DOCSLIB.ORG

Cognitive Engineering and User Interface Design

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Cognitive Engineering and User Interface Design BEHAVIOUR & INFORMATION TECHN OLOGY, 1998, VOL. 17, NO. 6, 338 ± 360 Representation still matters: cognitive engineering and user interface design CHRIS STARY² and MARK F. PESCHL³ ² University of Linz, Department of Business Information Systems, Communications Engineering, FreistaÈ dterstraû e 315, A-4040 Linz, Austria; e-mail: stary@ ce.uni-linz.ac.at ³ University of Vienna, Department for Philosophy of Science, Sensengasse 8/10, A-1090 Vienna, Austria; e-mail: Franz-Markus.Peschl@ univie.ac.at Abstract. With the increased utilization of cognitive models knowledge representation as one of its core issues, in for designing user interfaces several disciplines started to particular in the context of human-computer interac- contribute to acquiring and representing knowledge about tion, e.g. Woods et al. (1988, p. 3). At that time a strong users, artifacts, and tasks. Although a wealth of studies already exists on modeling mental processes, and although the goals of need for human-oriented design had been expressed, cognitive engineering have become quite clear over the last since in the ® eld of operator workplace design novel decade, essential epistemological and methodological issues in design solutions were required. It has been recognized the context of developing user interfaces have remained that the introduction of an interactive computer system untouched. However, recent challenging tasks, namely design- often changes the work environment and the cognitive ing information spaces for distributed user communities, have led to a revival of well known problems concerning the demands placed on employees. Several ® ndings help to representation of knowledge and related issues, such as detail the changes caused by the use of computer abstraction, navigation through information spaces, and systems: visualization of abstract knowledge. All of these issues are associated with mental processes and thus, might become part of Although the physical work load can be decreased cognitive models. · In this paper we reveal epistemological and methodological at most of the workplaces through the utilization assumptions in the ® eld of cognitive modeling as well as their of computer systems, in some cases the mental implications for user interface design. It turns out that in order to workload might increase for particular users, due achieve the goal of developing human-oriented (in contrast to to inherent problems in information systems, such technology-driven) human-computer interfaces developers have as according to Oliver (1995): to develop knowledge of the structure and the representational dynamics of the cognitive systems which are interacting with the computer. We show that in a ® rst step it is necessary to study and · disorientation investigate the diŒerent levels and forms of representation that · navigation ine ciency, and are involved in the interaction processes between computers and · cognitive overload. human cognitive systems. We propose a hybrid user modeling approach as part of the task-based development procedure in TADEUS (Task Analysis/Design/End User Systems). The · Although computers enhance the potential in hybrid approach does not only enable the representation of assistance of work, that extension might require functional roles end users have to perform, but also how end revisiting the allocation of functions to humans users perform these roles, i.e. the representation and re¯ ection, if and machines for human ± computer interaction not prediction of their behavior. This way, holistic system (e.g. Kantowitz et al. 1987). development that equally takes into account the organizational requirements and the end user reality at work places is facilitated. As a consequence, the potentials of computer systems have to be tuned to the context of their utilization (Hollnagl et al. 1983). In order to achieve the context- 1. Introduction sensitive utilization of technological artifacts designers need mechanisms to represent these contexts, i.e. on one Starting with Rasmussen (1986) cognitive engineering hand, an adequate cognitive language of description has been established as an interdisciplinary ® eld with (Rasmussen 1986), and on the other hand, a representa- 0144-929X/98 $12.00 Ó 1998 Taylor & Francis Ltd. Cognitive engineering and user interface design 339 tion of the end user tasks and their organization (i) the mental models of the end users of the target (Johnson, 1992). This task should be accomplished system: these representations are those internal through cognitive engineering. It has been established as models that can be speci® ed explicitly through a traditional applied cognitive science. The requirement one or more conceptual models by means of for an analysis and speci® cation of semantic and knowledge elicitation methods; pragmatic aspects has been stressed from that time on (ii) the conceptual model of the target system: this is up to recently, e.g., Roth et al. (1987). the external model that has to be developed by In the following we will term the speci® cation of the designer by using elicited knowledge from the semantic and pragmatic aspects of a domain several end users; representation. It might describe mental processes as (iii) the developer’s conceptual model of the end user’ s well as the results of those processes (see also Figure mental model of the target system: this is the 1, where two diŒerent externalized models of neural model of the