designer could use irrelevant parameters so that the CAD tool allows parametric variations, but these variations are poorly related to important topological variations. Digital engineering appears to be a design process of generalization. The artifact is one representation of a ‘genre,’ that is, it helps to address ‘generic variety.’ The product is robust to changes in its DPs (components, dimensions, etc.) and its FRs (environment, etc.) – one simple illustration of this is the logic of tolerances in engineering design.