Human operator response to error-likely situations in complex engineering systems

The causes of human error in complex systems are examined. First, a conceptual framework is provided in which two broad categories of error are discussed: errors of action, or slips, and errors of intention, or mistakes. Conditions in which slips and mistakes might be expected to occur are identified, based on existing theories of human error. Regarding the role of workload, it is hypothesized that workload may act as a catalyst for error. Two experiments are presented in which humans' response to error-likely situations were examined. Subjects controlled PLANT under a variety of conditions and periodically provided subjective ratings of mental effort. A complex pattern of results was obtained, which was not consistent with predictions. Generally, the results of this research indicate that: (1) humans respond to conditions in which errors might be expected by attempting to reduce the possibility of error, and (2) adaptation to conditions is a potent influence on human behavior in discretionary situations. Subjects' explanations for changes in effort ratings are also explored

Assessing the impact of modeling limits on intelligent systems

The knowledge bases underlying intelligent systems are validated. A general conceptual framework is provided for considering the roles in intelligent systems of models of physical, behavioral, and operational phenomena. A methodology is described for identifying limits in particular intelligent systems, and the use of the methodology is illustrated via an experimental evaluation of the pilot-vehicle interface within the Pilot's Associate. The requirements and functionality are outlined for a computer based knowledge engineering environment which would embody the approach advocated and illustrated in earlier discussions. Issues considered include the specific benefits of this functionality, the potential breadth of applicability, and technical feasibility

Human problem solving performance in fault diagnosis tasks

Issued as Quarterly reports no. [1-3], Project no. E-24-643Final report issued in series: CMMSR report no. 82-

Enterprise Readiness for IT Innovation: A Study of Mobile Computing in Healthcare

This research posits that enterprise-wide information technology (IT) innovation initiatives in uncertain economic times amplify the need and importance for decision makers to systemically evaluate their organization’s capabilities, competencies, and potential risk areas that could either accelerate or impede adoption and implementation. The purpose of this research is to develop a theoretically-grounded, conceptual framework of healthcare enterprise readiness for IT innovation that will aid health IT decision makers with this complex task. We study this in the context of mobile computing which is poised to fundamentally transform healthcare delivery by improving patient care and lowering costs. Preliminary findings of our multi-phase exploratory empirical study with healthcare CIOs reveal the relative importance of several key assessment dimensions and indicators. Our research has important implications for both adopters and providers of health IT and contributes to our broader understanding of IT-enabled transformation of healthcare

A Mathematical Model of the Illinois Interlibrary Loan Network: Report No. 4

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryIllinois State Library: grant under the Illinois Program for Title I of the Federal Library Services and Construction Ac

A Mathematical Model of the Illinois Interlibrary Loan Network: Final Report

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryIllinois State Librar

A Mathematical Model of the Illinois Interlibrary Loan Network: Project Report No. 5

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryIllinois State Library / Illinois Program for Title I of the Federal Library Services and Construction Ac

Certify for success: A methodology for human-centered certification of advanced aviation systems

This position paper uses the methodology in Design for Success as a basis for a human factors certification program. The Design for Success (DFS) methodology espouses a multi-step process to designing and developing systems in a human-centered fashion. These steps are as follows: (1) naturalizing - understand stakeholders and their concerns; (2) marketing - understand market-oriented alternatives to meeting stakeholder concerns; (3) engineering - detailed design and development of the system considering tradeoffs between technology, cost, schedule, certification requirements, etc.; (4) system evaluation - determining if the system meets its goal(s); and (5) sales and service - delivering and maintaining the system. Because the main topic of this paper is certification, we will focus our attention on step 4, System Evaluation, since it is the natural precursor to certification. Evaluation involves testing the system and its parts for their correct behaviors. Certification focuses not only on ensuring that the system exhibits the correct behaviors, but ONLY the correct behaviors

A Mathematical Model of the Illinois Interlibrary Loan Network

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryIllinois State Librar