developer that he/she has in mind representations are given). We term representations of in the course of knowledge elicitation and the mental processes as well as their results cognitive speci® cation of the conceptual model of the models. Such models help individuals to understand target system. `what knowledge of the world is needed and how this knowledge can be used to achieve eŒective perfor- In the traditional understanding of cognitive model- mance’ (Woods et al. 1988, p.34). In order to achieve ing all of the listed models are involved. The process eŒective performance, a translation of work tasks into for the construction of knowledge is driven by the the functions of the computer system has to be demand to improve the understanding of individuals performed by the individuals interacting with the with respect to features of interactive systems. As computer system, termed end users (Moran 1984). Figure 1 shows it is assumed that developing this The activity of mapping the mental models to process is a two-step procedure. The goals for knowl- representations will be termed cognitive modeling. edge construction are given through the computer Overall bene® ts of cognitive modeling are expected system itself, since it re¯ ects the outcome of the design in terms of and implementation process. The ® rst model re¯ ects the perspective of the developer: The Conceptual · predictability of human behavior in the course of (Representational) Model of the (target) Computer human-computer interaction, System (listed under (ii)) represents what the software · avoidance of errors in the course of task accom- developers are expecting or have expected as outcome plishment, and of their work. It contains the results of the transforma- · improved usability of interfaces, based on the tion of end-user and task requirements to technical represented knowledge about mental processes. functionality. This model is traditionally described through some kind of notation or language, such as The construction of cognitive models requires to take semantic networks or constructs in ® rst order logic, into account several activities and steps, since human respectively. It contains a more or less analog perception and learning are assumed to occur along a representation of the goals implemented in the certain path of actions, involving several key elements of computer system at hand. It is also that model users human cognition. Traditional cognitivists, such as Olson apply in order to interpret the technical functionality of et al. (1990), assume that the non-observable processes an artifact. This model comprises more or less knowl- of cognition are based on the interpretation of perceived edge about how to use system functions, rather than physical activities, and on intentional speci® cation of conveying the rationale behind, namely: actions that are actually executed. Goals and expecta- tions form a background against which the interpreta- · why they have been developed this way, tion and speci® cation of actions occur. Unfortunately, · why they have to be used the way they have to be only few components and transitions, such as the used, and memory performance checking intentions, have been · when to use them. investigated empirically (Norman 1986). According to Norman (1983), setting up a model of In order to succeed in interactive task accomplish- cognition involves several perspectives, namely the ment users have to connect their mental models to the perspective of the developer and the ones of the end cognitive model that explicitly states the goals of users that are involved in the development. As a developers that have been implemented (user perspec- consequence, several types of cognitive models of a tive). Since the users’ goals might not correspond to the target system can be distinguished: ones from the designer’s cognitive model, in traditional 340 C. Stary and M. F. Peschl Figure 1. Externalized cognitive models with respect to Figure 2. Results from the constructivist shift in cognitive interactive computer systems. modeling with respect to HCI. cognitive modeling
Load more

Recommended publications
  • A. Holzinger LV 709.049
    A. Holzinger LV 709.049 Welcome Students! At first some organizational details: 1) Duration This course LV 709.049 (formerly LV 444.152) is a one‐semester course and consists of 12 lectures (see Overview in Slide 0‐1) each with a duration of 90 minutes. 2) Topics This course covers the computer science aspects of biomedical informatics (= medical informatics + bioinformatics) with a focus on new topics such as “big data” concentrating on algorithmic and methodological issues. 3) Audience This course is suited for students of Biomedical Engineering (253), students of Telematics (411), students of Software Engineering (524, 924) and students of Informatics (521, 921) with interest in the computational sciences with the application area biomedicine and health. PhD students and international students are cordially welcome. 4) Language The language of Science and Engineering is English, as it was Greek in ancient times and Latin in mediaeval times, for more information please refer to: Holzinger, A. 2010. Process Guide for Students for Interdisciplinary WorkinComputer Science/Informatics. Second Edition, Norderstedt: BoD. http://www.amazon.de/Process‐Students‐Interdisciplinary‐Computer‐ Informatics/dp/384232457X http://castor.tugraz.at/F?func=direct&doc_number=000403422 WS 2015/16 1 A. Holzinger LV 709.049 Accompanying Reading ALL exam questions with solutions can be found in the Springer textbook available at the Library: Andreas Holzinger (2014). Biomedical Informatics: Discovering Knowledge in Big Data, New York: Springer. DOI: 10.1007/978‐3‐319‐04528‐3
    [Show full text]
  • Management of Data Elements in Information Processing
    PB-249-530 MANAGEMENT OF DATA ELEMENTS IN INFORMATION PROCESSING U.S. DEPARTMENT OF COMMERCE / National Bureau of Standards SECOND NATIONAL SYMPOSIUM NATIONAL BUREAU OF STANDARDS GAITHERSBURG, MARYLAND 1975 OCTOBER 23-24 Available by purchase from the National Technical Information Service, 5285 Port Royal Road, Springfield, Va. 221 Price: $9.25 hardcopy; $2.25 microfiche. National Technical Information Service U. S. DEPARTMENT OF COMMERCE PB-249-530 Management of Data Elements in Information Processing Proceedings of a Second Symposium Sponsored by the American National Standards Institute and by The National Bureau of Standards 1975 October 23-24 NBS, Gaithersburg, Maryland Hazel E. McEwen, Editor Institute for Computer Sciences and Technology National Bureau of Standards Washington, D.C. 20234 U.S. DEPARTMENT OF COMMERCE, Elliot L. Richardson, Secrefary NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Acfing Direc/or Table of Contents Page Introduction to the Program of the Second National Symposium on The Management of Data Elements in Information Processing ix David V. Savidge, Program Chairman On-Line Tactical Data Inputting: Research in Operator Training and Performance 1 Irving Alderman, Ph.D. "Turning the Corner" on MIS, A Proposed Program of Data Standards in Post-Secondary Education 9 Donald R. Arnold, Ph.D. ASCII - The Data Alphabet That Will Endure 17 Robert W. Bemer Techniques in Developing Standard Procedures for Data Editing 23 George W. Covill An Adaptive File Management Systems 45 Dennis L. Dance and Udo W. Pooch (Given by Dance) A Focus on the Role of the Data Manager 57 Ruth M, Davis, Ph.D. A Proposed Standard Routine for Generating Proposed Standard Check Characters 61 Paul -Andre Desjardins Methodology for Development of Standard Data Elements within Multiple Public Agencies 69 L.
    [Show full text]
  • A Re-Vision of Information Systems Neville Holmes Department Of
    A Re-Vision of Information Systems Neville Holmes Department of Applied Computing & Mathematics University of Tasmania Launceston 7250 Australia Email: [email protected] (published in the Proceedings of the 1996 Australasian Conference on Information Systems) Abstract The theme of the Conference, “Revisioning Information Systems”, is examined. A two decades old vision of information systems is reviewed here by its author to establish the groundwork for a re-vision. The original vision, and its prediction, is evaluated, and used as the basis for a re-vision and a new prediction. Some implications of the new prediction, and some impressions gained while arriving at it, are reviewed. THE CONFERENCE THEME The theme of this the 7th Australian Conference on Information Systems is Revisioning Infor- mation Systems. It must be assumed such curious wording was chosen deliberately to provoke, and it is indeed provocative at several levels. Even the use of the phrase information systems is provocative to anyone who is concerned that agreed and legal standards should be upheld. Ian Gould (1972) in reviewing the work that led to the International Standard Vocabulary (ISO 1991) wrote that “ it is difficult, if not impossible, to find a concept that could reasonably be called ‘information processing’; our machines can surely only process data.” So the very popular view that equates an information system with a computer system is, at the very least, non-standard. Although in one sense this battle for correct terminology is unwinnable, (like the battle to pre- serve impact from synonymy with effect), in another sense it must be kept up at least to influence how people see information systems.
    [Show full text]
  • IIS Phd: Course Descriptions
    UNT courses suitable for IIS PhD students Last updated: 18 February 2015 This list is used simply as a guide and should not be considered complete (i.e., new courses are often created and may not appear on this list). New courses may be added when discovered and if appropriate. CONSULT CURRENT COURSE SCHEDULES at http://essc.unt.edu/registrar/schedule/scheduleclass.html to determine if the course is offered in the specific semester and what is the course delivery format (face-to- face, online, or blended). A current Graduate Catalog should also be consulted. KEY P (col. 1) = program area. Codes: m = research methods; r = required; e = elective; 1 = info theory & design concentration; 2 = info & behavior concentration; 3 = info policy & mgmt concentration. P Course m ANTH 5032/5032. Ethnographic and Qualitative Methods. 3 hours. Focuses on ethnographic and qualitative methods and the development of the skills necessary for the practice of anthropology. Special e emphasis is given to qualitative techniques of data collection and analysis, grant writing, the use of computers to analyze qualitative data and ethical problems in conducting qualitative research. m ANTH 5041. Quantitative Methods in Anthropology. 3 hours. Basic principles and techniques of research design, sampling, and elicitation for collecting and comprehending quantitative behavioral data. Procedures for e data analysis and evaluation are reviewed, and students get hands-on experience with SPSS in order to practice organization, summarizing, and presenting data. The goal is to develop a base of quantitative and statistical literacy for practical application across the social sciences, in the academy and the world beyond.
    [Show full text]
  • Reverse-Engineering the Brain, Intersymp-2016, 1 August, 2016 RESU109-IS16
    Jens Pohl: Reverse-Engineering the Brain, InterSymp-2016, 1 August, 2016 RESU109-IS16 Reverse-Engineering the Brain: The parts are as complex as the whole. Jens Pohl, PhD Professor of Architecture (Emeritus) California Polytechnic State University (Cal Poly) Vice President, Engineering & Technology Tapestry Solutions (a Boeing Company) San Luis Obispo, California, USA Abstract The purpose of this paper is to review the current state of neuroscience research with a focus on what has been achieved to date in unraveling the mysteries of brain operations, major research initiatives, fundamental challenges, and potentially realizable objectives. General research approaches aimed at constructing a wiring diagram of the brain (i.e., connectome), determining how the brain encodes and computes information, and whole brain simulation attempts are reviewed in terms of strategies employed and difficulties encountered. While promising advances have been made during the past 50 years due to electron microscopy, the development of new experimental methods, and the availability of computer-enabled high throughput imaging systems, brain research is still greatly encumbered by inadequate monitoring and recording capabilities. Four hypotheses relating to comprehension through the assembly of parts, formation of memories, influence of genes, and synapse formation are described as plausible explanations even though they cannot be validated at this time. By assessing the feasibility of overcoming the principal problems that beleaguer brain research in comparison
    [Show full text]
  • AMSTATNEWS the Membership Magazine of the American Statistical Association •
    May 2017 • Issue #479 AMSTATNEWS The Membership Magazine of the American Statistical Association • http://magazine.amstat.org JSM Is Baltimore Bound! ALSO: ASA Visits Capitol Hill During Seventh Climate Science Day Pastimes of Statisticians: What Does Fred Faltin Do When He Is Not Being a Statistician? LessonPlan_8.33x11.83.indd 1 7/8/2015 4:55:36 PM AMSTATNEWS MAY 2017 • ISSUE #479 Executive Director Ron Wasserstein: [email protected] Associate Executive Director and Director of Operations features Stephen Porzio: [email protected] 3 President’s Corner Director of Science Policy Steve Pierson: [email protected] 5 PhD Student Credits Math Alliance with Success Director of Strategic Initiatives and Outreach 9 Interview with Editor of Statistics in Biopharmaceutical Donna LaLonde: [email protected] Research Director of Education 10 Cultivating a Culture of Collaboration (with Gusto) Rebecca Nichols: [email protected] in Your Career Managing Editor Megan Murphy: [email protected] 14 ASA Visits Capitol Hill During Seventh Climate Science Day Production Coordinators/Graphic Designers Sara Davidson: [email protected] Megan Ruyle: [email protected] Publications Coordinator Val Nirala: [email protected] Advertising Manager Claudine Donovan: [email protected] Contributing Staff Members Lara Harmon • Naomi Friedman Amy Nussbaum • Kathleen Wert Amstat News welcomes news items and letters from readers on matters of interest to the association and the profession. Address correspondence to Page 14 Managing Editor, Amstat News, American Statistical Association, 732 North Washington Street, Alexandria VA 22314-1943 USA, or email amstat@ amstat.org. Items must be received by the first day of the preceding month The ASA’s Amy Nussbaum introduces Rep.
    [Show full text]
  • Mobile Applications and Delivery of Bioinformatics Education in the Post
    University of Nevada, Reno Mobile Applications and Delivery of Bioinformatics Education in the Post-Secondary Introductory Biological Science Classroom A dissertation submitted in partial fulfillment of the requirement for consideration of a Doctor of Philosophy in Education by Joseph Wilcox Dr. David Crowther, Advisor December, 2020 © Joseph M. Wilcox Dec 2020 All Rights Reserved THE GRADUATE SCHOOL We recommend that the dissertation prepared under our supervision by JOSEPH WILCOX entitled Mobile Applications and Delivery of Bioinformatics Education in the Post-Secondary Introductory Biological Science Classroom be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy David Crowther, PhD Advisor Elizabeth de los Santos, PhD Committee Member Robert Quinn, PhD Committee Member Leping Liu, PhD Committee Member David Quilici, PhD Graduate School Representative David W. Zeh, Ph.D., Dean Graduate School December, 2020 i Abstract The field of life science is facing a great challenge, in that the tools are beginning to outpace the user. Technology has rapidly been accelerating while the knowledge to use this new tech has been unable to keep pace. For example: as the recent push to get the faster, cheaper sequencing machine designed has inspired engineers to design contraptions that achieve the original idea but also more complexity, greater amounts of data, and the need for scientists to learn new techniques to understand it all. In this case, by generating large amounts of data in a short amount of time, the ability to interpret the produced numbers becomes increasingly important (Bender, 2015; Frankel & Reid, 2008). Additionally, acquiring access to the tools necessary to interpret data can prove a challenge.
    [Show full text]
  • Information Technology System in INDIA”
    International Journal of IT & Knowledge Management (ISSN:: 0973-4414) Volume 13 • Issue 2 pp. 22-24 Jan 2020 - June 2020 www.csjournals.com An impact of “Information Technology System in INDIA” SIMRAN KODAL P.G. Department of Studies in Commerce, K.L.E’s J.G. College of Commerce, Vidyanagar, Hubballi Abstract: The purpose of this research paper is to analyze different kinds of information system that are developed for different purposes, depending on the need of the business. In today’s business world, there are varieties of information systems such as transaction processing systems (TPS), management information systems (MIS), and executive information systems (EIS) etc. each place a different role in organizational hierarchy and management operations. This study attempts to explain the purpose of each type of information systems in business organizations on the other side, it also focuses on the process of information system of the organization. Keywords: INFORMATION SYSTEM. INTRODUCTION: An Information System (IS) is a group of components that interact to produce information. An Information System is an integrated and cooperating set of software directed information technologies supporting individual, group, organizational, or social goals. An information system is a software system to capture, transmit, store, retrieve, manipulate, or display information, thereby supporting people, organizations, or other software systems. A computer information system is a system composed of people and computers that processes interprets information. Information is a study of system with specific reference to information and the complementary networks of hardware and software that people and organization use to collect, filter, process, create and also distribute data.an emphasis placed on an information system having a definitive boundary, users, processors, storage, inputs, outputs and the aforementioned communication network.
    [Show full text]
  • Downloads/Icmm Iucn Bioper Inbrief 11 14 .Pdf [Accessed 15 Apr
    A University of Sussex PhD thesis Available online via Sussex Research Online: http://sro.sussex.ac.uk/ This thesis is protected by copyright which belongs to the author. This thesis cannot be reproduced or quoted extensively from without first obtaining permission in writing from the Author The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the Author When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given Please visit Sussex Research Online for more information and further details Conserving nature power: An exploration of biodiversity offsetting in Europe and beyond Andrea Christiane Brock Doctor of Philosophy in International Relations University of Sussex May 2018 i I hereby declare that this thesis has not been and will not be submitted in whole or in part to another university for the award of any other degree. Name: Andrea Christiane Brock Signature:.................................................................... ii Summary This dissertation draws on multi-sited fieldwork to understand the history and development of biodiversity offsetting in Europe and beyond. It situates offsetting as a social technology of governance in the management of resistance and dissent against corporate and state degradation and violence, and as an instrument to flexibilise restrictive legislation imposing limits to industrial expansion in Europe. I analyse offsetting through the lens of corporate and state power and violence, contextualising it in the dominant social economic order, exploring its role in the advancement of social control and accumulation, and in the invisibilisation and entrenchment of the epistemic, physical and slow violence(s) exercised against human and nonhuman nature, in the form of industrialism and extractivism, state control and policing of dissent.
    [Show full text]
  • Data Processing and Government Administration: the Aif Lure of the American Legal Response to the Computer Paul Schwartz
    Hastings Law Journal Volume 43 | Issue 5 Article 2 1-1992 Data Processing and Government Administration: The aiF lure of the American Legal Response to the Computer Paul Schwartz Follow this and additional works at: https://repository.uchastings.edu/hastings_law_journal Part of the Law Commons Recommended Citation Paul Schwartz, Data Processing and Government Administration: The Failure of the American Legal Response to the Computer, 43 Hastings L.J. 1321 (1992). Available at: https://repository.uchastings.edu/hastings_law_journal/vol43/iss5/2 This Article is brought to you for free and open access by the Law Journals at UC Hastings Scholarship Repository. It has been accepted for inclusion in Hastings Law Journal by an authorized editor of UC Hastings Scholarship Repository. For more information, please contact [email protected]. Data Processing and Government Administration: The Failure of the American Legal Response to the Computer by PAUL SCHWARTZ* Table of Contents Introduction ................................................... 1322 I. The Data Processing Model and the Computer ............ 1325 A. The Information Society and the Data Processing M odel ............................................... 1326 B. The Service Administration and Its Need for Personal Inform ation .......................................... 1329 C. Capabilities of the Computer as Machine .............. 1334 1. Rapid Processing of Enormous Data Banks ........ 1335 2. Multifunctionality ................................ 1339 3. Seductive Precision of
    [Show full text]
  • Neuro Informatics 2013
    Neuro Informatics 2013 August 27 - 29 Stockholm, Sweden Artwork by Nina Johansson | ninajohansson.se ABSTRACT BOOK Neuroinformatics 2013 6th INCF Congress Program & abstracts August 27 - 29, 2012 Stockholm, Sweden Neuroinformatics 2013 3 What is INCF? The International Neuroinformatics Coordinating Facility (INCF), together with its 17 member countries, coordinates collaborative informatics infrastructure for neuroscience and manages scientific programs to develop standards for data sharing, analysis, modeling and simulation in order to catalyze insights into brain function in health and disease. INCF is an international organization launched in 2005, following a proposal from the Global Science Forum of the OECD to establish international coordination and collaborative informatics infrastructure for neuroscience. INCF is hosted by Karolinska Institutet and the Royal Institute of Technology, and the Secretariat is located on the Karolinska Institute Campus in Solna. INCF currently has 17 member countries across North America, Europe, Australia and Asia. Each member country establishes an INCF National Node to further the development of Neuroinformatics and to interface with the INCF Secretariat. The mission of INCF is to share and integrate neuroscience data and knowledge worldwide, with the aim to catalyze insights into brain function in health and disease. To fulfill this mission, INCF establishes and operates scientific programs to develop standards for neuroscience data sharing, analysis, modeling and simulation. Currently there are 4 program areas: Digital Brain Atlasing; Ontologies for Neural Structures, Multi-scale modeling, and Standards for Data Sharing. More than 180 leading international researchers are involved in the programs. A cloud-based data federation - the INCF Dataspace - has been developed to enable collaboration between researchers through the sharing of neuroscience data, text, images, sounds, movies, models and simulations.
    [Show full text]
  • 20090215 Midterm Preparation
    Systems Architecture Chapter 1 – Computer Technology, You’re Need to Know Technology and Knowledge Acquiring and Configuring Technology Devices Information Systems Development Systems Development Life Cycle (SDLC): series of steps for developing an information system Unified Process (UP): an iterative SDLC with 4-6 week cycles Disciplines: groupings of associated activities in the SDLC o Business Modeling and Requirements: building models of the processes to understand the system as it will be built. o Design: activities that determine the structure of the system as defined in the requirements. Architectural Design: select and determine configurations for hardware, networking, system software, and applications development tools. These affect all design that follows. Information Architecture: requirements and constraints defining information resources and how they interact with one another. Detailed Design: narrowed in scope, constrained by architecture o Implementation and Testing: build, aquire, and integrate software components. Verification of correct functioning components and that they meet requirements. o Deployment: install, configure, and bring solution into operation. o Systems Evaluation and Maintenance: handling and solving errors that occur in the system over time. Managing Computer Resources Need to manage hundreds of systems. Pay attention to compatibility and future trends. Broad understanding of current technology and future trends. Roles and Job Titles Application Developers: people who develop software for specific processing needs. Developers of scientific or technical applications have degrees in computer science. o Systems Analyst: business modeling and requirements. o Systems Designer: design and deployment o Applications Programmer: writes and tests software Systems Programmers: develops operating systems, DBMSes, Network Security, etc. Hardware Personnel: design, install, and maintain hardware.
    [Show full text]